A  STUDY  OF  UNDERSTANDING:     ALCHEMY,  ABSTRACTION,  AND  CIRCULATING  REFERENCE  IN  TERTIARY  SCIENCE  EDUCATION     By     Brett  W.  Merritt                                       A  DISSERTATION     Submitted  to     Michigan  State  University   in  partial  fulfillment  of  the  requirements     for  the  degree  of     Curriculum,  Instruction,  and  Teacher  Education  –  Doctor  of  Philosophy     2013   ABSTRACT     A  STUDY  OF  UNDERSTANDING:     ALCHEMY,  ABSTRACTION  AND  CIRCULATING  REFERENCE  IN  TERTIARY  SCIENCE  EDUCATION     By     Brett  W.  Merritt     Understanding  is  widely  touted  to  be  of  paramount  importance  for  education.  This  is   especially  true  in  science  education  research  and  development  where  understanding  is   heralded  as  one  of  the  cornerstones  of  reform.  Teachers  are  expected  to  ‘teach  for’   understanding  and  students  are  expected  to  ‘learn  with’  understanding.  This  dissertation  is  an   empirical  study  of  the  concept  of  understanding.  After  analyzing  various  constructions  of   understanding  in  current  U.S.  education  literature,  I  suggest  that  understanding  is  defined  by   five  distinct  features—they  are  knowledge  (or  knowledge  base),  coherence,  transfer,   extrapolation,  and  cognition—and  that  these  features  are  heavily  informed  and  shaped  by  the   psychological  sciences.  This  relationship  is  neither  good  nor  bad,  I  argue,  but  it  means  that   teaching  for  and  learning  with  understanding  are  not  heavily  informed  and  shaped  by,  for   example,  the  natural  sciences.  Drawing  from  historical,  philosophical,  and  anthropological   perspectives  of  science,  but  especially  from  the  work  of  Bruno  Latour,  I  enact  a  radical   revision(ing)  of  psychological  notions  such  as  “abstraction”  and  “transfer.”  The  two  main   purposes  of  this  re-­‐visioning  are  (1)  to  draw  critical  attention  to  particular  characteristics  of  a   cognitive  learning  theory  that  emphasizes  abstract  concepts,  and  (2)  to  align  many  of  the   principles  and  tools  used  in  science  education  more  closely  with  those  used  in  empirical   scientific  research.  Finally,  by  bringing  some  examples  of  teaching  and  learning  from  an   undergraduate  biology  classroom  into  conversation  with  both  psychological  and  empirical   practices  and  perspectives,  I  suggest  that  problematizing  the  current  construction  of   understanding  creates  much  needed  room  in  mainstream  science  education  for  more  empirical   forms  of  learning  and  styles  of  teaching.  A  shift  to  such  forms  and  styles,  I  conclude,  should   prove  to  be  more  inclusive  and  less  constraining  for  both  students  and  teachers.                                         Copyright  by   BRETT  W.  MERRITT   2013                                                   For  the  always  feisty  and  festive  Cleo  C.,  and  for  the  always  caring  and  supportive  Sarah  P...   I  am  forever  grateful  to  have  known  both  of  you.         v       ACKNOWLEDGEMENTS       Portions  of  this  dissertation  were  made  possible  by  support  from  the  Carnegie   Foundation’s  Teachers  For  a  New  Era  (TNE)  project  (Grant  No.  B7458),  the  National  Science   Foundation’s  Course,  Curriculum,  and  Laboratory  Improvement  (CCLI)  program  (Grant  No.   0736947),  and  MSU’s  Biological  Sciences  program.  In  particular,  I  would  like  to  thank  Gail   Richmond,  Joyce  Parker,  and  John  Merrill  for  supporting  this  project  with  a  generous  and   steady  supply  of  research  and  teaching  assistantships,  but  also  with  encouragement,  guidance,   insight,  and  patience.  In  addition  to  these  three  wonderful  people,  a  number  of  groups  and   individuals  have  made  significant  contributions  not  only  to  my  writing  and  thinking,  but  also  to   my  physical  and  social  well  being.  In  no  particular  order,  they  include  Ron  Patterson,  Duncan   Sibley,  Steve  Weiland,  Angie  Calabrese-­‐Barton,  Andy  Anderson,  Merle  Heidemann,  Mark  Urban-­‐ Lurain,  Ann  Lawrence,  Michael  Sherry,  Cleo  Cherryhomes,  Steve  Tuckey,  Irfan  Muzaffar,  Jory   Brass,  Amy  Parks,  Sharon  Strickland,  Adam  Greteman,  Donna  Dunlap,  Sarah  Paterson,  Tom   Hopper,  Kathy  Sheufelt,  Tom  Tweedy,  Gus  Flores,  William  Pettit,  Michael  Ulku-­‐Steiner,  the   Zacha  family,  and  the  Merritts.  Thanks  must  also  go  to  Robb  Gushiken  and  Ford  Shanahan,  aka.   The  Spitzberg  Crew.  And  finally,  deep  gratitude  must  be  directed  to  three  special  individuals,   Bruno  Latour,  Lynn  Fendler,  and  Kelly  Merritt.  To  Professor  Latour:  Although  I  happened  to  see   you  speak  when  you  passed  through  Michigan,  we’ve  never  formally  met,  but  your  books  and   ideas  have  been  my  almost  constant  companions  since  2005.  To  Lynn:  A  heap  of  thanks  to  you   for  your  friendship,  assistance,  and  guidance,  but  especially  for  your  patience  and  willingness  to   let  me  explore  and  pursue  my  own  interests  and  passions.  To  my  wife,  Kelly:  This  dissertation  is   vi       as  much  yours  as  it  is  mine.  Your  love  and  support  is  irreplaceable  and  unshakable.  I  couldn’t   have  done  this  without  you.  Ti  amo.             vii       TABLE  OF  CONTENTS       LIST  OF  TABLES......................................................................................................................  xii     LIST  OF  FIGURES....................................................................................................................  xiii     INTRODUCTION…………………..................................................................................................   1     The  Case  of  the  Mutant  Spinach  Plant......................................................................  1       About  Bio101.................................................................................................2       The  Application  Moment...............................................................................4     Overview  of  Remaining  Chapters..............................................................................   10       CHAPTER  1   UNDERSTANDING  IS  ALL  THE  RAGE......................................................................................  12     Four  Centuries  of  Enthusiasm  ...................................................................................  12       Enthusiasm  in  Contemporary  Science  Education..........................................  13     Understanding  Understanding..................................................................................  16       Learning  With  Understanding.......................................................................  18         Example  #1:  Science  for  All  Americans  (1990)..................................  21         Example  #2:  National  Science  Education  Standards  (1996)..............  23         Example  #3:  National  Center  for  Improving  Student  Learning     and  Achievement  in  Mathematics  and  Science  (1995-­‐2004)............  25         Example  #4:  How  People  Learn  (1999,  2000)...................................  28         Example  #5:  Learning  and  Understanding:  Improving  Advanced     Study  of  Mathematics  and  Science  in  U.S.  High  Schools  (2002).......  33         Example  #6:  Grant  Wiggins  and  Jay  McTighe  (2005)........................  36       Teaching  For  Understanding.........................................................................  42     Summary...................................................................................................................  46     CHAPTER  2   A  DISTINCT  HORIZON  OF  EXPECTATIONS.............................................................................  48     A  Mental  Horizon......................................................................................................  48   Some  Affordances  of  a  Mental  Horizon........................................................  51       Abstract  Conceptual  Learning  Theory...........................................................  55       The  Alchemy  of  School  Subjects...................................................................  58       Abstract  Conceptual  Learning  Theory:  A  Tool  for  Translation......................  60   A  Critical  View  of  the  Mental  Horizon.......................................................................  64   viii                       Raising  Questions  about  Cognition...............................................................  65   Raising  Questions  about  Abstract  Conceptual  Learning  Theory...................  67   Raising  Questions  about  Psychology.............................................................  70   In  Pursuit  of  Model-­‐Based  Reasoners:  An  Example  of  the     Alchemy  in  Action.........................................................................................  72   Summary...................................................................................................................  78       CHAPTER  3   A  HORIZONTAL  SHIFT............................................................................................................  81     An  Anthropologist  in  the  Classroom.........................................................................  82       Postscript  to  the  Classroom  Study................................................................  87     An  Anthropologist  in  the  Field..................................................................................  89       Postscript  to  the  Field  Study.........................................................................  92     Contrasting  Approaches  to  Learning  With  Understanding.......................................  94       The  Telos  of  the  Scientific  Expedition...........................................................  95       The  Telos  of  the  Pedagogical  Expedition.......................................................   97     Scientific  Research:  A  Resource  for  a  Different  Alchemy..........................................  98       Toward  an  Ecological  View  of  Learning  With  and     Teaching  For  Understanding.........................................................................  102     Summary...................................................................................................................  107     CHAPTER  4   A  SCIENTIFIC  HORIZON..........................................................................................................109     Section  A:  Science  In  Action......................................................................................  115       Knowledge  Gain.............................................................................................115       Knowledge  Application..................................................................................121     Section  B:  How  to  Speak  Latourian  About  Scientific  Figures.....................................123       Shifting  Terms:  From  Visual  Displays  to  Inscriptions.....................................130       Circulating  Reference:  A  Way  of  Understanding  the     Relationship  between  Fig.  20  and  Fig.  8.13  (Part  2)......................................  131   Scientific  Knowledge  Gain  in  Laboratories,  Forests,  and  Fields.....................135     I.  Acts  of  reference  as  crossing  (small)  gaps......................................  135     II.  Circulating  reference:  The  coupling  of     multiple  acts  of  reference  into  coherent  circuits..............................  141   Section  C:  How  to  Speak  Latourian  About  Classroom  Figures..................................  148   Section  D:  Tracking  Scientific  Reference  in  Bio101...................................................  156       ix       CHAPTER  5   HORIZONS  IN  ACTION............................................................................................................159     Looking  Back..............................................................................................................159     Addressing  a  Few  Unresolved  Issues.........................................................................166     Research  Question....................................................................................................  170     Methods....................................................................................................................  171       Practices  of  Study..........................................................................................  171       Equipment.....................................................................................................  171       Procedures....................................................................................................  173     Data  Analysis.............................................................................................................  178     Results.......................................................................................................................  179       Practice  1:  Figures.........................................................................................  180         Perspective  1A  -­‐  P.  psychologicus......................................................188         Perspective  1B  -­‐  P.  empiricus.............................................................191       Practice  2:  Clicker  Questions.........................................................................  194         Perspective  2A  -­‐  P.  psychologicus......................................................199         Perspective  2B  -­‐  P.  empiricus.............................................................202       Practice  3:  Exam  Questions...........................................................................  203         Perspective  3A  -­‐  P.  psychologicus......................................................207         Perspective  3B  -­‐  P.  empiricus.............................................................208     Discussion  -­‐  Part  A.....................................................................................................210       Empirical  profile  (A)  -­‐  P.  psychologicus..........................................................210       Empirical  profile  (B)  -­‐  P.  empiricus.................................................................212     CHAPTER  6   NEW  HORIZONS  FOR  SCIENTIST  TEACHERS...........................................................................214     Discussion  -­‐  Part  B.....................................................................................................  214       6.1  Purity........................................................................................................215       6.2  Composition.............................................................................................216         6.2a  Number  and  type  of  humans.....................................................216         6.2b  Number  and  type  of  non-­‐humans.............................................  217         6.2c  How  humans  and  non-­‐humans  are  arranged  in  time     and  space...........................................................................................218       6.3  Activity.....................................................................................................223       6.4  Potency....................................................................................................224     Exam  2  Review:  Lecture  20........................................................................................233     Conclusions................................................................................................................244       A  Student’s  Plea  for  Help...............................................................................245   x           From  Innerstanding  to  Overstanding.............................................................247     BIBLIOGRAPHY.......................................................................................................................251         xi         LIST  OF  TABLES       Table  5.1:  A  table  showing  the  content  related  terms  spoken  by  the     instructors  while  two  figures  were  visible  to  students.............................................  187     Table  5.2:  A  table  showing  the  content  related  terms  spoken  by  the     instructors  while  two  clicker  questions  and  their  answers  were  visible     to  students................................................................................................................  198     Table  6.1:  A  table  showing  the  number  of  content-­‐related  hits     generated  by  the  EmSIM  3000..................................................................................   226         xii       LIST  OF  FIGURES       Figure  1:  Question  “52,”  the  Mutant  Spinach  Question,  from  Bio101  Exam  2     (fall  2006)...............................................................................................................................4       Figure  3.1:  Photograph  of  a  small  tin  tag  affixed  to  the  horizontal  branch  of  a  tree     found  within  a  field  site  in  Brazil.  Figure  11.3  (Latour  1999).  (Reprinted  with  permission     by  the  copyright  holder.).......................................................................................................91     Figure  3.2.  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis     unit  in  an  undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava,  Heller,  Orians,     Purves,  and  Hillis  2007).  For  interpretation  of  the  references  to  color  in  this  and  all     other  figures,  the  reader  is  referred  to  the  electronic  version  of  this  dissertation.     (Reprinted  with  permission  by  the  copyright  holder.)..........................................................   104     Figure  4.1:  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that     Melvin  Calvin  submitted  when  accepting  the  1961  Nobel  Prize  for  chemistry.  Figure     20  (Calvin  1961).....................................................................................................................124     Figure  4.2:  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis  unit     in  an  undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava  et  al.  2007).     (Reprinted  with  permission  by  the  copyright  holder.)..........................................................   125     Figure  4.3:  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that     Melvin  Calvin  submitted  when  accepting  the  1961  Nobel  Prize  for  chemistry.  Figure     20  (Calvin  1961).....................................................................................................................132       Figure  4.4:  Figure  3.  Coupe  du  transect  1  (Silva  et  al.  1991).  A  figure  displayed  in  a     scientific  manuscript  reporting  on  the  findings  of  an  expedition  to  region  of  Boa  Vista,     Roraima,  Amazonia  (Brazil).  Figure  2.15  (Latour,  1999).  (Reprinted  with  permission  by     the  copyright  holder.)............................................................................................................133     Figure  4.5.  Latour’s  photograph  of  a  pedologist  using  a  handheld,  paginated  text     containing  a  wide  range  of  color  samples  that  have  been  aligned  with  alphanumeric     Munsell  codes.  Figure  2.16  (Latour  1999).  (Reprinted  with  permission  by  the  copyright     holder.)..................................................................................................................................136       xiii         Figure  4.6:  Three  images—a  photograph,  a  phrase,  and  a  diagram—illustrating     three  stages  of  a  coherent  circuit  of  reference..  A  handful  of  soil  (A);  an  example     of  a  Munsell  code  (B);  and  Figure  3.  Coupe  du  transect  1  (Silva  et  al.  1991).  A  figure     displayed  in  a  scientific  manuscript  reporting  on  the  findings  of  an  expedition  to     region  of  Boa  Vista,  Roraima,  Amazonia  (Brazil)  (C)..............................................................142     Figure  4.7:  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that     Melvin  Calvin  submitted  when  accepting  the  1961  Nobel  Prize  for  chemistry.     Figure  20  (Calvin  1961)..........................................................................................................149     Figure  4.8:  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that     Melvin  Calvin  submitted  when  accepting  the  1961  Nobel  Prize  for  chemistry.  Figure     20  (Calvin  1961).....................................................................................................................152     Figure  4.9:  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis  unit     in  an  undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava  et  al.  2007).     (Reprinted  with  permission  by  the  copyright  holder.)..........................................................   153     Figure  4.10:  “Calvin  Cycle”.  A  frequently  used  term  in  the  Bio101  classroom—both     in  spoken  and  written  forms—and  also  on  the  exams.........................................................157     Figure  5.1.  Photographs  of  two  figures  (A  and  C)  shown  to  undergraduate  students     by  the  course  instructors  during  the  photosynthesis  lectures.  Because  the  images  and     text  shown  in  photographs  A  and  C  may  be  difficult  to  see/read,  the  original  images     (B  and  D)  are  presented  with  the  ones  used  in  the  photosynthesis  lectures.  A  figure  of     the  “Calvin  Cycle”  shown  to  students  on  Day  3  (Lecture  13,  09-­‐29-­‐2006)  (A);  the  figure     of  the  “Calvin  Cycle”  as  it  appears  in  the  instructional  materials  (B);  a  figure  of  the     “Z-­‐scheme”  shown  to  students  on  Day  2  (Lecture  12,  09-­‐27-­‐2006)  (C);  and  the  figure     of  the  “Z-­‐scheme”  as  it  appears  in  the  instructional  materials  (D).  (Reprinted  with     permission  by  the  copyright  holder.)....................................................................................  181     Figure  5.2:  (At  left):  A  clicker  question  shown  to  students  on  Day  2  of  the  photosynthesis     unit  (Lecture  12,  09-­‐27-­‐2006).  (At  right):  A  clicker  question  shown  to  students  on  Day  3     of  the  photosynthesis  unit  (Lecture  13,  09-­‐29-­‐2006).  The  full  text  of  the  clicker  question     at  left  reads  as  follows:  “If  H2O  labeled  with  18O  is  added  to  a  suspension  of     photosynthesizing  chloroplasts,  which  compound  will  first  become  labeled  with  18O?     A.  ATP    B.  NADPH    C.  O2    D.  3PG.”  The  full  text  of  the  clicker  question  at  right  reads     xiv         as  follows:  “The  energy  derived  from  the  “light  dependent”  reactions  is  used  to:     A.  drive  endergonic  reactions  in  the  cytoplasm    B.  fix  inorganic  C  into  organic     molecules    C.  polymerize  CO2  and  H2O  into  glucose    D.  covert  NADPH  into  ATP     using  a  proton  gradient.”  The  bargraphs  seen  in  the  corners  of  the  two  figures     contain  information  that  is  not  relevant  to  my  analysis........................................................196     Figure  5.3:  Question  “52,”  the  Mutant  Spinach  Question,  from  Bio101  Exam  2     (fall  2006)...............................................................................................................................205       Figure  6.1:  Two  versions  of  Element  6,  which  was  identified  by  the  EmSIM  3000     as  having  the  most  relevance  to  question  “52.”  Two  versions  of  Element  6  are     included  because  the  images  and  text  in  the  photographed  version  may  be  difficult     to  read/see.  Figure  10.16  shown  by  the  Bio101  professors  during  Lecture  3  (09-­‐29-­‐06)     (A);  and  a  non-­‐annotated  version  of  Figure  10.16  as  it  appears  in  the  instructional     materials  (B).  (Reprinted  with  permission  by  the  copyright  holder).....................................229     Figure  6.2:  Two  versions  of  Element  17,  which  was  identified  by  the  EmSIM  3000  as     having  the  second  most  relevance  to  question  “52.”  Two  versions  of  Element  17  are     included  because  the  images  and  text  in  the  photographed  version  may  be  difficult  to     read/see.  A  still  image  made  from  an  animation  shown  by  the  Bio101  professors  during     Lecture  2  (09-­‐27-­‐06)  (A);  and  a  still  image  made  from  the  animation  as  it  appears  in  the   instructional  materials  (B).  (Reprinted  with  permission  by  the  copyright  holder)................231     Figure  6.3.  (At  left):  The  first  of  six  clicker  questions  asked  during  the  post-­‐Exam  2     review  session.  The  text  contained  within,  on  top,  and  underneath  the  vertical  arrow     to  the  far  left  of  the  figure  appearing  within  the  clicker  question  reads  as  follows:     “Energy  Level”  (within),  “High”  (on  top),  and  “Low”  (underneath).    (At  right):  The     second  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review  session.  The  text     in  the  upper  (blue)  portion  of  the  figure  contained  within  the  clicker  question  reads     as  follows  (starting  in  the  top  left  of  this  upper  portion  and  proceding  in  a  clockwise     direction):  “thylakoid  space,”  (multiple)  “H+,”  and  “FO  unit.”  The  text  in  the  lower     (orange)  portion  of  the  figure  reads  as  follows  (starting  in  the  top  left  of  this  lower     portion  and  proceding  in  a  clockwise  direction):  “stroma,”  “H+,”  “Stalk,”  “H+”  “F1     unit,”  “ATP,”  and  “ADP  +  Pi.”................................................................................................  235     Figure  6.4.  Juxtaposition  of  Element  6  and  a  figure  used  with  Bio101  students  during     the  post-­‐Exam  2  review  session.  Figure  10.16  shown  by  the  Bio101  professors  to     xv       students  during  Lecture  3  (09-­‐29-­‐06),  but  also  the  element  (Element  6)  identified     by  the  EmSIM  3000  as  having  the  most  relevance  to  question  52  (A);  A  non-­‐   annotated  version  of  Figure  10.16  as  it  appears  in  the  instructional  materials.     Notice  the  Z-­‐  (or  N-­‐shaped)  scheme  visible  in  the  image.  (B);  and  a  close-­‐up  of  the     image  used  in  the  first  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review     session.  Notice  the  Z-­‐  (or  N-­‐shaped)  scheme  visible  in  the  image.  The  text  contained     within,  on  top,  and  underneath  the  vertical  arrow  to  the  far  left  of  the  figure  reads  as     follows:  “Energy  Level”  (within),  “High”  (on  top),  and  “Low”  (underneath)  (C).     (Reprinted  with  permission  by  the  copyright  holder.)..........................................................   237     Figure  6.5.  Juxtaposition  of  Element  17  and  a  figure  used  with  Bio101  students  during     the  post-­‐Exam  2  review  session.  A  still  image  made  from  an  animation  shown  by  the     Bio101  professors  during  Lecture  2  (09-­‐27-­‐06),  but  also  the  element  (Element  17)     identified  by  the  EmSIM  3000  as  having  the  second  most  relevance  to  question  “52”     (A);  a  still  image  made  from  the  animation  as  it  appears  in  the  instructional  materials     (B).  Notice  the  (orange)  pear-­‐shaped  structure  visible  in  the  center  of  image;  and  a     close-­‐up  of  the  image  used  in  the  second  of  six  clicker  questions  asked  during  the     post-­‐Exam  2  review  session  (C).  The  text  in  the  upper  (blue)  portion  of  the  figure     contained  within  the  clicker  question  reads  as  follows  (starting  in  the  top  left  of  this     upper  portion  and  proceding  in  a  clockwise  direction):  “thylakoid  space,”  (multiple)     “H+,”  and  “FO  unit.”  The  text  in  the  lower  (orange)  portion  of  the  figure  reads  as     follows  (starting  in  the  top  left  of  this  lower  portion  and  proceding  in  a  clockwise     direction):  “stroma,”  “H+,”  “Stalk,”  “H+”  “F1  unit,”  “ATP,”  and  “ADP  +  Pi.”  Notice     the  similarities  between  the  (green)  structure  in  the  center  of  the  image  and  the     (orange)  pear-­‐shaped  in  the  previous  image.  (Reprinted  with  permission  by  the     copyright  holder.)..................................................................................................................241 xvi       INTRODUCTION         The  Case  of  the  Mutant  Spinach  Plant     I  spent  six  years  between  2004-­‐2009  in  and  around  a  number  of  different   undergraduate  biology  courses  in  the  Great  Lakes  region  of  the  United  States.  During  this   period,  I  gathered  a  wide  range  of  experiences  in  STEM  education.  For  instance,  I  logged  over   240  hours  of  observation  in  undergraduate  biology  classrooms  and  another  50  hours  in   undergraduate  biology  laboratories;  I  attended  no  fewer  than  200  lectures  and  had  the   opportunity  to  watch  the  interactions  between  a  handful  of  college  professors  and  almost  2000   undergraduate  science  majors;  I  sat  through  no  fewer  than  12  midterm  and  final  exams;  I   trained  a  cohort  of  professors  in  the  use  of  an  instructional  technology,  iClickers®,  a  real-­‐time   technology  designed  to  assess  student  learning  and  increase  student  engagement  during  class;  I   worked  with  an  interdisciplinary  team  on  the  use  of  lexical  analysis  software  to  analyze  student   responses  to  open-­‐ended  questions  pertaining  to  key  science  concepts;  I  spent  nearly  40  hours   interviewing  undergraduate  students  about  scientific  concepts  and  principles;  I  recorded  no   fewer  than  88  lectures  on  videotape;  I  logged  well  over  60  hours  in  planning  meetings  and   discussions  with  course  instructors  outside  of  their  classes;  finally,  I  collected  hundreds  of   digitally  and  non-­‐digitally  formatted  instructional  artifacts  produced  by  the  course  instructors.   Many  of  these  hours  were  spent  observing  the  day-­‐to-­‐day  practices  of  two  professors  and   nearly  four  hundred  students  in  a  cellular  biology  course,  Biological  Science  101  (hereafter   “Bio101”).   1           About  Bio101     Bio101  is  a  large-­‐enrollment,  introductory-­‐level  science  course  required  for  science   majors.  All  students  wishing  to  major  in  biological,  chemical,  physical,  earth,  space  or   environmental  sciences  must  successfully  complete  Bio101  in  order  to  earn  their  bachelor   degrees.  At  this  university,  Bio101  is  also  a  required  course  for  students  enrolled  in  the   university’s  preservice  science  teacher  training  program,  as  well  as  for  undergraduate  students   enrolled  in  other  ‘pre-­‐’  programs,  for  example,  pre-­‐medicine,  pre-­‐veterinary,  pre-­‐nursing  and   pre-­‐dentistry.   The  presence  of  preservice  science  teachers  in  Bio101  is  one  of  the  main  reasons  I  came   to  be  involved  in  the  course.  In  the  early  stages  of  my  Teacher  Education  Ph.D.  program,  I   received  financial  support  from  an  initiative  connected  to  the  Carnegie  Foundation’s  Teachers   For  a  New  Era  (TNE)  project.  One  of  the  guiding  principles  behind  the  TNE  project  was  to   encourage  “top-­‐level  collaboration  between  university  faculty  in  the  arts  and  sciences  with  the   school  of  education  faculty  to  ensure  that  prospective  teachers  are  well  grounded  in  specific   1 disciplines.”  Working  with  diverse  and  experienced  faculty  from  both  the  College  of  Education   and  the  College  of  Natural  Science,  I  participated  in  an  grant-­‐derived  initiative  whose  explicit   goal  was  to  find  and/or  develop  ways  of  improving  teaching  and  learning  in  introductory-­‐level   undergraduate  science  courses  in  which  preservice  science  teachers  were  known  to  be  in   attendance.  The  underlying  question  that  motivated  the  TNE-­‐supported  initiative  was  this:  In                                                                                                                   1.  Michigan  State  University  College  of  Education,  “A  New  Model  for  Teacher  Education,”  iii.   2       what  ways  can  introductory-­‐level  undergraduate  science  courses  more  positively  contribute  to   the  preparation  and  production  of  a  higher-­‐caliber  of  K-­‐12  science  teachers?   It  was  under  the  auspices  of  the  TNE-­‐supported  initiative  that  I  first  stepped  into  Bio101   with  research  responsibilities  in  fall  2004.  And  it  was  in  that  fall  course  that  I  first  met  the   professors,  both  of  who  were  veteran  faculty  members  and  experienced  research  biologists.  My   presence  in  Bio101  continued  during  summer  2005,  where  I  worked  with  one  of  the  professors   in  a  truncated,  six-­‐week  version  of  the  course.  In  addition  to  continuing  with  research   responsibilities,  I  was  also  the  course  teaching  assistant  and  technology  coordinator.  In  fall   2005  I  again  joined  the  two  professors  during  the  fifteen-­‐week  version  of  the  course.  Once   again,  I  had  responsibilities  that  included  research  and  technological  coordination.  In  fall  2006  I   joined  the  professors  for  yet  another  fifteen-­‐week  instantiation  of  the  course,  but  this  time   working  in  a  tripartite  capacity  as  researcher,  technology  coordinator,  and  laboratory  section   instructor.  In  fall  2007  I  returned  to  the  co-­‐taught  course  for  a  final  time  with  my   responsibilities  limited  to  research  and  instructional  technological  support.  In  total,  I  spent   substantial  time  in  five  different  instantiations  of  Bio101  between  2004-­‐2007,  with  the  most   sizeable  and  continuous  blocks  of  time  occurring  in  summer  2005,  fall  2006,  and  fall  2007.   Despite  the  occurrence  of  enough  interesting  moments  around  which  one  could   assemble  an  entire  career  of  research,  for  me  there  was  one  particular  type  of  moment  that   stood  out  against  the  broader  backdrop  of  this  biology  course.  In  this  dissertation,  I  will  simply   refer  to  it  as  the  application  moment.  The  case  of  the  mutant  spinach  plant  is  an  instance  of  the   application  moment  that  occurred  in  fall  2006.       3       The  Application  Moment     The  most  recognizable  feature  of  the  application  moment  is  rather  straightforward:   Usually  on  high-­‐stakes  assessments  (e.g.,  test  or  exams),  but  sometimes  during  class  and  on   homework  assignments,  teachers  or  professors  pose  questions  to  students—application   questions—whose  defining  feature  is  that  they  describe  some  sort  of  problem,  situation,  or   phenomenon  that  students  are  likely  to  find  entirely  new,  novel,  or  unfamiliar.  The  inclusion  of   these  novel  elements  is  both  deliberate  and  purposeful.  It  is  by  design.  Sometimes  known  in  the   trade  as  “twists,”  “tweaks,”  or  “curveballs”  (an  American  baseball  reference),  these  unfamiliar   elements  are  meant  to  make  students  hesitate,  scratch  their  head,  and  even  stumble   (intellectual  speaking).  These  elements  are  supposed  to  make  answering  the  application   question  a  less  straightforward  affair.  Their  intent  is  to  purposely  nudge  students  toward   intellectual  discomfort.   An  example  of  an  application  question  used  in  Bio101  appeared  on  Exam  2  as  question   “52.”  The  full  text  of  the  question  can  be  seen  in  Figure  1.       52)  Suppose  you  discovered  a  mutant  strain  of  spinach  in  which  the  thylakoid   membranes  were  slightly  permeable  to  H+  ions,  thus  allowing  a  slow  leakage   (remember  that  in  normal  membranes,  H+  is  not  permeable  at  all).  What  change     in  the  reactions  of  photosynthesis  might  occur  in  compensation  for  this  defect?     A) cyclic    photophosphorylation  would  increase   B) non-­‐cyclic  photophosphorylation  would  increase   C) O2  production  would  decrease   D) cyclic  photophosphorylation  would  decrease   E) non-­‐cyclic  photophosphorylation  would  decrease       Figure  1.  Question  “52,”  the  Mutant  Spinach  Question,  from  Bio101  Exam  2  (fall  2006).       4       I  came  to  know  this  particular  application  question  through  my  conversations  with  the   two  Bio101  professors  and  their  colleagues  as  “the  Mutant  Spinach  Question.”  Not  having  been   present  in  the  course,  readers  will  have  a  difficult  time  recognizing  the  unfamiliar  element,  but   nevertheless  it,  or  rather  they,  are  there.  The  unfamiliar  elements  are  collectively  held  by  the   two  phrases,  “mutant  strain  of  spinach”  and  “slow  leakage.”  Neither  of  these  phrases  had  ever   been  used  in  the  lectures,  assigned  readings,  or  homework  assignments  leading  up  to  Exam  2.   One  of  the  Bio101  professors  made  this  fact  quite  clear  in  a  statement  made  to  students  just   two  days  after  the  exam:  “You’ve  never  heard  about  spinach  with  leaky  membranes  before.   Right?  I  made  that  up...and  I  presented  to  you...and  I’m  asking  you  to  apply  your  newfound   2 scholarship  to  that,  OK?”   Here,  we  see  one  of  the  main  reasons  why  I  have  decided  to  call  the  Mutant  Spinach   Question  and  others  like  it  application  questions  (within  application  moments):  the  term  comes   3 straight  from  the  language  of  the  professors  themselves.  In  these  moments,  the  Bio101   professors  use  specially  designed  questions  that  ask  their  students  to  apply  their  newfound   scholarship  to  situations  and  problems  defined  by  new,  novel  or  unfamiliar  elements.  In  the   many  hats  I’ve  worn  in  science  education—teacher,  instructor,  teacher  educator,  professional   development  leader,  curriculum  designer,  and  researcher—I’ve  heard  these  same  questions   called  a  half  dozen  or  so  names  by  their  users  and  creators,  for  example,  “real-­‐world”  questions,   “transfer”  questions,  “reasoning”  questions,  “critical  thinking”  questions,  “higher-­‐order  thinking”   questions,  “challenge”  questions,  “analytical”  questions,  “weeder”  questions,  and  more.                                                                                                                   2.  Lecture  Transcript  (October  18,  2006):  00:20:44  -­‐  00:21:43.     3.  One  use  of  term  application  question  can  be  traced  back  to  the  work  of  the  American   psychologist  Benjamin  S.  Bloom  (1913-­‐1999)  (see  Bloom  et  al.  1956).   5       Although  others  are  free  to  choose  differently,  my  decision  to  call  them  application  questions— instead  of  using  one  of  those  other  aliases—is  because  I  want  to  ground  them  in  the  language   of  the  users,  that  is,  in  the  speech  of  those  in  whose  classroom  I  was  ever-­‐present.   One  of  the  more  interesting  functions  of  many  of  the  application  questions  used  in   Bio101,  including  the  Mutant  Spinach  Question,  is  that  the  professors  and  their  colleagues   often  used  them  to  identify  and  classify  certain  kinds  or  types  of  students.  For  example,  they   sometimes  used  students’  performance  on  application  questions  during  their  informal   conversations  with  one  another  to  talk  about  those  students  who  ‘got’  the  material  or  ‘grasped’   a  concept  versus  those  who  didn’t.  On  at  least  one  occasion,  the  classificatory  functionality  of   the  Mutant  Spinach  Question  was  coupled  with  a  predictive  one:  I  once  heard  one  of  the   Bio101  professors  say  of  the  Mutant  Spinach  Question,  “I  would  love  to  know,  could  I  just  ask   4 that  question  and  give  away  our  4.0s?”  Although  the  professor  made  the  statement  to  his   colleagues  with  a  full  measure  of  humor  in  it,  he  also  bestowed  it  with  an  equal  measure  of   seriousness.  He  and  others  in  the  room  genuinely  wondered  if  there  was  in  fact  a  strong   correlation  between  those  students  who  answered  the  Mutant  Spinach  Question  correctly  on   Exam  2  and  those  who  a)  earned  a  top  mark  on  Exam  2,  and  b)  would  end  up  earning  a  top   mark  in  the  course.  More  formally,  the  professors  and  their  colleagues  used  students’   performance  on  carefully  crafted  and/or  selected  collections  or  “clusters”  of  application   questions  to  facilitate  the  grouping  of  Bio101  students  into  different  categorical  schemes.  One   such  categorical  scheme  involved  the  diagnosis  of  students  as  having  one  of  three  types  of   difficulties:  a)  when  “students  interconvert  matter  and  energy,”  b)  when  “students  lose  track  of                                                                                                                   4.  Instructor  Interview  (June  2007):  00:81:18-­‐00:83:53.   6       matter  when  it  becomes  a  gas,”  and  c)  when  “students  do  not  follow  matter  and  therefore  do   5 not  catch  obvious  errors  in  their  thinking.”   For  their  part,  the  Bio101  students  had  their  own  names  for  such  questions,  including   “hard,”  “difficult”  and  “challenging,”  and  sometimes  “tricky,”  “unfair,”  and  even  “deceitful.”   This  was  certainly  the  case  with  the  Mutant  Spinach  Question,  a  fact  of  which  the  professors   were  made  only  too  aware  of  by  way  of  a  statistical  exam  report  provided  to  them  by  a   university  scoring  office.  According  to  the  report,  eighty  percent  of  the  nearly  four  hundred   Bio101  students  present  for  Exam  2  in  fall  2006  answered  the  Mutant  Spinach  Question   incorrectly—only  twenty  percent  of  the  students  had  selected  the  correct  answer.   Understandably  so,  this  kind  of  statistic  earned  the  Mutant  Spinach  Question  some  degree  of   notoriety  and  distinction  among  the  instructors  and  many  of  their  interested  colleagues.  It  was   the  most  missed  question  on  Exam  2  and  one  of  the  most  missed  questions  on  any  of  the  four   semester  exams.  When  the  professors  first  saw  that  eighty  percent  of  their  students  had   missed  the  Mutant  Spinach  Question  their  disappointment  was  clearly  visible.  I  could  see  in  the   expressions  on  their  faces  that  they  not  only  wanted  more  from  their  students—for  example,   more  effort,  more  commitment,  more  studying,  more  hard  work—but  also  more  from   themselves.  And  yet,  they  seemed  rather  unsure  of  exactly  what  to  do  in  their  role  as   facilitators,  as  experts,  as  teachers,  as  instructors...as  professors.  They  were  unsure  as  to  how   to  go  about  trying  to  raise  the  percentage  of  their  students  able  to  answer  the  Mutant  Spinach   Question  correctly.                                                                                                                   5.  Wilson  et  al.,  “Assessing  Students’  Ability,”  323-­‐331. 7       A  few  months  later,  the  professors  knowingly  and  generously  agreed  to  meet  with  me   and  revisit  their  disappointment  to  make  it  audible.  In  June  2007,  I  held  a  joint  interview  with   them.  The  Mutant  Spinach  Question  came  up  repeatedly  during  the  interview,  sometimes  at   my  prompting,  but  more  frequently  because  of  their  interest  and  volition.  It  was  apparent  to   me  by  the  end  of  the  interview  that  both  professors  were  still  at  a  loss  to  explain  with  any   confidence  the  high  failure  rate  precipitated  by  the  Mutant  Spinach  Question.  At  one  point  in   the  interview  they  explicitly  asked  me  for  help.  More  specifically,  they  asked  for  help  in  finding   ways  to  improve  student  performance  on  these  types  of  questions  in  the  future.  They  said  it   was  the  one  thing  they  wanted  most  out  of  their  involvement  and  participation  in  a  number  of   teaching-­‐  and  learning-­‐related  research  projects  in  which  their  course  had  assumed  a  central   role.  Once  asked,  I  must  admit  I  have  felt  duty-­‐bound  to  try  and  honor  it.  At  the  time,  I   understood  their  request—as  I  still  do—as  a  call  for  help  to  find  ways  to  improve  students’   ability  to  apply  existing  knowledge  to  novel  situations  and  unfamiliar  events.  Although  the   professors  may  not  recall  the  moment  with  the  same  clarity  and  force  as  I  do  now,  it  should  be   clear  to  them  and  others  that  I  took  their  request  seriously.  The  work  presented  in  dissertation   is  the  culmination  of  the  better  part  of  six  years  of  time  and  energy  devoted  to  their  request.   As  a  science  educator,  science  teacher  educator,  and  science  education  researcher,  I  am   expected  to  pay  close  attention  to  moments  in  classrooms  when  things  go  poorly  for  teachers   and/or  students.  Without  a  doubt,  question  “52”  was  a  clear-­‐cut  case  of  an  application  moment   gone  wrong.  Although  the  Mutant  Spinach  Question  was  just  one  of  many  application  questions   used  by  the  Bio101  professors  throughout  the  semester,  it  was  one  of  the  more  dramatic   examples  of  a  instance  in  which  learning  did  not  unfold  as  planned.  As  such,  the  Mutant   8       Spinach  Question  assumes  a  significant  role  within  this  dissertation,  but  it  is  admittedly  just  one   6 of  many  questions  that  could  have  assumed  a  starring  role.  Although  the  Bio101  instructors   invented  the  Mutant  Spinach  Question,  they  did  not  invent  application  questions.  I  know  this   because  I  have  seen  them  used  again  and  again  in  classrooms  and  curricula  since  first  becoming   involved  in  science  education  in  the  early  1990s.  I  have  seen  application  questions  used  in   primary,  secondary,  and  tertiary  science  education;  in  preservice  science  teacher  programs;  and   in  professional  development  programs  for  more  experienced  science  teachers.  I’ve  seen  them   used  with  rural,  urban,  and  suburban  students;  with  public  and  private  school  students;  and   with  students  from  six  continents.  In  other  words,  application  questions  are  trans-­‐age,  trans-­‐ discipline,  trans-­‐experience,  trans-­‐community,  and  trans-­‐continental.  They  are  a  well-­‐ established  feature  of  an  educational  landscape  that  extends  well  beyond  the  practices  found   in  an  undergraduate  biology  course.  Clearly,  application  questions  are  part  of  something  much   bigger,  more  layered,  more  interesting,  and  more  complex.   In  pursuit  of  the  goal  of  finding  ways  to  help  the  professors  improve  student   performance  on  application  questions  in  the  future,  I  trusted  that  the  professors  would  point   me  in  the  general  direction  this  bigger,  more  layered,  more  interesting,  more  complex   something.  Whenever  they  discussed  the  results  of  application  questions  with  students  in  the   classroom,  and  whenever  they  discussed  them  with  colleagues  (as  well  as  with  me)  outside  of                                                                                                                   6.  In  the  discourse  of  the  Bio101  instructors  and  their  colleagues,  a  number  of  these  questions,   like  the  Mutant  Spinach  Question  had  their  own  unique  identifiers.  For  example,  there  was  the   “Two  Viruses  Question,”  the  “Jared  Question,”  the  “Grape  Question,”  the  “Maple  Tree   Question,”  the  “Radish-­‐in-­‐the-­‐Dark  Question  (as  well  as  the  “Radish-­‐in-­‐the-­‐Light  Question”),   and  the  “Corn  Question.”   9       the  classroom,  they  almost  always  turned  in  their  conversations  to  something  they  routinely   called  “understanding.”     Overview  of  Remaining  Chapters     This  dissertation  is  a  study  of  a  concept,  specifically,  the  concept  of  understanding.  It  is   not  a  study  of  a  classroom,  a  teacher,  or  a  student.  It  is  not  a  study  of  teaching  or  learning.   Following  an  approach  developed  by  Bruno  Latour  and  others  working  in  Science  Studies,  my   approach  to  the  study  of  a  concept  is  to  observe  and  describe  that  concept  in  action.  I  take  the   first  steps  in  following  the  concept  of  understanding  in  Chapter  1  (“Understanding  is  All  the   Rage”),  where  I  chronicle  how  six  contemporary  science  education  texts  define  and  describe   understanding.  I  take  a  particular  interest  in  the  notion  of  learning  with  understanding,  which   seems  to  have  enlisted  many  supporters  in  science  education  over  the  past  25  years.  In  Chapter   2  (A  Distinct  Horizon  of  Expectations),  I  make  the  case  that  learning  with  understanding  is   predominantly  informed  by  the  psychological  sciences  through  a  process  Popkewitz  calls,  “the   alchemy  of  school  subjects.”  Although  unavoidable,  the  alchemy  transforms  how  scientists   learn  with  understanding  into  something  different  by  the  time  this  set  of  practices  makes  its   way  into  classrooms.  The  alchemy  is  neither  a  good  nor  a  bad  thing,  but  a  psychological   alchemy  gives  a  distinct  shape  to  what  it  means  to  learn  with  and  teach  for  scientific   understanding.  In  Chapter  3  (A  Horizontal  Shift)  and  Chapter  4  (A  Scientific  Horizon),  I  aim  to   disrupt  the  tenets  of  a  predominant  psychological  learning  theory—abstract  conceptual   learning  theory—by  familiarizing  readers  with  the  anthropological  and  philosophical  work  of   Latour,  who  offers  us  vital  empirical  insight  into  how  scientists  confront  unfamiliar  phenomena.   This  disruption  is  meant  to  prepare  the  ground,  so  to  speak,  not  only  for  a  radical  revision  of   10       psychological  notions  such  as  “abstraction”  and  “transfer,”  but  also  for  the  specific  purpose  of   trying  to  make  abstract  conceptual  learning  theory  more  inclusive  and  less  constraining  for   teachers  and  students.  The  general  form  of  my  contention  is  that  abstract  conceptual  learning   theory  doesn’t  have  to  be  so  individualized,  secretive,  clandestine,  rationalistic,  and   universalized.  In  other  words,  the  historically  and  culturally  specific  formulation  of  abstract   conceptual  learning  theory  is  not  inevitable.  It  can  be  different.  It  can  be  otherwise.  More   specifically,  it  can  be  more  inclusive,  visible,  material,  empirical,  and  perhaps  even  more   scientific.  Chapter  5  (Horizons  In  Action)  and  Chapter  6  (New  Horizons  for  Scientist  Teachers)   takes  the  concepts  and  sensibilities  developed  in  Chapters  3  and  4  and  embeds  them  within  an   example  of  instruction  in  an  undergraduate  biology  course.  Here,  two  distinct  styles  of  science   teaching  and  learning—one  psychological  and  the  other  empirical—are  contrasted  in  an   experiment  called  a  “bioeducational  assay.”  The  function  of  this  assay  is  to  evaluate  the  two   styles  according  to  traits  or  characteristics  such  as  relative  purity,  composition,  activity,  and   potency,  but  it  also  allows  us  to  make  statements  about  the  overall  effectiveness  of  the  styles   relative  to  some  important  aims  and  goals  of  U.S.  science  education.         11       CHAPTER  1   UNDERSTANDING  IS  ALL  THE  RAGE         Understanding  is  a  tricky  thing  to  get  one's  mind  around.  We  want   students  to  be  able  to  employ  knowledge  in  flexible  and  novel   ways,  to  develop  coherent  networks  of  concepts,  to  use  what   they  learn  in  school  to  understand  the  world  around  them,  and  to   develop  an  interest  in  lifelong  intellectual  pursuits.  But  to  help   students  achieve  such  understanding  is  no  mean  feat.     —Rebecca  Simmons,  Educational   Leadership  (February  1994)       Four  Centuries  of  Enthusiasm     For  those  readers  attuned  to  Western  intellectual  history  and  the  Modern  Age   (hereafter  Modernity),  the  naming  of  understanding  by  the  Bio101  professors  will  come  as  little   to  no  surprise.  In  this  simple  act,  the  professors  are  vocalizing  a  construct  to  which  many   historical  figures  have  given  substantial  attention.  In  fact,  understanding  has  forged  a  visible   trail  through  Western  culture  for  at  least  the  past  four  hundred  years.  Western  philosophers,  in   particular,  have  taken  a  keen  interest  in  it.  During  the  Enlightenment,  a  number  of  the  most   noted  natural  philosophers  wrote  extensively  about  the  notion  of  human  understanding   including  Descartes  (1596-­‐1650),  Locke  (1632-­‐1704),  Leibniz  (1646–1716),  Hume  (1711-­‐1776)   7 and  Kant  (1724–1804)  among  others.  More  recently,  and  perhaps  more  relevant  to  the                                                                                                                   7.  For  example,  see  Descartes’s  Rules  for  the  Direction  of  the  Mind  (1684),  Locke’s  An  Essay   Concerning  Human  Understanding  (1689),  Lebniz’s  New  Essays  Concerning  Human   Understanding  (finished  in  1704  but  not  published  until  1765),  Hume’s  An  Enquiry  Concerning   12       concerns  of  contemporary  science  educators,  the  American  philosopher,  psychologist,  and   progressive  educator  John  Dewey  (1859-­‐1952)  heaped  praise  upon  understanding  at  the  start   of  the  20th  century  by  way  of  a  warning  to  all  Americans  as  to  the  steep  price  of  failing  to   acquire  it.  As  Dewey  once  wrote,  “To  grasp  a  meaning,  to  understand,  to  identify  a  thing  in  a   situation  in  which  it  is  important,  are  thus  equivalent  terms;  they  express  the  nerves  of  our   intellectual  life.  Without  them  there  is  (a)  lack  of  intellectual  content,  or  (b)  intellectual   8 confusion  and  perplexity,  or  else  (c)  intellectual  perversion—nonsense,  insanity.”   A  more  forceful  case  for  the  importance  understanding  would  be  difficult  to  make.  In   the  absence  of  understanding,  Dewey  claims,  only  intellectual  confusion,  perplexity,  and   perversion  can  be  expected  to  thrive  in  human  societies.  Devoid  of  understanding,  we  see  only   individuals  who  are  at  once  nonsensical  and  insane.   Enthusiasm  in  Contemporary  Science  Education   Rather  than  wane  since  the  early  years  of  the  20th  century,  education’s  enthusiasm  for   9 both  teaching  for  and  learning  with  understanding  has  significantly  waxed.  In  science   education,  the  case  for  the  importance  for  understanding  has  taken  a  number  of  forms,  but  two   of  most  influential  documented  forms  published  in  the  past  25  years  are  entirely  continuous   and  consistent  with  the  case  for  understanding  articulated  by  Dewey  in  the  early  1900s.  For                                                                                                                                                                                                                                                                                                                                                                       Human  Understanding  (1748),  and  Kant’s  three  Critiques:  the  Critique  of  Pure  Reason   (1781/1787),  the  Critique  of  Practical  Reason  (1788),  and  the  Critique  of  the  Power  of  Judgment   (1790).   8.  Dewey,  How  We  Think,  117. 9.  As  one  observer  noted  while  attending  to  mathematics  education,  “The  concern  for  teaching   for  understanding  is  as  old  as  the  20th  century.  The  intuitive  rightness  of  learning  with   understanding  [...]  has  led  to  the  widespread  importance  of  developing  students’   understanding...”  Fennema  and  Romberg,  “Preface,”  ix  (emphasis  added).     13       example,  eighty  years  after  the  initial  publication  of  Dewey’s  How  We  Think,  the  American   Association  for  the  Advancement  of  Science’s  Project  2061  put  forth  a  forceful  case  for  the   importance  of  understanding  in  their  landmark  reform  publication  Science  For  All  Americans:   Education  has  no  higher  purpose  than  preparing  people  to  lead  personally  fulfilling  and   responsible  lives.  For  its  part,  science  education—meaning  education  in  science,   mathematics,  and  technology—should  help  students  to  develop  the  understandings  and   habits  of  mind  they  need  to  become  compassionate  human  beings  able  to  think  for   themselves  and  to  face  life  head  on.  It  should  equip  them  also  to  participate   thoughtfully  with  fellow  citizens  in  building  and  protecting  a  society  that  is  open,  decent,   and  vital.  America's  future—its  ability  to  create  a  truly  just  society,  to  sustain  its   economic  vitality,  and  to  remain  secure  in  a  world  torn  by  hostilities—depends  more   than  ever  on  the  character  and  quality  of  the  education  that  the  nation  provides  for  all   10 of  its  children.     Six  years  after  Science  For  All  Americans  was  published,  the  National  Research  Council   put  forward  their  case  for  understanding  in  another  landmark  reform  publication,  the  National   Science  Education  Standards:   Why  is  science  literacy  important?  First,  an  understanding  of  science  offers  personal   fulfillment  and  excitement—benefits  that  should  be  shared  by  everyone.  Second,   Americans  are  confronted  increasingly  with  questions  in  their  lives  that  require  scientific   information  and  scientific  ways  of  thinking  for  informed  decision  making.  And  the   collective  judgment  of  our  people  will  determine  how  we  manage  shared  resources— such  as  air,  water,  and  national  forests.     Science  understanding  and  ability  also  will  enhance  the  capability  of  all  students  to  hold   meaningful  and  productive  jobs  in  the  future.  The  business  community  needs  entry-­‐level   workers  with  the  ability  to  learn,  reason,  think  creatively,  make  decisions,  and  solve   problems.  In  addition,  concerns  regarding  economic  competitiveness  stress  the  central   importance  of  science  and  mathematics  education  that  will  allow  us  to  keep  pace  with   11 our  global  competitors.                                                                                                                     10.  American  Association  for  the  Advancement  of  Science  (AAAS),  Science  for  All  Americans,  xiii. 11.  NRC,  National  Science  Education  Standards,  11-­‐12.   14       As  did  Dewey,  both  the  American  Association  for  the  Advancement  of  Science  (AAAS)   and  the  National  Research  Council  (NRC)  see  the  price  of  not  acquiring  understanding  as   infinitely  costly.  In  the  absence  of  properly  developed  “understanding(s),”  “habits  of  mind,”  and   “scientific  ways  of  thinking”—the  authors  of  both  landmark  reform  documents  forewarn—only   indifference,  dependence,  uninformed  decision  making,  and  faint-­‐heartedness  can  be  expected   to  thrive.   As  recently  as  June  2013,  the  release  of  the  Next  Generation  Science  Standards   demonstrates  that  this  same  conceptual  backbone  remains  largely  unaltered.  As  its  authors   communicate  in  the  opening  sentence  in  their  Executive  Summary:   There  is  no  doubt  that  science—and,  therefore,  science  education—is  central  to  the   lives  of  all  Americans.  Never  before  has  our  world  been  so  complex  and  science   knowledge  so  critical  to  making  sense  of  it  all.  When  comprehending  current  events,   choosing  and  using  technology,  or  making  informed  decisions  about  one’s  healthcare,   science  understanding  is  key.  Science  is  also  at  the  heart  of  the  United  States’  ability  to   continue  to  innovate,  lead,  and  create  the  jobs  of  the  future.  All  students—whether   they  become  technicians  in  a  hospital,  workers  in  a  high  tech  manufacturing  facility,  or   12 Ph.D.  researchers—must  have  a  solid  K–12  science  education.     Once  again,  understanding  is  seen  as  preeminent.  Without  it,  the  thinking  goes,  only   nonsense,  incomprehension,  and  indecision  can  be  expected  to  thrive.  And  so,  we  see  a   recurring  theme  in  science  education  throughout  the  1990s,  as  well  as  now  into  the  second  full   decade  of  the  2000s:  individuals,  families,  and  societies,  but  also  governments,  economies,  and   nation  states,  are  widely  reported  to  pay  a  high  price  for  misunderstanding(s)  in  the  areas  of                                                                                                                   12.  NRC,  “Executive  Summary,”  1. 15       13 science,  mathematics,  engineering,  and  technology.  Understanding  is  widely  billed  as  a   phenomenon  that  is  “of  paramount  importance  for  education,”  and  this  is  this  is  especially  true   in  education  research  and  development  where  understanding  is  widely  heralded  as  one  of  the   14 cornerstones  of  STEM  education  reform.  In  other  words,  in  much  of  K-­‐16  STEM  education   15 understanding  has  been—and  still  remains—all  the  rage.   Today’s  science  students—whether  primary,  secondary,  tertiary,  or  lifelong—are   expected  to  read,  listen,  and  learn  with  understanding;  science  teachers  are  encouraged  to   teach  and  assess  for  understanding;  science  curriculum  is  expected  to  promote  and  support   understanding;  and  professional  development  programs  are  told  to  deepen  science  teachers’   understanding  (e.g.,  of  students,  content,  and  pedagogy).  In  many  respects,  understanding  is   educational  equivalent  of  truffles  (or  bacon):  The  taste  of  everything  said  to  be  enhanced  by  its   mere  presence.   Understanding  Understanding   The  reach  and  influence  of  understanding  even  gives  distinct  form  to  two  of  the  most   high-­‐profile  constructs  in  science  education  reform  over  the  past  25  years:  science  literacy  and   scientific  inquiry.  For  example,  an  important  part  of  science  literacy  is  said  to  involve   16 “understanding  some  of  the  key  concepts  and  principles  of  science.”  In  addition,  scientific   inquiry  is  said  to  refer  to  “the  activities  of  students  in  which  they  develop  knowledge  and                                                                                                                   13.  Since  approximately  2000,  these  four  disciplines—science,  technology,  engineering,  and   mathematics—are  often  collectively  referred  to  as  the  “STEM”  disciplines.   14.  NRC,  How  People  Learn:  Brain,  8.   15.  I  thank  my  advisor  and  dissertation  director,  Lynn  Fendler,  for  allowing  me  to  play  off  of  a   phrase  she  uses  in  one  of  her  publications  (see  Fendler  2006).   16.  AAAS,  Science  for  All  Americans,  xvii.   16       understanding  of  scientific  ideas,  as  well  as  an  understanding  of  how  scientists  study  the   17 natural  world.”  Thus,  at  times  understanding  functions  as  if  it  were  a  web,  network,  or  some   sort  of  electromagnetic  field:  one  can  hardly  move  from  place  to  place  in  science  education   without  coming  into  contact  with  or  being  affected  by  at  least  one  of  its  extensive  threads,   tendrils,  or  resonant  forces.   Those  working  within  science  education  research  and  development  must  be  so   acclimated  to  its  almost  constant  companionship  that  I  suspect  it  would  be  rather  difficult  if   they  were  to  try  to  imagine  their  profession  without  it.  As  one  researcher/developer  writes,   “Almost  everyone  involved  in  science  education  research  and  development  claims  'learning   18 with  understanding  for  all'  as  our  basic  goal.”  Another  contributor  points  out  that  many  of   America’s  national  goals  and  standards  for  science/mathematics  curricula  and  teaching  now   19 reflect  a  deep  affection  for  and  commitment  to  learning  with  understanding.  In  the  next   section,  I  want  to  draw  specific  attention  the  notion  of  learning  with  understanding  so  that  we   (you  and  I)—still  in  the  early  stages  of  finding  ways  to  improve  student  understanding—may   come  to  recognize  some  of  its  more  defining  features.                                                                                                                       17.  NRC,  National  Science  Education  Standards,  23. 18.  Anderson,  “Designing  Systems,”  para.  6.   19.  As  the  authors  of  the  NRC’s  Learning  and  Understanding  write:  “Learning  with   understanding  is  strongly  advocated  by  leading  mathematics  and  science  educators  and   researchers  for  all  students,  and  also  is  reflected  in  the  national  goals  and  standards  for   mathematics  and  science  curricula  and  teaching  (American  Association  for  Advancement  of   Science  [AAAS],  1989,  1993;  National  Council  of  Teachers  of  Mathematics  [NCTM],  1989,  1991,   2000;  NRC,  1996).”  NRC,  Learning  and  Understanding,  118. 17       Learning  With  Understanding   In  my  tracing  of  the  notion  of  learning  with  understanding  in  the  literature,  I  have   noticed  that  this  construct  has  come  to  have  no  fewer  than  five  defining  features  associated   with  it.  The  first  of  these  features  is  that  learning  with  understanding  is  routinely  associated   with  the  possession  of  something.  Most  often,  this  something  is  said  to  include  entities  such  as   ‘information,’  ‘skills,’  ‘previous  learning’  and  ‘prior  knowledge’  (among  other  entities).  I  shall   endeavor  to  refer  to  these  entities  collectively  as  a  “base  of  knowledge”  or,  more  succinctly,  a   “knowledge  base.”  Therefore,  students  who  learn  with  understanding  are  said  to  possess  a   knowledge  base.  I  will  refer  to  this  discursive  feature  of  learning  with  understanding  as  the   knowledge  base.  The  second  of  these  features  is  that  learning  with  understanding  is  routinely   associated  with  a  knowledge  base  that  is  defined  by  such  qualities  as  ‘continuity,’  ‘coherence,’   and  ‘connectedness’  as  opposed  to,  say,  ‘discontinuity,’  ‘fragmentation,’  and  ‘isolation.’   Therefore,  students  who  learn  with  understanding  are  said  to  possess  a  certain  kind  of   knowledge  base,  that  is,  one  that  is  both  deep  (in  quantity)  and  rich  (in  connections).  I  will  refer   to  this  particular  discursive  feature  as  coherence.  The  third  of  these  features  is  that  learning   with  understanding  is  routinely  associated  with  a  deep,  rich  knowledge  base  that  is  subjected   to  various  actions,  processes  or  performances  such  as  ‘application,’  ‘extension’  or  ‘transfer.’   Therefore,  students  who  learn  with  understanding  are  said  to  be  able  to  apply  their  knowledge,   extend  their  skills,  and/or  transfer  their  learning.  I  will  refer  to  this  particular  discursive  feature   as  transfer.  The  fourth  of  these  features  is  a  corollary  to  the  third.  Students  who  learn  with   understanding  are  said  to  be  able  to  apply,  extend,  and/or  transfer  their  deep,  rich  knowledge   base  to  certain  types  or  kinds  of  situations.  Many  of  these  situations  are  said  to  be  ‘new,’   18       ‘different,’  ‘novel,’  ‘unfamiliar,’  ‘unscripted’  or  ‘strange.’  In  other  words,  these  situations  are   said  to  lie  just  beyond  or  outside  of  the  plain,  ordinary,  initial,  and/or  familiar  realm  of  students’   typical  everyday  experience(s).  To  put  this  differently,  students  who  learn  with  understanding   are  said  to  be  able  to  apply,  extend,  and/or  transfer  their  deep,  rich  knowledge  base  to   situations  beyond  the  original  context  of  learning.  I  will  refer  to  this  particular  discursive  feature   as  extrapolation.  The  fifth  defining  feature  is  that  learning  with  understanding  is  routinely   associated  with  the  mind  or  brain.  In  the  discourse  of  learning  with  understanding,  not  only  is   the  knowledge  base  commonly  associated  with  the  mind/brain,  so  too  are  the  various  actions,   processes,  and/or  performances  students  are  said  to  need  to  perform  when  demonstrating   their  understanding.  Students  who  learn  with  understanding  are  said  to  be  able  to  mentally  or   cognitively  apply,  extend,  and/or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond   the  original  context  of  learning.  Thus,  I  will  refer  to  this  particular  discursive  feature  as   cognition.     To  summarize,  the  five  features  are  knowledge  base,  coherence,  transfer,  extrapolation,   and  cognition.   This  characterization  should  make  it  clear  that  in  this  dissertation  I  am  studying  a   concept,  specifically,  the  concept  of  learning  with  understanding.  It  is  not  a  study  of  a   classroom,  a  teacher,  or  a  student.  It  is  not  a  study  of  teaching  or  learning.  My  overall  approach   is  to  study  the  understanding  while  it  is,  so  to  speak,  in  action—in  this  chapter,  deployed  within   six  texts  that  circulate  widely  among  communities  of  science  educators  and  science  education   researchers.  The  six  texts  presented  below  are  meant  to  illustrate  the  consistent  use  of  these   five  distinct  discursive  features.  Collectively,  however,  they  help  us  see  a  particular  way  in   19       which  the  notion  of  learning  with  understanding  has  been  constructed  during  the  period  of   years  from  1990-­‐2013.  There  are  at  least  two  sound  reasons  for  limiting  the  scope  of  this   review  to  this  particular  historical  period.  First,  this  span  of  years  subsumes  the  entire  period  of   time  during  which  the  Bio101  professors  had  been  teaching  the  course  together,  as  well  as   many  of  the  years  they  taught  the  course,  or  one  similar  to  it,  separately.  If  these  professors   were  consulting  the  literature  or  their  colleagues  during  this  period  for  insight  on  learning  with   understanding,  then  the  six  examples  presented  below  typify  what  they  might  have  read  or   heard.  Second,  and  perhaps  more  importantly,  this  period  encapsulates  an  era  that  one  group   20 of  science  educators  has  named,  “The  Age  of  Reform  in  Science  Education.”  The  Age  of   Reform  in  Science  Education  (or  Reform  Age)  began  in  approximately  1990  when  several   organizations  took  the  initiative  to  provide  goals,  standards,  frameworks,  and/or  curriculum   21 recommendations  designed  to  increase  student  achievement  on  a  national  basis.  In  limiting   my  review  to  literature  published  during  the  Reform  Age,  I  am  assuming  that  a)  the  discursive   construction  of  learning  with  understanding  by  those  writing  within  the  Reform  Age  is  mostly— but  not  always—continuous  with  one  another,  and  b)  the  discursive  construction  of  learning   with  understanding  by  those  writing  within  the  Reform  Age  is  mostly—but  not  always— discontinuous  with  those  constructing  it  in  Ages  immediately  preceding  the  Reform  Age—for   22 example,  the  so-­‐called  “Age  of  Crisis”  (1970-­‐1989)  and  “Golden  Age”  (1950-­‐1969).                                                                                                                   20.  This  is  a  wonderful  term  used  by  the  University  of  Arkansas’s  Project  to  Advance  Science   Education  (PASE)  on  their  “Interactive  Timeline  -­‐  Science  Education  in  the  U.S.A.”  As  of  August   2013,  the  timeline  is  still  accessible  at  http://coehp.uark.edu/pase/itseusa/.     21.  For  an  accessible  history  of  the  Reform  Age  see  DeBoer  1991.   22.  The  “Age  of  Crisis”  and  “Golden  Age”  are  also  terms  used  by  PASE  on  their  “Interactive   Timeline  -­‐  Science  Education  in  the  U.S.A.”  (see  note  18  above).     20       It  is  important  to  note  that  this  review  of  the  history  of  understanding  in  science   education  is  far  from  exhaustive.  It  does  not  claim  to  include  every  individual,  group,  or   organization  that  contributed  to  the  notion  of  learning  with  understanding  during  the  Reform   Age.  Instead,  the  selection  of  texts  included  below—which  is  followed  by  the  spoken  “text”  of   the  Bio101  professors—are  meant  to  illustrate  its  five  distinct  discursive  features  so  that  we   may  see  with  more  clarity  and  precision  the  margins  and/or  boundaries  of  this  notion’s   23 envelope  of  possibilities,  or  rather,  its  horizon  of  expectations.   Example  #1:  Science  for  All  Americans  (1990)   Science  For  All  Americans  (SFAA)  is  a  product  of  AAAS’s  Project  2061.  AAAS’s  Project   2061  has  produced  a  number  of  influential  publications  throughout  the  Reform  Age  including   SFAA  (1990),  Benchmarks  for  Science  Literacy  (1993),  Blueprints  for  Reform  (1998),  Designs  for   Science  Literacy  (2001),  and  the  Atlas  of  Science  Literacy,  Volumes  1  (2001)  and  2  (2007).   Project  2061  has  been  described  as  “a  long-­‐term  initiative  of  the  American  Association  for  the   Advancement  of  Science  (AAAS)  to  help  all  Americans  become  literate  in  science,  mathematics,   and  technology.  To  achieve  that  goal,  Project  2061  conducts  research  and  develops  tools  and   services  that  educators,  researchers,  and  policymakers  can  use  to  make  critical  and  lasting   24 improvements  in  the  nation’s  education  system.”  Project  2061  described  SFAA  in  this  way,   “This  book  is  about  science  literacy.  Science  for  All  Americans  consists  of  a  set  of   recommendations  on  what  understandings  and  ways  of  thinking  are  essential  for  all  citizens  in  a                                                                                                                   23.  For  the  British  historian,  philosopher,  and  educator  Stephen  Toulmin  (1922-­‐2009),  horizons   of  expectation  are  those  entities  that  “mark  limits  to  the  field  of  action  in  which,  at  the  moment,   we  see  it  as  possible  or  feasible  to  change  human  affairs.”  Toulmin,  Cosmopolis,  p.  1. 24.  AAAS,  “About  Project  2061,”  para.  1.   21       25 world  shaped  by  science  and  technology.”  The  phrase  “learning  with  understanding”  is  never   used  in  SFAA,  so  we  must  pursue  statements  about  this  notion  alternatively  through  its  use  of   the  term  understanding.  Fortunately,  SFAA  uses  the  term  understanding  in  its  sixteen  main   sections  no  fewer  than  sixty-­‐eight  times.     Although  this  text  claims  to  convey  the  “levels”  and  “contexts”  of  understanding   appropriate  for  all  people,  it  does  not  contain  an  explicit  definition  of  the  term  understanding.   Nevertheless,  there  are  instances  in  the  text  that  communicate  what  the  authors  of  SFAA  think   understanding  is,  as  well  as  what  they  think  it  is  not.  An  example  of  one  of  these  instances  is   found  in  the  Introduction,   So  Science  for  All  Americans  represents  the  informed  thinking  of  the  science,   mathematics,  and  technology  communities  as  nearly  as  such  a  thing  can  be  ascertained.   It  is  a  consensus,  to  be  sure,  but  not  a  superficial  one  of  the  kind  that  would  result  from,   say,  a  survey  or  a  conference.  The  process  cannot  be  said  to  have  led  to  the  only   plausible  set  of  recommendations  on  the  education  in  science,  mathematics,  and   technology  for  all  children,  but  it  certainly  yielded  recommendations  in  which  we  can   have  confidence.  It  is  an  ambitious  but  attainable  vision  that  emphasizes  meanings,   connections,  and  contexts  rather  than  fragmented  bits  and  pieces  of  information  and   favors  quality  of  understanding  over  quantity  of  coverage.  Is  not  that  precisely  the  kind   26 of  education  that  we  should  want  for  all  Americans?     Near  the  end  of  this  passage  we  see  an  example  of  the  second  discursive  feature  of   learning  with  understanding—coherence  (i.e.,  students  who  learn  with  understanding  are  said   to  possess  a  certain  kind  of  knowledge  base,  that  is,  one  that  is  both  deep  (in  quantity)  and  rich   (in  connections)).  In  contrasting  “quality  understanding”  with  “quantity  of  coverage,”  the   authors  of  SFAA  associate  understanding  with  things  like  “meanings,”  “connections”  and                                                                                                                   25.  AAAS,  Science  for  All  Americans,  xiii.   26.  AAAS,  Science  for  All  Americans,  xxiii  (emphasis  added). 22       “contexts,”  whereas  coverage  is  associated  with  “fragmented  bits”  and  “pieces  of  information.”   Thus,  in  this  text  we  see  that  understanding  is  not  about  fragmentation  and  isolation,  it’s  about   coherence  and  connectedness.   Example  #2:  National  Science  Education  Standards  (1996)   The  National  Research  Council  (NRC)  publishes  the  National  Science  Education  Standards   (NSES).  The  NRC  has  been  described  as  the  “working  arm”  of  the  U.S  National  Academies  and  is   responsible  for  carrying  out  the  studies  endorsed  by  its  three  major  branching  organizations,   the  National  Academy  of  Sciences  (NAS),  National  Academy  of  Engineering  (NAE),  and  the   Institute  of  Medicine  (IOM).  The  NRC  has  published  influential  group-­‐reviewed  reports   throughout  the  Reform  Age.  They  have  published  many  important  documents  during  the   Reform  Age,  but  by  far  one  of  their  most  influential  documents  thus  far  is  the  National  Science   Education  Standards  (hereafter  NSES)  published  in  1996.  As  is  the  case  with  AAAS  Project   2061’s  SFAA,  the  phrase  “learning  with  understanding”  is  never  used  in  the  NSES,  so  we  must   pursue  statements  about  this  notion  through  its  use  of  the  term  understanding.  Fortunately,   the  NSES  uses  the  term  understanding  in  its  first  ten  main  sections  no  fewer  than  four  hundred   and  thirty-­‐five  times.     Understanding  is  defined  explicitly  in  Chapter  2  (“Principles  and  Definitions”)  at  the   same  time  as  the  term  knowledge:   KNOWLEDGE  AND  UNDERSTANDING  [emphasis  in  the  original].  Implementing  the   National  Science  Education  Standards  implies  the  acquisition  of  scientific  knowledge  and   the  development  of  understanding.  Scientific  knowledge  refers  to  facts,  concepts,   principles,  laws,  theories,  and  models  and  can  be  acquired  in  many  ways.  Understanding   science  requires  that  an  individual  integrate  a  complex  structure  of  many  types  of   knowledge,  including  the  ideas  of  science,  relationships  between  ideas,  reasons  for  these   relationships,  ways  to  use  the  ideas  to  explain  and  predict  other  natural  phenomena,   23       and  ways  to  apply  them  to  many  events.  Understanding  encompasses  the  ability  to  use   knowledge,  and  it  entails  the  ability  to  distinguish  between  what  is  and  what  is  not  a   scientific  idea.  Developing  understanding  presupposes  that  students  are  actively   27 engaged  with  the  ideas  of  science  and  have  many  experiences  with  the  natural  world.       In  this  passage  we  see  examples  of  four  of  the  five  discursive  features  of  learning  with   understanding.  With  respect  to  the  first  feature,  knowledge  base,  we  get  a  precise  formulation   of  the  different  components  thought  to  constitute  a  proper  knowledge  base.  According  to  the   NSES,  “scientific”  knowledge  includes  elements  such  as  “facts,  concepts,  principles,  laws,   theories,  and  models.”  With  respect  to  the  second  feature,  coherence,  we  see  that  the  NSES   stipulates  that  understanding  requires  individuals  to  “integrate  a  complex  structure  of  many   types  of  knowledge.”  With  respect  to  the  third  and  fourth  features,  transfer  and  extrapolation,   we  see  that  NSES  combines  them  together  in  phrases  such  as  “ways  to  use  the  ideas  to  explain   and  predict  natural  phenomena,”  “ways  to  apply  them  to  many  events,”  and  “the  ability  to  use   knowledge.”  Each  of  these  phrases  speaks  directly  to  the  transfer  feature  (e.g.,  when  drawing   from  the  notion  of  knowledge  ‘application’  or  knowledge  ‘use’),  as  well  as  to  the  extrapolation   feature  (e.g.,  when  asking  individuals  to  use/apply  their  complexly  structured  knowledge  to   explain  and  predict  “natural  phenomena”  and  unfamiliar  “events”).  We  do  not  see  the  fifth   feature,  cognition,  explicitly  mentioned  in  this  same  section.  Nevertheless,  a  few  pages  earlier   in  the  same  chapter  the  NSES  authors  define  science  learning  as  an  “active  process,”  and  then   clarify  the  term  active  process  by  saying  that  it  “implies  physical  and  mental  activity.  Hands-­‐on   28 activities  are  not  enough—students  also  must  have  ‘minds-­‐on’  experiences.”  Here,  we  can                                                                                                                   27.  NRC,  National  Science  Education  Standards,  p.  23  (emphasis  added).   28.  NRC,  National  Science  Education  Standards,  p.  20  (emphasis  added).   24       see  that  cognition  is  a  key  feature  of  what  the  NSES  authors  mean  when  they  talk  about   learning  science.  Thus,  we  might  safely  presume  that  the  NSES’s  notion  of  learning  science  with   understanding  would  also  necessarily,  but  not  sufficiently,  include  an  element  of   29 mental/cognitive  activity.   Example  #3:  National  Center  for  Improving  Student  Learning  and  Achievement  in  Mathematics   and  Science  (1995-­‐2004)     The  National  Center  for  Improving  Student  Learning  and  Achievement  in  Mathematics   and  Science  (NCISLA)  is  a  collaborative  research  group  engaged  in  long-­‐term  studies  and   teacher  professional  development  programs  in  science  and  mathematics.  Its  participating   members  work  in  six  higher  education  institutions—five  in  the  U.S  and  one  in  The  Netherlands.   First  formed  in  1995,  they  were  charged  by  the  U.S.  Department  of  Education  to  assemble  a   30 research  base  about  ways  science  and  mathematics  instruction  can  be  improved.  Although   their  main  focus  is  to  advance  effective  reform  of  science  and  mathematics  education  mainly  at   the  K-­‐12  level,  NCISLA’s  construction  of  the  notion  of  learning  with  understanding  is  consistent   with  the  constructions  of  other  documents  targeting  reform  throughout  both  secondary  and   tertiary  science  education.  I  did  not  query  a  single  NCISLA  text  for  its  use  of  the  term   understanding  or  for  the  phrase  “learning  with  understanding.”  Instead,  I  queried  a  number  of   documents  and  statements  appearing  on/in  their  entire  website.   On  their  website,  NCISLA  reports  the  aim  of  the  center’s  research  as,                                                                                                                       29.  We  can  see  that  the  NSES  define  science  learning  not  only  as  “minds-­‐on,”  but  also  as   “hands-­‐on.”  Although  I  focus  exclusively  on  the  minds-­‐on  component  of  their  definition  here,  I   will  return  to  the  important  notion  of  hands-­‐on  science  learning  in  Chapter  6     30.  For  more  about  NCISLA  (1995-­‐2004)  see  http://ncisla.wceruw.org/index.html. 25       to  identify  ways  that  students  can  learn  mathematics  and  science  with  understanding.   To  this  end,  researchers  designed  and  evaluated  instruction  that  can  enhance  students'   abilities  to  connect  ideas  and  concepts  and  apply  what  they  know  to  new  situations  and   phenomena.  Researchers  reasoned  that  these  abilities,  in  addition  to  students'  mastery   31 of  basic  skills,  are  vital  for  students  facing  an  increasingly  complex  world.     In  this  short  passage  we  see  examples  of  four  of  the  five  discursive  features  of  learning   with  understanding.  The  knowledge  base  and  coherence  features  are  combined  within  a  single   sentence.  According  to  NCILSA,  a  proper  knowledge  base  includes  “ideas”  and  “concepts”   which  are  connected.  We  saw  a  similar  idea  in  the  NSES—both  constructions  emphasize  the   continuity,  coherence,  and  connectedness  of  the  knowledge  base.  The  transfer  and   extrapolation  features  are  also  combined  within  a  single  sentence.  When  NCISLA  uses  phrases   such  as  “to  connect  ideas  and  concepts  and  apply  what  they  know  to  new  situations  and   phenomena,”  they  speak  directly  to  the  active,  processual  or  performative  component  of   learning  with  understanding  (in  this  instance,  knowledge  ‘application’),  as  well  as  to  the   situational  one  (e.g.,  to  apply  connected  ideas  and  concepts  to  “new  situations  and   phenomena”).   We  see  an  example  of  the  fifth  feature,  cognition,  in  NCISLA’s  articulation  of  the   conceptual  basis  for  their  work,   The  conceptual  basis  for  our  work  at  the  National  Center  for  Improving  Student  Learning   and  Achievement  (NCISLA)  is  centered  on  learning  with  understanding.  It  is  difficult  to   define  understanding  without  engaging  in  circular  argument.  Because  virtually  all   complex  ideas  or  processes  can  be  understood  at  a  number  of  levels  and  in  quite   different  ways,  we  characterize  understanding  as  emerging  or  developing.  As  a   consequence,  we  choose  to  define  understanding  in  terms  of  mental  activity  that                                                                                                                   31.  NCISLA,  “Program  Overview”  (emphasis  added).   26       contributes  to  the  development  of  understanding  rather  than  as  a  static  attribute  of  an   individual's  knowledge.     We  propose  five  forms  of  mental  activity  from  which  mathematical  and  scientific   understanding  emerges:  (a)  constructing  relationships,  (b)  extending  and  applying   mathematical  and  scientific  knowledge,  (c)  reflecting  about  experiences,  (d)  articulating   what  one  knows,  and  (e)  making  mathematical  and  scientific  knowledge  one's  own.   These  ideas  are  elaborated  in  more  detail  in  Carpenter  and  Lehrer  (1999),  Fennema  and   Romberg  (1999)  and  specific  examples  of  how  they  are  instantiated  in  classrooms  are   32 described  throughout  our  web  site.     In  short,  NCISLA  explicitly  associates  learning  with  understanding  with  “five  forms  of   mental  activity.”  Relationship  construction,  knowledge  extension/application,  experiential   reflection,  knowledge  articulation,  and  knowledge  personalization  are  all  constructed  as   “mental  activities”  from  which  understanding  emerges.   If  we  follow  the  Carpenter  &  Lehrer  (1999)  citation  from  second  paragraph  in  the   passage  included  above,  we  can  then  see  all  five  of  the  distinct  discursive  features  of  learning   33 with  understanding  woven  into  a  relatively  concise  and  coherent  discursive  fabric.  When   making  a  case  for  learning  with  understanding,  Carpenter  and  Lehrer  include  the  following   statements  in  relatively  close  proximity  to  one  another,   Perhaps  the  most  important  feature  of  learning  with  understanding  is  that  such  learning   is  generative.  When  students  acquire  knowledge  with  understanding,  they  can  apply   that  knowledge  to  learn  new  topics  and  solve  new  and  unfamiliar  problems.  When   students  do  not  understanding,  they  perceive  each  topic  as  an  isolated  skill.  They  cannot   apply  their  skills  to  solve  problems  not  explicitly  covered  by  instruction,  nor  extend  their   learning  to  new  topics.  In  this  day  of  rapidly  changing  technologies,  we  cannot  anticipate   all  the  skills  that  students  will  need  over  their  lifetimes  or  the  problems  they  will                                                                                                                   32.  NCISLA,  “Learning  with  Understanding,”  1  (emphasis  added).   33.  The  main  reason  for  following  this  citational  pathway  and  including  it  in  Example  #3  is   because  the  NCISLA  website  lists  Thomas  Carpenter  as  its  director  and  Richard  Lehrer  as  a   faculty  member  at  one  of  the  six  collaborating  NCISLA  institutions  (Vanderbilt  University).   27       encounter.  We  need  to  prepare  students  to  learn  new  skills  and  knowledge  and  to  adapt   their  knowledge  to  solve  new  problems.  Unless  students  learn  with  understanding,   34 whatever  knowledge  they  acquire  is  likely  to  be  of  little  use  to  them  outside  the  school.     And  then  a  little  bit  later,     We  propose  five  forms  of  mental  activity  from  which  mathematical  understanding   emerges:  (a)  constructing  relationships,  (b)  extending  and  applying  mathematical   knowledge,  (c)  reflecting  about  experiences,  (d)  articulating  what  one  knows,  and  (e)   making  mathematical  knowledge  one’s  own.  Although  these  various  forms  of  mental   35 activity  are  highly  interrelated,  for  the  sake  of  clarity  we  discuss  each  one  separately.     Despite  the  fact  that  Carpenter  and  Lehrer  write  only  of  “mathematical  understanding”   within  this  selection,  an  analysis  of  NCISLA’s  larger  corpus  of  work  shows  that  these  two  NCISLA   representatives  and  their  many  colleagues  assume  that  the  mental  activities  from  which   mathematical  and  scientific  understanding  emerge  are  one  and  the  same.   Example  #4:  How  People  Learn  (1999,  2000)     Between  1999-­‐2000,  the  NRC  published  two  texts  under  the  general  title,  How  People   Learn.  The  text  released  in  1999  had  the  added  title,  Bridging  Research  and  Practice.  There  are   three  authors  of  this  document:  three  co-­‐editors  (M.  Suzanne  Donovan,  John  D.  Bransford,  and   James  W.  Pellegrino),  one  committee  (Committee  on  Learning  Research  and  Educational   Practice),  and  one  council  (National  Research  Council).  The  text  released  in  2000  had  the  added   title  Brain,  Mind,  Experience,  &  School.  There  are  two  authors  of  this  document:  one  committee   (Committee  on  Developments  in  the  Science  of  Learning  with  additional  material  from  the   Committee  on  Learning  Research  and  Educational  Practice)  and  one  council  (National  Research                                                                                                                   34.  Carpenter  and  Lehrer,  “Teaching  and  learning  mathematics,”  18-­‐19  (emphasis  added).   35.  Carpenter  and  Lehrer,  “Teaching  and  learning  mathematics,”  19  (emphasis  added).   28       Council).  Both  How  People  Learn  texts  listed  the  same  two  authoring  organizations:  the  Board   on  Behavioral,  Cognitive,  and  Sensory  Sciences  (BBCSS)  and  the  Division  of  Behavioral  and   Social  Sciences  and  Education  (DBASSE).  Bridging  Research  and  Practice  (hereafter  Bridging)   mentions  the  term  understanding  in  its  first  six  main  sections  no  less  than  one  hundred  and   fifteen  times  (the  phrase  “learning  with  understanding”  is  used  four  times).  Brain,  Mind,   Experience,  &  School  (hereafter  Brain)  mentions  the  term  understanding  in  its  first  twelve  main   sections  no  less  than  three  hundred  and  sixty-­‐six  times  (the  phrase  “learning  with   understanding”  is  used  seventeen  times).  Although  this  review  will  draw  at  times  from  both   texts,  most  of  my  analytical  attention  will  concentrate  on  how  the  notion  of  learning  with   understanding  is  constructed  in  Brain.   In  a  section  titled  “Learning  with  Understanding”  (Chapter  1),  the  authors  of  Brain  speak   directly  to  our  notion  of  interest:     One  of  the  hallmarks  of  the  new  science  of  learning  is  its  emphasis  on  learning  with   understanding.  Intuitively,  understanding  is  good,  but  it  has  been  difficult  to  study  from   a  scientific  perspective.  At  the  same  time,  students  often  have  limited  opportunities  to   understand  or  make  sense  of  topics  because  many  curricula  have  emphasized  memory   rather  than  understanding.  Textbooks  are  filled  with  facts  that  students  are  expected  to   memorize,  and  most  tests  assess  students’  abilities  to  remember  the  facts  [...]  The  new   science  of  learning  does  not  deny  that  facts  are  important  for  thinking  and  problem   solving.  Research  on  expertise  in  areas  such  as  chess,  history,  science,  and  mathematics   demonstrate  that  experts’  abilities  to  think  and  solve  problems  depend  strongly  on  a   rich  body  of  knowledge  about  subject  matter  (e.g.,  Chase  and  Simon,  1973;  Chi  et  al.,   1981;  deGroot,  1965).  However,  the  research  also  shows  clearly  that  “usable  knowledge”   is  not  the  same  as  a  mere  list  of  disconnected  facts.  Experts’  knowledge  is  connected  and   organized  around  important  concepts  (e.g.,  Newton’s  second  law  of  motion);  it  is   “conditionalized”  to  specify  the  contexts  in  which  it  is  applicable;  it  supports   29       understanding  and  transfer  (to  other  contexts)  rather  than  only  the  ability  to   36 remember.     In  this  passage  we  see  examples  of  four  of  the  five  discursive  features  of  learning  with   understanding.  The  knowledge  base  feature  is  visible  in  the  later  half  of  the  paragraph.   According  to  Brain,  a  proper  knowledge  base  includes  a  “rich  body  of  knowledge  about  subject   matter.”  Furthermore,  “concepts”  are  cited  as  one  of  the  key  epistemological  elements  found   37 in  expert  knowledge.  The  coherence  feature  is  also  visible  in  the  later  half  of  the  paragraph,   where  expert  knowledge  is  said  to  be  “useable,”  by  which  is  meant  “connected  and  organized   around  important  concepts”  and  also  “conditionalized.”  Once  again,  we  see  a  construction  of   the  knowledge  base  that  foregrounds  continuity,  coherence,  and  connectedness.  With  respect   to  transfer  and  extrapolation,  we  see  that  Brain  combines  them  together  in  phrases  such  as   “[expert’s  knowledge]  is  “conditionalized”  to  specify  the  contexts  in  which  it  is  applicable”  and   “[expert’s  knowledge]  supports  understanding  and  transfer  (to  other  contexts)  rather  than  only   the  ability  to  remember.”  When  the  authors  of  Brain  use  these  phrases  they  speak  directly  to   the  active,  processual  or  performative  component  of  learning  with  understanding  (in  this   instance,  knowledge  ‘application’  and  knowledge  ‘transfer’),  as  well  as  to  the  situational  one   (e.g.  to  apply  and/or  transfer  expert  knowledge  to  “other  contexts”).   At  least  at  first  glance,  examples  of  the  cognitive  feature  may  be  hard  to  see.  They  never   explicitly  use  the  terms  mind,  brain  or  mental  abilities.  On  a  number  of  occasions,  however,  the   authors  set  learning  with  understanding  in  opposition  to  “memory.”  Although  this  doesn’t                                                                                                                   36.  NRC,  How  People  Learn:  Brain,  8-­‐9  (emphasis  added).   37.  This  emphasis  on  the  importance  of  “concepts”  in  learning  with  understanding  is  one  of  the   likely  sources  of  the  notion  of  conceptual  understanding.   30       preclude  the  possibility  that  understanding  could  be  associated  with  entities  outside  of  the   mind/brain,  that  possibility  is  quickly  closed  by  the  authors’  explicit  use  of  the  term  transfer.   Historically,  the  notion  of  transfer  belongs  to  psychology.  One  of  its  earliest  formal  uses  in  the   20th  century  was  in  the  work  of  American  psychologists  Edward  L.  Thorndike  (1874-­‐1949)  and   Robert  S.  Woodworth  (1869-­‐1962).  Thorndike  and  Woodworth  made  use  of  the  phrase  “the   transfer  of  practice”  in  a  paper  published  in  the  Psychological  Review  in  1901.  In  it,  transfer  was   38 described  as  a  “mental  function.”   We  learn  even  more  about  what  Brain  means  by  the  term  transfer  in  a  section  titled   “Transfer  of  Learning”  (Chapter  10).   A  major  goal  of  schooling  is  to  prepare  students  for  flexible  adaptation  to  new  problems   and  settings.  Students’  abilities  to  transfer  what  they  have  learned  to  new  situations   provides  an  important  index  of  adaptive,  flexible  learning  [...]  Transfer  can  be  explored   at  a  variety  of  levels,  including  transfer  from  one  set  of  concepts  to  another,  one  school   subject  to  another,  one  year  of  school  to  another,  and  across  school  and  everyday,   39 nonschool  activities.     Here,  we  see  that  transfer  is  associated  with  problem  solving  in  new  settings  and  also   “adaptive,  flexible  learning.”  We  also  see  that  transfer  is  a  generic  term  used  to  describe  that   which  takes  place  between  two  different  settings  or  situations:  for  example,  between  two  sets   of  concepts  (e.g.,  photosynthesis  and  cellular  respiration);  between  two  school  subjects  (e.g.,   biology  and  chemistry  or  biology  and  U.S.  history);  between  two  school  years  (e.g.,  high  school   seniors  and  college  freshman);  and/or  between  two  activities  (e.g.,  a  lab  experiment  and  a  walk                                                                                                                   38.  See  Thorndike,  Edward  L.,  and  Robert  S.  Woodworth.  “The  Influence  of  Improvement  in  One   Mental  Function  Upon  the  Efficiency  of  Other  Functions  (I).”  Psychological  Review  8  (1901),   247-­‐261.   39.  NRC,  How  People  Learn:  Brain,  235.   31       in  the  woods).  This  particular  use  of  the  term  transfer  has  both  temporal  and  spatial   components  that  will  be  explored  in  the  next  chapter,  but  it  does  not  help  us  clarify  the   relationship  between  transfer  and  learning  with  understanding.  However,  this  next  selection  of   text  accomplishes  this  particular  goal.   Learning  with  understanding  is  more  likely  to  promote  transfer  than  simply  memorizing   information  from  a  text  or  a  lecture.  Many  classroom  activities  stress  the  importance  of   memorization  over  learning  with  understanding.  Many,  as  well,  focus  on  facts  and   details  rather  than  larger  themes  of  causes  and  consequences  of  events.  The  shortfalls   of  these  approaches  are  not  apparent  if  the  only  test  of  learning  involves  tests  of   memory,  but  when  the  transfer  of  learning  is  measured,  the  advantages  of  learning  with   40 understanding  are  likely  to  be  revealed.     Here,  a  relationship  between  transfer  and  understanding  is  made  clear:  learning  with   understanding  promotes  transfer.  In  other  words,  learning  with  understanding  increases  the   likelihood  or  probability  that  transfer  (i.e.,  knowledge  use,  extension  or  application)  will  happen   successfully.  With  the  clarification  of  this  relationship,  as  well  as  with  the  help  of  all  the  quoted   passages  above,  we  can  finally  see  an  important  relationship  between  knowledge,   understanding,  and  transfer:  According  to  the  authors  of  Brain,  understanding  is  the  product  or   result  of  knowledge  that  has  been  mentally  transformed—in  other  words,  it’s  the  result  of   knowledge  that  has  been  memorized  and  then  organized  (e.g.,  connected,  conceptualized,  and   conditionalized).  Knowledge  that  has  been  transformed  in  these  particular  ways  can  be   described  as  “a  rich  body  of  knowledge”  or  “expert  knowledge.”  The  authors  of  Bridging  offer   other  useful  phrases  to  describe  this  particular  type  of  knowledge,  including  “a  strong                                                                                                                   40.  Ibid.,  236  (emphasis  added).   32       41 conceptual  framework”  and  “a  richly  structured  information  base.”  They  also  call  this   particular  type  of  knowledge  “deep”  understanding.  Transfer,  then,  is  the  subsequent  mental   application,  use,  or  extension  of  that  deep  understanding  (i.e.,  that  transformed,  rich,  expert   knowledge)  to  new  contexts  characterized  by  one  (or  more)  of  four  spatio-­‐temporal  levels.   Example  #5:  Learning  and  Understanding:  Improving  Advanced  Study  of  Mathematics  and   Science  in  U.S.  High  Schools  (2002)       The  NRC  published  Learning  and  Understanding:  Improving  Advanced  Study  of   Mathematics  and  Science  in  U.S.  High  Schools  in  2002.  There  are  two  authors  of  this  document:   one  committee  (Committee  on  Programs  for  Advanced  Study  of  Mathematics  and  Science  in   American  High  Schools)  and  one  council  (National  Research  Council).  There  are  three  authoring   organizations:  the  Board  on  Science  Education  (BOSE),  the  Board  on  Testing  and  Assessment   (BOTA),  and  the  Division  of  Behavioral  and  Social  Sciences  and  Education  (DBASSE).  Learning   and  Understanding  mentions  the  term  understanding  in  its  first  thirteen  main  sections  no  less   than  two  hundred  and  twenty-­‐three  times  (however,  there  are  three  Appendices  and  four   additional  Reports  which  use  the  term  another  two  hundred  and  thirty-­‐two  times).  The  phrase   “learning  with  understanding”  appears  in  the  main  sections  thirty-­‐one  times.  Learning  with   understanding  is  first  discussed  in  the  Executive  Summary.   The  concept  of  “learning  with  understanding”  is  concerned  with  knowledge  and  how  it  is   organized.  Effective  instruction  is  focused  on  enabling  learners  to  uncover  and  formulate   the  deep  organizing  patterns  of  a  domain,  and  then  to  actively  access  and  create   meaning  around  these  organizing  principles.  Learning  with  understanding  also  helps   students  develop  the  ability  to  evaluate  the  relevance  of  particular  knowledge  to  novel   problems  and  to  explain  and  justify  their  thinking.  As  students  learn  and  practice  these                                                                                                                   41.  NRC,  How  People  Learn:  Bridging,  2.   33       skills  of  critical  reflection,  they  become  able  to  apply  knowledge  in  multiple  contexts,   42 develop  adaptive  expertise,  and  serve  as  active  members  of  learning  communities.     In  this  passage  we  see  examples  of  four  of  the  five  discursive  features  of  learning  with   understanding.  The  knowledge  base  and  coherence  features  are  visible  in  the  first  and  second   sentences  of  the  paragraph.  According  to  the  authors  of  Learning  and  Understanding,  learning   with  understanding  “is  concerned  with  knowledge  and  how  it  is  organized.”  In  the  second   sentence,  we  see  an  emphasis  placed  on  a  particular  type  of  epistemological  unit,  the   “organizing  patterns”  or  “organizing  principles”  of  a  domain.  Once  again,  we  see  a  construction   of  the  knowledge  base  that  foregrounds  continuity,  coherence,  and  connectedness.  With   respect  to  the  transfer  and  extrapolation  features,  we  see  that  Learning  and  Understanding   combines  them  together  in  phrases  such  as  “to  evaluate  the  relevance  of  particular  knowledge   to  novel  problems”  and  “to  apply  knowledge  in  multiple  contexts.”  When  the  authors  of   Learning  and  Understanding  use  these  phrases  they  speak  directly  to  the  active,  processual  or   performative  component  of  learning  with  understanding  (in  this  instance,  knowledge   ‘evaluation’  and  knowledge  ‘application’),  as  well  as  to  the  situational  one  (for  example,  to   evaluate  knowledge  relevance  to  “novel  problems”  and  to  apply  knowledge  “in  multiple   contexts”).   A  bit  deeper  into  the  Executive  Summary  we  are  made  aware  of  another  valued   epistemological  unit  said  to  help  provide  additional  organization  to  a  knowledge  base.   Learning  with  understanding  is  facilitated  when  knowledge  is  related  to  and  structured   43 around  major  concepts  and  principles  of  a  discipline.                                                                                                                   42.  NRC,  Learning  and  Understanding,  6  (emphasis  added).   43.  Ibid.,  7.   34         In  addition  to  integrating  organizing  patterns  and  principles  into  their  knowledge  base,   students  who  learn  with  understanding  also  integrate  “major  concepts”  into  them.  The   expectation  that  students  integrate  major  concepts  into  their  knowledge  base  goes  a  long  way   toward  helping  explain  the  large  number  of  appearances  of  the  term  conceptual  understanding   in  the  text.  The  term  appears  fifty-­‐six  times  in  the  first  thirteen  major  sections  and  is  defined  as   follows:     Conceptual  understanding  involves  the  creation  of  rich  integrated  knowledge  structures   around  an  underlying  concept.  Understanding  is  not  a  static  point  in  learning,  but  rather   44 a  continually  developing  mental  activity.     In  seeing  how  Learning  and  Understanding  constructs  conceptual  understanding,  one   can’t  help  but  notice  the  continuity  between  this  notion  and  what  the  previous  example—the   NRC’s  How  People  Learn—referred  to  alternately  and  equivalently  as,  “a  rich  body  of   knowledge,”  “a  strong  conceptual  framework,”  “a  richly  structured  information  base,”  “expert   knowledge,”  and/or  “deep  understanding.”  One  also  can’t  help  but  notice  how  the  authors   construct  conceptual  understanding  as  “a  continually  developing  mental  activity.”  How  People   Learn  achieved  the  cognitive  feature  by  way  of  associating  learning  with  understanding  with  the   notion  of  transfer.  There  is  good  reason  for  the  presence  of  these  two  continuities:  the  authors   of  Learning  and  Understanding  explicitly  reference  How  People  Learn  just  prior  to  stating  their   “seven  principles  of  human  learning”  in  Chapter  6  (“Learning  with  Understanding:  Seven   Principles”).  In  fact,  the  Learning  and  Understanding  authors  state  that  it  was  research   summarized  in  How  People  Learn  upon  which  they  decided  to  base  their  principles  for  learning                                                                                                                   44.  Ibid.,  22n8  (emphasis  added).   35       with  understanding.  In  the  text  supporting  and  explaining  these  principles,  we  see  a  number  of   terms  and  ideas  that  also  appeared  in  How  People  Learn.  For  example,  Learning  and   Understanding  speaks  of  “expert  strategies  for  thinking  and  problem  solving,”  and  knowledge   that  is  “connected,”  “organized”  and  “conditionalized.”  Taken  collectively,  we  see   complementary  constructions  of  learning  with  understanding  between  these  two  texts.   Despite  a  few  subtleties  here  and  there,  the  construction  of  learning  with  understanding   is  more  or  less  the  same  for  both  texts.  Understanding—whether  deep  or  conceptual—is  the   product  or  result  of  transforming  knowledge  inside  of  the  mind.  In  How  People  Learn,  the   transformation  is  driven  by  mental  actions  or  processes  such  as  memorization,  organization,   building  connections,  conceptualizing,  and  conditionalizing.  In  Learning  and  Understanding,   organizing  knowledge  around  the  deep  patterns,  key  principles,  and/or  major  underlying   concepts  of  a  domain  or  discipline  drives  the  transformation.  Once  organized  in  deep,  rich,   meaningful,  structured,  principled,  patterned,  and/or  conceptual  arrangements,  this  new   knowledge—i.e.,  the  understanding—is  deemed  fit  for  its  mental  extrapolation  (application,   use,  extension,  transfer)  to  novel  and,  it  is  hoped,  multiple  contexts.   Example  #6:  Grant  Wiggins  and  Jay  McTighe  (2005)     Prentice  Hall  publishers  released  the  first  edition  of  Wiggins  and  McTighe’s   Understanding  by  Design  (or  UbD)  in  2000.  The  ASCD  (formerly  the  Association  for  Supervision   and  Curriculum  Development)  then  published  a  second,  expanded  edition  in  2005.  “As  the  title   suggests,”  the  authors  write,  “this  book  is  about  good  design—of  curriculum,  assessment,  and   36       45 instruction—focused  on  developing  and  deepening  understanding  of  important  ideas.”   According  to  Wiggins  and  McTighe,  UbD  is  not  written  specifically  for  science  or  STEM   educators,  but  rather,  it  is  a  book  intended  for  all  those  “educators,  new  or  veteran,  interested   in  enhancing  student  understanding  and  in  designing  more  effective  curricula  and  assessment   46 to  achieve  that  end.”  Nevertheless,  UbD  is  a  widely  cited  publication  in  K-­‐16  science   education  and  it  is  used  extensively  in  science  teacher  education  and  professional  development   programs.  UbD  contains  some  of  the  most  precise  and  explicit  treatment  of  understanding  of   any  of  the  texts  selected  for  this  review  of  texts.   According  to  the  UbD  authors,  “There  are  different  kinds  of  understanding;  we  need  to   be  clear  about  which  kinds  we  are  after.  Understanding,  we  argue,  is  not  a  single  goal,  but  a   familiar  of  interrelated  abilities—six  different  facets  of  transfer—and  an  education  for   47 understanding  would  develop  them  all.”  Two  pages  later,  they  expand  on  this  statement,  as   follows:   The  word  understanding  turns  out  to  be  a  complex  and  confusing  target  despite  the  fact   that  we  aim  for  it  all  the  time.  The  word  naturally  deserves  clarification  and  elaboration,   which  is  the  challenge  for  the  rest  of  this  book.  For  now,  though,  consider  our  initial   working  definition  of  the  term:  To  understand  is  to  make  connections  and  bind  together   our  knowledge  into  something  that  makes  sense  of  things  (whereas  without   understanding  we  might  see  only  unclear,  isolated,  or  unhelpful  facts).  But  the  word   also  implies  doing,  not  just  a  mental  act:  A  performance  ability  lies  at  the  heart  of   understanding,  as  Bloom  (1956)  noted  in  his  Taxonomy  in  discussing  application  and   synthesis.  To  understand  is  to  be  able  to  wisely  and  effectively  use—transfer—what  we   know,  in  context;  to  apply  knowledge  and  skill  effectively,  in  realistic  tasks  and  settings.   To  have  understood  means  that  we  show  evidence  of  being  able  to  transfer  what  we                                                                                                                   45.  Wiggins  and  McTighe,  Understanding  By  Design,  5.   46.  Ibid.,  5.   47.  Ibid.,  4.   37       know.  When  we  understand,  we  have  a  fluent  and  fluid  grasp,  not  a  rigid,  formulaic   48 grasp  based  only  on  recall  and  “plugging  in.”     Because  of  the  authors’  already  existing  emphasis  within  the  passage,  I  have  chosen  not   to  add  emphasis  as  I  did  in  the  previous  three  examples.  However,  I  suspect  that  by  now   readers  will  be  able  to  see  clearly  the  backbone  of  many  of  the  five  discursive  facets  of  learning   with  understanding  without  my  help.  In  just  the  third  sentence  in  the  paragraph  we  see   elements  of  the  first  four  features:  knowledge  base  (“knowledge”),  coherence  (“to  make   connections,”  “to  bind  together  knowledge”),  and  transfer  and  extrapolation  (“to  make  sense   of  things”).  Many  of  these  same  four  features  can  also  be  identified  within  the  last  two   sentences  in  the  paragraph  (e.g.,  “to  wisely  and  effectively  use—transfer—what  we  know,”  and   “to  apply  knowledge  and  skill  [...]  in  realistic  tasks  and  settings”).  Although  the  cognition   feature  is  easy  to  identify  within  the  fourth  sentence  (“...a  mental  act”),  Wiggins  and  McTighe   suggest  that  the  notion  of  learning  with  understanding  also  goes  beyond  mental  actions.  To   clarify  what  sort  of  actions  lie  beyond  mental  ones  in  learning  with  understanding,  they  cite  the   work  of  “Bloom  (1956)”  and  draw  explicit  attention  to  two  terms—application  and  synthesis— that  appear  in  what  is  now  commonly  referred  to  by  educators  as  “Bloom’s  Taxonomy”  (or   “Bloom’s  Taxonomy  of  Educational  Objectives”).   Interestingly,  the  terms  application  and  synthesis  appear  in  Bloom  et  al.’s  1956  paper  as   49 two  of  six  “levels”  that  help  define  learning  objectives  in  the  “cognitive  domain.”  Bloom  and   his  fellow  authors  were  all  contributing  to  the  field  of  educational  psychology  in  the  1950s  and   60s.  It  remains  unclear  to  me  as  to  whether  their  collective  use  of  the  term  cognition  is  meant                                                                                                                   48.  Ibid.,  6-­‐7  (emphasis  in  the  original).   49.  See  Bloom  et  al.  1956.   38       to  mean  actions  beyond  or  within  the  mind/brain.  However,  we  gain  some  clarification  as  to   what  Wiggins  and  McTighe  mean  by  their  use  of  the  phrase  “not  just  a  mental  act”  in  a  chapter   titled  “Understanding  Understanding”  (Chapter  2).   In  Chapter  2,  Wiggins  and  McTighe  write  about  learning  with  understanding  as  having   three  main  dimensions  or  facets:  1)  understanding  as  meaningful  inferences,  2)  understanding   as  transferability,  and  3)  understanding  as  a  noun.  The  first  of  these  facets,  they  explain  as   follows:   Understanding  thus  involves  meeting  a  challenge  for  thought.  We  encounter  a  mental   problem,  an  experience  with  puzzling  or  no  meaning.  We  use  judgment  to  draw  upon   our  repertoire  of  skill  and  knowledge  to  solve  it.  As  Bloom  (1956)  put  it,  understanding   is  the  ability  to  marshal  skills  and  facts  wisely  and  appropriately,  through  effective   application,  analysis,  synthesis,  and  evaluation.  Doing  something  correctly,  therefore,  is   not,  by  itself,  evidence  of  understanding.  It  might  have  been  an  accident  or  done  by  rote.   To  understand  is  to  have  done  it  in  the  right  way,  often  reflected  in  being  able  to  explain   why  a  particular  skill,  approach,  or  body  of  knowledge  is  or  is  not  appropriate  in  a   50 particular  situation.     Here,  we  see  an  even  sharper  focus  on  the  cognitive  feature  of  learning  with   understanding.  Students  who  learn  with  understanding  are  said  to  be  able  to  mentally  apply,   extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning.  The  authors  talk  about  understanding  fluidly  as  meeting  a  “challenge  for  thought,”  as   requiring  “judgment,”  and  as  encountering  a  puzzling  “mental”  problem  or  experience  devoid   of  meaning.  Once  again,  they  cite  terms  from  Bloom  et  al.’s  cognitive  domain,  but  this  time   they  cite  four  of  the  six  “levels”—application,  analysis,  synthesis,  and  evaluation—rather  than   just  two  of  them.                                                                                                                   50.  Wiggins  and  McTighe,  Understanding  By  Design,  p.  39  (emphasis  in  the  original).   39       In  the  second  of  their  three  facets  of  understanding,  Wiggins  and  McTighe  continue  to   construct  learning  with  understanding  as  a  predominant  mental  activity  by  making  repeated   use  of  the  term  transfer.  As  I  noted  in  a  previous  example  (Example  #2:  How  People  Learn),   transfer  is  a  concept  that  historically  belongs  to  psychology.  Here  is  how  the  authors  of  UbD  use   the  term:   Understanding  is  about  transfer,  in  other  words.  To  be  truly  able  requires  the  ability  to   transfer  what  we  have  learned  to  new  and  sometimes  confusing  settings.  The  ability  to   transfer  our  knowledge  and  skill  effectively  involves  the  capacity  to  take  what  we  know   and  use  it  creatively,  flexibly,  fluently,  in  different  settings  or  problems,  on  our  own.   Transferability  is  not  mere  plugging  in  of  previously  learned  knowledge  and  skill.  In   Bruner's  famous  phrase,  understanding  is  about  “going  beyond  the  information  given”;   we  can  create  new  knowledge  and  arrive  at  further  understandings  if  we  have  learned   51 with  understanding  some  key  ideas  and  strategies.     The  UbD  authors  then  elaborate  upon  the  notion  of  transfer.  Once  again,  they  relate   their  ideas  about  understanding,  and  now  transfer,  to  work  of  Bloom:   Transfer  is  the  essence  of  what  Bloom  and  his  colleagues  meant  by  application.  The   challenge  is  not  to  “plug  in”  what  was  learned,  from  memory,  but  modify,  adjust,  and   adapt  an  (inherently  general)  idea  to  the  particulars  of  a  situation:   ‘Students  should  not  be  able  to  solve  the  new  problems  and  situations  merely  by   remembering  the  solution  to  or  the  precise  method  of  solving  a  similar  problem  in   class.  It  is  not  a  new  problem  or  situation  if  it  is  exactly  like  the  others  solved  in   class  except  that  new  quantities  or  symbols  are  used.  .  .  .  It  is  a  new  problem  or   situation  if  the  student  has  not  been  given  instruction  or  help  on  a  given  problem   and  must  do  some  of  the  following.  .  .  .  1.  The  statement  of  the  problem  must  be   modified  in  some  way  before  it  can  be  attacked.  .  .  .  2.  The  statement  of  the   problem  must  be  put  in  the  form  of  some  model  before  the  student  can  bring  the   generalizations  previously  learned  to  bear  on  it.  .  .  .  3.  The  statement  of  the   problem  requires  the  student  to  search  through  memory  for  relevant   generalizations.  (Bloom,  Madaus,  &  Hastings,  1981,  p.  233)’                                                                                                                   51.  Ibid.,  40  (emphasis  in  the  original).   40       Knowledge  and  skill,  then,  are  necessary  elements  of  understanding,  but  not  sufficient   in  themselves.  Understanding  requires  more:  the  ability  to  thoughtfully  and  actively  “do”   the  work  with  discernment,  as  well  as  the  ability  to  self-­‐assess,  justify,  and  critique  such   “doings.”  Transfer  involves  figuring  out  which  knowledge  and  skill  matters  here  and   52 often  adapting  what  we  know  to  address  the  challenge  at  hand.     Since  transfer  is  a  term  that  historically  belongs  to  psychology,  we  can  therefore  allow   ourselves  to  see  cognitive  feature  of  learning  with  understanding  in  the  use  of  terms  such  as   “transfer,”  “transferability,”  and  also  “application”  (which  they  claim  is  the  Bloomian  equivalent   of  transfer).  Furthermore,  we  can  also  allow  ourselves  to  see  the  cognitive  feature  in  their  use   of  phrases  such  as  “going  beyond  the  information  given”  and  to  “modify,  adjust,  and  adapt  an   (inherently  general)  idea  to  the  particulars  of  a  situation.”  Wiggins  and  McTighe  construct  these   particular  actions  as  mental  performances.  They  are  the  kinds  of  performances  enacted  when   individuals  act  “thoughtfully.”  We  also  should  be  aware  of  the  fact  that  the  transfer  and   extrapolation  features  are  present  too.  When  Wiggins  and  McTighe  use  sentences  such  as,  “To   be  truly  able  requires  the  ability  to  transfer  what  we  have  learned  to  new  and  sometimes   confusing  settings,”  and  “The  ability  to  transfer  our  knowledge  and  skill  effectively  involves  the   capacity  to  take  what  we  know  and  use  it  creatively,  flexibly,  fluently,  in  different  settings  or   problems,  on  our  own,”  they  speak  directly  to  the  active,  processual  or  performative   component  of  learning  with  understanding  (in  this  instance,  knowledge  ‘transfer’  and   knowledge  ‘use’),  as  well  as  to  the  situational  one  (for  example,  to  transfer  knowledge  and  skills   to  “new  and  sometimes  confusing  settings,”  to  use  knowledge  “in  different  settings  or   problems,”  and  to  address  “the  challenge  at  hand”).                                                                                                                   52.  Ibid.,  41  (emphasis  in  the  original).   41       In  the  third  and  final  of  their  three  facets  of  understanding,  Wiggins  and  McTighe   remind  us  that  the  term  understanding  “has  a  verb  meaning  and  a  noun  meaning.”   To  understand  a  topic  or  subject  is  to  be  able  to  use  (or  “apply,”  in  Bloom's  sense)   knowledge  and  skill  wisely  and  effectively.  An  understanding  is  the  successful  result  of   trying  to  understand—the  resultant  grasp  of  an  unobvious  idea,  an  inference  that  makes   meaning  of  many  discrete  (and  perhaps  seemingly  insignificant)  elements  of  knowledge.     A  genuine  understanding  involves  another  kind  of  transfer.  We  go  beyond  what  we  see,   53 using  big  ideas,  to  make  meaning  of  it  [...].     This  last  facet  of  understanding,  which  effectively  summarizes  the  first  two,  neatly   summarizes  Wiggins  and  McTighe’s  contribution  to  the  notion  of  learning  with  understanding.   If  we  see  knowledge  transfer  (aka.  knowledge  ‘use’  or  ‘application’)  as  a  predominantly  mental   activity,  then  the  construction  of  understanding  by  the  authors  of  UbD  exhibits  all  five  of  the   distinct  discursive  features  I  outlined  at  the  beginning  of  this  chapter.  Furthermore,  it  does  so  in   a  way  that  very  few  other  texts  produced  within  the  Reform  Age  do.  Wiggins  and  McTighe’s   treatise  on  understanding  and  its  design  is  more  elaborate  and  more  precise  than  almost  all   other  texts  circulating  in/through  science  education.  For  these  and  other  reasons,  it  is  a  text   that  I  shall  return  to  again  later  in  this  dissertation.  For  now,  we  should  be  content  to   remember  that  for  the  UbD  authors  understanding  is  “a  mental  construct,  an  abstraction  made   54 by  the  human  mind  to  make  sense  of  many  distinct  pieces  of  knowledge.”   Teaching  For  Understanding     We  now  turn  to  the  Bio101  professors  themselves  so  as  to  examine  how  they  construct   the  notion  of  learning  with  understanding  in  practice.  As  with  the  previous  six  texts,  we  are                                                                                                                   53.  Ibid.,  43  (emphasis  in  the  original).   54.  Ibid.,  37.   42       looking  for  the  five  discursive  features  of  learning  with  understanding.  We  are  also  looking  to   highlight  the  continuities  and/or  discontinuities  between  their  constructions  and  those   presented  in  the  previous  six  examples.   In  a  joint  summer  2007  interview,  one  of  the  professors  defined  understanding  in  this   way:   Professor  1:  So  I  think  [understanding  is]  two  components.  I  think  [students]  have  to   know  a  certain  number  of  facts.  I’ve  always  felt  that  an  introductory  or  foundation   course  [...]  is  based  upon  a  certain  number  of  facts  that  the  student  has  to  know  about  a   topic,  a  subject,  whatever.  So  I  clearly  feel  that  they  have  to  memorize  things  or  learn   55 things  by  understanding  those  facts.     When  I  asked  this  professor  to  clarify  what  he  meant  by  the  phrase  "learn  things  by   understanding  those  facts,"  he  then  added,   Professor  1:  So  when  I  say  do  they  understand  something...80%...70...60%  of  it  is   facts...and  the  rest  of  it  is  trying  to  integrate  those  facts  in  a  way  that  they  may  have  not   56 seen  before.     At  which  point  the  other  professor  picked  up  the  issue:     Professor  2:  We’re  really  not  too  far  apart  on  all  of  that,  I  mean,  I  don’t  think  that  one   can  understand  without  having  some  knowledge...so  there’s  this  knowledge  base...the   facts...and  the  understanding  has  to  be  built  upon  really  assembling  and  organizing  a  lot   of  facts.  And  then  being  able  to  bring  those  facts...somehow  use  those  facts...reorganize   those  facts  in  order  to  draw  explanations.  That  to  me  is  the...the  understanding  part   comes  in  being  able  to  provide  the  explanations  or  predictions.  So  that’s  how  we  get  to   these  higher  order  questions  that  are  analytical...the  analysis-­‐type  questions.  And,  uh,   but  I  am  constantly  reaffirmed  in  my  conviction  that  the  students  have  gotta  know  a  lot   57 of  stuff  in  order  to  make  that  work.                                                                                                                       55.  Instructor  Interview  (June  2007):  00:12:24-­‐00:14:30   56.  Instructor  Interview  (June  2007):  00:12:24-­‐00:14:30  (emphasis  added).   57.  Instructor  Interview  (June  2007):  00:14:31-­‐00:18:21  (emphasis  added).   43       In  these  two  passages,  once  again,  we  see  examples  of  four  of  the  five  discursive   features  of  learning  with  understanding.  The  knowledge  base  feature  is  clearly  visible  (“...so   there’s  this  knowledge  base...”).  In  this  case,  “facts”  are  cited  as  one  of  the  key  epistemological   elements  found  in  the  knowledge  base.  The  coherence  feature  is  also  clearly  visible.  Within  the   knowledge  base  in  question,  the  facts  are  said  to  need  to  be  ‘integrated,’  ‘assembled,’   ‘organized,’  and  ‘reorganized.’  Once  again,  we  see  a  construction  of  the  knowledge  base  that   foregrounds  continuity,  coherence,  and  connectedness.  The  transfer  feature  is  also  clearly   visible.  The  professors  say  that  their  students  need  to  be  able  to  “bring”  and  “use”  facts  for  the   purpose  of  doing  things  (e.g.,  “draw  explanations,”  “provide  explanations  or  predictions”).   Although  the  extrapolation  feature  is  less  clearly  visible,  nevertheless,  it  is  present.  When  the   Professor  1  says,  “...and  the  rest  of  [understanding]  is  trying  to  integrate  those  facts  in  a  way   that  [students]  may  have  not  seen  before,”  he  is  pointing  directly  to  new,  unfamiliar  contextual   situations.  When  the  Professor  2  says,  “So  that’s  how  we  get  to  these  higher  order  questions   that  are  analytical...the  analysis-­‐type  questions,”  he  is  pointing  directly  at  questions  such  as  the   Mutant  Spinach  Question  and  other  like  it.  In  other  words,  he  is  drawing  attention  to  questions   that  contain  elements  students  are  likely  to  find  new,  novel,  different,  and/or  unfamiliar.  What   we  don’t  explicitly  see  in  these  two  passages  is  the  cognition  feature.  In  other  words,  we  don’t   see  any  obvious  mention  of  either  the  knowledge  base  or  the  act  of  using  the  knowledge  base   characterized  as  a  mental  activity.  Professors  1  and  2  never  explicitly  use  terms  such  as  “mind,”   “brain”  or  “mental  abilities.”  In  another  portion  of  the  interview,  however,  as  Professor  2  was   explaining  to  me  how  he  thought  his  students  should  have  answered  the  Mutant  Spinach   Question,  a  connection  to  the  mind/brain  was  made  explicit,   44       Professor  2:  So  what  [students]  have  to  bring  is,  what  is  going  on?  And  they  had  to  bring   in  the  idea  of  the  membrane  which  was  from  3  to  4  chapters  earlier,  and  they  had  to   bring  in  the  ideas  of  the  ATP  synthase,  and  they  had  to  bring  in  the  idea  then  of  the  light   reactions  and  the  different  parts  of  the  light  reactions,  and  they  had  to  put  this  whole   idea  of  cyclic  and  non-­‐cyclic  photophosphorylation...or,  parts  of  the  Z-­‐scheme...and  so   this  is  where  it  gets  dicey  because  the  picture—I  can  imagine  the  picture  they  have  in   their  heads  of  this  membrane  [Professor  2  points  with  his  right  hand  to  the  right  side   of  his  head]  with  the  ATP,  sitting  in  it,  is  different  than  the  picture  they  have  over  here   [Professor  2  points  with  his  left  hand  to  the  left  side  of  his  head]  of  the  Z-­‐scheme  and   the  arrow  showing  cyclic  photophosphorylation...even  though  we  say,  phos-­‐phoryl-­‐a-­‐ tion  [Professor  2  pronounces  the  word  slowly]  which  ought  to  trigger,  ‘Ding!  Ding!   Ding!  Synthase!’...you  know...over  here  [Professor  2  again  points  with  his  right  hand  to   the  right  side  of  his  head]  [...]  You  know...it’s  this...going...they...going  back  and  forth   on  these  things  very  fluidly  from  representation  to  representation  is  another   58 manifestation  of  being  able  to  tie  it  together.     In  this  passage  Professor  2  constructs  a  hypothetical  situation  in  which  he  describes  how   Bio101  students  might  have  answered  the  Mutant  Spinach  Question.  In  doing  so,  he  models  the   strategy  as  a  mental  process.  He  speaks  very  clearly  about  “pictures”  in  the  students  heads  and   also  about  various  mental  processes—e.g.,  bringing  ideas  in,  putting  ideas  together,  going  back   and  forth  between  mental  representations  with  fluidity,  and  tying  ideas  together.  At  this  point,   this  is  nothing  new.  It  is  the  same  construction  that  we  have  seen  throughout  all  six  textual   examples.  Like  so  many  of  their  Reform  Age  colleagues,  the  Bio101  professors  construct  the   notion  of  learning  with  understanding  as  the  ability  to  mentally  apply,  extend,  or  transfer  a   deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of  learning.                                                                                                                         58.  Instructor  Interview  (June  2007):  01:21:18-­‐01:23:53  (emphasis  in  the  original).   45       Summary   At  the  beginning  of  this  review,  I  stated  that  the  Reform  Age  construction  of  learning   with  understanding  has  come  to  have  no  fewer  than  five  defining  discursive  features  associated   with  it.  These  five  features  can  be  summarized  as  follows:   First:  Students  who  learn  with  understanding  are  said  to  possess  a  knowledge  base.     Second:  Students  who  learn  with  understanding  are  said  to  possess  a  certain  kind  of   knowledge  base—one  that  is  coherent.  In  other  words,  one  that  is  both  deep  (in   quantity)  and  rich  (in  connections).     Third:  Students  who  learn  with  understanding  are  said  to  be  able  to  apply  their   knowledge,  extend  their  skills,  and/or  transfer  their  learning.     Fourth  (and  a  corollary  to  the  third):  Students  who  learn  with  understanding  are  said  to   be  able  to  apply,  extend,  transfer  or  extrapolate  their  deep,  rich  knowledge  base  to   situations  beyond  the  original  context  of  learning.   Fifth:  Students  who  learn  with  understanding  are  said  to  be  able  to  use  cognition  to   mentally  extrapolate  their  deep,  rich  knowledge  base  to  situations  beyond  the  original   context  of  learning.   The  seven  examples  presented  above  are  meant  to  illustrate  the  consistent  use  of  these   five  distinct  discursive  features  through  the  K-­‐16  science  education  continuum.  Collectively,   they  help  us  see  a  particular  way  in  which  the  notion  of  learning  with  understanding  is   constructed  during  the  period  of  years  from  1990-­‐2013.  This  is  not  to  say  that  the  discourse  of   learning  with  understanding  has  no  other  distinct  features,  but  rather,  only  that  these  five   features  have  achieved  a  noticeable  and  traceable  density  within  Reform  Age  discourse.  These   46       five  features  help  give  distinct  shape  and  meaning  to  what  I  will  call  the  existing  “horizon  of   expectations”  for  learning  with  and  teaching  for  understanding.  It  other  words,  these  five   features  help  articulate  the  limits  and/or  boundaries  of  what  is  both  possible  and  probable  in   science  teaching  and  learning  throughout  the  K-­‐16  continuum.   These  five  features  help  shape  how  teachers  act  in  classrooms,  including  what  they  do,   what  they  say,  and  how  they  think;  they  help  shape  what  teachers  teach  and  how  they  teach  it;   and  they  help  shape  not  only  who  teachers  think  their  students  are,  but  also  what  they  think   their  students  can,  and  should,  do.  In  other  words,  these  five  features  help  make  it  both   possible  and  probable  for  the  Bio101  professors  to  see  and  approach  themselves,  their  students,   and  their  subject  matter  in  particular  ways.  In  the  next  chapter,  together  we  will  examine  a   number  of  the  affordances  and  constraints  of  this  particular  horizon  of  expectations  for   learning  with  and  teaching  for  understanding.         47       CHAPTER  2   A  DISTINCT  HORIZON  OF  EXPECTATIONS         Science  education  is  still  in  the  grip  of  psychology.             —  Wolff-­‐Michael  Roth  &  Michelle  K.   Mc  Ginn     Understanding  something  in  one  way  does  not  preclude   understanding  it  in  other  ways.     —  Jerome  Bruner,  The  Culture  of   Education       A  Mental  Horizon     As  a  way  of  rendering  the  affordances  and  constraints  of  the  horizon  of  expectations  for   learning  with  understanding  in  the  Reform  Age  discourse  more  explicit,  let  us  consider  the  first   defining  discursive  feature—that  students  who  learn  with  understanding  must  possess  a   knowledge  base.  If  none  of  the  other  four  defining  discursive  features  are  present,  then  there   are  many  possibilities  for  what  a  useable  knowledge  base  can  be  and  where  it  can  exist.  For   example,  untethered  from  the  other  four  features,  a  useable  knowledge  base  can  take  the  form   of  a  notebook,  a  recipe  box,  a  3-­‐ring  binder,  a  file  cabinet,  a  library,  or  a  laptop  computer.   Alternatively,  it  can  consist  of  file  cabinets,  shelves,  books,  paper,  words,  diagrams,   photographs,  computer  chips,  electric  wires,  batteries,  and  a  range  of  other  visible,  material   items.  However,  if  we  constrain  the  knowledge  base  with  the  second  feature  of  coherence,  then   the  possibilities  for  what  a  useable  knowledge  base  can  be  and  where  it  can  exist  are  altered.  A   48       useable  knowledge  base  that  is  both  deep  in  quantity  and  rich  in  connections  will  most  likely   need  to  be  different  than  one  defined  by  characteristics  such  as  aesthetics,  expedience,  or   political  correctness.  For  example,  a  recipe  box  might  need  to  be  bigger  in  volume  to  hold  more   recipe  cards,  or  to  fit  properly  on  a  shelf.  To  increase  the  connectivity,  the  cards  themselves   might  need  to  re-­‐designed  so  that  there  would  be  space  where  one  can  record  the  name  of  the   person  with  whom  the  recipe  originated.  Such  a  modification  in  connectedness  might  better   facilitate  problem  solving  when  culinary  chaos  ensues  (for  example,  when  bread  doesn’t  rise  or   when  a  soufflé  collapses).  Something  similar  happens  every  time  another  defining  feature  is   added  or  subtracted.  In  every  instance  of  layering  or  addition,  the  scope—and  even  the   shape—of  the  knowledge  base  is  likely  to  be  in  need  of  alteration.   Not  all  features  are  created  equally,  however,  and  the  cognitive  feature  of  learning  with   understanding  embodies  this  maxim.  If  we  allow  the  cognitive  feature  (that  students  who  learn   with  understanding  must  be  able  to  mentally  apply,  extend  or  transfer  their  deep,  rich   knowledge  base  to  situations  beyond  the  original  context  of  learning),  then  just  like  before,  the   possibilities  for  what  a  knowledge  base  can  be  and  where  it  can  exist  are  altered.  In  the   example  I  have  developed  thus  far,  the  same  visible,  material  recipe  box  might  no  longer  count   as  a  useable  knowledge  base  because  such  a  recipe  box  is  not  typically  considered  a  mental   object.  To  be  considered  useable,  it  must  be  transformed  into  something  that  counts  as  mental   (or  cognitive),  for  example,  into  a  ‘concept,’  an  ‘idea,’  or  a  structured  ‘framework.'  If  the  recipe   box  is  not  transformed  into  something  mental  or  cognitive,  then  it  won’t  be  able  to  be  mentally   applied  or  transferred  to  situations  beyond  its  original  context  (e.g.,  outside  of  its  home   49       kitchen).  To  summarize  and  emphasize  the  key  point:  the  cognitive  feature  functions  as  a  kind   of  prerequisite  for  the  transfer  and  extrapolation  features.   The  cognitive  feature  helps  define  the  limits  and  boundaries  of  the  horizon  of   expectations  for  learning  with  understanding  in  Reform  Age  discourse  more  than  any  of  the   other  features.  We  might  even  go  as  far  as  saying  that  the  horizon  of  expectations  for  learning   with  understanding  in  Reform  Age  discourse  is  a  largely  mental,  psychological  or  cognitive  one.   In  other  words,  because  Reform  Age  discourse  demands  that  students  mentally  apply  or   transfer  their  deep,  rich  knowledge  bases  to  situations  beyond  the  original  context  of  learning,   the  expectation  is  that  students  need  to  transform  their  deep,  rich  knowledge  bases  into  purely   mental  forms.  How  else  will  students  be  able  to  mentally  apply  them  to  new,  different,   unfamiliar,  unscripted  or  strange  situations?  How  else  will  they  be  able  to  transfer  them— cognitively  speaking—to  experiences  beyond  those  commonly  considered  to  be  plain,  familiar,   ordinary,  scripted  and  familiar?  This  is  why  the  application  moment  is  so  important  in  science   education  assessments,  and  the  Mutant  Spinach  Question  is  an  example  of  assessing  the   cognitive  capacities  of  the  students,  especially  the  cognitive  capacities  of  transfer  and   extrapolation.  The  Mutant  Spinach  Question  does  not  assess  perceptions,  observation  skills,  or   manipulation  of  empirical  things;  it  assesses  what’s  inside  of  students’  minds/brains.   Before  examining  some  of  the  affordances  of  the  construction  of  learning  with   understanding  in  accordance  with  a  mental  horizon,  however,  I  want  to  pause  to  make  an   important  point.  Whether  learning  with  understanding  is  or  isn’t  mental  is  of  almost  no  concern   to  me.  My  major  concern  in  this  dissertation  amounts  to  something  entirely  different.  As  the   analysis  in  Chapter  1  tries  to  communicate,  science  educators  and  researchers  in  the  historical   50       period  in  which  I  live  and  work  routinely  assume  that  learning  with  understanding  is  a  mental  or   cognitive  skill/practice.  It’s  true;  this  is  one  way  to  construe  learning  with  understanding.   However,  in  contrast,  I  wish  to  raise  the  possibility  that  this  particular  assumption  about   understanding  could  be  viewed  as  rather  presumptuous  based  on  the  fact  that  it  does  not  align   59 with  anthropological  accounts  of  scientific  practice  produced  by  scholars  in  Science  Studies.   Accounts  of  scientific  practice  in  Science  Studies  often  show  that  scientific  understanding  is   typically  based  on  empirical  observations  and  the  subsequent  inscription  of  these  observations   into  visible,  material  forms.  Once  again,  this  particular  stance  should  make  it  clear  that  in  this   dissertation  I  am  studying  a  concept,  specifically,  the  concept  of  learning  with  understanding.  It   is  not  a  study  of  a  classroom,  a  teacher,  or  a  student.  It  is  not  a  study  of  teaching  or  learning.   My  overall  approach  is  to  study  the  understanding  while  it  is  in  action  or  in  practice.  In  the   remaining  parts  of  this  chapter,  I  will  draw  attention  to  both  the  affordances  and  constraints  of   60 constructing  learning  with  understanding  according  to  a  mental  or  cognitive  horizon.     Some  Affordances  of  a  Mental  Horizon     To  be  sure,  there  are  obvious  benefits  to  be  had  in  constructing  learning  with   understanding  primarily  as  a  mental  activity.  Here  are  four  of  them:   Capacity                                                                                                                   59.  I  will  have  much  more  to  say  about  the  domain  of  Science  Studies  later  in  this  chapter,  but   also  in  Chapter  4.   60.  My  approach  to  studying  learning  with  understanding  as  a  concept  is  primarily  inspired  by   Jonathan  Crary’s  approach  to  studying  “vision”  and  “attention”  (see  Crary  1990  and  Crary  1999)   and  Lorraine  Daston  and  Peter  Galison’s  approach  to  studying  “objectivity”  (see  Daston  and   Galison  2007),  but  also  Lynn  Fendler’s  approach  to  constructs  such  as  “teacher  reflection”  (see   Fendler  2003),  “community”  (see  Fendler  2006),  and  “generalisability”  (see  Fendler  2006).   51       The  human  brain  is  widely  believed  to  be  able  to  store  a  sizeable  amount  of  data  or   information.  According  to  one  source,  “most  computational  neuroscientists  tend  to   estimate  human  storage  capacity  somewhere  between  10  terabytes  and  100  terabytes,   61 though  the  full  spectrum  of  guesses  ranges  from  1  terabyte  to  2.5  petabytes.”  This   strong  belief  in  the  large  storage  capacity  of  the  brain  makes  it  an  ideal  location  to  store   the  deep,  rich  knowledge  base  deemed  necessary  to  carry  out  learning  with   understanding.   Portability   As  strange  as  this  may  sound,  the  human  brain  is  quite  conveniently  portable.  Other   than  a  regular  supply  of  food,  water,  and  oxygen,  the  human  brain  requires  little  else  to   sustain  it.  For  example,  it  does  not  require  its  owners  to  hook  themselves  up  to  any   external  electrical  leads.  This  obvious  fact  makes  it  well  suited  to  the  task  of  learning   with  understanding.  When  students  are  asked  to  mentally  apply,  extend  or  transfer   their  deep,  rich  knowledge  base  to  new,  novel,  unscripted  and/or  unfamiliar  situations,   some  of  these  situations  require  travel  through  space  and  time—e.g.,  from  one   classroom  to  another  (with  a  single  day  or  week),  from  one  classroom  to  another  (in   different  school  years),  or  from  one  classroom  experience  to  an  experience  outside  of   school.  The  portability  of  the  brain  ensures  that  the  deep,  rich  knowledge  base  deemed   necessary  to  carry  out  learning  with  understanding  will  always  be  present  when  needed.     Speed                                                                                                                   61.  Wickman,  “Your  Brain’s  Technical  Specs,”  para.  2.   52       The  human  brain  is  widely  believed  to  be  able  to  process  sizeable  amounts  of  stored   data  or  information  relatively  quickly.  At  least  part  of  this  belief  is  probably  held   collectively  between  and/or  among  the  results  of  studies  attempting  to  estimate  things   such  as  the  average  number  of  neurons  found  in  a  human  brain,  the  average  speed  at   which  these  neurons  can  ‘fire,’  and  the  average  number  of  connections  found  between   these  neurons.  Although  the  general  consensus  is  that  the  processing  speed  of  a  single   neuron  is  actually  quite  slow  compared  to  say,  the  processing  speed  contained  with  a   common,  1  gigahertz  (GHz)  smartphone,  the  sheer  number  of  neurons  and  their  often   multiple  connections  with  one  another  allows  us  to  see  the  human  brain  as  something   capable  of  performing  tasks  at  great  speed.  This  rather  common  belief  in  the  brain’s   processing  capacity  makes  it  possible  to  see  the  brain  as  a  tool  that  can  function  with   greater  speed  (and  also  efficiency)  than  many  other  tools.  The  ability  to  think  quickly   when  confronted  by  new,  novel,  unscripted  and/or  unfamiliar  situations  is  highly  valued   not  only  in  schools,  but  also  in  many  other  aspects  of  contemporary  society.  ‘Faster’  is   generally  deemed  to  be  ‘better.’  When  this  is  the  case,  it’s  not  surprising  that  educators   look  to  take  full  advantage  of  the  processing  capacity  of  the  brain.     Privacy   Protected  by  anatomical  features  such  as  hair,  skin,  and  bone,  as  well  often  further   shrouded  by  cultural  artifacts  such  as  hats,  wigs,  hoods  and/or  scarves,  the  mental   activities  and  processes  occurring  within  the  human  brain  remain  mostly  hidden  from   the  view  of  others.  In  other  words,  to  really  ‘see’  what  someone  else  is  thinking  is  a   difficult  thing  to  do.  In  situations  where  the  abilities  of  individuals  are  prioritized,  privacy   53       can  be  an  affordance  because  it  prevents  others  from  easily  co-­‐opting  or  stealing  their   ideas.  The  ability  to  think  independently—that  is,  to  think  for  one’s  self,  to  think  on   one’s  own  two  feet—is  often  highly  valued  in  schools.  When  this  is  the  case,  it’s  not   surprising  that  educators  look  to  take  full  advantage  of  the  privacy  offered  by  the  brain.   Among  other  things,  it  helps  ensure  that  individuals  will  be  rewarded  for  their  own  hard   work  as  opposed  to  the  hard  work  of  others.   To  summarize,  although  there  are  surely  other  benefits  not  accounted  for  here,  the   human  brain  is  widely  believed  and  reported  to  offer  students  the  affordances  of  capacity  (for   storage),  portability  (for  transport),  speed  (for  processing),  and  privacy  (for  reward).  These  four   benefits—or  rather,  cognitive  affordances—may  help  explain  why  science  education  constructs   learning  with  understanding  in  accordance  with  a  largely  mental/cognitive  horizon.  When  asked   to  apply  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning,  students  are  told  to  enlist  that  which  is  held  within  the  space  of  their  brains.  “Your   minds,”  students  are  often  told  by  their  teachers,  “Are  perhaps  your  greatest  ally.”   Describing  the  four  cognitive  affordances  is  a  way  of  providing  a  reason  or  explanation   for  the  analytical  observation  I  put  forth  in  Chapter  1—namely,  that  the  notion  of  learning  with   understanding  has  come  to  be  strongly  associated  with  a  mental  or  cognitive  horizon  of   expectations  in  the  Reform  Age.  When  science  educators  and  researchers  value  qualities  such   as  capacity,  portability,  speed,  and  privacy,  then  a  mental/cognitive  horizon  of  expectations  for   understanding  is  a  reasonable  pairing.  Before  raising  critical  questions  and  concerns  about  this   particular  historical  pairing,  however,  I  first  want  to  merge  the  cognitive  affordances  with  yet   another  layer  of  the  Reform  Age  discourse.  This  merging  exercise  is  made  possible  by  the   54       scholarship  of  the  educational  theorist  Jay  Lemke.  Lemke’s  work  helps  make  the  key  terms  and   commitments  of  the  mentalist/cognitive  horizon  more  explicit.           Abstract  Conceptual  Learning  Theory       The  dominant  theory  of  learning  that  guides  educational  practice  in  our  society  says   what  people  need  to  learn  are  "abstract  concepts,"  which  they  can  then  apply  to  a  wide   variety  of  specific  situations.  Nearly  everyone  is  convinced  that  conceptual  learning  is   the  most  powerful  form  of  learning,  and  the  only  problem  is  how  to  get  more  people  to   be  able  to  successfully  learn  abstract  concepts.  The  way  to  teach  abstract  concepts  is  to   demonstrate  how  they  apply  to  several  different  situations  until  the  student  "catches   on"  or  generalizes  and  "gets"  the  concept  at  an  abstract  level.  The  student  will  then  be   62 able  to  use  the  concept  wherever  it  is  relevant.     From  Lemke’s  description  of  “[t]he  dominant  theory  of  learning  that  guides  educational   practice  in  our  society,”  we  can  relatively  painlessly  extract  a  formal  name  for  a  theory  that   appears  to  be  the  lynchpin  or  cornerstone  of  the  mentalist/cognitive  horizon:  abstract   conceptual  learning  theory.  For  our  purposes,  then,  the  language  of  abstract  conceptual   learning  theory  should  be  added  as  yet  another  layer  to  our  two  already  existing  layers,  that  is,   to  the  five  discursive  features  of  learning  with  understanding  (see  Chapter  1)  and  the  four   cognitive  affordances  (see  previous  section).  If  we  look  carefully  at  Lemke’s  brief  description  of   abstract  conceptual  learning  theory,  we  can  quickly  identify  all  five  of  the  discursive  features  at   work  including  the  knowledge  base,  coherence,  transfer  and  extrapolation,  and  cognition.   Elaborating  abstract  conceptual  learning  theory  even  further,  Lemke  helps  familiarize  us   with  the  types  of  sensibilities  and  commitments  needed  to  sustain  a  mentalist/cognitive                                                                                                                   62.  Lemke,  “Semiotics  and  the  Deconstruction,”  para.  30.   55       construction  of  learning  with  understanding.  If  you  ask  most  science  teachers  what  their  main   goal  is,  Lemke  explains,  they  will  probably  say,  “for  my  students  to  understand  the  basic   63 concepts  of  physics,  chemistry,  biology,  or  whatever  other  field  is  being  studied.”     When  they  say  things  like  this,  Lemke  adds,  we  can  be  relatively  sure  that  abstract   conceptual  learning  theory  is  both  present  and  active.  “The  critical  words  here  are  ‘understand’   and  ‘concept,’”  Lemke  writes,  “and  both  of  these  terms  assume  a  fundamentally  psychological   approach  to  learning.  They  belong  to  the  tradition  of  mentalism,  in  which  concepts  are  mental   64 objects  and  understanding  is  a  mental  process."     In  this  particular  view  of  learning,  Lemke  writes,     a  concept  exists  outside  of  all  language,  and  indeed  outside  of  all  languages,  in  the  sense   of  representational  systems  like  images,  symbols,  actions,  etc.  It  exists  in  some   65 imaginary  “lingua  mentis”  [...]  a  “language  of  the  mind.     In  this  view  of  learning,  he  continues,  teachers  often  expect  their  students  to,   be  able  to  “discover”  the  concept  of  energy  for  themselves;  they  should  be  able  to   “generalize”  from  different  instances  of  energy  and  “see”  the  conceptual  unity  of  the   various  representations  [...]  It  should  be  possible  for  them  to  “leap”  to  the  abstraction   because  in  some  sense  that  abstraction  is  real,  and  is  always  naturally  there  as  a  target   66 for  their  leap.   In  this  view  of  learning,  Lemke  writes  elsewhere,  teachers  “assume  that  students  can   learn  abstract  principles  by  induction  from  examples  and  by  descriptions  of  abstract  properties                                                                                                                   63.  Lemke,  “Teaching  All  the  Languages,”  para.  1  (emphasis  in  the  original).   64.  Ibid,  para.  1  (emphasis  in  the  original).   65.  Ibid.,  para.  23.   66.  Ibid.,  para.  29.   56       67 and  relations.”  Furthermore,  Lemke  adds,  teachers  expect  students  to  “‘catch  on,’  to   formulate  abstract  generalizations  that  will  then  apply  to  new  and  unfamiliar  examples,”  and  to   68 “‘transfer’  the  abstract  principle  to  new  settings.”     The  approach  of  abstract  conceptual  learning  theory  is  clearly  a  psychological  one.   However,  as  we  will  soon  see  later  in  this  chapter  and  also  in  Chapters  3  and  4,  a  psychological   approach  to  learning  about  science  is  sometimes  not  aligned,  and  sometimes  not  compatible,   with  a  scientific  approach  to  learning  about  the  world.  Furthermore,  when  Lemke  writes  about   abstract  concepts,  abstract  principles,  and  abstract  properties  and  relations,  when  he  writes   about  discovery,  generalization,  induction,  understanding,  and  conceptual  unity,  and  when  he   writes  about  application,  transfer,  lingua  mentis,  and  leaping  to  new  settings,  specific  situations,   and  unfamiliar  examples,  by  now  readers  should  recognize  that  we  are  in  highly  familiar   discursive  territory.  This  is  precisely  the  same  mentalist/cognitive  territory  that  we  encountered   when  examining  the  Reform  Age  construction  of  learning  with  understanding  in  Chapter  1.   Because  many  of  the  discursive  features  and  commitments  of  abstract  conceptual  learning   theory  are  homologous  to  both  the  five  discursive  features  of  learning  with  understanding  and   the  four  cognitive  affordances,  we  can,  with  very  little  effort,  see  clearly  the  threads  of   complementarity  between  them.  Collectively,  these  three  overlapping  discursive  registers   underpin  the  mentalist  attitude;  they  are  part  of  the  same  discursive  family;  and  they  help   constitute  the  cognitive  horizon  of  expectations.  However,  a  few  of  important  questions  still   remain:  How  did  this  particular  horizon  come  to  dominate  the  Reform  Age  in  Science                                                                                                                   67.  Lemke,  “Semiotics  and  the  Deconstruction,”  para.  37.   68.  Lemke,  “Semiotics  and  the  Deconstruction,”  para.  40.   57       Education?  By  what  means  did  it  enter  the  Reform  Age  and  for  what  purpose?  And  perhaps   more  importantly,  are  there  possible  horizons  of  expectations  for  learning  with  understanding   that  are  something  other  than  mental/cognitive?   To  begin  the  process  of  generating  satisfactory  answers  to  these  questions  and  others,   we  briefly  turn  our  attention  to  another  educational  theorist,  Tom  Popkewitz,  and  his  concept   69 of  “the  alchemy.”     The  Alchemy  of  School  Subjects       Popkewitz’s  concept  of  the  alchemy  directs  attention  to  those  practices  in  modern   teaching  and  teacher  education  that  help  transform  the  disciplinary  subjects  into  school   subjects.  In  other  words,  it  directs  attention  to  those  practices  in  schooling  that  help  transform,   say,  the  content  of  biology  into  the  course  “BIO  100”  or  the  content  of  algebra  into  the  course   “MTH  101.”  As  Popkewitz  explains,   An  odd  thing  happens  on  the  way  to  school.  As  the  sorcerer  of  the  middle  ages  sought   to  turn  lead  into  gold,  modern  teaching  and  teacher  education  produce  a  magical   transformation  in  the  disciplines  of  the  sciences,  social  sciences,  and  humanities  [...]  I   70 call  this  transformation  an  alchemy.       Popkewitz’s  concept  of  the  alchemy  draws  our  attention  to  what  happens  to  disciplinary   knowledge  as  it  is  moved  from  scientific  laboratories  and  into  school  classrooms.  In  order  to   render  subject  matter  knowledge  and  practices  compatible  with  the  realities  of  schooling—the   school  timetable,  conceptions  of  childhood,  and  organizational  theories  of  teaching—they  must                                                                                                                   69.  What  Popkewitz  often  calls  "the  alchemy"  he  also  refers  to  as  "the  alchemy  of  pedagogy"   (Popkewitz  1998)  and  "the  alchemy  of  school  subjects"  (Popkewitz  2002;  2004).  In  this  text,  I   use  all  three  terms  interchangeably.   70.  Popkewitz,  “Alchemy  Makes  Inquiry,”  262.   58       be  translated,  ordered,  reconfigured,  transformed,  and/or  transmogrified.  After  all,  as   71 Popkewitz  observes,  “Children  are  not  scientists  or  mathematicians.”  For  Popkewitz,  then,   the  alchemy  of  school  subjects  is  unavoidable.  The  practical  reality  is  that  there  must  be  some   kind  of  alchemical  activity  that  takes  place  as  the  disciplines  are  transported  and  integrated  into   72 classrooms  because  alchemy  is  “a  necessary  part  of  schooling.”   But  how  does  the  concept  of  the  alchemy  help  us  account  for  the  construction  of   learning  with  understanding  as  largely  mental/cognitive?  According  to  Popkewitz,  the  stark   reality  of  modern  schooling  is  that  the  governing  principles  of  the  alchemy  are  no  longer  those   73 of  science  or  mathematics  “but  those  of  pedagogy.”  To  put  this  differently,  Popkewitz  claims   that  the  transformation  of  disciplinary  fields  such  as  biology  and  chemistry  are  more  likely  to  be   determined  by  disciplinary  tools  from  outside  biology  and  chemistry.  These  tools—or  what   Popkewitz  sometimes  calls  “translation  tools”—include  but  are  by  no  means  limited  to   disciplinary  assumptions,  commitments,  concepts,  and  theories.  In  other  words,  Popkewitz   suggests  that  the  ‘hard(er)’  sciences  are  more  likely  to  be  disciplined  by  ‘soft(er)’  sciences  as   they  make  their  way  into  school  and  classrooms  rather  than  their  own  disciplines.  These   circumstances  are  neither  inherently  good  nor  bad,  Popkewitz  notes,  but  it  practice  it  means   that  the  governing  principles  of  science  are  not  the  governing  principles  of  science  education— 74 instead,  they  are  the  governing  principles  of,  for  example,  social  sciences  such  as  psychology.                                                                                                                   71.  Ibid.,  262.   72.  Popkewitz,  “The  Alchemy,”  4.   73.  Ibid.,  4.   74.  For  a  provocative  and  insightful  account  of  the  historical  intersection  of  psychology  and   teacher  education,  see  Fender  2012.   59       And  when  this  happens,  Popkewitz  observes,  events  transpire  and  practices  emerge  which  are   75 at  the  same  time  both  “magical”  and  “odd.”   Abstract  Conceptual  Learning  Theory:  A  Tool  for  Translation     Now,  let  us  together  consider  abstract  conceptual  learning  theory  when  cast  in  light  of   the  alchemy  the  school  subjects.     At  the  end  of  Chapter  1,  we  saw  that  learning  with  understanding  in  the  Reform  Age  is   often  conceptualized  as  follows:  To  learn  with  understanding  is  to  be  able  to  mentally   demonstrate  the  ability  to  apply,  extend  or  transfer  a  deep,  rich  knowledge  base  to  situations   beyond  the  original  context  of  learning.  When  seen  through  the  lens  of  the  alchemy,  we  should   see  this  particular  definition  as  the  result  or  product  of  an  alchemical  transformation.  This   product  presupposes  that  there  is  something  outside  of  schools  and  classrooms  that  we  might   recognize  as  ‘authentic’  scientific  learning  with  understanding.  In  other  words,  the  alchemy  asks   us  to  assume  that  there  are  actual  moments  or  practices  during  which  scientists  can  be  seen   applying,  extending  or  transferring  their  existing  scientific  knowledge  to  new  problems,  strange   events,  and/or  unfamiliar  phenomena.  In  reality,  there  are  such  moments  and  practices.  We  in   science  education  commonly  recognize  them  in  both  formal  and  informal  conversation  as   scientific  “research,”  “inquiries,”  and  perhaps  even  as  “investigations.”  The  alchemy  asks  us   recognize  these  authentic  moments  and  practices  as  the  starting  or  ‘raw’  material  for  a   necessary  alchemical  transformation  in  large  part  because  the  realities  of  research  science  and   scientists  are  different  from  those  of  classroom  teachers  and  students.                                                                                                                   75.  Popkewitz,  “Alchemy  Makes  Inquiry,”  262.   60       What  I  want  to  suggest  here,  then,  is  that  Lemke  has  identified  for  us  one  of  the  main   translation  tools  for  this  alchemy.  Abstract  conceptual  learning  theory—which  Lemke  identifies   as  a  “fundamentally  psychological  approach  to  learning,”  as  belonging  to  “the  tradition  of   76 mentalism,”  and  as  a  “cognitive  model  of  science  education” —is  precisely  what  helps   transmogrify  the  raw  material  of  how  scientists  learn  with  understanding  into  the  refined   product  of  how  science  students  learn  with  understanding  in  the  Reform  Age.  Not  only  that,  but   abstract  conceptual  learning  theory  also  helps  give  distinct  shape  and  focus  to  how  science   professors  and  teachers  teach  for  understanding.  When  considered  in  the  light  and  shadows   cast  by  the  alchemy  of  school  subjects,  it  is  no  great  surprise  that  students  are  expected  to   demonstrate  the  ability  to  apply,  extend  or  transfer  a  deep,  rich  knowledge  base  to  situations   beyond  the  original  context  of  learning  in  ways  deemed  and  described  as  mental/cognitive.  It  is   also  not  surprising  that  in  teaching  science  for  understanding,  professors  and  teachers  spend  a   great  deal  of  instructional  time  and  energy  trying  to  target  and  improve  their  students’  mental   and  cognitive  abilities.  As  is  the  case  with  every  exercise  of  the  alchemy,  the  translation  tools  in   use  make  some  actions,  perspectives,  and  pedagogies  more  likely  while  simultaneously   rendering  others  less  so.  An  alchemy  using  abstract  conceptual  learning  theory  and  the   concepts  of  application  and  transfer  as  its  main  translation  devices  will  produce  certain  kinds  or   styles  of  teaching  for  understanding.  However,  there  is  no  guarantee  that  those  psychological   styles  will  always  resemble  scientific  styles.  For  example,  translation  tools  such  as  application   and  transfer  make  it  more  likely  that  teachers  will  ask  their  students  to  apply  or  transfer  their   deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of  learning  with  the  help  of                                                                                                                   76.  Lemke,  “Teaching  All  the  Languages,”  para.  1  (emphasis  in  the  original).   61       mental  or  cognitive  faculties  instead  of  with  the  help  of  other  types  of  faculties.  These  particular   translation  tools  also  make  it  more  likely  that  teachers  will  ask  their  students  to  enlist  mental  or   cognitive  allies  during  learning  instead  of  recruiting  other  types  of  allies.  In  other  words,  these   particular  translation  tools  make  it  more  likely  that  teachers  will  limit  or  bound  their   pedagogical  designs,  decisions,  and  other  actions  according  to  the  possibilities  articulated  by  a   mental  or  cognitive  horizon  instead  of  those  articulated  by  other  types  of  horizons.   In  practice,  the  use  of  abstract  conceptual  learning  theory  as  a  tool  with  which  to   translate  scientific  learning  with  understanding  into  classroom  learning  with  understanding   makes  it  extremely  difficult  to  conceive  of  learning  with  and  teaching  for  understanding  as   something  other  than  psychological,  mental,  and  cognitive.  In  other  words,  when  abstract   conceptual  learning  theory  is  directing  and  disciplining  the  alchemy  of  scientific  learning  with   understanding,  a  mental  horizon  appears  as  though  it  is  logical,  reasonable,  commonsensical,   and  perhaps  even  inevitable.  It  communicates  the  unnecessary  impression  that  psychology,   mentalism,  and  cognition  are  part  of  a  ‘natural’  order  of  things  or  ‘fundamental’  state  of  affairs.     If  there  is  one  thing  we  learn  from  the  Popkewitz’s  concept  of  the  alchemy,  however,  it’s   that  alchemists  have  a  choice  when  it  comes  to  selecting  their  translations  tools.  One  of  the   great  values  of  Popkewitz’s  concept  is  that  it  helps  make  possible  the  following  ‘What  if...’   questions:     What  if...     ● Science  educators  were  to  choose  a  different  kind  of  tool  of  translation  for  the   alchemy  of  how  scientists  learn  with  understanding?     62       ● Science  educators  were  to  move  away  from  the  governing  principles,  concepts,   and  theories  of  psychology,  mentalism,  and  cognition?     ● The  notion  of  mentality  was  temporarily  removed  from  the  Reform  Age   definition  of  learning  with  understanding?     ● Science  students  were  able  to  demonstrate  the  ability  to  apply,  extend  or   transfer  a  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning  without  having  to  do  so  mentally?     ● The  governing  principles,  concepts,  and  theories  of,  say,  scientific  research  were   allowed  to  inform  and  infuse  our  notion  of  learning  with  and  teaching  for   understanding?     ● Science  education  allowed  scientific  tools  to  be  the  basis  for  a  new  alchemy?       In  accordance  with  the  original  goal  stated  in  the  Introduction,  if  we  want  to  try  and   help  science  professors  and  teachers  find  ways  to  improve  student  performance  on  application   or  transfer  questions  in  the  future—in  other  words,  to  learn  with  understanding—then  one   course  of  action  would  be  to  disturb  or  disrupt  the  possibilities  articulated  by  a  mental  or   cognitive  horizon.  To  do  so  would  have  the  effect  of  distracting  us—at  least  for  the  moment— from  maintaining  too  strong  or  sharp  of  a  focus  on  mental  faculties  and  allies.  The  next  major   section  of  this  chapter  is  devoted  to  the  negative,  critical  task  of  such  a  disruption,  distraction,   and  provocation.  Once  readers  are  left  feeling  satisfactorily  disrupted,  distracted,  and  provoked,   only  then  can  I  begin  the  positive,  constructive  task  of  exploring  new  possibilities  for  the   alchemy  of  learning  with  and  teaching  for  understanding.       63       A  Critical  View  of  the  Mental  Horizon     In  the  previous  section,  we  saw  that  learning  with  and  teaching  for  understanding  in  the   Reform  Age  has  come  to  be  associated  with  a  mental/cognitive  horizon  of  expectations.  We   saw  that  this  construction  is  a  product  of  an  unavoidable  alchemy  of  school  subjects  that   transforms  how  scientists  learn  with  understanding  into  something  different.  Finally,  we  saw   that  this  alchemy  relies  on  psychological  and  cognitive  translation  tools  such  as  abstract   conceptual   learning   theory   and   concepts   such   as   “understanding,”   “application,”   and   “transfer.”   These  tools  give  a  distinct  shape  to  what  it  means  to  learn  with  and  teach  for  understanding.   They  help  actively  limit  or  bound  the  thoughts,  speech,  and  other  actions  of  both  teachers  and   students.  Not  only  do  they  help  define  an  envelope  of  possibilities,  but  they  also  help  define  an   envelop  of  probabilities  as  well,  and  those  probabilities  make  science  more  accessible  to  some   students  than  to  others.   In  the  remaining  sections  of  this  chapter,  I  take  a  critical  approach  to  this   mental/cognitive  horizon.  Once  again  drawing  heavily  from  the  scholarship  of  Lemke  and   Popkewitz,  I  offer  a  challenge  to  the  association  of  learning  with  and  teaching  for   understanding  with  a  mental/cognitive  horizon.  In  using  the  term  critical,  I  mean  to  say  that  I   aim  to  render  certain  commitments  and  assumptions  of  this  historically  situated  discourse   explicit.  By  rendering  these  elements  explicit,  they  become  available  to  various  modes  or  styles   of  critique.  Among  other  uses,  critique  can  help  a)  delineate  the  existing  boundaries  of  a   current  cultural  practice  with  increased  precision,  b)  draw  attention  to  various  ironies,   problems,  obstacles,  challenges,  discrepancies  and/or  conundrums  posed  to  and  faced  by  the   64       members  of  a  particular  community,  and  c)  remind  the  members  of  a  particular  community   that  it  is  possible  to  think,  speak,  and  act  differently.     Raising  Questions  about  Cognition     To  ask  science  educators  to  distance  themselves  from  a  mental/cognitive  horizon  is  to   risk  professional  heresy.  Such  is  the  depth  of  support  given  to  the  power  and  promise  of  the   mind/brain  in  science  education.  We  already  have  one  sensible  reason  to  take  this  risk,   however,  and  it  comes  to  us  in  the  form  of  the  Mutant  Spinach  Question.  Let  us  not  forget  the   fact  that  eighty  percent  of  the  fall  2006  Bio101  students  answered  the  Mutant  Spinach   77 Question  incorrectly.  There  is  at  least  one  more  sensible  reason  to  add  to  this  list  of   grievances.  This  one  is  related  to  cognition.  Despite  the  aforementioned  affordances  of  the   brain,  which  included  capacity,  portability,  speed,  and  privacy,  there  are  at  least  two  widely   acknowledged  cognitive  constraints  shackling  this  so-­‐called  ‘super’  organ.  First,  the  human   brain’s  working  or  short-­‐term  memory  is  widely  reported  to  be  capable  of  holding  somewhere   between  five  to  seven  “chunks”  of  information  depending  on  the  category  and  features  of  the   78 chunks.  This  characteristic  of  the  brain  could  be  seen  as  a  constraint  on  students’  ability  to   learn  with  understanding.  Depending  on  the  size,  structure,  and  integrity  of  a  chunk  (a   construct  that  is  still  hotly  debated  among  cognitive  scientists),  this  characteristic  could  hinder                                                                                                                   77.  Because  the  Mutant  Spinach  Question  was  a  multiple-­‐choice  question,  the  Bio101   professors  openly  acknowledged  that  there  was  no  way  of  knowing  how  many  of  the  twenty   percent  of  students  who  answered  the  Mutant  Spinach  Question  correctly  got  it  right  “for  the   right  reasons.”  In  other  words,  they  were  fully  prepared  to  concede  that  the  twenty  percent  of   students  who  answered  question  “52”  correctly—and  for  the  right  reasons—was  in  reality   probably  something  less  than  twenty  percent.   78.  See  Miller,  G.A.  "The  Magical  Number  Seven  Plus  or  Minus  Two:  Some  Limits  on  Our   Capacity  for  Processing  Information."  Psychological  Review  63,  no.  2  (1956):  81–97.  (Re-­‐ published  in  Psychological  Review  in  April  1994.)   65       students’  ability  to  efficiently  access  and  make  use  of  the  deep,  rich  knowledge  base  deemed   necessary  to  carry  out  learning  with  understanding.  Second,  a  new  generation  of  high-­‐ resolution  neuroimaging  techniques  has  prompted  some  researchers  to  claim  that  the  human   79 brain’s  complexity  is  beyond  both  imagination  and  belief.  The  task  of  mapping  the  brain  so  as   to  better  display  its  many  levels  (and  layers)  of  both  structural  and  functional  complexities  is   seen  as  so  challenging,  that  a  Nobel  Prize  winning  brain  researcher,  Eric  Kandel,  had  this  to  say   of  U.S.  President  Barack  Obama’s  2013  announcement  of  the  BRAIN  project  (Brain  Research   through  Advancing  Innovative  Neurotechnologies):  “Going  to  the  moon  –  I  don’t  mean  to  in  any   way  minimize  it  –  was  in  part  an  engineering  project.  This  [BRAIN  project]  is  going  into  the   80 unknown.  This  is  like  Columbus  discovering  America,  if  you  will.”  This  particular  characteristic   of  the  brain  could  be  seen  as  a  constraint  on  students’  ability  to  learn  with  understanding.  Such   complexity  could  hinder  the  ability  of  researchers  in  science  education  to  know  with  precision   where  in  the  brain  the  many  facets  of  learning  with  understanding  occur  (not  to  mention  how).   Admittedly,  our  list  of  grievances  is  rather  short—in  fact,  we  now  have  two.  Most   science  educators,  however,  will  require  a  lengthier  list  of  grievances  before  they  begin  to   consider  distancing  themselves  from  such  a  long-­‐standing  mental/cognitive  horizon.  For                                                                                                                   79.  Stephen  Smith,  a  professor  of  molecular  and  cellular  physiology  described  the  brain’s   complexity  this  way:  “One  synapse,  by  itself,  is  more  like  a  microprocessor—with  both  memory-­‐ storage  and  information-­‐processing  elements—than  a  mere  on/off  switch.  In  fact,  one  synapse   may  contain  on  the  order  of  1,000  molecular-­‐scale  switches.  A  single  human  brain  has  more   switches  than  all  the  computers  and  routers  and  Internet  connections  on  Earth.”  Moore,   “Human  Brain,”  para.  7  (see  inset).  This  fact  is  particularly  impressive  when  considering  that  in   the  cerebral  cortex  alone  there  are  roughly  125  trillion  synapses.     80.  Pathe,  “Obama  Hopes,”  para.  5.     66       assistance  in  this  endeavor  I  return  to  the  work  of  Lemke,  and  later  to  Popkewitz,  who  will  each   help  us  populate  the  list  with  additional  grievances.   Raising  Questions  about  Abstract  Conceptual  Learning  Theory       Let  us  quickly  review  what  Lemke  said  about  abstract  conceptual  learning  theory   (hereafter  ACLT).  First,  ACLT  is  the  dominant  theory  of  learning  that  guides  educational  practice   in  our  society.  It  says  that  what  people  need  to  learn  are  abstract  concepts,  which  they  apply  or   transfer  to  a  wide  variety  of  specific  situations.  Second,  nearly  everyone  is  convinced  that   abstract  conceptual  learning  is  the  most  powerful  form  of  learning.  Therefore,  the  problem  of   teaching  can  be  formulated  as  follows:  how  can  we  get  even  more  students  to  successfully   learn  even  more  abstract  concepts?  Third,  because  ACLT  foregrounds  both  “concepts”  and   “understanding,”  it  assumes  a  fundamentally  psychological  approach  to  learning.  It  belongs  to   the  tradition  of  mentalism,  in  which  concepts  are  mental  objects  and  understanding  is  a  mental   process.  In  more  contemporary  terms,  it  belongs  to  a  cognitive  model  in  science  education.   Fifth,  in  this  view  of  learning,  concepts  exists  outside  of  all  language.  They  exist  in  some   81 imaginary  “lingua  mentis”  [...]  a  “language  of  the  mind.'   In  practice,  Lemke  reports  that  this  particular  construction  of  ACLT  produces  a  style  of   science  teaching  in  which:   ● Teachers  teach  abstract  science  concepts  by  demonstrating  how  they  apply  to  several   different  situations  until  their  students  catch  on  or  generalize  and  get  the  concept  at  an                                                                                                                   81.  Lemke,  “Teaching  All  the  Languages,”  para.  23.   67       abstract  level.  Once  this  happens,  they  assume  their  students  will  then  be  able  to   transfer  that  knowledge,  that  is,  to  use  the  concept  wherever  it  is  relevant.   ● Teachers  expect  their  students  to  be  able  to  a)  discover  science  concepts  for  themselves,   b)  generalize  from  different  instances  of  the  concepts,  c)  see  the  conceptual  unity  of  a   science  concept  among  its  various  representations,  and  d)  leap  to  the  abstraction   because  in  some  sense  that  abstraction  is  real,  and  is  always  naturally  there  as  a  target   for  their  leap.   ● Teachers  assume  that  students  can  learn  abstract  principles  by  induction  from  examples   and  by  descriptions  of  abstract  properties  and  relations.     ● Teachers  expect  students  to  a)  catch  on,  b)  formulate  abstract  generalizations  that  will   then  apply  to  new  and  unfamiliar  examples,  and  c)  transfer  the  abstract  principle  to  new   settings.   When  reading  these  statements,  we  should  see  that  ACLT  tends  to  push  entities  such  as   knowledge,  thinking,  concepts,  abstraction,  reasoning,  logic,  and  understanding  (as  well  as   other  entities)  into  an  existence  defined  largely  by  qualities  such  as  invisibility  and  immateriality.   Qualities  such  as  these  tend  to  render  entities  such  as  knowledge  and  understanding  incredibly   difficult  for  students,  teachers  (including  teacher  educators),  and  researchers  to  see  and  touch.   In  some  ways,  these  particular  qualities  tend  to  render  highly  valued  entities  as  individualized,   secretive,  clandestine,  undocumentable,  and  universal  (among  other  renderings).  And  yet,   knowledge,  thinking,  reasoning,  and  understanding  are  some  of  the  most  celebrated  and   promoted  allies  in  the  movement  to  reform  all  of  science  education.   68       To  take  a  mentalist  approach  to  entities  such  as  knowledge,  thinking,  reasoning,  and   understanding  is  to  make  a  choice  that  privileges  individuality,  secrecy,  clandestinity,   undocumentability,  and  universality  over  other  qualities.  In  order  words,  to  take  a  mentalist   approach  to  these  allies  is  to  be  selective  and  exclusive.  It  limits  our  conceptions  of  what  these   entities  can  be  to  a  culturally  and  historically  specific  set  of  values,  ethics,  assumptions,  and   beliefs.  Lemke  helps  us  contextualize  this  line  of  critique  explicitly  within  science  education:     Of  course  students  do  independently  construct  some  kinds  of  [conceptual]  similarities   between  situations  on  their  own.  These  may  agree  with  those  constructed  by  the   discourses  and  practices  of  science  or  they  may  not.  The  odds  are  not  in  the  students'   favor.  When  students  do  effectively  and  more  or  less  independently  recapitulate  the   history  of  modern  European  science,  it  is  largely  because  they  are  so  positioned  within   contemporary  society  that  they  have  already  begun  to  construct  some  of  the  higher-­‐ order  patterns  that  characterize  how  our  dominant  cultural  tradition  approaches  certain   kinds  of  problems.  This  will  be  much  more  commonly  the  case  for  students  of  upper-­‐ middle  class  cultural  background  than  for  students  who  are  not  daily  immersed  in  the   dominant  subculture  of  our  society,  the  one  that  dictates  the  curriculum.  It  is  not   82 evidence  of  superior  intelligence,  but  of  privileged  cultural  positioning.       For  Lemke,  the  set  of  values,  ethics,  assumptions  and  beliefs  that  define—and  thus   place  limits  on—our  current  approach  to  entities  such  as  knowledge  and  understanding  are   mostly  those  of  “upper-­‐middle  class”  cultural  backgrounds.  According  to  this  logic,  those   students  from  backgrounds  outside  of  the  upper-­‐middle  class  are  more  likely  to  struggle  in   educational  moments  in  which  knowledge  and  understanding  are  defined  exclusively  as  mental   and  cognitive.  On  the  other  hand,  this  same  logic  also  makes  it  possible  to  formulate  a  reverse   argument:  those  students  from  backgrounds  outside  of  the  upper-­‐middle  class  are  more  likely                                                                                                                   82.  Lemke,  “The  Missing  Context,”  para.  22  (emphasis  added).   69       to  find  greater  success  in  moments  in  which  knowledge  and  understanding  are  defined  as   something  other  than  mental/cognitive.   To  define  entities  such  as  knowledge  and  understanding  as  something  other  than   mental  or  cognitive  requires  a  disruption  of  abstract  conceptual  learning  theory.  To  disrupt   ACLT  one  needs  to  revise  the  psychological  notions  of  the  “concept”  and  “abstraction.”  Only   then  can  ACLT  be  made  more  inclusive  and  less  constraining  for  teachers  and  students.  If  ACLT   can  be  given  permission  to  value  other  styles  of  learning,  including  and  especially  non-­‐ psychological  or  empirical  styles  of  learning,  then  we  will  have  succeeded  in  making  learning   with  and  teaching  for  understanding  more  inclusive  educational  practices.  Abstract  conceptual   learning  theory  doesn’t  have  to  be  so  individualized,  secretive,  clandestine,  rationalistic,  and   universalized.  This  historically  and  culturally  specific  formulation  of  ACLT  is  not  inevitable.  It  can   be  different.  It  can  be  otherwise.  More  specifically,  it  can  be  more  inclusive,  more  empirical,   and  more  scientific.   Raising  Questions  about  Psychology       The  histories  of  psychology  and  science  education  are  entangled  in  complex  ways.   Fortunately,  Popkewitz  has  already  done  a  fair  bit  of  disentangling  for  us—at  least  enough  to   allow  us  to  continue  to  raise  doubts  about  the  suitability  of  the  use  of  translation  tools  from   psychology.   When  speaking  earlier  of  the  alchemy  of  school  subjects,  it  was  said  that  because  so   many  of  the  translation  tools  used  in  science  education  originate  in  the  psychological  sciences,   science  education  frequently  ‘minds’  the  gaps  between  scientists’  science  and  school  science.   Another  way  of  saying  this  is  that  when  it  comes  to  science  teaching  and  learning,  the   70       mind/brain  is  still  the  primary  object  of  interest  and  affection.  For  Popkewitz,  however,  we   should  perceive  this  practice  of  minding  the  gap  between  disciplinary  fields  and  school  subjects   from  at  least  two  viewpoints.   First,  we  must  recognize  that  the  use  of  psychological  tools  to  translate  disciplines  like   science  is  neither  inherently  good  nor  bad.  Instead,  the  use  of  such  tools  should  be  viewed  as   having  certain  affordances  and  constraints.  Whether  or  not  a  particular  psychological  tool  is  an   affordance  or  a  constraint  can  depend  largely  on  a  variety  of  issues  including  pragmatic  (what  is   the  desired  outcome?)  and  socio-­‐political  (who  benefits?  who  doesn’t?)  concerns.  For  example,   Popkewitz  goes  to  great  lengths  to  show  how  the  governing  principles  of  psychological  and   social  psychological  concepts  and  tools  are  well  suited  to  the  tasks  of  normalization  and  division.   The  relocation  of  school  subjects  into  psychology  inscribes  divisions  that  locate  the  child   who  does  not  have  the  dispositions  and  sensitivities  inscribed  in  the  alchemy.  The   deviant  child  is  the  child  who  does  not  learn  the  alchemy,  does  not  follow  the  conduct  of   the  alchemic  problem  solving,  and  thus  needs  to  be  rescued  through  better   management  and  self-­‐management.  Few  notice  that  the  evidence  of  teaching  school   subjects,  pedagogical  content  knowledge,  and  curriculum  standards  are  about  the   83 psychological  well-­‐being  or  the  deviancy  of  the  child.         In  the  field  of  education,  most  influences  of  psychology  are  regarded  as  authoritative   and  beneficial.  However,  Popkewitz's  analysis  helps  open  a  possibility  in  which  it  is  possible  to   recognize  the  limitations  and  exclusions  of  psychological  approaches  to  teaching  and  learning.   One  limitation  of  abstract  conceptual  learning  has  already  been  mentioned:  its  privileges  some                                                                                                                   83.  Popkewitz,  “Alchemy  Makes  Inquiry,”  p.  265  (emphasis  added).  See  also  Popkewitz  1998;   2004.     71       84 students  while  excluding  others.  An  example  from  my  own  experience  in  science  education   research  might  illustrate  more  clearly  how  psychological  tools  are  effective  tools  for  particular   ends  such  as  normalizing  and  sorting  students.   In  Pursuit  of  Model-­‐Based  Reasoners:  An  Example  of  the  Alchemy  in  Action     As  a  member  of  a  university  research  team  trying  to  improve  teaching  and  learning  in   undergraduate  biology  courses,  my  team  looked  to  research  accounts  of  disciplinary  science  for   tools  and  concepts  commonly  used  by  scientists  in  their  daily  practices.  “Scientific  models,”  it   was  decided,  were  representational  tools  that  seemed  to  do  much  of  the  intellectual  heavy   85 lifting  in  science.  In  the  process  of  bringing  scientific  models  to  the  forefront  of  teaching  and   learning  in  introductory-­‐level  biology  courses,  we  translated  our  initial  ideas  about  scientific   86 models  into  a  taxonomy  similar  to  Bloom's  Taxonomy  of  Educational  Objectives.  Bloom's   Taxonomy,  with  its  division  of  educational  objectives  into  three  "domains"—affective,   psychomotor,  and  cognitive—has  obvious  roots  in  psychology.  Each  domain  is  subsequently   divided  into  various  "levels."  Our  taxonomic  tool  also  included  levels  that  we  called   87 "categories,"  which  we  then  used  to  classify  and  group  multiple-­‐choice  exam  questions.  Our   taxonomy  helped  us  classify  and  order  existing  exam  questions  in  used  the  course  as  Category  1,   2,  3  or  4  questions  corresponding  to  the  following  descriptions:                                                                                                                   84.  Another  limitation,  one  that  will  be  developed  and  discussed  further  in  Chapters  3  and  4,  is   that  abstract  conceptual  learning  is  not  even  the  preferred  style  of  inquiry  for  most  scientists.   85.  For  example,  see  Rudolph  2000  and  Giere  2004.   86.  See  Bloom  et  al.  1956.   87.  See  Richmond  et  al.  2010.   72       Category  1:  Not  directly  associated  with  features  of  the  specific  photosynthesis  teaching   model  as  presented   Category  2:  Describe  or  reproduce  the  specific  model   Category  3:  Manipulate  the  photosynthesis  model  in  context   Category  4:  Apply  the  model  in  situations  beyond  the  original  context         With  the  aid  of  additional  translation  tools  such  as  statistics,  we  evaluated  a  longitudinal   data  set  containing  student  performance  on  the  four  categories  of  exam  questions.  The  results   of  our  statistical  analysis  eventually  helped  us  divide  students  into  two  new  types  or  kinds  of   students:  “model-­‐based  reasoners”  and  “non  model-­‐based  reasoners.”  In  the  language  of  the   research  group,  those  students  who  regularly  answered  the  Category  4  questions  correctly  on   exams  were  said  to  reason  “more  like  scientists,"  while  those  students  who  regularly  answered   the  Category  4  questions  incorrectly  on  exams  were  said  to  reason  “more  like  students."   The  alchemical  path  on  which  our  research  group  traveled  should  by  now  be  evident.   We  subjected  scientific  models  to  an  alchemical  reaction  by  way  of  the  use  of  translation  tools   from  both  psychology  and  statistics.  Along  the  way,  we  created  an  efficient  means  of   normalizing  and  sorting  both  the  exam  questions  (into  four  categories)  and  the  students  (into   two  categories).  As  a  result  of  this  particular  alchemy,  new  potentials  were  created  for  the   governing  of  each  of  these  two  entities.  If  they  wanted  to,  the  professors  could  exert  new  forms   of  governance  on  the  test  questions.  For  example,  they  could  select  certain  questions  for   deletion,  revision,  or  promotion  based  solely  on  their  “Category”  status.  If  they  wanted  to,  the   professors  could  also  exert  new  forms  of  governance  on  the  students.  For  example,  they  could   identify  certain  students  as  candidates  for  either  “advanced  study”  or  “remediation”  based   73       88 upon  their  newly  earned  status  as  either  model-­‐based  or  non  model-­‐based  “reasoners.”  In   other  words,  one  of  the  outcomes  of  our  study  was  that  we  created  a  new  reality  in  which   certain  questions  with  particular  traits  and  certain  students  with  particular  traits  could  be   89 subjected  to  educational  practices  that  they  had  never  previously  encountered.   More  generally,  when  tests  ask  students  to  display  knowledge  they  have  never  been   explicitly  taught,  it  suffices  to  say  that  those  test  questions  privilege  some  students  and  exclude   others.  Those  whose  cultural  experiences  match  those  of  the  instructors  will  have  prior   knowledge  that  puts  them  at  an  advantage.  The  test  questions  assume  a  trajectory  of  inference   that  is  particular  to  a  specific  historical  and  cultural  subgroup.  This  assumption  of  abstract   conceptual  learning,  then,  functions  to  normalize  and  to  sort—it  includes  some  styles  of   thinking  and  excludes  other  styles.   One  may  be  inclined  to  label  Popkewitz's  work  as  anti-­‐division,  anti-­‐normalizing,  and   anti-­‐governance.  To  that  charge,  however,  Popkewitz  explicitly  states  that  psychological   concepts  and  theories  "are  not  necessarily  bad  and  may  have  importance  in  the  governing  of   90 schooling."  Thus,  Popkewitz  is  open  to  the  possibility  of  the  there  being  strong  social  and                                                                                                                   88.  This  anecdote  offers  us  a  way  of  understanding  the  concept  of  governmentality  that  is   somewhat  different  from  Foucault’s  use  of  the  term.  That  is,  when  the  means  of  crossing  a  gap   between  scientists'  science  and  school  science  is  conceptualized  primarily  as  the  'minding'  of  it,   one  of  the  end  results  is  that  researchers  and  teachers  gain  in  their  ability  to  direct  the  minds  of   a  student  or  group  of  students  towards  certain  ends—in  other  words,  they  gain  in  their  ability   to  govern  their  students’  mentality.   89.  Another  way  to  describe  what  my  research  group  did  with  the  scientific  models  is  that  we   engaged  in  the  practice  of  "psychological  reductionism"  (see  Popkewitz  2004,  27).  That  is,  we   took  a  complex  cultural  practice  that  enables  scientific  knowledge  production  and  reduced  it  to   a  psychological  concept—model-­‐based  reasoning—that  we  then  used  to  divide,  normalize,  and   govern  students.   90.  Popkewitz,  “Alchemy  Makes  Inquiry,”  p.  265.     74       political  reasons  for  undergraduate  science  students  to  learn,  for  example,  how  to  be  "model-­‐ based  reasoners"  and  how  to  improve  their  "model-­‐based  reasoning  skills."  The  problem  is  that   psychological  concepts  tend  to  govern  teaching  and  learning  to  the  exclusion  of  other   approaches,  and  this  narrow  limitation  has  the  effect  of  making  science  more  accessible  to   some  students  than  to  others.   This  last  point,  which  addresses  the  potential  desirability  for  students  that  can  engage  in   a  certain  type  of  reasoning,  finally  brings  us  to  the  second  of  the  two  viewpoints  that  are  critical   for  understanding  Popkewitz's  critical  position  on  the  minding  the  gap  between  disciplinary   fields  and  school  subjects.  To  recapitulate,  his  first  viewpoint  is  that  we  must  recognize  that  the   use  of  psychological  tools  to  translate  disciplines  like  science  is  neither  inherently  good  nor  bad.   His  second  perspective  is  that  we  must  also  recognize  that  the  use  of  psychological  tools  may   have  functions  originally  designed  for  purposes  other  than  translating  disciplinary  fields  into   school  subjects.  Or,  as  Popkewitz  explains,  “The  psychologies  of  childhood,  learning,  and   cognition  are  inventions  that  have  different  purposes  from  those  of  understanding  and   91 translating  disciplinary  knowledge  into  pedagogical  problems.”   At  this  point,  one  might  be  tempted  to  reach  the  conclusion  that  Popkewitz  is  anti-­‐ alchemy.  On  the  contrary,  he  writes,  "The  fact  that  an  alchemy  exists  in  schools  is  not   92 93 surprising."  Furthermore,  Popkewitz  writes,  "Alchemy  is  a  necessary  part  of  schooling."   Instead,  what  Popkewitz  finds  surprising  and  unnecessary  is  the  "peculiar"  school  alchemy  that   relies  on  psychological/social  psychological  concepts  and  tools  in  its  transformation  of  the                                                                                                                   91.  Ibid.,  p.  265  (see  also  Popkewitz  1998).   92.  Ibid.,  p.  262.   93.  Popkewitz,  “The  Alchemy,”  4.   75       disciplines  for  use  in  schooling  to  the  exclusion  of  all  other  approaches.  In  its  construction  of   pedagogies,  Popkewitz  argues  that  schooling  has  turned  repeatedly  toward  psychologies  of   instruction,  which  he  sees  as  intellectual  tools  that  have  little  to  do  with  the  practices  found  in   disciplinary  fields  such  as  science  and  mathematics.   Instead,  he  suggests  an  "unthinking"  of  the  alchemy  by  turning  to  fields  other  than   psychology.  One  candidate  field  he  finds  promising  is  Science  Studies—a  field  constituted  by  a   collection  of  sociologists,  historians,  economists,  political  scientists,  philosophers,  and   anthropologists  of  science  and  technology.  A  consideration  of  Science  Studies  as  a  resource  for   the  alchemy,  Popkewitz  explains,     requires  different  intellectual  tools  and  strategies  for  thinking  about  and  ordering  the   practices  of  an  academic  field  than  are  found  in  current  curriculum  models  […]  This   alternative  reading  would  focus  on  relations  or  assemblages  that  construct  disciplines,   historicizing  how  the  subject  is  constructed  and  changes  over  time,  and  on  the   epistemes  or  the  systems  of  thought  that  make  possible  particular  types  of  knowledge   in  a  field.  That  is,  pedagogy  needs  intellectual  tools  that  consider  the  relation  between   the  knowledge  (concepts,  generalizations)  and  the  cultural  practices  that  enable  the   94 production  of  that  knowledge.       For  Popkewitz,  to  engage  Science  Studies  as  a  resource  for  pedagogical  alchemies  does   not  eliminate  the  problem  of  alchemy  because  disciplinary  fields  must  undergo  some  sort  of   transformational  processes  on  their  way  into  the  spaces  of  schooling.  Additionally,  it  does  not   deny  a  place  for  psychology/social  psychology  in  curriculum  construction.  Rather,  as  Popkewitz   writes,     it  suggests  that  in  constructing  pedagogies  we  should  turn  to  fields  of  scholarship   concerned  with  interpreting  the  intellectual  styles,  rules  of  thought,  and  practices   through  which  knowledge  is  generated  in  academic  disciplines.  The  psychologies  of                                                                                                                   94.  Ibid.,  27.   76       instruction  in  standards-­‐based  reforms  are  inventions  to  normalize  the  child  and  thus   are  inadequate  for  purposes  of  translating  mathematics,  science,  or  other  academic   95 fields  into  curriculum  projects.         To  summarize,  Popkewitz's  problematization  of  the  performance  of  psychological   alchemies  in  contemporary  education  is  twofold.  First,  he  states  that  while  the  alchemy  of   school  subjects  may  be  unavoidable,  a  psychological  or  social  psychological  alchemy  is  a  choice.   Even  though  disciplinary  fields  must  undergo  some  sort  of  transformation  for  use  in  schools,   the  governing  principles  of  the  alchemy  need  not  be  those  of  psychology/social  psychology.   There  are  other  options.  There  are  other  pathways  one  can  chose.  In  other  words,  the  alchemy   does  not  require  minding  the  gap  between  disciplinary  fields  and  school  subjects.  Second,  there   are  ways  to  unmind—or,  as  Popkewitz  writes,  to  "unthink"—the  gap.  Much  research  in  Science   Studies  examines  the  practices  through  which  knowledge  is  generated  the  sciences.  This   discipline  can  also  provide  translation  tools  for  the  alchemy.  Rather  than  being  well  suited  to   normalizing,  dividing,  and  governing  individuals,  however,  Science  Studies  offers  concepts  and   tools  designed  for  other  purposes  (I  will  discuss  some  of  these  purposes  in  Chapter  4).   What  we  should  take  from  this  brief  (and  limited)  summary  of  Popkewitz’s  position  is   this:  historically,  the  psychological  sciences  weren't  intellectual  practices  designed  for  the   purpose  of  understanding,  say,  fields  of  practice  such  as  science  and  mathematics.  Instead,  they   were  concerned  with  the  interior  of  individuals,  as  well  as  the  rules  and  standards  of  "reason"   that  enabled  human  progress  and  self-­‐betterment.  In  other  words,  historically  the  psychological   sciences  weren't  concerned  with  the  practices  of  scientists  trying  to  learn  with  understanding.   They  were  concerned  with  refashioning  a  new  type  of  citizen  who  would  be  more  'fit'  to  the                                                                                                                   95.  Ibid.,  27.   77       current  (and  future)  times—individuals  who  would  be  more  aware  of  their  individual,  subjective   96 selves—including  their  desires,  affects,  attitudes,  and  bodily  practices.     Summary     And  so  we  return  to  a  question  I  raised  earlier  in  the  chapter:  Is  it  possible  that  our   current  assumptions  about  understanding  might  produce  obstacles  and/or  undesirable  effects   for  those  teachers  trying  to  teach  for  understanding,  as  well  as  those  students  trying  to  learn   with  understanding?  My  simple  answer  is,  Yes.  Absolutely.  Without  a  doubt.  ACLT  privileges   some  ways  of  thinking  about  science  and  excludes  other  ways  of  thinking  about  science,  so  a   mentally-­‐  or  cognitively-­‐committed  ACLT  is  not  a  productive  theory  or  model  to  meet  the   widely  heralded  goal  of  ‘science  for  all  Americans.’  If  science  educators  were  serious  about  the   goal  of  science  for  all,  they  would  give  serious  consideration  to  ways  of  including  more  students   and  excluding  less  of  them.  One  way  they  might  do  this  is  by  considering  an  alchemy  of   scientific  understanding  that  is  not  informed  by  the  psychological  sciences.  Instead,  they  might   consider  an  alchemy  that  is  informed  by  Science  Studies.     Consider  for  a  moment  the  simple  observation  that  every  day  the  Bio101  students  come   into  the  classroom  they  see  things,  touch  things,  do  things,  and  leave  with  things  in  their  arms,   hands,  and  book  bags.  On  the  day  of  the  exam,  however,  what  they  can  see,  touch,  and  do  in   class  and  what  they  can  bring  with  them  to  class  is  much  more  constrained.  This  is  because   learning  with  understanding  is  enacted  by  its  participants  as  if  it  were  a  mental  or  cognitive   practice  and  not  a  physical  or  material  one.  At  the  same  time  this  construction  of   understanding  draws  attention  to  entities  that  are  both  invisible  and  immaterial  (e.g.,                                                                                                                   96.  For  Popkewitz,  people’s  desires,  affects,  attitudes,  and  bodily  practices  count  as  the  “soul.”   78       knowledge,  concepts,  reasoning,  etc.),  it  effectively  draws  attention  away  from  entities  with   more  visible  and  material  constitutions  (e.g.,  handouts,  notes,  textbooks,  etc.).     Question  “52,”  the  Mutant  Spinach  Question,  is  an  excellent  example  of  a   mental/cognitive  horizon  of  expectations  in  action.  When  nearly  eighty  percent  of  the  students   answer  the  question  incorrectly  on  the  test,  the  professors  immediately  seek  agents  for  the   widespread  failure  in  the  mind/brains  of  their  students.  They  talk  about  things  such  as   “misconceptions,”  “misunderstanding,”  and  “procedural  display.”  Unfortunately,  attempting  to   penetrate  the  minds/brains  of  almost  four  hundred  undergraduate  students  is  too  daunting  of   a  task.  The  instructors  quickly  become  frustrated  because  they  don’t  seem  to  know  what  their   students  were  thinking  and  how  they  were  reasoning  during  the  exam—it’s  no  wonder,  the   entire  class  sat  in  almost  complete  silence  during  the  exam.  “If  only  we  could  get  inside  of  their   heads,”  one  of  the  Bio101  professors  once  lamented  to  me  after  the  exam,  “If  only  we  could   see  what  they  were  thinking  during  the  exam.”  In  this  instance,  the  professors  locate  their   students’  lack  of  understanding  in  a  space  that  the  professors  have  little  empirical  access  to— that  of  the  mind/brain.  Understanding,  which  is  so  often  discussed  as  one  of  the  more   paramount  phenomena  in  contemporary  science  education  reform,  is  treated  as  if  belonged   exclusively  to  the  domain  of  psychology.  However,  psychology  studies  the  inner  world,  which  is   a  different  kind  of  empirical  work  compared  to  studies  in  say,  biology  and  anthropology.  Could   not  a  biologist  help  render  a  organismal  horizon  of  expectations?  Could  not  an  anthropologist   help  render  a  cultural  horizon  of  expectations?  What  might  happen  to  learning  with   understanding  if  it  were  to  undergo  an  alchemical  transformation  that  was  something  other   79       than  psychological?  What  might  happen  to  teaching  for  understanding  if  it  were  to  undergo  an   alchemical  transformation  that  was  something  other  than  cognitive?   In  the  next  chapter,  we  will  try  to  confront  these  issues  and  more  by  following  an   anthropologist  into  the  classroom  while  he  studies  the  application  moment.  He  happens  to  be   an  anthropologist  of  science,  which  allows  him  to  make  some  interesting  comparisons  between   how  learning  with  understanding  unfolds  in  a  classroom  (during  a  pedagogical  expedition)  and   in  Brazil  (during  a  scientific  expedition).           80       CHAPTER  3   A  HORIZONTAL  SHIFT         Since  the  turn  of  the  century,  scores  of  men  and  women  have   penetrated  deep  forests,  lived  in  hostile  climates,  and  weathered   hostility,  boredom,  and  disease  in  order  to  gather  the  remnants  of   so-­‐called  primitive  societies.  By  contrast  to  the  frequency  of  these   anthropological  excursions,  relatively  few  attempts  have  been   made  to  penetrate  the  intimacy  of  life  among  tribes  which  are   much  nearer  at  hand.     —Bruno  Latour  &  Steve  Woolgar,   Laboratory  Life     Science  can  teach  us  [...]  no  longer  to  look  around  for  imaginary   supports,  no  longer  to  invent  allies  in  the  sky,  but  rather  to  look  to   our  own  efforts  here  below  to  make  this  world  a  fit  place  to  live  in.       —  Bertrand  Russell,  Why  I  Am  Not  a   Christian       As  mentioned  in  the  introduction,  the  main  purpose  of  this  dissertation  is  to  help   professors  find  new  ways  to  improve  students’  ability  to  apply  their  existing  knowledge  to  novel   situations  and  new,  unfamiliar  events—in  other  words,  to  help  them  find  new  ways  to  improve   students’  ability  to  acquire  meaningful,  conceptual,  and/or  enduring  understanding.  To  begin   this  daunting  task,  I’ve  created  a  thick  description  of  the  application  moment  in  the  style  of   anthropology.  I  am  not  an  anthropologist,  but  describing  the  application  practice  in  an   anthropological  style  helps  me  render  certain  features  of  the  application  moment  more  readily   visible  to  readers  than  they  might  be  rendered  in  other  styles  (e.g.,  sociology  or  psychology).   Once  visible,  these  selected  features  can  then  be  subjected  to  a  variety  of  scholarly  practices   81       such  as  analysis,  synthesis,  reflection,  and  critique  (among  others).  Thus,  this  chapter  aims  to   destabilize  how  understanding  is  often  understood  in  mainstream  science  education  discourse   and  to  create  an  initial  opening  for  new  alliances  and  different  possibilities.   An  Anthropologist  in  the  Classroom     Rather  than  penetrating  deep  forests,  living  in  hostile  climates,  and  weathering  hostility,   boredom,  and  disease  in  order  to  gather  the  remnants  of  so  called  primitive  societies,  an   anthropologist  attempts  to  penetrate  the  intimacy  of  life  among  tribes  which  are  much  nearer   97 at  hand.  Looking  for  research  opportunities  near  or  within  his  own  university,  he  succeeds   positioning  himself  as  an  observer  in  an  undergraduate  biology  course.  The  two  veteran   instructors,  both  professors  and  both  microbiologists,  generously  grant  him  almost  unlimited   access  to  their  course.  As  well  as  the  thrice-­‐weekly  classes,  for  example,  the  professors  also   invite  him  to  attend  their  weekly  meetings  in  which  they  often  plan  and  discuss—frequently   joined  by  other  science  educators  and  researchers—course-­‐related  issues  about  teaching-­‐  and   learning-­‐related  issues.     The  anthropologist  is  particularly  interested  in  moments  in  which  the  professors  expect   their  students  to  extend  or  apply  existing  knowledge  to  novel  situations  or  new,  unfamiliar   phenomena.  The  reason  why  he  is  interested  in  these  moments  is  because  they  are  of  great   interest  to  the  professors.  But  it’s  not  just  the  two  professors  who  express  a  deep  interest  in   them.  As  it  happens,  a  sizeable  portion  of  a  broader  group  of  science  educators  is  interested  in   them  too.  For  example,  the  professors  and  their  colleagues  give  the  anthropologist  copies  of                                                                                                                   97.  The  wording  of  this  opening  sentence  is  inspired  by  two  sentences  written  by  Bruno  Latour   and  Steve  Woolgar  in  Laboratory  Life  (see  Latour  and  Woolgar  1986,  17).   82       many  articles  and  books  in  which  a  consistent  message  is  present:  U.S.  science  students  need  to   learn  how  to  apply  their  existing  knowledge  to  novel  situations  and  new,  unfamiliar  phenomena.   It’s  almost  always  part  of  something  the  texts  mention  when  they  discuss  terms  such  as   “science  literacy”  and  “scientific  inquiry.”  It’s  also  an  important  part  of  something  the  texts   mention  when  they  discuss  “learning  with  understanding”  and  “the  transfer  of  learning.”  In   these  texts,  the  future  health  and  well  being  of  the  students—as  well  as  that  of  their  nation—is   repeatedly  said  to  depend  on  students’  ability  to  learn  with  “deep,”  “rich,”  “meaningful,”   “conceptual”  and/or  “enduring”  understanding.   As  far  as  the  anthropologist  can  tell,  this  is  what  teaching  for  and  learning  with   understanding  looks  like  in  this  particular  course:  For  approximately  three  to  four  weeks,   students  report  three  times  per  week  to  a  large,  auditorium-­‐styled  meeting  space.  Under  the   tutelage  of  their  professors,  they  embark  on  a  pedagogical  expedition.  During  much  of  their   expedition  together,  students  and  instructors  and  spend  the  majority  of  their  time  in  class   looking  at  and  talking  about  “figures.”  During  one  stretch  of  three  continuous  class  periods  that   the  professors  call  “the  topic  of  photosynthesis”  (or  sometimes  just  “photosynthesis”),  the   professors  display  for  their  students  no  less  than  45  different  figures—an  average  of  one  figure   every  3.33  minutes.  “Figures”  are  what  the  professors  call  the  visible  displays—including   illustrations,  equations,  drawings,  diagrams,  graphs,  photographs,  etc.—that  they  project  onto   a  large,  theater-­‐sized  projection  screen  located  at  the  front  of  the  auditorium.  Many  of  the   students  happen  to  possess  full  color  reproductions  of  these  figures  on  the  pages  of  a  textbook   that  many,  but  not  all  of  them,  bring  to  class.  By  the  end  of  each  fifty-­‐minute  class  period  or   “lecture,”  many  of  the  students  have  highlighted,  marked  on,  underlined,  and/or  otherwise   83       annotated  the  figures  in  their  textbook  in  ways  that  are  similar  to  those  shown  on  the   projection  screen  by  the  professors.  Those  students  not  producing  a  figure-­‐laden  textbook   during  class  often  attempt  to  draw  the  annotated  figures  in  their  notebooks  from  scratch.     If  there  is  some  sort  of  marketplace  or  financial  exchange  operating  within  the  confines   of  classroom,  the  anthropologist  feels  that  the  figures  are  likely  one  of  the  most  highly  valued,   highly  traded  commodities.  As  it  happens,  there  is  no  such  visible  marketplace,  but   nevertheless  the  professors  bring  new  figures  to  class  with  them  to  almost  every  day.  They  take   great  care  when  selecting,  sequencing,  and  displaying  them  to/for  their  students.  The   anthropologist  sees  evidence  of  this  care  in  “lecture  outlines”  given  to  him  by  the  professors.   These  outlines  make  it  clear  that  the  professors  spend  substantial  portions  of  time  outside  of   classroom  thinking  about,  selecting,  and  ordering  the  different  figures  they  show  to  students  in   the  lectures.  For  their  part,  the  students  go  to  great  lengths  during  class  to  either  recreate  the   figures  presented  by  the  professors  or  to  annotate  them  if  the  figures  are  already  contained   within  the  textbook  they  possess.  Quite  noticeably,  although  the  students  leave  many  items   behind  them  on  the  auditorium  floor  (e.g.,  newspapers,  food  wrappers,  and  drink  containers)   98 they  rarely  ever—at  least  purposely—leave  any  figures  behind.                                                                                                                     98.  On  at  least  one  occasion  the  anthropologist  runs  into  a  group  of  students  from  the  class  at   the  university  library.  Recognizing  him  from  his  presence  in  the  lectures,  they  stop  him  as  he’s   walking  by  the  room  they’ve  reserved  for  something  they  call  their  “Bio  101  Study  Group.”  He   enters  the  windowed  room  to  say  hello  and  immediately  notices  that  the  large  conference   table  around  which  the  students  are  all  seated  is  littered  with  figures  from  the  course.  On  the   wall  is  a  chalkboard.  This  surface,  too,  is  cluttered  with  crudely  drawn  reproductions  of  many  of   the  figures  strewn  across  the  table  (as  well  as  some  that  are  not).   84       Approximately,  every  three  or  four  weeks,  the  professors  and  students  typically  set   aside  a  day  to  depart  from  this  routinized  routine  in  which  figures  are  presented,  collected,  and   annotated.  This  departure  is  called  a  “midterm  exam,”  and  on  these  days  the  routine  practices   of  the  participants  take  a  turn  for  the  different.  There  are  a  total  of  four  exams  during  each   fifteen-­‐week  semester—three  “midterm”  and  one  “final”  exam.  Of  particular  interest  to  the   anthropologist   is   the   fact   that   each   of   the   exams  contains   items   (or   “multiple-­‐choice  questions,”   as  the  professors  and  students  call  them)  in  which  students  are  given  the  opportunity  to  prove   to  their  professors  that  they’ve  “mastered  the  course  material.”  Some  of  these  questions  ask   students  to  apply  their  existing  knowledge  to  novel  problems  or  new,  unfamiliar  situations.   Many  of  these  questions  even  have  unique  names  given  to  them  either  by  the  professors   themselves  or  by  some  of  their  colleagues.  For  example,  there  is  the  “Virus  Question,”  the   “Jared  Question,”  the  “Radish-­‐in-­‐the-­‐Light”  question  (as  well  as  the  “Radish-­‐in-­‐the-­‐Dark   question”),  and  the  “Grape  Question,”  among  others.  One  common  feature  uniting  these   questions  is  the  fact  that  the  professors  have  deliberately  withheld  mention  of  certain  elements   contained  within  them  during  the  three-­‐  to  four-­‐week  instructional  phase  of  the  course.  For   example,  on  the  second  of  the  three  midterm  exams  the  professors  put  before  students  a   question  about  a  “mutant  strain  of  spinach”  whose  salient  defect  is  the  production  of  a  set  of   “slightly  permeable”  membranes  within  its  leaves.  The  professors  and  their  colleagues  know   this  question  as  the  “Mutant  Spinach  Question.”  By  the  professors’  own  admission,  in  all  of  the   classes  and  homework  assignments  leading  up  to  the  exam  the  students  were  never  told  about   mutant  spinach  plants  with  malfunctioning  or  “leaky”  membranes.  Despite  this  deliberate   omission,  however,  the  questions  are  still  posed  to  the  students  on  the  exam.  According  to  the   85       professors,  the  Mutant  Spinach  Question  tests  whether  the  students  “really,  truly  understand”   the  concept  of  photosynthesis.   As  they  did  during  the  lectures,  many  students  bring  book  bags  and  backpacks  into  the   classroom  on  examination  days.  However,  one  of  the  major  differences  between  lectures  and   examination  days  is  that  much  of  what  students  have  in  their  bags  and  backpacks  is  never   removed  from  them.  The  only  empirical  allies  students  are  allowed  to  remove  from  their  bags   and  put  to  use  during  the  exams  include  paper  (in  the  form  of  an  inscribed  paper  exam  given  to   them  by  the  professors),  a  pencil  (only  No.2  pencils,  however),  a  wristwatch  (but  there  is  also  a   clock  for  use  on  the  classroom  wall),  and  a  university-­‐issued  photographic  ID,  but  that  is  all.   While  the  students  are  allowed  to  use  the  paper,  pencils,  and  wristwatches  during  the   examination,  they  typically  don’t’  use  the  photographic  ID  until  after  they  complete  the  exam.  It   turns  out  that  the  professors  don’t  trust  their  own  mental  faculties  to  remember  the  names   and  faces  of  their  nearly  four  hundred  undergraduate  students—including  a  handful  of  who   only  occasionally  show  up  for  classes  in  person.  So,  in  an  effort  to  ensure  the  integrity  of  the   end-­‐of-­‐semester  course  grades,  at  the  end  of  every  exam  the  professors  ask  each  of  their   students  to  prove  their  identity  by  means  of  triangulation.  In  other  words,  each  student’s  true   identity  is  held  between  three  visible,  material  objects:  (1)  the  photographic  ID  (which  contains   a  photograph  of  the  student,  their  legally  established  name  (first  and  last),  and  a  one-­‐of-­‐a-­‐kind   “student  number”  (a  unique  9-­‐digit  alphanumeric  code)),  (2)  a  paper  “class  roster”  provided  by   the  university  Registrar’s  office  (which  lists  each  student's  legal  name  and  university  student   number),  and  (3)  the  face  of  the  student  (the  instructors  concern  is  mainly  for  their  students   from  the  neck  ‘up’).  Besides  these  three  allies,  any  student  attempt(s)  to  enlist  other  empirical   86       allies—e.g.,  enlisting  other  students  or  a  personal  notebook—is  strictly  forbidden.  In  fact,  right   before  distributing  the  paper  exams  to  their  students,  the  professors  often  remind  the  students   to  place  all  their  unapproved  empirical  allies  safely  away  underneath  chairs  and/or  into  folders,   purses,  shoulder  bags,  backpacks,  etc.  As  a  final  way  of  dissuading  individual  students  from   enlisting  any  other  student’s  exam  paper  as  a  potential  exam  ally,  the  professors  tell  students  to,   “Remember,  be  sure  to  keep  your  eyes  on  your  own  exam.”   A  few  days  after  the  second  midterm  exam  (“Exam  2”),  the  anthropologist  is  present   when  the  professors  receive  a  statistical  summary  of  the  Exam  2  results  from  the  university   scoring  office.  The  anthropologist  sees  that  the  performance  results  of  question  “52”—the   Mutant  Spinach  Question—immediately  grabs  the  attention  of  the  professors.  As  it  happens,  it   turns  out  that  nearly  eighty  percent  of  the  students  answered  question  “52”  incorrectly.  This   percentage  makes  it  the  most  missed  question  on  the  entire  exam.  Over  three  quarters  of  the   undergraduate  students  failed  to  apply  their  existing  knowledge  to  the  novel  phenomenon  as   the  professors  had  hoped  they  would.  In  other  words,  the  professors  see  this  as  a  clear   indication  that—when  given  the  opportunity  to  do  so  on  the  exam—more  than  three-­‐quarters   of  the  undergraduate  students  failed  to  demonstrate  that  they  had  learned  the  concept  of  the   “light  reactions  of  photosynthesis”  with  understanding.     Postscript  to  the  Classroom  Study     Months  later,  sitting  comfortably  in  his  office  and  reading  through  his  field  notebooks,   the  anthropologist  outlines  a  recurring  practice  he  witnessed  throughout  the  fifteen-­‐week   course.  When  asked  by  their  professors  to  demonstrate  that  they  could  apply  their  existing   knowledge  to  new  situations  or  novel,  unfamiliar  problems—in  other  words,  when  asked  to   87       demonstrate  that  they  had  learned  important  scientific  topics  or  concepts  “with   understanding”—students  were  consistently  put  into  moments  or  events  in  which  they  were   required  to  place  nearly  all  of  their  trust  in  their  own  mental  faculties.  Reminded  by  his  field   notes  detailing  the  densely  populous  presence  of  visible,  material  “figures”  in  the  lessons   leading  up  to  the  examinations,  the  anthropologist  is  struck  by  the  almost  complete  invisibility   of  these  figures  during  the  exam  events.     A  quick  glance  through  the  paper  exams  themselves—which,  because  he  doesn’t  fully   trust  his  own  memory,  the  anthropologist  collected  and  archived  during  his  fieldwork— confirms  that  the  exams  contained  almost  no  visible,  material  figures  within  them.  Eager  to   hear  how  the  professors  explain  this  absence,  the  anthropologist  requests  a  follow-­‐up  interview   with  the  professors.  In  it,  he  asks  them  about  the  absence  of  these  empirical  allies.  During  the   interview,  the  professors  are  quick  to  draw  the  anthropologist’s  attention  to  a  different  class  of   allies.  Rather  than  bring  empirical  allies  to  exams,  they  tell  him,  their  expectation  is  that   students  bring  with  them  an  almost  unlimited  number  of  mental  allies  for  use.  According  to  the   professors,  such  allies  go  by  names  such  as  “logic,”  “reason,”  “facts,”  “concepts,”  “induction,”   “deduction,”  “analytical  skills,”  “critical  thinking  skills,”  and  “abstract  thinking  skills,”  among   others.  Satisfied  that  he  now  has  a  more  nuanced  understanding  of  the  various  allies  available   for  student  use  during  exams—both  empirical  and  mental—the  anthropologist  thanks  the   professors  for  their  time  and  concludes  the  interview.  He  then  records  the  following  entry  in  his   notebook:     In  this  undergraduate  biology  course,  one  of  the  ways  that  teaching  for  and  learning   with  understanding  can  be  described  is  as  a  series  of  three-­‐  to  four-­‐week  progressions   from  the  empirical  to  the  mental.  During  the  weeks  leading  up  to  an  examination,   88       students  and  teachers  typically  gather  around  and  devote  much  of  their  collective   energy  toward  an  almost  continuous  presentation  of  visible,  material  “figures.”  These   figures  are  at  the  center  of  much  of  what  goes  on  in  the  classroom  on  a  daily  basis.  On   exam  days,  however,  these  same  empirical  figures  must  be  kept  out  of  sight,  but  not  out   of  mind.  In  fact,  it  is  the  professors’  expectation—as  well  as  their  genuine  hope!—that   their  undergraduate  students  find  ways  to  efficiently  and  effectively  internalize  the  once   visible,  material  figures.  Thus,  within  the  context  of  this  biology  course,  teaching  for  and   learning  with  understanding  can  be  described  as  a  set  of  practices  whose  ultimate   trajectory  is  the  successful  transformation  (or  transfiguration)  of  vast  numbers  of   empirical  allies  into  mental  ones.       An  Anthropologist  in  the  Field     Not  more  than  a  year  after  spending  a  semester  in  an  undergraduate  biology  course,  an   anthropologist  has  the  opportunity  to  study  a  team  of  research  scientists  working  in  a  remote   99 forest  in  the  Boa  Vista  region  of  Brazil.  The  scientists  are  there  because  they  are  confused  by   the  distribution  of  plants  species  in  the  region.  In  this  area,  a  particular  species  of  fire-­‐resistant   tree  has  stopped  adhering  to  the  law  of  the  land:  instead  of  restricting  its  presence  to  the  open   savanna  (its  natural  habitat)  and  the  areas  along  the  savanna/forest  boundary  (the  edge  of  its   natural  habitat),  one  of  the  scientists,  a  local  botanist,  has  also  found  this  same  species  of  tree   as  many  as  ten  meters  into  the  forest.  In  other  words,  she  has  found  them  living  some  distance   away  from  its  natural  habitat.  As  the  four  scientists—a  botanist,  two  pedologists  (soil  scientists),   and  a  geomorphologist—record  observations  and  collect  representative  samples  of  the  area’s   plants  and  soils,  much  as  he  did  the  previous  year  in  the  college  biology  course,  the   anthropologist  records  representative  observations  and  collects  representative  artifacts  as  the   scientists  go  about  their  daily  work.                                                                                                                   99.  See  Latour  1999.   89       On  the  night  before  their  first  day  in  the  field,  the  anthropologist  is  struck  by  an   interesting  parallel  between  the  situation  in  Brazil  and  the  one  he  encountered  a  year  ago  at   the  American  university.  Like  the  undergraduate  science  students,  these  scientists  are  also   facing  a  novel  problem.  They  are  confronting  a  situation  that  is  entirely  new  to  all  four  of  them.   Like  the  students,  these  scientists  need  to  apply  their  existing  knowledge  to  an  unfamiliar  event.   The  anthropologist  can  hardly  believe  his  dumb  luck!  Here,  in  the  Boa  Vista  region  of  Brazil,  he   has  the  opportunity  to  witness  how  a  group  of  research  scientists  engage  in  the  construction  of   scientific  knowledge.  Whether  or  not  it  will  result  in  enduring  scientific  understanding  is   something  only  time  will  be  able  to  tell.     One  of  the  things  the  anthropologist  notices  almost  immediately  is  that  this  team  of   research  scientists  consistently  distrusts  their  own  mental  faculties.  Case  in  point:  while   watching  the  botanist  at  work,  the  anthropologist  notices  that  she  fixes  little  “tin  tags”  to  the   100 horizontal  branches  of  individual  trees.  Each  tin  tag  has  a  number  inscribed  in  it  as  shown  in   Figure  3.1.                                                                                                                     100.  This  anthropological  account  is  taken  from  Latour  1995  and  Latour  1999  (see  esp.  Chapter   2).   90           Figure  3.1.  Photograph  of  a  small  tin  tag  affixed  to  the  horizontal  branch  of  a  tree  found  within   a  field  site  in  Brazil.  Figure  11.3  (Latour  1999).  (Reprinted  with  permission  by  the  copyright   holder.)   Why  does  the  botanist  deploy  the  small  tin  tags?     There  are  many  reasons,  but  one  is  that  she  does  not  trust  her  own  memory  to  reliably   and  accurately  organize  the  objects  found  within  her  field  site.  She  does  not  trust  her  mental   faculties  to  remember  the  exact  placements  and  identities  of  individual  trees  after  leaving  the   study  site.  With  over  two  hundred  and  thirty-­‐four  individual  trees  to  remember  it’s  no  wonder   91       101 she  distrusts  her  mind!  For  this  botanist,  as  well  as  for  many  research  scientists  on   expeditions  and  in  laboratories,  too  much  reliance  on  mental  abilities  such  as  memory   increases  the  potential  for  lasting  doubt  and  uncertainty.  Instead  of  (or  in  addition  to)  her   mental  faculties,  this  scientist  places  the  bulk  of  her  trust  in  wooden  trees,  tin  tags,  paper  maps,   and  a  grid  of  Cartesian  coordinates  inscribed  into  her  field  notebook.  That  is,  in  order  to   increase  her  understanding  of  the  novel  phenomenon  she  takes  deliberate  steps  to  shift  the   weight  of  responsibility  from  her  mental  faculties—which  are  less  reliable,  as  well  as  more   difficult  for  others  to  see  and/or  grasp—to  a  more  visible,  more  material,  more  mundane   ‘network’  of  objects  outside  of  her  mind.  In  other  words,  she  creates  an  empirical  form  of   insurance.  As  the  anthropologist  learns  over  the  course  of  the  scientists’  fifteen-­‐day  expedition,   given  the  choice  between  (on  the  one  hand)  firmly  affixed  tin  tags  plotted  against  a  Cartesian   grid  created  by  the  use  of  maps,  notebooks,  and  surveying  instruments  and  (on  the  other  hand)   nothing  but  their  own  cognitive  faculties,  uncertain  research  scientists  like  the  botanist  and  her   colleagues  will  choose  former  every  time.  Thus,  the  anthropologist  concludes  that  in  scientific   practice  it  is  not  from  mental  allies  that  research  scientists  acquire  certainty;  it  is  not  in   cognitive  allies  in  which  they  place  their  trust.  Instead,  she  gains  these  value  commodities  from   building  and  maintaining  a  well-­‐coordinated  network  of  empirical  allies.   Postscript  to  the  Field  Study     Months  later,  sitting  comfortably  in  his  office  and  reading  through  his  field  notebooks,   the  anthropologist  reflects  on  the  events  he  witnessed  during  the  fifteen-­‐day  scientific                                                                                                                   101.  Recall  that  the  university  classroom  professors  also  distrusted  their  mental  faculties  when   needing  to  verify  the  identity  of  nearly  four  hundred  undergraduate  students  at  the  conclusion   of  the  exams.   92       expedition.  Satisfied  that  he  now  has  a  more  thorough  understanding  of  the  work  of  a  team  of   research  scientists,  he  records  the  following  entry  in  his  notebook:   On  this  scientific  expedition,  one  of  the  ways  that  scientists  learn  with  understanding   can  be  described  as  a  fifteen-­‐day  engagement  with  empirical  allies.  Although  it  would  be   silly  to  deny  that  the  scientists  are  engaged  in  thinking  and  reasoning,  it  is  unnecessary   to  consider  these  important  actions  as  mental  practices.  When  confronted  by  a   phenomena  on  the  boundary  of  the  Brazilian  forest  and  savanna—a  phenomena  which   they  could  not  understand  at  first  glance  (or,  for  that  matter,  at  second,  third  or  fourth   glance)—the  team  of  scientists  chose  to  apply  their  existing  knowledge  to  a  perplexing   situation  by  deliberately  shifting  the  weight  of  responsibility  from  their  internal,  mental   faculties  to  a  network  of  empirically  observable  objects  and  practices.  It  wasn’t  only  the   botanist  who  enacted  this  strategy.  Her  two  pedologist  colleagues  enacted  a  similar   strategy  when  looking  at  the  characteristics  of  the  soil  beneath  the  trees.  Rather  than   tin  tags,  they  used  shovels,  core  samplers,  small,  open-­‐ended  cardboard  cubes,  a   modified  wooden  suitcase  to  organize  the  soil-­‐stuffed  cardboard  cubes,  and  a  number   of  other  empirical  objects—including  some  of  the  maps  and  notebooks  used  by  the   botanist.  In  practice,  it  appears  as  though  the  scientists’  expectation  of  one  another  is   that  they  find  ways  to  efficiently  and  effectively  externalize  the  perplexing  natural   phenomenon.  Thus,  within  the  context  of  this  expedition,  scientific  learning  with   understanding  can  be  described  as  a  set  of  practices  whose  ultimate  success  depends   almost  entirely  upon  the  coherent  and  careful  coordination  of  a  vast  army  of  empirical   allies.  In  the  heat  of  an  epistemological  engagement,  the  scientific  mantra  amounts  to   this:  mental  allies  can’t  be  trusted.       Later,  when  comparing  his  accounts  of  the  pedagogical  and  scientific  expeditions,  the   anthropologist  is  struck  by  at  least  two  differences  between  (one  the  one  hand)  those  practices   enacted  by  scientists  to  understand  an  unfamiliar  phenomenon  and  (on  the  other  hand)  those   enacted  by  two  college  professors  and  their  students.  First,  when  compared  to  the  empirical   allies  enlisted  by  scientists  in  Brazil,  the  number  and  kind  of  empirical  allies  available  for   enlistment  by  students  in  the  classroom  appears  relatively  depauperate.  Second,  whereas   research  scientists  shift  the  weight  of  responsibility  from  their  mental  faculties  to  a  network  of   93       empirical  allies,  science  professors  demand  that  their  students  shift  the  weight  of  responsibility   from  a  network  of  empirical  allies  to  their  mental  faculties.  In  other  words,  the  practice  of   learning  with  understanding  in  science  appears  to  be  the  inverse  of  learning  with  understanding   in  science  education.     Contrasting  Approaches  to  Learning  with  Understanding     The  two  anthropological  vignettes  above  chronicle  two  expeditions:  one  scientific  and   one  pedagogical.  Admittedly,  there  are  vast  differences  to  be  considered  when  speaking  of  the   goals,  aims,  audiences,  and  purposes  of  scientific  research  and  science  education.  And  yet,   despite  these  vast  differences  it  should  now  be  clear  that  they  share  at  least  one  vital  thread  of   continuity:  In  both  accounts,  the  two  groups  of  protagonists  confront  moments  in  which  they   are  required  apply  or  extend  their  existing  knowledge  to  an  unfamiliar  phenomenon.  In  other   words,  both  scientists  and  science  students  endeavor  to  learn  with  deep,  rich,  and  meaningful   understanding.     One  thing  this  juxtaposition  of  vignettes  is  meant  to  show  is  the  existence  of  two   distinctly  different  approaches  to  learning  with  understanding:  one  that  relies  on  mental   cognition  and  another  that  relies  on  empirical  perceptions.  In  the  first  vignette,  which  is  inspired   by  a  two-­‐year  classroom  study  I  carried  out  in  2006-­‐2007,  we  see  one  envelope  of  possibility  for   learning  with  understanding.  This  envelope  is  defined  by  traits  such  as  invisibility,  immateriality,   intangibility,  and  internality.  In  other  words,  the  envelope  in  which  the  two  professors  and  their   nearly  four  hundred  students  engage  in  learning  with  understanding  is  one  that  is  largely   defined  by  a  shift  from  empiricality  to  mentality.  In  the  second  vignette,  much  of  which  is  based   on  the  work  of  anthropologist  of  science  Bruno  Latour,  we  see  another  envelope  of  possibility   94       102 for  learning  with  understanding.  Among  others,  this  particular  envelope  is  defined  by  traits   such  as  visibility,  materiality,  tangibility,  and  externality.  In  other  words,  the  envelope  in  which   the  four  research  scientists  engage  in  learning  with  understanding  is  one  that  is  largely  defined   by  a  shift  from  mentality  to  empiricality.  Bathed  in  the  light  of  these  inverse  practices,  let  us   briefly  consider  the  end  result  of  these  respective  expeditions.   The  Telos  of  the  Scientific  Expedition       At  the  conclusion  of  their  fifteen-­‐day  scientific  expedition,  the  research  scientists   publish  a  scientific  report.  In  it,  they  write  about  a  growing  need  to  detach  themselves  from   certain  foundational  assumptions  within  classical  pedology.  You  see,  if  only  botanical   observations  are  taken  into  account,  then  these  scientists  must  conclude  that  the  Brazilian   forest  is  advancing  on  the  savanna.  However,  if  only  pedological  observations  are  taken  into   account,  then  these  scientists  must  conclude  that  the  Brazilian  savanna  is  advancing  on  the   forest.  By  combining  their  differing  perspectives,  however,  their  observations  force  them  to  ask   an  entirely  different  question:  What  can  explain  the  fact  that  the  predominantly  sandy  soils   found  underneath  the  portion  of  savanna  immediate  next  to  the  edge  of  the  forest  appear  as   though  they  are  becoming  enriched  with  clay?  Classical  pedology  instructs  them  to  answer,  “In   accordance  with  the  laws  of  thermodynamics,  the  clay  enrichment  can  be  explained  by  a   process  known  as  neoformation.”  However,  neoformation  requires  a  source  of  Aluminum  to   carry  out  a  known  geochemical  reaction  and  the  scientists  can  find  no  such  source  within  the   soils  in  question.                                                                                                                     102.  In  particular,  see  Latour  1999  (Chapter  2).   95       One  of  the  main  reasons  they  are  now  in  the  position  to  ask  this  intriguing  question  is   due  to  the  extensive  empirical  network  of  objects  and  practices  they  cast  over  the  Brazilian   forest  and  savanna  throughout  their  fifteen-­‐day  expedition.  All  four  scientists  will  be  the  first   ones  to  admit  that  their  mental  faculties  were  never  enough  to  address  the  problem.  To  better   understand  this  unfamiliar  phenomenon  they  needed  to  shift  the  weight  of  responsibility  from   their  mental  faculties  to  an  eclectic  cast  of  empirical  allies.  At  the  conclusion  of  the  expedition,   most  of  these  allies  are  invisible,  not  because  they  are  mental,  but  because  they  are  now   packed  safely  away  inside  of  luggage,  creates,  duffle  bags,  shipping  containers,  and  the  back   ends  of  a  fleet  of  four-­‐wheel  drive  vehicles.  Some  of  these  empirical  allies  will  return  to  Brazil  if   and  when  the  scientists  can  procure  funding  for  a  follow-­‐up  expedition.  At  their  departure,  they   are  confident  they  will  do  so  because  they  see  the  results  of  this  particular  expedition  as  a  great   success.  Through  a  collaborative  approach  to  an  entirely  perplexing  phenomenon,  they  have   successfully  challenged  a  number  of  assumptions  widely  held  in  classical  pedology.  As  a  result,   this  team  of  scientists  now  understands  that  their  next  expedition  must  focus  not  on  the   botanical  or  the  pedological,  but  instead  on  the  zoological...on  earthworms.  Sometime  in  the   future,  they  plan  to  invade  the  forest-­‐savanna  boundary  with  a  new  army  of  empirical  allies  (as   well  as  some  old  ones),  and  the  genuine  hope  is  that  this  alliance  of  new  and  old  allies  will  help   them  make  the  routine  actions  of  the  earthworms—which  are  presently  invisible  actors   beneath  the  soil—visible  to  others.  At  least  one  thing  is  certain:  it  is  not  the  scientists'  individual   or  collective  mental  powers  that  will  bring  the  actions  of  the  earthworms  to  the  surface  for  all   to  see—no  matter  the  prestige  of  their  degrees,  awards,  and  various  accolades—but  a  shovel   might.   96       The  Telos  of  the  Pedagogical  Expedition       At  the  conclusion  of  a  four-­‐week  pedagogical  expedition,  two  college  professors  receive   a  published  report  from  the  university  scoring  office.  In  it,  they  are  made  aware  of  the  results  of   question  “52.”  In  the  pages  of  the  report,  they  learn  that  eighty  percent  of  their  students  could   not  successfully  demonstrate  that  they  could  apply  their  existing  knowledge  to  a  problem   defined  by  the  presence  of  a  couple  of  unfamiliar  elements.  In  other  words,  they  learn  that  over   three-­‐quarters  of  their  students  had  not  learned  with  understanding.  The  mutant  strain  of   spinach  with  the  slow  leaking  membranes  remains  unfamiliar  to  most  of  the  students;  it  is  as   strange  a  phenomenon  to  them  now  as  it  was  before  the  four-­‐week  pedagogical  expedition.   The  professors  and  their  colleagues  in  science  education  have  ways  of  describing  the   unsuccessful  students.  For  example,  some  students  are  said  to  lack  “basic  knowledge,”  while   others  are  said  to  possess  “misconceptions.”  Of  some  students  it  is  said  that  they  lack   “understanding,”  while  of  other  students  it  is  said  that  they  lack  certain  (mental  or  cognitive)   “abilities.”  Some  students  will  simply  be  said  to  be  “unmotivated”  and/or  “lazy.”  For  the  most   part,  all  of  these  explanations  are  psychological  in  character.  That  is,  they  relate  to  objects  and   processes  said  to  occur  inside  of  the  minds/brains  of  individual  students.  One  of  the  professors   underlines  this  fact  in  conversation  with  the  anthropologist.  After  seeing  the  results  of  question   “52,”  he  says  that  he  wished  he  knew  more  about  “what  students  were  thinking  when  tackling   the  Mutant  Spinach  Question.”  He  also  says  that  he  wished  he  had  some  way  of  knowing  “what   was  happening  inside  of  their  minds”  as  they  tried  to  answer  it.           97       Scientific  Research:  A  Resource  for  a  Different  Alchemy     Here,  at  this  moment,  we  have  arrived  at  a  position  in  which  it  is  now  possible  to   consider  seriously  the  following  proposition:  much  of  the  success  of  a  team  of  research   scientists  in  Brazil  is  attributable  to  their  practice  of  shifting  from  mental  to  empirical  allies.  To   give  this  notion  more  clarity,  we  might  claim  that  in  pursuit  of  greater  understanding  of  a   perplexing  natural  phenomenon  (in  this  case,  a  previously  unencountered  distribution  of  fire-­‐ resistant  trees)  one  of  the  main  reasons  why  scientists  tend  to  keep  written  notes  is  because   the  conventions  of  scientific  practice  dictate  that  they  refuse  to  trust  their  mental  faculties.  At   the  very  same  moment,  we  have  also  arrived  at  a  position  in  which  it  is  now  possible  to   seriously  consider  a  second  proposition:  much  of  the  failure  of  group  of  college  students  is   attributable  to  their  practice  of  shifting  from  empirical  to  mental  allies.  To  give  this  notion  more   clarity,  we  might  claim  that  in  pursuit  of  greater  understanding  of  a  perplexing  natural   phenomenon  (a  ‘mutant’  strain  of  spinach),  one  of  the  main  reasons  why  students  do  not  use   their  written  notes—many  of  which  contain  heavily  annotated  “figures”—is  because  the   conventions  of  pedagogical  practice  dictate  that  they  must  place  almost  exclusive  trust  within   their  mental  faculties.   One  of  the  benefits  of  an  anthropological  style  should  now  be  evident  because  at  least   one  of  the  ironies  of  pedagogical  practice  should  now  be  visible:  science  professors  require   students  to  shift  from  empirical  to  mental  allies  when  confronting  unfamiliar  situations  despite   the  fact  that  they  often  don’t  trust  their  own  mental  faculties  when  engaging  in  work  as  both   professors  and  as  scientific  researchers.  Recall  that  the  professors  did  not  trust  their  own   mental  faculties  when  it  came  to  remembering  the  names  and  faces  of  their  undergraduate   98       students  during  the  semester  examinations.  To  counteract  this  distrust,  on  each  of  these  four   occasions  the  professors  behaved  like  research  scientists.  That  is,  they  shifted  their  trust  from   mental  to  empirical  allies.  That  is,  they  shifted  their  trust  from  internal  allies  (for  example,   memory)  to  external  allies  (including  paper  lists,  photographic  IDs,  the  actual  faces  of  students,   and  alphanumeric  codes).  We  can  reasonably  assume  that  this  shift  came  as  second  nature  to   these  two  professors  because,  in  addition  to  their  role  as  professors  at  their  university,  they  are   also  both  scientists.  That  is,  at  the  same  time  they  are  teaching  “Biological  Science  101:  Cells   and  Molecules,”  both  of  them  are  actively  engaged  in  scientific  research  in  microbiology.   Therefore,  let  us  now  give  permission  for  ourselves  to  entertain  the  following  question:   What  if  learning  for  understanding  in  classrooms  was  more  aligned  with  a  shift  from  mental  to   empirical  allies  rather  than—as  is  the  case  in  Bio101—a  shift  from  empirical  to  mental  allies?  In   other  words,  what  if  pedagogical  expeditions  in  Bio101  were  more  like  scientific  expeditions   when  it  came  to  understanding  unfamiliar  events?  In  (yet)  other  words,  what  if  professors   extended  to  their  own  undergraduate  students  sets  of  empirical  tools  and  strategies  similar  to   the  ones  they  use  in  their  own  work  as  both  research  scientists  and  supervisors  of   examinations?     If  such  a  shift  were  to  be  enacted,  would  students  more  frequently  find  themselves  in   positions  in  which  it  could  be  said  of  them  that  they  learned  with  understanding?  Would  they   more  regularly  find  themselves  in  situations  in  which  it  could  be  said  of  them  that  they  had   successfully  applied  their  existing  knowledge  to  the  novel  and/or  unfamiliar?  Furthermore,   what  new  possibilities  for  science  teaching  might  be  created  if  science  professors,  as  well  as   science  teachers  throughout  the  K-­‐16  continuum,  were  given  permission  to  uncouple  learning   99       with  understanding  from  its  present  mental  moorings?  Would  not  students  and  teachers— including  professors  and  teacher  educators—effectively  double  the  ways  in  which  it  was   possible  for  them  to  approach  learning  with  understanding?  Would  not  scores  of  students  who   struggle  to  learn  with  understanding  when  aligned  with  a  mental  or  cognitive  horizon  of   expectations  stand  to  gain  from  being  allowed  to  demonstrate  understanding  in  other  ways?   These  are  some  of  the  overarching  questions  considered  in  the  remaining  chapters  of  this   dissertation.   Before  going  further,  however,  let  me  briefly  pause  here  so  as  to  address  one  potential   misunderstanding  of  what  I  am  suggesting  thus  far.  Understandably  so,  some  readers  may   construe  my  suggestion  to  shift  the  emphasis  in  classrooms  from  mental  to  empirical  allies  as   joining  an  already  established  vocal  and  influential  chorus  of  science  education  reformers   calling  for  more  ‘hands-­‐on’  or  more  ‘inquiry-­‐based’  instruction  in  college  science  courses.  These   same  individuals  and  groups  may  be  tempted  to  use  the  stance  I  have  communicated  thus  far   as  a  way  of  legitimizing  their  demands  for  college  science  professors  to  engage  their  students  in   more  authentic,  experiential,  real-­‐world,  inquiry-­‐based  modes  of  instruction.  Despite  my   genuine  affection  and  enthusiasm  for  these  various  instructional  approaches,  that’s  not  actually   what  I’m  suggesting.  In  other  words,  I  am  not  saying  that  the  solution  to  the  problem  of   learning  with  understanding  is  to  start  taking  four  hundred  undergraduate  students  on  research   expeditions  to  Brazil.  Conversely,  I  am  also  not  saying  that  the  solution  to  the  problem  of   learning  with  understanding  is  to  transform  the  interiors  of  lecture  halls  into  replicas  of   Brazilian  forests/savannas—in  other  words,  to  fill  college  auditoriums  with  soil,  fire-­‐resistant   trees,  and  hyperactive  populations  of  earthworms.     100       To  be  sure,  these  would  be  two  solutions  to  the  problem  of  learning  with   understanding—and  in  my  opinion  interesting  ones!  However,  for  reasons  practical,  structural,   economic,  and  even  medical,  I  cannot  see  an  immediate  future  in  which  large  universities  begin   seriously  restructuring  their  existing  undergraduate  science  education  programs  along  either  of   these  particular  lines  of  reform.  As  those  working  within  it  already  well  know,  change  is   notoriously  slow  in  higher  education  and—at  least  in  the  near  future  of  large,  research-­‐oriented   universities—I  fully  expect  that  many  undergraduate  science  courses  will  continue  to  resemble   those  that  I  was  present  in  as  a  researcher  from  2004-­‐2009  in  at  least  three  distinct  ways:  (1)   undergraduate  science  courses  will  continue  to  meet  in  largish  spaces  defined  primarily  by  the   presence  of  fixed  student  seating,  audio-­‐enhancing  equipment,  and  large  projection  screens;   (2)  such  courses  will  continue  to  have  sizeable  teacher  to  student  ratios  (e.g.,  one  instructor  for   every  two  hundred  or  so  students);  and  (3)  when  it  comes  to  assessing  student  learning,  one  of   the  most  important  criteria  used  in  selecting  modes  of  assessment  in  these  courses  will   continue  to  be  those  modes  that  can  be  graded  or  otherwise  evaluated  relatively  expediently.   In  light  of  these  three  near-­‐future  expectations  for  undergraduate  science  education—and   compared  to  the  thrilling  visions  of  placing  students  in  the  midst  of  thick  tropical  forests  or   promoting  the  growth  of  thick  tropical  forests  inside  of  university  auditoriums—I  must   knowingly  disappoint  many  readers  by  preemptively  warning  them  that  what  I  will  eventually   suggest  in  this  dissertation  is  far  less  ambitious,  much  less  exciting,  and  much  more  mundane.   Nevertheless,  what  I’m  about  to  suggest  has  at  least  one  key  advantage  over  these  two  other   exciting  visions...it  is  much  more  realistic.       101       Toward  an  Ecological  View  of  Learning  With  and  Teaching  For  Understanding   I  want  to  suggest  that  one  productive  means  of  expanding  the  ways  in  which  students   approach  and  demonstrate  learning  with  understanding  is  to  redefine  and  reconsider  the  ways   in  which  K-­‐16  science  teachers  approach  teaching  for  understanding.  Rather  than  taking   students  and  relocating  them  into  earthly  forests  or  taking  earthly  forests  and  relocating  them   into  classrooms,  one  of  the  keys  to  expanding  the  ways  in  which  teachers  can  approach   teaching  for  understanding  rests  in  the  existence  of—or,  perhaps  more  precisely,  in  the   acknowledgement,  critical  examination,  and  subsequent  coherent  coordination  of—two   agents/actors  already  present  inside  of  many  college  science  classrooms.  In  other  words,  my   proposed  solution  to  the  problem  of  teaching  for  and  learning  with  and  understanding  doesn’t   require  acts  of  relocation  because  much  of  what  is  needed  in  order  to  expand  the  envelope  of   existing  possibilities  is  already  in  the  classroom.  Although  much  more  attention  will  be  given  to   these  two  agents  in  the  chapters  that  follow,  let  me  at  least  identify  them  and  give  them  brief   consideration  here.     The  first  agent  of  my  interest  is  human.  It  is  the  professor.  We  must  remember  that  at   many  colleges  and  universities,  the  professors  who  teach  undergraduate  science  courses  are   also  research  scientists.  To  background,  forget,  overlook  and/or  ignore  this  aspect  of  their   professional  identity  is  to  lose  sight  of  something  critical:  when  research  scientists  apply  their   knowledge  to  unfamiliar  events  beyond  the  walls  of  their  university  classrooms  they  routinely   recruit,  use,  value,  coordinate,  trust,  and  align  vast  numbers  of  empirical  allies.  As  mentioned   previously,  one  of  the  reasons  why  scientists  do  this  is  because  they  tend  to  distrust  their  own   mental  faculties.  Thus,  in  practice  scientists  tend  to  find  ways  to  shift  their  trust  from  networks   102       of  mental  allies  over  to  networks  of  empirical  ones.  As  most  scientists  will  openly  tell  you,  a   scientist’s  distrust  of  mental  allies  is  far  from  a  simple  matter  of  personal  taste  or  preference.   It’s  a  matter  of  professional  expectation.  Throughout  scientific  research  communities,  scientists   tend  to  value  empirical  demonstrations  over  mental  or  psychological  ones.  And  so,  if  we  draw   from  this  professional  expectation  instead  of  backgrounding,  forgetting,  overlooking  and/or   ignoring  it,  then  it  soon  becomes  possible  to  change  one  of  the  ways  in  which  we  commonly   perceive  and  construct  the  university  science  professor.  Rather  than  seeing  them  as  teachers   (e.g.,  when  working  in  the  classroom  with  students)  or  as  scientists  (e.g.,  when  working  outside   of  the  classroom  away  from  students),  it  becomes  possible  to  see  them  as  something   altogether  different.  For  example,  we  might  begin  seeing  them  instead  as  scientist  teachers.   Whereas  the  routine  professional  expectation  of  contemporary  science  teachers  is  to  demand   that  teachers  ask  their  students  to  shift  the  bulk  of  their  trust  from  empirical  to  mental  allies,   the  routine  professional  expectations  of  scientist  teachers  would  be  different.  Instead  of   demanding  that  students  go  about  the  work  of  learning  with  understanding  psychologically,  the   professional  expectation  of  scientist  teachers  would  demand  that  professors  ask  their  students   to  go  about  things  more  scientifically—in  other  words,  they  would  ask  their  students  to  shift   the  bulk  of  their  trust  in  certain  situations  from  mental  to  empirical  allies.     Such  a  shift  in  the  professional  expectations  of  one’s  peers  brings  us  to  the  second  agent   of  interest  in  this  dissertation,  a  non-­‐human  one.  It  is  the  “figure.”  In  all  of  the  undergraduate   biology  courses  I  observed  between  2004-­‐2009,  nearly  all  of  the  day-­‐to-­‐day  activities  in  the   weeks  leading  up  to  the  examinations  revolved  around  the  almost  constant  display  of  empirical   figures  to  and  for  students.  An  example  of  one  of  these  figures  is  shown  in  Figure  3.2.   103             Figure  3.2.  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis  unit  in  an   undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava,  Heller,  Orians,  Purves,  and  Hillis   2007).  For  interpretation  of  the  references  to  color  in  this  and  all  other  figures,  the  reader  is   referred  to  the  electronic  version  of  this  dissertation.  (Reprinted  with  permission  by  the   copyright  holder.)     We  must  recall,  however,  that  in  the  space  of  the  classroom  the  biology  professors  I   witnessed  routinely  denied  their  students  the  use  of  these  figures  on  examinations.  To  clarify,   104       while  the  biology  professors  denied  their  students  the  recruitment  and  use  of  empirical  figures,   they  strongly  encouraged  their  students  to  recruit  and  use  mental  or  psychological  figures.   What  sort  of  professional  expectations  could  make  such  a  denial  and  like-­‐for-­‐like  substitution   possible?  logical?  favorable?  preferable?     One  professional  expectation  that  would  make  this  particular  practice  possible  is  the   expectation  that  science  teachers  enact  a  theory  or  mechanism  of  correspondence.  If  and  when   science  educators  assume  that  an  empirical  figure  and  a  mental  figure  can  be  simultaneously   one  and  the  same  thing,  it  then  becomes  both  possible  and  logical  to  see  the  empirical  figure   shown  in  Figure  2  not  only  as  something  that  can  be  found  on  a  theater-­‐sized  projection  screen   during  a  lecture,  but  also  as  the  very  thing  that  can  be  found  inside  of  the  minds/brains  of   students.  When  empirical  and  mental  figures  are  construed  as  identical  reflections  of  one   another—in  other  words,  when  they  are  construed  as  mimetic—it  becomes  possible  to  see  the   substitution  of  one  for  the  other  as  entirely  unproblematic.  In  other  words,  it  becomes  possible   in  practice  for  science  teachers  to  deny  their  students  the  enlistment  of  an  empirical  figure  on   an  exam  because  in  principle  the  mental  figure  is  thought  to  possess  exactly  the  same  traits  and   benefits  as  its  empirical  ‘twin.’     But  what  if  we  choose  not  to  see  empirical  and  mental  figures  as  identical?  What  if  we   choose  not  to  see  them  as  the  corresponding  sides  of  a  two-­‐faced  coin?  What  if  we  choose  not   to  articulate  the  relationship  between  an  empirical  figure  of  the  Calvin  Cycle  and  a  mental   figure  of  the  Calvin  Cycle  as  mimetic?  If  and  when  these  denials  are  permitted,  new  kinds  of   professional  expectations  become  possible,  logical,  favorable,  and  even  preferable.  What   105       resources  might  begin  to  help  us  create  these  new  kinds  of  professional  expectations?  Well,  we   might  consider  looking  in  the  direction  of  scientists  and  scientific  research.     Since  the  1970s,  a  diverse  and  loosely  organized  group  of  scholars  and  researchers   including  anthropologists,  sociologists,  historians,  economists,  philosophers,  and  political   scientists  (among  others),  have  turned  science  and  scientists  into  legitimate  objects  of  interest.   One  of  the  most  interesting  results  of  their  work—and  in  particular  the  work  of  Bruno  Latour— is  the  observation  that  scientists  engaged  in  research  never  seem  to  rely  on  correspondence   theory  to  articulate  the  relationship  between  the  world  of  nature  and  the  world  of  ideas  (or,  as   103 Latour  writes,  the  relationship  between  what’s  “out  there”  and  what’s  “in  there”).  Although   philosophers  of  both  science  and  language  have  long  argued  the  opposite  to  be  true,  Latour’s   anthropological  studies  of  professional  scientists  in  both  laboratories  and  on  field  expeditions   show  that  in  practice  correspondence  theory  plays  almost  no  functioning  role  in  scientific   104 research.  According  to  Latour,  the  primary  means  by  which  research  scientists  actually   articulate  the  relationship  between  the  world  of  nature  and  the  world  of  ideas  is  dictated  by  an   entirely  different  mechanism  altogether.  Rather  than  by  correspondence,  Latour  describes  a   105 mechanism  dictated  by  actions  such  as  “reference”  and  “circulation.”  Rather  than  by   mimesis,  Latour  claim  is  that  in  practice  much  of  the  heavy  lifting  of  scientific  discovery  is   instead  accomplished  by  a  scientist’s  ability  to  enlist  vast  armies  of  empirical  allies—including   both  human  and  non-­‐human  allies—into  a  “network”  of  stable  but  fragile  relations.  Thus,  for                                                                                                                   103.  Latour,  Pandora’s  Hope,  14.   104.  See  in  particular  Latour  1986;  1995;  and  1999.   105.  Latour,  Pandora’s  Hope,  69.   106       Latour,  scientific  thinking  is  not  something  that  is  accomplished  with  the  mind  or  brain,  but   106 rather  with  “eyes  and  hands.”  In  other  words,  for  Latour,  the  cognition  of  scientists  can  be   described  more  accurately,  adequately,  and  interestingly  as  logistical  practices  rather  than  as   107 logical  ones.     Summary     In  this  chapter,  we  have  seen  that  scientists  and  science  students  can  experience  a   common  dilemma.  That  is,  there  are  occasions  in  both  research  and  education  when  collections   of  individuals  are  confronted  by  novel,  perplexing  phenomena.  How  they  confront  these   situations,  however,  is  quite  different.  Research  scientists  tend  to  shift  the  weight  of   responsibility  from  their  mental  faculties  to  a  network  of  empirical  allies;  science  professors   demand  that  their  students  shift  the  weight  of  responsibility  from  a  network  of  empirical  allies   to  their  mental  faculties.  In  other  words,  the  practice  of  learning  with  understanding  in  science   appears  to  be  the  opposite  of  learning  with  understanding  in  science  education.  This  statement   of  contrast  is  made  possible  by  the  anthropological  (but  also  philosophical)  work  of  Latour,  who   manages  to  draw  our  attention  away  from  the  mind/brain  and  towards  the  hands/eyes.  The   logics  of  science,  Latour  claims,  can  be  satisfactorily  accounted  for  by  a  logistics  of  science.     I  will  have  much  more  to  say  about  the  work,  vocabulary,  concepts,  claims,  motivations,   and  resources  of  Latour  in  Chapter  4,  but  for  now  suffice  it  to  say  that  Latour  offers  science   educators  something  different  than  a  set  of  mental  or  psychological  resources  with  which  to  set   about  improving  the  work  of  teaching  for  and  learning  with  understanding.  Instead  of  mental                                                                                                                   106.  See  Latour  1986.   107.  See  Latour  1987  (Chapter  6).   107       resources—which,  if  one  prefers,  are  already  available  in  ample  abundance  in  science   education—Latour  offers  science  educators  something  that  might  be  more  accurately  described   as  ecological.  I  use  this  descriptor  because  first  and  foremost  Latour  is  interested  in  the   relationships  formed  by  an  immense  variety  of  humans  and  non-­‐humans  including  both  living   (biotic)  and  non-­‐living  (abiotic)  things.  To  put  this  differently:  Latour  is  as  interested  in  scientists   as  he  is  in  earthworms,  beakers,  trees,  rocks,  shovels,  tin  tags,  cardboard  cubes,  notebooks,   maps,  figures,  and  scientific  publications.  Rather  than  a  singular  focus  on  humans,  Latour   generously  gives  permission  for  non-­‐human  actors  to  populate  a  scene.  Rather  than  serve  as   ‘mere’  props  or  backdrops  to  and  for  human  actors,  however,  Latour  grants  an  equality  of   agency  to  these  non-­‐human  actors  such  that  they  too  can  possess  and  exercise  both  practical   and  theoretical  relevance.   In  the  next  chapter,  we  will  begin  to  learn  how  to  ‘speak’  Latour  in  the  hopes  of   cultivating  a  particular  type  of  ecological  sensibility—one  that  grants  us  needed  permission  to   pay  attention  to  both  humans  and  non-­‐humans  in  the  space  of  science  classrooms.  By  the  end   of  Chapter  4  we  should  be  more  ready  to  see  professors  and  figures  differently.  If  we  can  take  a   positive  step  in  that  general  direction,  then  we  will  succeed  in  substantially  increasing  the   possibility  that  we  can  meet  one  of  our  original  goals:  To  increase  number  of  ways  in  which  it  is   possible  to  conceive  of  teaching  for  and  learning  with  understanding.           108       CHAPTER  4   A  SCIENTIFIC  HORIZON         When  you  hear  someone  say  that  he  or  she  ‘masters’  a  question   better,  meaning  that  his  or  her  mind  has  enlarged,  look  first  for   inventions  bearing  on  the  mobility,  immutability  or  versatility  or   the  traces;  and  it  is  only  later,  if  by  some  extraordinary  chance,   something  is  still  unaccounted  for,  that  you  may  turn  towards  the   mind.   —  Bruno  Latour,  Science  In  Action     Memory  is  often,  and  wrongly,  conceived  of  as  an  act  of   consciousness  and  associated  with  what  can  be  called  the  mind   [...]  We  don’t  analyze  the  movements  of  icebergs  by  studying  the   bit  that  appears  above  the  surface  of  the  sea;  nor  should  we  study   memory  in  terms  of  that  which  fires  a  certain  set  of  neurons  at  a   determinate  time.  We  as  social  and  technical  creatures  engage  in   a  vast  span  of  memory  practices,  from  the  entirely  non-­‐conscious   to  the  hyperaware.     —G.C.  Bowker,  Memory  Practices  in   the  Sciences         In  this  chapter  I  begin  the  work  of  trying  to  reassemble  the  existing  notions  of  concepts   and  understanding  around  something  new  and  different.  More  specifically,  I  draw  from  Latour’s   work  regarding  what  he  has  called  the  “logistics”  of  science  and  “thinking  with  eyes  and  hands.”   According  to  Latour,  many  social  scientists  have  long  explained  knowledge  gain  and  knowledge   use  in  the  Western  natural  sciences  as  primarily  the  result  of  individuals  with  supreme  mental   abilities.  Despite  more  recent  movement  toward  the  social  and  cultural  explanations—which  I   happen  to  think  suffers  from  a  set  of  problems  similar  to  those  encountered  by  a  belief  in  the   109       power  of  the  individual—we  see  a  similar  trend  in  science  education.  That  is,  when  push  comes   to  shove  in  classrooms,  for  example,  during  high-­‐stakes  exams,  individual  mental  abilities  still   reign  supreme.  Counter  to  this  explanation,  Latour  offers  a  body  of  empirical  and  philosophical   work  that  allows  us  to  see  the  past,  present,  and  future  work  of  natural  scientists  differently.   Latour  offers  us  a  new,  fresh  view  of  scientific  knowledge  production  and  knowledge  use  (or   knowledge  application)  in  which  humans  are  demoted,  so  to  speak,  in  their  roles  and   importance.  In  a  Latourian  calculus,  humans  must  share  their  long-­‐coveted  and  carefully   cultivated  plane  of  immanence  with  others.   Of  particular  interest  to  me  is  that  Latour  makes  room  for  the  full  participation  of   material,  non-­‐humans  in  science.  This  enlistment  of  non-­‐human  entities  (or  “actors,”  as  he   sometimes  calls  them)  creates  an  entirely  new  horizon  of  possibilities  for  what  it  means  to   produce  and  extend  scientific  knowledge.  I  propose  that  we  in  science  education  consider  a   similar  enlistment.  In  other  words,  I  propose  that  we  allow  material,  non-­‐human  actors  to  flood   our  descriptions  of  classroom  science  teaching  and  learning  so  that  we  may  see  things  like   concepts  and  understanding  from  new,  different,  and  fresh  perspectives.   I  am  using  a  Latourian  methodology  to  investigate  two  classroom  common  practices  in   an  undergraduate  science  course:  knowledge  gain  and  knowledge  application.  This  is  to  say  that   I’ve  deliberately  limited  my  observations  and  data  collection  to  aspects  of  these  two  practices   that  are  both  visible  and  material—to  things  occurring  outside  of  the  minds/brains  of  teachers   and  students.  If  aspects  of  the  practices  I  was  studying  ever  became  invisible  or  immaterial,   they  were  no  longer  considered  to  be  of  interest  to  me.  This  rule  of  method  drew  much  of  my   initial  attention  to  the  use  of  what  the  Bio101  instructors  often  referred  to  as  “figures.”  During   110       a  four-­‐day  unit  on  photosynthesis,  for  example,  the  instructors  displayed  nearly  forty-­‐five  visual   images  to/for  their  students  at  an  average  rate  of  one  new  figure  shown  every  3.33  minutes.  In   their  attempts  to  help  the  Bio101  students  gain  and  apply  scientific  knowledge,  the  display  of   visible,  material  figures  appeared  central  to  these  two  classroom  activities.   My  analysis  of  the  use  of  these  classroom  figures  is  informed  by  a  prolonged   engagement  with  the  ideas  of  anthropologist  Bruno  Latour,  as  well  as  by  other  scholars   belonging  to  the  loosely  organized  domain  of  Science  Studies.108  In  work  published  over  a   period  of  over  30  years  between  1979-­‐2013,  Latour  and  others  offer  an  empirical  account  of   the  production  of  figures  routinely  appearing  in  research  reports,  articles,  and  other  scientific   manuscripts.  I  decided  on  the  use  of  a  Latourian  framework  for  my  analysis  of  the  use  of   classroom  figures  for  two  main  reasons.  First,  Latour’s  account  is  empirical.  Regarding  the   investigation  of  knowledge  gain  and  application  in  classrooms,  many  of  the  tools  and  concepts   available  to  science  educators  and  researchers  are  psychological,  that  is,  they  are  centrally   concerned  with  products  and  processes—often  in  isolation—occurring  in  the  minds  of  students   and  teachers.  A  Latourian  analysis  of  knowledge  gain  and  application  demands  a  central  focus   on  empirically  observable  products  and  practices  occurring  outside  of  minds/brains.  Second,   increased  ‘authenticity,’  by  which  is  often  mean  that  science  education  should  be  more  like                                                                                                                   108.  Besides  Latour,  the  work  of  a  number  of  other  scholars  work  in  Science  Studies  have   informed  this  dissertation.  A  short  list  would  include—but  would  by  no  means  be  limited  to— the  work  of  Michael  Lynch,  John  Law,  Michael  Callon,  Steve  Woolgar,  Lorraine  Daston,  Peter   Galison,  Ian  Hacking,  and  Michel  Serres.   111       st research  science,  is  one  of  the  major  goals  of  early  21  century  science  education  reform. 109   This  makes  a  comparative  study  of  knowledge  gain  and  application  as  they  occur  both  inside   and  outside  of  science  classrooms  not  only  timely,  but  also  useful.  Such  a  comparative  account   stands  to  offer  rich,  empirical  descriptions  of  the  ways  in  which  knowledge  gain  and  application   in  contemporary  classrooms  is  visibly  and  materially  continuous  and  discontinuous  with   research  science.  It  other  words,  such  a  comparison  will  offer  science  educators,  teacher   educators,  and  education  researchers  an  empirical  platform—which  is  very  different  from  a   psychological  one—upon  which  the  practices  of  science  education  can  be  re-­‐imagined  and  re-­‐ shaped  into  practices  more  proximate  to  what  we  might  call  scientific  education,  scientific   teaching,  and/or  scientific  learning.  Such  an  expansion  of  the  resources  available  to/for   educators,  teacher  educators,  and  researchers—but  also  to/for  students—should  prove  highly   desirable.   Of  particular  interest  and  use  to  me  in  this  analysis  are  Latour’s  notions  of:   ● Inscriptions—inscriptions  were  ever-­‐present  in  Bio  101.  Every  lecture  was  structured   around  the  continuous  display,  explication,  and  annotation  of  visible,  material   inscriptions  (or  what  the  professors  called  “figures”).     ● Material  or  “circulating”  reference—inscriptions  have  visible,  material,  historical   trajectories.  As  Latour  and  others  have  shown,  these  trajectories  can  be  described  in   great  empirical  detail.  The  practices  of  circulating  reference  are  a  direct  challenge  the                                                                                                                   109.  I  am  aware  that  there  are  at  least  three  ways  in  which  the  term  authenticity  is  used  in   science  education  research.  For  example,  Buxton  describes  three  different  models  of   authenticity  in  operation  in  research  (see  Buxton  2006).  I  am  interested  in  what  he  calls   “canonical”  authenticity,  i.e.,  making  school  science  more  like  scientists’  (or  research)  science.   112       notion  of  a  direct,  one-­‐to-­‐one  correspondence  between  the  ‘world’  and  the  ‘word.’  It  is   not  anti-­‐realist,  however;  on  the  contrary,  in  Latour’s  own  words  it’s  a  more  realistic   form  of  realism.     One  advantage  of  looking  to  Latour  is  that  abstract  conceptual  learning  theory  can  become   something  different.  For  example,  it  can  become  something  that  is  more  visible,  tangible,   material,  historical,  and  local.  In  addition,  it  can  become  more  empirical  and  more  disciplinary.   In  other  words,  it  can  become  more  like  science.  This  is  because  the  Latourian  concepts  were   derived  from  empirical  studies  of  science/scientists  in  action  and  not  from  psychology  or  the   alchemy  of  school  subjects.  One  interesting  thing  that  distinguishes  Latour's  work  from   psychology  or  abstract  conceptual  learning  theory  is  that  in  Latour,  there  is  no  such  thing  as   transfer.  There  is  only  “transformation  with  deformation”  because  transformation  without   110 deformation  is  simply  transportation.  Thus,  Latour's  theory  is  not  a  psychological  one;  it   does  not  rely  on  mental  processes  as  the  primary  allies  of  understanding.   I  know  some  will  have  questions  about  the  appropriateness  of  looking  to  Latour  for  ways  to   replace  and/or  reconstruct  science  education.  For  instance,  some  readers  may  have   reservations  about  an  account  of  science  education  derived  from  studies  of  science  and   scientists.  Scientists  have  different  goals  compared  to  science  teachers,  they  might  say,   Scientists  have  different  facilities,  audiences,  purposes,  equipment,  etc.  However,  I  have   anticipated  these  objections  and  have  put  together  some  pretty  compelling  reasons  for  taking  a   Latourian  route  instead  of  others.  They  are  included  throughout  the  chapter.                                                                                                                   110.  The  authors  of  How  People  Learn  actually  incorporate  the  notion  of  transportation:  “The   most  effective  learning  occurs  when  learners  transport  what  they  have  learned  to  various  and   diverse  new  situations.”  NRC,  How  People  Learn:  Brain,  238  (emphasis  added).   113       The  two  main  purposes  of  this  chapter  are:     (1)  To  outline  a  Latourian  account  of  how  knowledge  is  gained  and  applied  in  science.     • Across  much  of  his  work,  Latour  draw  special  attention  to  the  production  and   use  of  scientific  figures  or  “inscriptions.”  Latour’s  empirical  interest  in   inscriptions  intersects  with  the  highly  visible  use  of  material  inscriptions  in  the   undergraduate  classrooms  I  observed.  I  use  this  intersection  as  my  main  point  of   departure.   And,   (2)  To  connect—both  empirically  and  conceptually—the  classroom  figures  I  routinely   saw  displayed  to/for  students  in  Bio101  with  the  scientific  figures  Latour  routinely  saw   displayed  to/for  other  scientists  in  reports,  articles,  and  other  types  of  scientific   manuscripts.     • This  is  an  important  connection  to  forge,  for  it  helps  to  narrow  the  theoretical   and  practical  distance  often  seen  as  standing  between  the  world(s)  of  science   and  science  education.   Once  again,  I  must  lean  heavily  into  vocal  and  ongoing  calls  for  increased  authenticity  in   K-­‐16  science  education.  A  major  goal  of  contemporary  science  education  reform  is  to  make   science  education  more  like  research  science  (to  make  school  science  more  like  scientists’   science).  In  this  dissertation,  I  do  not  intend  to  take  a  stand  as  to  whether  such  a  vision  should   be  considered  good  or  bad,  desirable  or  undesirable.  Instead,  my  dissertation  is  an  exploration   of  both  the  possibilities  and  the  perils  of  enacting  such  a  vision  of  authenticity  when  the  vision   is  grounded  empirically  instead  of  psychologically.  To  put  this  in  terms  first  introduced  in   114       Chapter  2,  I  want  to  engage  in  an  alchemical  transformation,  but  one  that  takes  its  measure   from  empirical  studies  of  scientific  research  rather  than  from  psychological  studies  of  it.   In  the  next  four  sections  (Sections  A-­‐D),  I  will  explicate  four  different  readings  of  two   classical  figures  of  the  Calvin  Cycle.  Read  with  Latourian  sensibilities,  the  four  readings  illustrate   relationships  between  scientific  figures  and  classroom  figures.     Section  A:  Science  in  Action     Empirical  studies  of  science  have  led  to  new  ways  of  conceptualizing  how  scientific   knowledge  is  gained  in  laboratories  and  on  field  expeditions.  Since  the  1970s,  researchers  from   a  variety  of  disciplines  have  committed  to  following  research  scientists  at-­‐work  across  the  globe.   Their  main  object  of  interest  has  been  the  mundane,  day-­‐to-­‐day  practices  of  scientists  in  action   111 or  “science  in  the  making.”  This  dissertation  brings  forward  the  work  of  anthropologist   Bruno  Latour  (and  others)  and  in  particular  his  empirical  descriptions  of  how  scientists  gain  and   apply  scientific  knowledge.   Knowledge  Gain     For  Latour,  scientific  knowledge  gain  usually  starts  in  some  sort  of  center—i.e.,  physical   spaces  where  scientists  accomplish  work.  Centers  can  be  university  offices,  company  and   government  laboratories,  field  stations,  museums,  etc.  How  do  we  know  when  a  physical  space   is  a  center  of  science?  It’s  likely  full  of  but  by  no  means  limited  to  instruments  and  equipment,   maps  and  protocols,  bookshelves  and  furniture,  cabinets  for  paper  files,  cages  for  live   specimens,  collections,  scientists,  technicians,  and  secretaries.  Centers  of  science  are  places                                                                                                                   111.  See  Latour  1987,  Introduction.   115       where  scientists  typically  begin  (and  end)  important  aspects  of  their  work  such  as  inquiries,   experiments,  expeditions,  and  investigations. 112   113 From  centers  of  science,  many  scientists  embark  on  “cycles  of  accumulation.”  That  is,   they  go  out  into  nature  and  find/invent  ways  to  bring  representatives  of  nature  back  to  the   centers.  However,  a  major  challenge  facing  scientists  is  that  nearly  all  the  delegates  of  the   natural  world  offer  various  forms  of  resistance  to  being  mobilized  and  transported.  Most   mountains  are  heavy,  some  gases  can  explode,  plants  die  and  decay,  bacteria  can  kill  their   capturers,  animals  can  be  aggressive,  stars  are  hot  and  far  away.  Because  of  this  active   resistance,  scientists  must  find/invent  ways  to  transform  the  delegates  into  more  mobile,  stable,   and  eventually  combinable  forms  (they  are  “delegates”  because  they  are  almost  always   representatives  of  larger  populations  of  rocks,  plants,  stars,  etc.).  Scientists  must  transform  the   delegates  while  simultaneously  protecting  them  from  too  much  deformation  or  degradation.  In   other  words,  scientists  must  try  to  ensure  that  the  delegates  remain  the  same  despite  the  fact   that  they  must  be  changed.  Latour  calls  the  products  of  such  transformations  of  natural  objects   “immutable  mobiles.” 114  However,  Daston  &  Galison  offer  another  helpful  term  for  such   115 products,  “working  objects.”  For  the  scientist,  natural  objects  prove  too  plentiful  and  too   various  to  deal  with  efficiently  and  constructively.  Thus,  natural  objects  must  be  selected  and   constituted.  In  order  for  science  to  work  smoothly  and  efficiently,  the  representatives  of  the   ‘sectors’  or  ‘slices’  of  nature  under  investigation  must  be  made  manageable.  “No  science  can  be                                                                                                                   112.  See  Latour  1987,  Chapter  6,  Part  B.   113.  See  Latour  1987,  Chapter  6,  Part  A.   114.  Latour,  “Visualization  and  Cognition,”  7.   115.  Daston  and  Galison,  Objectivity,  19.   116       without  such  standardized  working  objects,”  as  Daston  &  Galison  explain,  “for  unrefined   116 natural  objects  are  too  quirkily  particular  to  cooperate  in  generalizations  and  comparisons.”   Latour  characterizes  the  practice  of  transforming  more  raw-­‐form  natural  objects  into   more  refined-­‐  or  final-­‐form  working  objects  as  scientific  “acts  of  reference.” 117  Acts  of   reference,  which  I  explain  in  detail  in  Section  B  of  this  document,  can  also  be  loosely  defined  as   the  ways  in  which  scientists  make  the  world  more  mobile,  stable,  immutable,  combinable,  and   superimposable.  In  other  words,  acts  of  reference  can  be  loosely  defined  as  the  ways  in  which   scientists  make  the  world  more  abstract.  For  Latour,  scientific  knowledge  gain  hinges  upon   scientists  ability  to  successfully  couple  or  chain  multiple  acts  of  reference  together  to  form   118 visible,  material  “circuits.”  I  provide  an  example  of  a  scientific  circuit  of  reference  in  Section   B.  Such  circuits  of  reference  usually  result  in  the  production  of  numerous  two-­‐dimensional   119 working  objects  that  are  written  on  paper.  He  calls  these  working  objects  “inscriptions.”  And   so,  in  a  Latourian  scenography,  we  might  say  that  scientific  knowledge  gain  can  be   conceptualized  as  scientists  engaging  in  cycles  of  accumulation  in  which  the  scientists  select   representatives  of  a  natural  world  and  help  them  take  steps—by  transforming  them  through   acts  of  reference  and  then  chaining  these  individual  acts  into  coherent  circuits—to  becoming   full-­‐fledged  members  of  a  paper  world,  a  world  of  inscriptions.   However,  scientific  knowledge  gain  does  not  stop  with  the  production  of  paper-­‐based   inscriptions.  According  to  Latour,  inscriptions  are  then  gathered  en  masse  in  centers  of  science                                                                                                                   116.  Ibid.,  19,  22.   117.  See  Latour  1999  (esp.  Chapter  2),  but  also  Latour  1995.   118.  See  Latour  1999  (esp.  Chapter  2),  but  also  Latour  1995.   119.  See  Latour  and  Woolgar  1986.  See  also  Latour  1986;  1987;  and  1999.   117       and  subjected  to  additional  work.  In  centers,  inscriptions  are  resources  that  allow  other   scientists  to  see  distant  things  and  become  familiar  with  distant  events  without  ever  having   traveled  far  away  from  the  center.  And  because  scientists  create  elaborate  accounting  systems   within  their  circuits  of  scientific  reference,  these  same  untraveled  scientists  can  then  venture   out/back  to  the  source  of  the  inscriptions  so  that  they  may  bring  back  even  more  working   objects.  Thus,  in  a  Latourian  scenography  we  can  imagine  that  centers  of  science  might  also  be   called  ‘centers  of  accumulation,’  for  they  are  a  central  gathering  point  for  the  refined  products   numerous  of  scientific  circuits  of  reference.  As  we  will  see  later,  it  is  these  highly  refined   characteristics—mobility,  stability,  immutability,  superimposability,  and  combinability—that   eventually  allow  scientists  to  apply  or  extend  scientific  knowledge  to  the  world  outside  of   120 centers  or,  as  Latour  writes,  to  act  on  the  natural  world  “from  a  distance.”   Scientific  centers  of  accumulation  face  a  significant  challenge,  however;  the  more  cycles   of  accumulation  that  are  successfully  completed,  the  more  working  objects  delivered  to  the   centers.  Left  untended  and  unprocessed,  scientists  within  centers  of  accumulation  would  likely   suffocate  beneath  the  sheer  volume  of  working  objects,  for  these  incoming  objects  would   quickly  clog  and/or  fill  up  the  hallways,  basements,  offices,  desks,  cabinets,  bookshelves,   network  servers,  and  computer  hard  drives.  So,  how  do  scientists  inside  of  centers  effectively   manage  the  constant  stream  of  scientific  colleagues  returning  from  cycles  of  accumulation  with   working  objects  in  their  hands,  bags,  boxes,  crates,  bottles,  and  briefcases?  For  Latour,  the   answer  to  this  question  is  through  performing  yet  additional  acts  of  transformation.  In  other   words,  through  the  production  of  yet  more  working  objects,  which  effectively  consumes  the                                                                                                                   120.  See  Latour  1987,  Chapter  6,  Part  A.  See  also  Latour  1986.   118       existing  ones.  In  the  hands  of  scientists  (and  often  now  in  the  circuitry  of  computers),  each   working  object  produced  must  be  more  condensed,  more  summarized,  more  reduced,  and   more  abstracted  than  its  predecessor.  How  else  would  the  steady  incoming  tide  of  working   objects  be  overcome?  The  scenario  is  comparable  to  a  temperate  forest  ecosystem:  in  the   absence  of  the  various  decomposing  insects,  fungi,  molds,  and  bacteria  present  in  the   ecosystem,  the  forest  would  fill  up  with  leaves.  In  scientific  centers  of  accumulation,  as  in   temperate  forests,  the  active  transformation  of  more  raw-­‐form  entities  into  more  refined  forms   is  vital.   In  a  sense,  each  newly  constituted  working  object  (the  nth  form  inscription)  is  a   summary  or  collection  of  the  working  objects  it  replaces  (the  nth-­‐1,  nth-­‐2,  nth-­‐3...nth-­‐n  forms).   Through  such  “cascades  of  inscriptions,”  inflated,  three-­‐dimensional  natural  objects  are   effectively  transformed  into  deflated,  flattened,  two-­‐dimensional  forms  that  can  then  be   combined  in  ways  that  they  never  could  in  their  more  worldly  or  earthly  forms. 121 122 of  science,  centers  of  accumulation  behave  more  like  “centers  of  calculation.”  At  this  stage    The  forms   produced  by  the  cascades  of  inscriptions  are  increasingly  abstract  but  yet  still  visible  and  still   material.  Even  a  single  letter  “E,”  a  standard  letter  used  for  “energy”  in  science  and  a  highly   abstracted  form,  still  retains  some  visibility  and  materiality.  For  instance,  it  is  often  made  of  ink   and  printed  on  a  matrix  of  wood-­‐fibered,  chemically  treated  paper.  These  visible,  material   characteristics  allow  it  to  be  combined  with  other  letters—for  example,  with  letters  such  as  “M”   and  “C”  in  equations—and  brought  into  relationships  with  other  inscriptions.  In  other  words,                                                                                                                   121.  See  Latour  1999,  Chapter  2.  See  also  Latour  1986;  1995.   122.  See  Latour  1987,  Chapter  6,  Part  B.   119       the  working  objects  produced  at  this  stage  allow  for  something  quite  extraordinary  and   powerful  to  occur:  finally,  after  many  acts  of  reference  have  been  coherently  coupled  or   chained  together,  equations  can  be  constructed  and  calculations  can  be  made.     An  important  point  to  emphasize  at  this  juncture  is  that  mental  or  psychological   “cognition”  never  appears  in  a  Latourian  account  of  scientific  knowledge  gain.  At  no  point  in  a   Latourian  scenography  are  scientific  objects  and  practices  associated  with  knowledge  gain   located  in  the  minds/brains  of  scientists.  Instead,  scientific  objects  and  practices  are   externalized  and  located  among  a  heterogeneous  network  that  includes  but  is  not  limited  to   people,  instruments,  institutions,  furniture,  working  objects,  paper,  technology,  and  money.   Because  Latour  does  not  conceptualize  knowledge  gain  as  mental/cognitive  or  psychological,  he   creates  that  possibility  of  following  and  studying  it  without  needing  to  know  what  scientists  are   thinking.  Latour  is  not  interested  in  what’s  happening  inside  of  scientists’  minds/brains  when   they  are  engaged  in  cycles  of  accumulation,  working  in  centers  of  accumulation,  or  involved  in   making  calculations.  Instead,  he  is  keenly  interested  in  what’s  happening  outside  of  scientists’   minds/brains  when  they  are  engaged  in  these  scientific  activities.  This  dramatic  shift  opens  up   the  possibility  for  analysts  of  science  to  conceptualize  practices  like  abstraction  and  scientific   reasoning  as  external  processes—by  which  is  meant  objects  and  processes  that  are  visible,   material,  accessible,  and  observable—that  one  can  study  empirically.  As  we  will  see,  this  also   opens  up  similar  possibilities  in  science  education.  That  is,  we  can  study  abstraction  and   reasoning  in  classrooms  as  external  processes.  We  can  study  them  empirically.         120       Knowledge  Application     Knowledge  gain  is  not  enough.  As  we  will  see  in  Section  B,  scientists  gain  many   advantages  from  cycles  of  accumulation,  as  well  as  from  the  additional  transformational  work   accomplished  inside  of  the  centers  of  calculation.  However,  in  science  these  advantages  must   be  translated  back  to  the  periphery  or  else  they  will  disappear.  In  order  to  translate  these   advantages  back  to  the  natural  world,  that  is,  in  order  to  apply  them  to  the  world  outside  of   scientific  centers,  there  is  still  much  work  to  be  done.  Abstract  theories  and  concepts  cannot  be   applied  everywhere  and  at  every  time  unless  the  world  outside  of  centers  of  science  is  made  to   resemble  the  network  in  which  the  cascades  of  inscriptions  were  articulated.  For  Latour,  this  is   partly  accomplished  through  the  work  of  “metrology.”  As  Latour  explains,   Metrology  is  the  name  of  this  gigantic  enterprise  to  make  of  the  outside  a  work  inside   which  facts  and  machines  can  survive.  Termites  build  their  obscure  galleries  with  a   mixture  of  mud  and  their  own  droppings;  scientists  build  enlightened  networks  by  giving   the  outside  the  same  paper  form  as  that  of  their  instruments  inside.  In  both  cases  the   123 result  is  the  same;  they  can  travel  very  far  without  ever  leaving  home.     I  will  have  more  to  say  about  metrology  later,  but  for  now  we  can  think  about  metrology   as  the  scientific  organization  of  stable  measurement  and  standards  such  as  those  physical   124 constants  used  to  measure  time,  space,  weight,  wavelength,  etc.  At  least  for  now,  however,   we  can  say  that  scientific  knowledge  application  involves  the  active  and  deliberate   transformation  of  the  world  outside  of  scientific  centers  into  spaces  that  resemble  the  world   inside  of  scientific  centers.  For  example,  Latour  ascertained  through  an  historical  study  that   Louis  Pasteur  had  transformed  provincial  French  farms  into  visible,  material  extensions  of  his                                                                                                                   123.  Latour,  Science  In  Action,  251.   124.  Latour,  “Visualization  and  Cognition,”  30.  See  also  Latour  1987,  Chapter  6,  Part  C.   121       Parisian-­‐based  laboratory.  Similarly,  Latour  observed  one  of  his  own  colleagues,  a  botanist,   attach  hundreds  of  little  tin  tags  to  branches  of  trees  in  a  section  of  a  Brazilian  forest,  and  on   which  she  wrote  numbers  such  as  “234.”  The  tags  were  used  to  help  her—but  also  other   scientists  who  had  yet  to  visit  this  section  of  the  Brazilian  forest—find  their  way  to  particular   spot  at  some  point  in  the  future.  One  of  the  things  these  transformations  of  the  world  enable  is   the  execution  of  “rehearsals.” 125  For  example,  Latour  notes  that  simulators  allowed  astronauts   to  land  on  the  Moon  thousands  of  times  before  they  actually  ever  did  so,  and  that  scientists  at   the  Delft  Hydraulics  Laboratory  in  Holland  constructed  a  scaled  down  model  of  the  Rotterdam   harbor  to  rehearse  various  natural  phenomena  (e.g.,  flooding,  silting,  dredging  scenarios)   before  they  actually  happened  to  the  scaled  up  or  actual/real  harbor.     In  sum,  knowledge  application  in  science  involves  anything  and  everything  used  to  help   abstract  (yet  still  visible,  material)  forms—e.g.,  scientific  inscriptions—travel  and  survive   outside  of  centers  of  accumulation/calculation.  Metrological  work,  transformations  of  the   world  to  resemble  laboratories,  and  rehearsals  are  just  a  few  of  the  ways  in  which  abstract   scientific  products  such  as  laws,  theories,  and  concepts  earn  the  reputation  of  being  ‘universal.’   It  is  how  they  appear  to  analysts  of  science  as  having  their  own  internal  momentum  or  inertia.   However,  in  Latour  this  reputation  and  appearance  are  the  result  of  the  careful  preparation  of   visible,  material  “landing  strips”;  they  are  the  result  of  the  transformation  of  as  many  points  of   126 the  world  outside  of  scientific  centers  into  actively  functioning  instruments.                                                                                                                 125.  See  Latour  1987,  Chapter  6,  Part  C.   126.  Latour,  Science  In  Action,  253.   122         And  so,  in  a  Latourian  scenography  knowledge  application  is  not  the  application  of   mental  concepts  and  cognitive  processes  from  a  psychological  domain  to  a  natural/material   one—from  an  internalize  domain  to  an  externalized  one.  If  we  want  to  talk  about  “cognition,”   Latour  is  willing  to  talk  about  it  but  only  if,  once  again,  cognition  is  granted  permission  to  be   externalized.  Thus,  a  Latourian  scenography  does  not  attending  to  the  logics  of  science;  by   deliberate  choice,  it  tends  to  the  logistics  of  science.  For  Latour,  the  abstract  products  of   science—e.g.,  facts,  theories,  and  concepts—are  like  “trains,  electricity,  packages  of  computer   bytes  or  frozen  vegetables:  they  can  go  everywhere  as  long  as  the  track  along  which  they  travel   is  not  interrupted  in  the  slightest”;  they  have  no  inertia  of  their  own,  like  “kings  or  armies  they   127 cannot  travel  without  their  retinues  or  impedimenta.”   A  key  question  to  pose  at  this  juncture  is  this:  How  and  where  does  a  Latourian  account   of  scientific  knowledge  gain  and  knowledge  application  intersect  and/or  overlap  with   approaches  to  knowledge  gain  and  knowledge  application  found  in  college  science  education?   This  is  an  important  question  and  it  frames  the  main  purpose  of  Section  B.  That  is,  in  the  next   section  I  aim  to  connect—both  conceptually  and  empirically—knowledge  gain  and  knowledge   application  as  practiced  in  science  with  knowledge  gain  and  knowledge  application  as  practiced   in  schools.  I  find  the  most  visible  and  material  intersection  to  be  in  the  appearance  of  “figures”   in  both  science  classrooms  and  scientific  publications.  And  so,  Section  B  begins  the  task  of   forging  a  connection  between  these  figures  or  inscriptions.   Section  B:  How  to  Speak  Latourian  about  Scientific  Figures     Figures  4.1  and  4.2  juxtapose  two  figures,  a  scientific  and  a  classroom  figure.                                                                                                                 127.  Latour,  Science  In  Action,  250.   123           Figure  4.1.  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that  Melvin  Calvin  submitted  when  accepting  the   1961  Nobel  Prize  for  chemistry.  Figure  20  (Calvin  1961). 124                   Figure  4.2.  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis  unit  in   an  undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava  et  al.  2007).  (Reprinted  with   permission  by  the  copyright  holde 125       Figure  4.1  (“Fig.  20”)  shows  an  example  of  a  scientific  figure.  It  was  published  in  1961   and  is  attributed  to  Melvin  Calvin,  a  research  scientist.  Fig.  20  is  one  of  nearly  two-­‐dozen  figures   included  by  Calvin  in  a  manuscript  submitted  to  the  Nobel  Foundation  as  part  of  his  acceptance   128 of  the  1961  Nobel  Prize  for  chemistry.  It  never  appeared  in  the  Bio101  course  I  studied,   either  in  lecture  or  in  the  course  textbook.  In  other  words,  Fig.  20  was  never  made  visible  to   Bio101  students.   Figure  4.2  (“Fig.  8.13  (Part  2)”)  shows  an  example  of  a  classroom  figure.  It  was  published   in  2007  and  is  attributed  to  Sadava,  Heller,  Orians,  Purves,  and  Hillis.  All  five  of  these  individuals   are  research  scientists.  Fig.  8.13  (Part  2)  is  one  of  hundreds  of  figures  included  by  Sadava  et  al.   in  a  manuscript  submitted  to  and  developed  with  W.H.  Freeman  publishers.  It  appeared  in  the   8th  edition  of  an  introductory-­‐level  college  textbook  titled,  Life:  The  Science  of  Biology. 129  Fig.   8.13  (Part  2)  also  appeared  multiple  times  in  the  Bio101  classroom.  It  was  included  in  the   course  textbook  and  it  was  also  displayed  on  a  large,  white,  theater-­‐sized  projection  screen  to   and  for  the  Bio101  students.   For  Latour,  Fig.  20  is  a  particular  kind  of  scientific  figure  to  which  his  attention  was   inescapably  drawn  while  studying  how  research  scientists  gain  scientific  knowledge.  What  he   once  referred  to  as  scientific  literature’s  most  “powerful  tool,”  he  less  dramatically  labeled  “the   visual  display.” 130  With  almost  every  group  of  scientists  he  ever  followed—whether  into   laboratories  or  out  on  field  excursions—Latour  found  that  visual  displays  similar  to  Fig.  20  were   distinctively  involved  in  scientific  communication  and  in  the  very  production  of  scientific                                                                                                                   128.  See  Calvin  1961.   129.  See  Sadava  et  al.  2007.   130.  Latour,  Science  In  Action,  67.   126       knowledge. 131  It  is  one  of  Latour’s  colleagues,  however,  Michael  Lynch,  who  offers  us  a  more   instructive  conceptual  and  empirical  orientation  to  scientific  visual  displays—including  what   they  are,  where  they’re  found,  and  what  they  do  in  science.     For  Lynch,  as  well  as  for  Latour,  visual  displays  such  as  Fig.  20  are  “a  characteristic   feature  of  scientific  activity.” 132 133  Furthermore,  they  are  “the  products  of  scientific  work.”   Visual  displays  include,  but  are  not  limited  to,  “illustrative  photographs,  diagrams,  graphs  and   other  data  displays.” 134  However,  for  Lynch  visual  displays  are  much  more  than  “pictorial   illustrations  for  scientific  texts”  and  he  makes  the  case  that  we  are  deficient  in  our   understanding  of  scientific  visual  displays  if  we  simply  pay  attention  to  what  they  are—we  must   also  pay  close  attention  to  what  they  do. 135     In  a  Lynchian  scenography,  which  is  complimentary  to  a  Latourian  one,  visual  displays   have  multiple  functions.  For  example,  they:   1)  Enable  greater  public  access  to  “new  structures  wrestled  out  of  obscurity  or   chaos.” 136   2)  Display  “objects,  processes,  relationships  and  theoretical  constructs”  of  interest  to   137 scientists.                                                                                                                   131.  See  Latour  &  Woolgar  1986;  Latour  1987;  1999.   132.  Lynch,  “Discipline  and  Material  Form,”  37.   133.  Lynch,  “The  Externalized  Retina,”  204.   134.  Lynch,  “Discipline  and  Material  Form,”  37.   135.  See  Lynch  1988.   136.  Lynch,  “The  Externalized  Retina,”  204.   137.  Lynch,  “Discipline  and  Material  Form,”  37.   127       3)  Are  “essential  to  how  scientific  objects  and  orderly  relationships  are  revealed  and   138 made  analyzable.”   4)  Are  “irreplaceable  as  documents  which  enable  objects  of  study  to  be  initially   perceived  and  analyzed.” 139   5)  “Systematically  transform  specimen  materials  into  observable  and  mathematically   140 analyzable  data.”   A  common  thread  running  through  the  collective  functions  listed  above  is  an  explicit   emphasis  on  the  external,  the  visual,  and  the  publicly  accessible.  In  a  Lynchian  vocabulary,  as   well  as  in  a  Latourian  one,  the  scientific  visual  display  is  not  a  term  reserved  for  internal   viewership  (e.g.,  visualization  occurring  within  the  ‘mind’s  eye’),  psychological  imagery  (e.g.,   mental  models  and/or  representations),  or  private  cognitive  processes  (e.g.,  thinking  or   reasoning  abstractly).  On  the  contrary,  for  both  Lynch  and  Latour  scientific  visual  displays   always  possess  some  sort  of  visible,  material  form  that  allows  them  to  be  studied  empirically.   What  scientific  visual  displays  are  and  what  they  do  let  us  quickly  anticipate  where  they   are  found,  which  is  primarily  in  “scientific  publications  and  texts.” 141  However,  as  Lynch  adds,   we  must  be  aware  that  visual  documents  can  be  found  during  “all  stages  of  scientific   142 research.”  In  other  words,  even  though  highly  cleansed,  ultra-­‐refined  visual  displays  typically   appear  in  scientific  publications  and  texts,  Lynch  suggests  that  analysts  of  science  should  always                                                                                                                   138.  Lynch,  “The  Externalized  Retina,”  201-­‐202.   139.  Lynch,  “Discipline  and  Material  Form,”  37.   140.  Ibid.,  37.   141.  Ibid.,  37.   142.  Lynch,  “The  Externalized  Retina,”  202.   128       expect  to  see  many  other  kinds  of  visual  documents  throughout  scientific  research.  These  other   visual  documents  may  be  less  cleansed  and  less  refined  than  final-­‐form  visual  displays   appearing  in  scientific  publications,  but  these  documents  will  be  no  less  visible  and  no  less   material.  In  describing  the  research  process  itself,  Lynch  writes  that  in  much  scientific  research,   “A  series  of  [external]  representations  or  renderings  is  produced,  transferred,  and  modified  as   research  proceeds  from  initial  observation  to  final  publication.  At  any  stage  in  such  a   production,  such  representations  constitute  the  physiognomy  [i.e.,  face,  features,  expression,   143 look]  of  the  object  of  the  research.”   In  classifying  visual  displays  as  one  form—albeit  one  of  the  more  polished  forms—in  a   series  of  visual  documents,  and  in  describing  scientific  research  as  a  set  of  practices  involving   the  production,  transfer,  and  modification  of  a  series  of  external  representations  or  renderings,   Lynch  opens  up  an  interesting  possibility:  it  would  seem  that  final-­‐form  scientific  visual  displays   such  as  Fig.  20  and  others  found  in  scientific  publications  could  be  understood  as  the  later   stages  of  a  long(er)  series  of  externally  visible,  material,  and  publicly  accessible  visual   documents.  In  other  words,  in  a  Lynch  scenography,  highly  polished  scientific  visual  displays  can   be  understood  as  the  products  of  historical  practices  whose  histories  are  closely  linked  to  the   production  and  transformation  of  other  types  of  visual  documents  in  science.   If  Melvin  Calvin’s  Fig.  20  is  the  product  of  a  set  of  historical  practices,  how  might  a   history  of  this  figure  be  written?  To  what  other  kinds  or  types  scientific  visual  documents  is  Fig.   20  connected  and  related?  From  what  other  visual  document  or  documents  was  it  transformed   or  modified?  From  what  other  visual  documents  did  it  descend?  Out  of  what  types  of  scientific                                                                                                                   143.  Ibid.,  202  (emphasis  in  the  original).   129       practices  did  it  originate?  If  we  can  answer  these  questions  about  Fig.  20,  we  might  find   ourselves  in  a  better  position  to  see  a  connection  between  Fig.  20,  a  figure  used  in  science,  and   Fig.  8.13  (Part  2),  a  figure  used  in  science  education.     For  possible  answers  to  these  questions  it’s  best  to  return  to  the  vocabulary  and   empirical  studies  of  Latour.   Shifting  Terms:  From  Visual  Displays  to  Inscriptions     One  good  reason  to  come  back  to  Latour  at  this  point  is  economy:  Latour  simplifies   Lynch’s  vocabulary.  Instead  of  speaking  of  visual  displays  as  one  type  of  visual  document   appearing  near  the  end  of  scientific  research  processes—which  also  suggests  that  there  are   other  types  of  not-­‐so-­‐highly-­‐polished  visual  displays  produced  within  scientific  research— Latour  introduces  the  term  “inscription”  to  subsume  all  of  the  different  types  of  visual  objects   discussed  and  suggested  by  Lynch.  For  now,  it’s  best  to  define  inscriptions  as  some  kind  of   written  output  regarded  as  having  a  direct  relationship  to  some  original  entity  or  substance. 144   Melvin  Calvin’s  Fig.  20  is  a  classic  example  of  an  inscription:  it  is  written  on  paper  and  is  said  to   have  a  direct  relationship  with  processes  said  to  occur  in  the  chloroplasts  of  green  plants.   Similarly,  Sadava  et  al.’s  Fig.  8.13  (Part  2))  is  also  an  inscription.  It  too  is  written  on  paper  and  it   too  is  said  to  have  a  direct  relationship  with  processes  said  to  occur  in  the  chloroplasts  of  green   plants.  Still,  this  similarity  between  Fig.  20  and  Fig.  8.13  (Part  2)  is  not  enough  to  render  both   inscriptions  as  scientific.  While  it  is  true  that  the  authors  of  both  figures—Calvin  and  Sadava,   Heller,  Orians,  Purves,  and  Hillis  2007—are  all  research  scientists,  this  professional  status  is  not                                                                                                                   144.  See  Latour  and  Woolgar  1986,  Chapter  2.   130       enough  to  render  both  inscriptions  as  scientific. 145  Similarly,  while  it  is  also  true  that  both   figures  are  visible  and  material,  these  two  qualities  of  the  two  figures  is  still  not  enough  to   render  both  inscriptions  as  scientific.  The  simple  fact  remains  that  Fig.  20  and  Fig.  8.13  (Part  2)   are  visibly  different.   In  the  remaining  parts  of  Section  B,  I  draw  heavily  from  Latour  to  help  us  understand   how—despite  their  obvious  visible  differences—both  Fig.  20  and  Fig.  8.13  (Part  2)  can  be   understood  as  two  distinct  stages  (and,  as  it  turns  out,  closely  related  stages)  in  a  longer  chain   of  scientific  reference  or,  as  Latour  refers  to  it,  “circulating  reference.”     Circulating  Reference:  A  Way  of  Understanding  the  Relationship  between  Fig.  20  and  Fig.  8.13   (Part  2)     To  best  understand  Latour’s  notion  of  circulating  reference,  it  is  best  to  walk  step-­‐by-­‐ step  through  a  straightforward  example  of  it.  Before  beginning,  however,  I  must  endeavor  to   make  a  straightforward  substitution,  which  is  best  captured  by  the  two  scientific  inscriptions   juxtaposed  in  Figures  4.3  and  4.4.                                                                                                                 145.  The  textbook’s  website  discusses  the  scientific  research  interests  of  all  four  authors.  W.H.   Freeman,  “Author  Bios,”  Life:  The  Science  of  Biology,  accessed  on  August  10,  2013,   http://www.whfreeman.com/Catalog/authorseditorscontributors/discipline/Biology.     131           Figure  4.3.  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that  Melvin  Calvin  submitted  when  accepting  the  1961   Nobel  Prize  for  chemistry.  Figure  20  (Calvin  1961).     132               Figure  4.4.  Figure  3.  Coupe  du  transect  1  (Silva  et  al.  1991).  A  figure  displayed  in  a  scientific  manuscript  reporting  on  the  findings  of   an  expedition  to  region  of  Boa  Vista,  Roraima,  Amazonia  (Brazil).  Figure  2.15  (Latour  1999).  (Reprinted  with  permission  by  the   copyright  holder.) 133           In  Figure  4.3  is  the  now  familiar  Figure  20  (“Fig.  20”).  It  is  a  description.  It  is  Calvin’s  map   of  certain  processes  said  to  occur  in  green  plants  throughout  the  world.  In  Figure  4.4  is  Figure  3   146 (“Figure  3.  Coupe  de  transect  1”).  It  too  is  a  description.  It  too  is  a  map,  but  of  certain  soil   characteristics  in  the  Boa  Vista  region  of  Brazil.  Both  are  scientific  visual  displays.  Both  are   diagrams.  Both  are  inscriptions.  And  by  the  end  of  this  section  we  will  understand  why  they   should  both  be  considered  scientific.     I  need  to  ask  my  readers  to  shift  their  collective  attention—at  least  for  a  while—from  Fig.   20  to  Fig.  3  and  to  treat  them  as  conceptual  equals  (near  the  end  of  Section  B,  however,  I  will   ask  readers  to  undo  the  current  substitution  and  shift  back  to  Calvin’s  Fig.  20).  The  reason  for   this  shift  is  because  Latour  did  not  articulate  circulating  reference  by  studying  how  Melvin   Calvin  and  his  many  colleagues  produced  Fig.  20  over  a  period  of  twelve  years.  Instead,  he   articulated  it  by  studying  how  a  team  of  five  scientists—Silva,  Boulet,  Filizola,  Morais,  Chauvel,   147 and  Latour—produced  Fig.  3  over  a  period  of  approximately  twelve  days.  Even  for  someone   as  patient  as  Latour,  the  study  of  a  research  expedition  lasting  twelve  days  is  preferable  to  one   lasting  more  than  twelve  years.   Silva  et  al.’s  Figure  3  will  be  prove  an  invaluable  companion  as  we  engage  Latour’s   account  of  how  and  why  a  group  of  French  and  Brazilian  scientists  created  Figure  3,  which  was   inserted  into  a  scientific  report  at  the  conclusion  of  a  scientific  expedition.                                                                                                                   146.  Figure  3  also  appeared  in  Pandora’s  Hope  as  “Figure  11.15”  (see  Latour  1999,  p.  57).   147.  Interestingly,  Latour  is  included  as  one  of  the  authors  of  a  scientific  report  in  which  Figure   3  appeared.  The  report  was  titled,  “Relations  between  Vegetation  Dynamics  and  the   Differentiation  of  Soils  in  the  Forest-­‐Savanna  Transition  Zone  in  the  Region  of  Boa  Vista,   Roraima,  Amazonia  (Brazil).  Report  on  Expedition  in  Roraima  Province,  October  2-­‐14,  1991.”   134       Scientific  Knowledge  Gain  in  Laboratories,  Forests,  and  Fields     How  does  a  handful  of  soil  become  an  explanatory  diagram  published  in  a  scientific   report?  By  what  means  does  a  graspable  piece  of  earth  become  a  detailed  illustration  on  a   148 graspable  piece  of  paper?  In  other  words,  how  do  things  become  words?  The  relationship   between  things  and  words  is  Latour's  primary  concern  in  Chapter  Two  of  Pandora’s  Hope.  To   explore  how  scientists  load  or  “pack”  the  world  into  words  Latour  follows  a  team  of  scientists   into  a  Brazilian  forest  intent  on  describing  those  scientific  practices  that  "produce  information   about  a  state  of  affairs." 149  Following  the  completion  of  their  twelve-­‐day  scientific  expedition,   Latour  offers  a  fresh  description  of  a  highly  specialized  disciplinary  practice  that  he  calls   “circulating  reference.”  In  order  to  better  understand  what  Latour  means  by  circulating   reference,  I  will  now  summarize  Latour's  description  of  the  practices  of  a  group  of  soil  scientists   (pedologists).   I.  Acts  of  reference  as  crossing  (small)  gaps     According  to  Latour,  many  scientists  spend  large  portions  of  their  professional  careers   performing  routine  “acts  of  reference.”  Acts  of  reference  are  instances  of  highly  regulated,   disciplinary-­‐specific,  and  audience-­‐specific  transformations  of  things  into  words.  We  can  think   of  transformations  as  the  scientific  practice  of  moving  from  more  concrete  things  to  more   abstract  words  or,  in  the  reverse  direction,  from  more  abstract  words  to  more  concrete  things.                                                                                                                   148.  Throughout  Pandora’s  Hope,  Latour  uses  a  number  of  different  dichotomies   interchangeably:  world/word,  thing/sign,  matter/form,  more  abstract/less  abstract,  and  state   of  affairs/statement.  In  this  paper,  I  too  will  use  a  number  of  terms  in  these  dichotomies   interchangeably.   149.  Latour,  Pandora’s  Hope,  24.   135       Such  actions,  Latour  writes,  could  alternatively  be  considered  "mediations"  or  "substitutions"  in   which  things  are  changed  in  form  or  appearance.  Take  an  earthly  thing,  say,  a  handful  of  soil.  In   the  hands  of  a  skilled  pedologist,  this  soil  will  often  undergo  a  series  of  carefully  linked   transformations.  An  example  of  a  single  transformation  of  a  handful  of  soil  is  one  that  is   facilitated  by  the  pedologist’s  use  of  a  slick  tool  inscribed  with  something  called  the  “Munsell   color  system"  or,  for  short,  the  “Munsell  code.”  A  picture  of  this  tool  appears  in  Figure  4.5.         Figure  4.5.  Latour’s  photograph  of  a  pedologist  using  a  handheld,  paginated  text  containing  a   wide  range  of  color  samples  that  have  been  aligned  with  alphanumeric  Munsell  codes.  Figure   2.16  (Latour  1999).  (Reprinted  with  permission  by  the  copyright  holder.)       Not  unlike  a  collection  of  paper-­‐based  color  swatches  commonly  found  in  paint  supply   or  home  improvement  stores,  this  common  pedological  tool  consists  of  samples  of  a   136       conventionally  accepted  palette  of  colors  organized  by  three  color-­‐derived  dimensions:  hue,   value  (lightness)  and  chroma  (color  purity).  Each  Munsell  color  is  aligned  with  a  specific   alphanumeric  code:  a  somewhat  saturated  purple  of  medium  lightness,  for  example,   corresponds  to  the  code  “5P  5/10.”   Practicing  pedologists  regularly  hold  handfuls  of  soil  next  to  the  Munsell  color  samples   to  determine  precisely  which  Munsell  color,  and  thus  which  alphanumeric  code,  their  soil   samples  most  closely  match.  This  basic  matching  exercise  is  a  straightforward  example  of  an  act   of  reference:  the  alphanumeric  code  refers  to  a  particular  soil  trait,  i.e.,  color,  of  which  there   are  three  existing  dimensions  of  interest  to  soil  scientists.  This  matching  exercise  is  also  an   example  of  a  highly  regulated  transformation:  the  handful  of  soil  (a  thing)  is  transformed  into   an  alphanumeric  code  (a  sign)  through  the  use  of  a  standard  disciplinary  tool.  Alternatively,   Latour  calls  such  a  transformation  the  “loading”  or  “disciplining”  of  things  into  words.  It  is  often   said  that  there  is  a  large  gap  between  the  world  and  the  word,  writes  Latour,  but  in  the  hands   of  a  skilled  pedologist  the  gap  between  the  two  is  incredibly  small,  not  so  imposing,  entirely   navigable,  and  completely  understandable.   What  is  important  to  note  in  this  single  act  of  reference  is  that  it  creates  a  certain  type   of  movement.  In  the  example  above,  a  thing  (a  handful  of  soil)  has  been  transformed  into  a   word  (an  alphanumeric  code),  and  in  this  transformation  the  soil  has  taken  one  small  step   closer  to  becoming  a  more  widely  recognized  sign  among  the  world’s  practicing  pedologists.   The  movement  illustrated  here  is  not  necessarily  directional,  that  is,  it  is  not  a  forward   movement,  as  in  ‘progress.’  It  is  simply  a  movement  from  a  position  of  less  abstraction  to  a   position  of  more  abstraction.  Latour  calls  this  movement  from  world  to  words  or  from  things  to   137       signs,  "upstream"  movement.  In  this  upstream  movement,  much  as  in  the  translation  of  a   foreign-­‐language  film  for  an  English-­‐speaking  audience,  something  is  lost.  Or,  as  Latour  writes,   the  resulting  abstraction  is  “an  economy,  an  induction,  a  shortcut,  a  funnel.” 150  The  newly   produced  Munsell  code  doesn’t  represent  all  of  the  many  possible  qualities  of  soil  (e.g.,  color,   mass,  density,  texture,  etc.);  it  simply  represents  one  of  them  (i.e.,  color).  In  other  words,  the   transformation  from  thing  to  word  decreases  the  soil's  complexity.  However,  what  the  soil  loses   in  terms  of  its  worldly  qualities,  it  gains  in  terms  of  its  wordly  ones.  To  put  this  differently,  while   the  soil  loses  some  of  its  thing-­‐ness,  at  the  same  time  it  gains  in  terms  of  its  sign-­‐ness.  For   instance,  in  its  rather  unremarkable  transformation  from  thing  to  word  the  soil  is  now  more   mobile,  more  compatible,  more  calculable,  and  more  universal  than  before.  In  other  words,  the   transformation  of  soil  from  a  handful  (not  an  inscription)  to  an  alphanumeric  code  (an   inscription)  has  increased  the  soil's  manageability.   There  is  yet  another  movement  made  possible  in  the  routine  scientific  transformations   of  things  to  inscriptions.  Weeks  after  the  pedologists  leave  the  Brazilian  forest,  when  they  are  in   their  university  offices  or  laboratory  and  revisiting  their  field  notes,  the  presence  of  a  single   Munsell  code  in  one  of  their  field  notebooks  is  both  a  record  and  a  reminder  that  they  once   kneeled  and  held  a  very  specific  handful  Brazilian  forest  soil  in  their  hands.  A  single  Munsell   151 code,  as  Latour  writes,  is  itself  “a  guarantor,  a  record,  a  preservation,  a  footnote.”  The   collection  of  alphanumeric  Munsell  codes  in  their  notebooks  act  as  markers  or  signposts  that   allow  them  to  travel  from  words  back  to  things.  Once  again  the  gap  between  the  world  and  the                                                                                                                   150.  Latour,  Pandora’s  Hope,  34.     151.  Ibid.,  34.     138       word,  but  this  time  in  the  reverse  direction,  is  not  so  imposingly  large.  In  the  hands  of  a   meticulously  organized  pedologist,  the  field  notebook  is  a  tool  to  help  scientists  retrace  their   steps  back  to  Brazil,  and  likely  to  the  very  spot  where  they  extracted  code  “5P  5/10.”   The  direction  of  movement  described  here  is  not  a  backwards  movement,  as  in  ‘regress.’   It  is  simply  a  movement  from  a  position  of  more  abstraction  to  a  position  of  less  abstraction.   Latour  calls  this  movement  from  words  to  world  or  from  signs  to  things,  "downstream"   movement.  This  downstream  movement  from  word  to  thing  decreases  the  soil’s  manageability:   compared  to  the  coded  soil  the  handful  of  soil  is  much  more  difficult  to  discipline—it  (quite   literally)  slips  through  one’s  fingers.  In  other  words,  in  moving  from  its  coded  from  to  its   decoded  form,  the  soil  has  lost  some  of  its  previous  mobility,  compatibility,  standarizability,  and   universality.  However,  what  the  decoded  soil  loses  in  terms  of  its  wordly  qualities,  it  gains  in   terms  of  its  worldly  ones.  This  movement  from  word  to  thing  increases  the  decoded  soil's   complexity.  When  compared  to  the  coded  soil,  the  handful  of  soil  has  traits  like  color,  mass,   density,  shape,  and  texture.  Thus,  in  its  downstream  movement  from  code  (an  inscription)  to   handful  (not  an  inscription),  the  soil  has  recaptured  some  of  its  earthly  qualities.   To  summarize  one  of  the  key  characteristics  of  transformative  acts  of  reference,  we  can   say  that  a  single  act  of  reference  flows  both  upstream  and  downstream  to  create  a  "double   152 direction  of  the  movement  of  reference."  Often,  these  acts  involve  ingenious  tools—like  the   Munsell  code  booklet—which  mediates  the  transformation  of  more  matter-­‐like  substances  into   more  sign-­‐like  forms.  In  more  practical  terms,  such  tools  mediate  the  transformation  of   handfuls  of  soil  into  alphanumeric  codes.  Such  tools  help  scientists  perform  acts  in  which                                                                                                                   152.  Ibid.,  74.   139       something  more  concrete  becomes  something  more  abstract.  However,  with  every   153 transformation  of  matter  in  form  there  is  a  “dialectic  between  gain  and  loss.”  On  the  one   hand,  making  something  more  abstract  decreases  its  complexity.  On  the  other  hand,  making   something  more  abstract  increases  its  manageability.  For  Latour,  this  double  direction  of  the   movement  of  reference  and  its  accompanying  dialectic  of  loss-­‐gain  is  an  important  insight  in   trying  to  understand  how  it  is  that  scientists  gain  scientific  knowledge  in  places  such  as  forests,   fields,  and  laboratories.     Part  of  what  makes  an  act  of  reference  scientific  is  the  careful  mapping  of  the  act  itself,   for  both  the  upstream  and  downstream  movement  must  be  accounted  for  by  the  active   scientist,  as  well  as  traceable  by  other  scientists.  That  is,  some  sort  of  accounting  system  must   be  created  and  maintained  in  which  it  is  possible  to  follow  an  upstream  transformation  back   downstream.  Whereas  psychological  studies  of  science  offer  us  a  picture  of  knowledge  gain  in   which  the  manipulation  of  ideas  and  concepts  in  the  mind/brain  are  the  driving  force  of  science,   Latour’s  empirical  studies  offer  us  one  in  which  the  transformation  and  accounting  of  earthly   things  into  visible,  material  signs  matters  most.  Already  in  this  dissertation,  I  have  referred  to   the  former  sensibility  as  “logics”  and  the  later  sensibility  as  “logistics.”  In  field  and  laboratory   sciences,  notebooks  or  logs  are  one  of  the  central  gathering  points  in  which  these  accounting   systems  can  be  seen  in  a  visible,  material  form.  However,  the  system  itself  is  distributed  across   other  types  of  visible,  material  forms.  For  example,  numbered  cabinets  in  university  hallways   contain  hundreds  of  individual  field  samples  and  each  field  sample  has  alphanumeric  writing  on                                                                                                                   153.  Ibid.,  74.   140       it  that  records  such  information  as  the  sample  date,  sample  location,  sampling  conditions,   sample  number,  name  of  the  sampling  scientist/technician,  etc.   II.  Circulating  reference:  The  coupling  of  multiple  acts  of  reference  into  coherent  circuits     Before  we  go  further  there  is  at  least  one  pressing  problem  in  need  of  attention.  The   Munsell  code  “5P  5/10”  is  clearly  not  the  final-­‐form  inscription  published  by  Silva  et  al.  in  their   scientific  report  and  shown  in  Figure  4.6  (Part  C).  To  help  emphasize  this  discontinuity,  Figure   4.6  allows  readers  to  visually  compare  (A)  a  handful  of  soil,  (B)  the  Munsell  code  “5P  5/10,”  and   (C)  Silva  et  al.’s  Figure  3. 141               A.  A  handful  of  soil.       Figure  4.6.  Three  images—a  photograph,  a  phrase,  and  a  diagram—illustrating  three  stages  of  a  coherent  circuit  of  reference.  A   handful  of  soil  (A);  an  example  of  a  Munsell  code  (B);  and  Figure  3.  Coupe  du  transect  1  (Silva  et  al.  1991).  A  figure  displayed  in  a   scientific  manuscript  reporting  on  the  findings  of  an  expedition  to  region  of  Boa  Vista,  Roraima,  Amazonia  (Brazil)  (C).           142       Figure  4.6.  (cont’d)                                   B.  An  example  of  a  Munsell  code.                     143       Figure  4.6.  (cont’d)             C.  A  figure  displayed  in  a  scientific  manuscript  reporting  on  the  findings  of  an  expedition  to  region  of  Boa  Vista,  Roraima,   Amazonia  (Brazil).  Figure  11.15  (Latour  1999).  (Reprinted  with  permission  by  the  copyright  holder.)   144       When  compared  to  Figure  3,  the  simplistic  alphanumeric  code  “5P  5/10”  (Figure  4.6,   part  B)—which  resulted  from  a  single  act  of  reference  performed  on  the  more  earthly  soil   (Figure  4.6,  part  A)—does  indeed  look  like  it  still  remains  a  great  distance  from  the  diagram  that   Silva  et  al.  called  “Figure  3.  Coupe  du  transect  1”  (Figure  4.6,  part  C).  Indeed,  it  still  looks  to  be   on  the  far  side  of  a  yawning  ontological  gap  that  requires  a  giant  leap-­‐like  movement  to  cross.   While  it  is  true  that  one  way  to  traverse  sizable  gaps  is  via  giant  leaps  and  bounds,  as   daredevils  know  all  too  well,  giant  leaps  over  large  gaps  leave  much  room  for  error  and  canyon   walls  can  be  unforgiving.  Another  way  to  traverse  a  large  gap  is  to  take  it  slow,  one  small  step  at   a  time,  by  descending  down  the  steep  canyon  walls  and  traveling  along  the  valley  floor.  Here,   the  gaps  are  much  smaller  and  easier  to  navigate  without  superhuman  powers  or  experimental   rockets.  Here,  there  is  more  room  for  error.  In  this  next  section,  we  will  see  how  scientists  cross   large  gaps  between  things  and  signs  by  nesting  multiple  acts  of  reference  together  into  longer   chains  or  “circuits.”   According  to  Latour,  much  of  the  beauty,  elegance,  efficiency,  certainty,  and  truth-­‐ perpetuating  value  of  scientific  knowledge  gain  rests  not  on  solitary  acts  of  reference,  but   instead  on  the  careful  coupling  of  multiple  acts  of  reference  into  coherent  circuits.  This  coupling   is  easy  to  see  by  returning  to  the  activities  of  our  pedologists.  In  their  laboratory,  we  can  easily   imagine  our  pedologists  taking  the  Munsell  codes  assigned  to  each  of  their  individual  soil   samples  and  subjecting  them  to  yet  another  transformative  act  of  reference.  For  example,  we   can  image  them  physically  transferring  each  of  the  alphanumeric  codes  from  their  field   notebooks  onto  sticky  notes,  and  then  arranging  these  individual  notes  on  a  large  piece  of   paper  meant  to  represent  a  birds-­‐eye  view  of  the  original  study  site.  With  the  aid  of  other  signs   145       and  tools,  such  as  GPS  coordinates,  topographic  maps,  and  rulers,  they  might  begin  arranging   the  soil  codes  on  a  large,  desk-­‐sized  piece  of  paper  in  their  conference  room.  As  they  (quite   literally)  trace  the  similarities  or  tendencies  amongst  the  alphanumeric  codes  with  pens  and   pencils,  we  can  imagine  something  resembling  a  contour  map  of  the  forest  floor  taking  shape   on  their  table.   This  is  a  different  kind  of  map  of  the  forest  floor,  one  that  they  cannot  likely  create  with   a  camera  or  satellite  imaging.  This  hand  drawn  map  is  the  equivalent  of  a  pedological  strip   mine:  in  the  pedologists  actions  every  animal,  rock,  and  kilogram  of  vegetation  is  hypothetically   scoured  from  the  study  site  to  reveal  a  view  of  the  forest  soil  that  our  pedologists  will  likely   never  actually  witness  first  hand.  By  making  the  Munsell  codes  more  mobile  via  transferring   them  onto  sticky  notes,  by  placing  and  arranging  the  coded  sticky  notes  on  a  large  piece  of   paper,  by  connecting  tendencies  in  codes  with  contour  lines,  and  then  by  removing  the  codes   to  leave  only  the  contour  lines  themselves,  our  pedologists  have  created  a  coherent  circuit  of   scientific  reference.  This  careful  and  deliberate  coupling  of  at  least  two  acts  of  reference  into  a   chain  or  circuit—thus,  circulating  reference—allows  for  the  flow  of  certain  continuities  or   qualities  in  both  the  upstream  and  downstream  directions.  In  the  upstream  direction—from  the   handfuls  of  soil  towards  the  contour  map—the  pedologists  can  move  from  less  abstract  things   to  increasingly  more  abstract  signs.  This  is  how,  as  Latour  writes,  "a  text  truly  speaks  of  the   154 world."  In  the  downstream  direction—from  the  contour  map  towards  the  handfuls  of  soil— the  pedologists  can  also  move,  if  they  so  desire,  from  the  more  abstract  word  to  the  less   abstract  world.  This  is  how,  as  Latour  writes,  the  pedologist  establishes  a  "reversible  route"  that                                                                                                                   154.  Ibid,  61.   146       makes  it  possible  to  retrace  her  own  footsteps  when  needed:  "Across  the  variations  of   matters/forms,"  Latour  continues,  "scientists  forge  a  pathway." 155  Here,  we  no  longer  need   speak  about  large  gaps  separating  the  world  and  the  word.  Instead,  we  can  speak  about  the   ever-­‐present  world  and  the  ever-­‐present  word  in  a  series  of  linked  acts  of  reference.   One  important  feature  of  circulating  reference  to  take  special  note  of  is  the  strange   twist  of  fate  of  both  world  and  word,  of  both  things  and  signs.  In  the  first  act  of  reference  above,   a  less  abstract  handful  of  soil  (a  concrete  thing)  was  transformed  into  a  more  abstract  Munsell   code  “5P  5/10”  (an  abstract  sign).  In  a  later  act  of  reference  within  the  same  circuit,  however,   this  same  Munsell  code  shifted  its  own  function  from  sign  to  thing.  That  is,  the  less  abstract   Munsell  code  “5P  5/10”  (a  concrete  thing)  was  transformed  into  a  more  abstract  contour  line   (an  abstract  sign).  Thus,  in  a  coherent  circuit  of  reference  the  Munsell  code  “5P  5/10”  has  both   worldly  and  wordly  attributes  depending  on  whether  it  is  the  abstract  product  of  one   transformation  or  the  concrete  material  for  a  subsequent  one.  In  other  words,  as  soon  as  the   alphanumeric  code  “5P  5/10”  becomes  integrated  into  a  coherent  scientific  circuit  of  reference,   it  simultaneously  acts  as  both  thing  and  sign.  By  assigning  both  matter  and  form  to  the  Munsell   code  “5P  5/10”—as  well  as  to  all  of  the  other  intermediate  transformations  found  throughout  a   circuit  of  scientific  reference  for  we  must  say  exactly  the  same  thing  about  the  contour  line  for   it  too  is  both  matter  and  sign—Latour  offers  a  spirited  challenge  to  canonical  ways  of   conceptualizing  the  relationship  between  worldly  things  and  wordly  signs.  In  a  Latourian   scenography,  something  abstract  will  always  have  a  visible,  material  form  regardless  of  how  far   upstream  it  is  located  within  a  circuit.  In  other  words,  abstraction—whether  as  products  or                                                                                                                   155.  Ibid,  61.   147       processes—never  fully  disappears.  An  abstraction  never  becomes  invisible  or  immaterial.  If  it   does,  it  ceases  to  exist.   Section  C:  How  to  Speak  Latourian  about  Classroom  Figures     Now  is  the  moment  when  we  need  to  reverse  the  previous  substitution.  Because  the   plant  processes  presented  in  Figure  20  are  much  closer  to  biological  topics  taught  in  Bio101,  we   must  let  a  good  deal  of  our  attention  slip  away  from  soil,  pedologists,  Munsell  codes,  and   contour  lines.  Figure  4.7  is  meant  to  helps  readers  accomplish  this  necessary  shift  as  we  now   come  to  the  third  reading  of  Melvin  Calvin’s  diagram  of  the  “photosynthetic  carbon  cycle. 148             Figure  4.7.  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that  Melvin  Calvin  submitted  when  accepting  the  1961   Nobel  Prize  for  chemistry.  Figure  20  (Calvin  1961). 149       With  the  help  of  two  Latourian  concepts  presented  in  Section  B—acts  of  reference  and   circuits  of  reference—we  can  now  see  Calvin’s  Figure  20  as  part  of  an  active  scientific  circuit  of   reference.  Figure  20  is  a  working  object;  it  is  a  visual  display  published  in  a  scientific  manuscript;   it  is  an  inscription.  Figure  20  is  also  one  of  the  refined  products  of  multiple  cycles  of   accumulation  in  a  center  of  accumulation/calculation.  Calvin  and  his  colleagues  at  the   University  of  California,  Berkeley’s  E.O.  Lawrence  Radiation  Laboratory  worked  on  its   production  mainly  between  the  years  1949-­‐1961.  Figure  20  is  also  a  visible,  material  form  that   is  located  a  fair  distance  upstream  of  other  inscriptions  produced  by  Calvin  and  his  many   scientific  collaborators. 156  Figure  20  is  one  of  the  more  abstract  products  of  many  intersecting   circuits  of  reference.   If  we’ve  learned  anything  about  centers  of  calculation  and  scientific  circuits  of  reference,   however,  it  is  that  the  abstract  products  of  these  centers  and  circuits  can  always  be  made  even   more  abstract.  There  are  always  additional  acts  of  reference  that  can  be  performed.  There  are   always  additional  transformations  that  can  be  enacted.  In  other  words,  scientific  circuits  of   reference  are  not  closed  loops;  they  are  open-­‐ended.  To  move  farther  upstream  in  circulating   reference,  a  visible,  material  form  simply  needs  to  be  made  more  mobile,  more  stable,  more   immutable,  more  combinable,  and  more  superimposable.  In  other  words,  it  simply  needs  to  be   made  more  abstract.     Finally,  then,  we  are  in  position  to  connect—both  conceptually  and  empirically— scientific  figures  and  classroom  figures.  At  last,  we  are  in  position  to  connect  Calvin’s  Fig.  20                                                                                                                   156.  I’ve  obtained  and  examined  copies  of  most  of  the  (declassified)  scientific  manuscripts   produced  by  Calvin  and  his  colleagues  while  at  UC-­‐Berkeley  and  I  have  examples  of  other   working  objects  that  are  located  farther  downstream  than  Figure  20.   150       with  Sadava  et  al.’s  Fig.  8.13  (Part  2).  Now  deep  within  a  Latourian  scenography,  we  should  be   able  to  easily  see  Figure  8.13  as  yet  one  more  transformation,  as  yet  one  more  act  of  reference.   Figures  4.8  and  4.9  juxtapose  Calvin’s  Fig.  20  with  Sadava  et  al.’s  Fig.  8.13  so  as  to  help  aid  in   this  connective  work. 151           Figure  4.8.  The  photosynthetic  carbon  cycle.  A  figure  used  in  a  manuscript  that  Melvin  Calvin  submitted  when  accepting  the  1961   Nobel  Prize  for  chemistry.  Figure  20  (Calvin  1961).     152                   Figure  4.9.  The  Calvin  Cycle.  A  figure  shown  to  students  during  a  photosynthesis  unit  in  an   undergraduate  biology  course.  Figure  8.13  (Part  2)  (Sadava  et  al.  2007).  (Reprinted  with   permission  by  the  copyright  holder.)             153       Notice  that  the  ‘distance’  between  Fig.  20  to  Fig.  8.13  is  not  simply  an  act  of   transformation  (acts  of  transformation  are  not  enough  to  be  considered  scientific);  it  is  a   referenced  act  of  transformation.  Through  a  combination  of  the  phrase  located  in  the  middle  of   Fig.  8.13  (“CALVIN  CYCLE”),  the  alphanumeric  phrase  that  at  one  time  appeared  in  the  lower   left  hand  portion  of  the  figure  (“Life  8e,  Figure  8.13  (Part  2)”),  and  the  index  of  “Figures”   included  in  Sadava  et  al.’s  textbook,  we  can,  if  we  are  both  persistent  and  resourceful,   eventually  connect  Fig.  8.13  with  Fig.  20.     Admittedly,  these  two  figures  are  sure  to  be  separated  by  a  number  of  other   intermediary  working  objects  created  and  published  at  various  times  between  1961-­‐2007.   However,  just  as  we  saw  in  the  previous  section,  at  every  point  along  this  circuit  of  reference   we  should  expect  to  see  working  objects  that  simultaneously  act  as  matter  and  form,  thing  and   sign,  world  and  word.  And  so,  we  must  ask  ourselves:  At  any  point  in  the  existing  circuit  of   reference—which  is  organized  in  the  downstream  direction  by  Calvin’s  Fig.  20  and  in  the   upstream  direction  by  Sadava  et  al.’s  Fig.  8.13—do  the  intermediary  figures  in  between  these   working  objects  ever  lose  their  visibility  or  materiality?  Here,  we  must  recall  the  dialectic  of  loss   and  gain  always  present  in  circulating  reference.  We  must  remember  that  while  every   transformation  upstream  leads  to  a  loss  of  locality,  particularity,  materiality,  multiplicity,  and   continuity,  at  the  same  time  this  movement  results  in  gains  in  compatibility,  standardizability,   textuality,  calculability,  circulability,  and  universality. 157     When  compared  to  Calvin’s  Fig.  20,  Sadava  et  al.’s  Fig.  8.13  appears  more  highly   cleansed.  In  other  words,  through  observable—and  possibly  even  quantifiable—differences  in                                                                                                                   157.  See  Latour  1999,  Chapter  2.   154       its  use  of  color,  symbols,  formatting,  and  design,  Sadava  et  al.’s  inscription  is  more  refined  and   more  orderly.  One  of  the  gains  afforded  by  this  increased  order  is  that  Figure  8.13  is  able  to   separate  the  cyclical  process  occurring  in  green  plant  cells  into  three  equally  weighted  divisions   or  stages  and  label  them  as  follows:  “Carbon  fixation,”  “Reduction  and  sugar  production,”  and   “Regeneration  of  RuBP.”  This  same  sort  of  tripartite  division  is  not  as  clearly  visible  (if  visible  at   all)  in  Figure  20.  Indeed,  with  as  many  curved  arrows  and  chemical  substances  that  crisscross   the  middle  of  Calvin’s  inscription,  it  is  visually  difficult  to  cleanly  divide  the  overarching  cyclical   process  into  the  three  stages  so  cogently  presented  in  Figure  8.13.   However,  in  the  dialectic  of  gain  and  loss  such  orderly  gains  always  come  at  a  price:   when  compared  to  Sadava  et  al.’s  working  object,  Calvin’s  provides  its  readers  with  more   detailed  molecular  drawings  for  a  number  of  carbon-­‐based  compounds  found  within  the  Calvin   Cycle.  Whereas  Sadava  et  al.’s  working  object  displays  the  sequence  and  arrangement  of  mainly   carbon  (“C”)  and  phosphorous  (“P”)  atoms  of  the  carbon-­‐based  compounds  found  within  the   cycle,  Calvin’s  includes  not  only  the  sequence  and  arrangement  “C”  and  “P”  atoms,  but  also  of   oxygen  (“O”)  and  hydrogen  (“H”)  atoms.  Thus,  while  Fig.  8.13’s  more  abstract  form  makes  for   some  important  affordances,  at  the  same  time  this  new  form  results  in  equally  important  losses.     Despite  its  greater  degree  of  abstraction,  however,  Sadava  et  al.’s  Figure  8.13  (Part  2)   remains  both  visible  and  material  for  both  inscriptions  are  paper-­‐based.  Both  are  two-­‐ dimensional  traces  of  three-­‐dimensional  processes  or  entities  said  to  exist  in  the  chloroplasts  of   most  green  plants.  Are  they  representations  of  one  another?  Yes  and  no.  It’s  true,  Sadava  et   al.’s  inscription  re-­‐presents  some  of  the  information  found  in  Calvin’s  inscription,  but  it  does   not  re-­‐present  all  of  it.  As  mentioned  above,  there  is  a  measurable  loss  of  information  that   155       occurs  when  Calvin’s  figure  is  transformed  into  Sadava  et  al.’s  figure.  Figure  8.13  (Part  2)  is  not   an  exact  replica  of  Figure  20;  they  are  by  no  means  one  hundred  percent  mimetic.  There  may   be  some  resemblance  between  the  two  inscriptions,  but  there  is  no  complete  and  faithful  one-­‐ to-­‐one  correspondence.   Section  D:  Tracking  Scientific  Reference  in  Bio101     Here,  we  come  to  a  key  set  of  questions  in  this  dissertation.     If  Fig.  8.13  is  already  considered  to  be  a  part  of  an  active  circuit  of  scientific  reference— in  other  words,  if  it  is  already  an  inscription  in  a  circuit  located  slightly  upstream  of  Calvin’s  Fig.   20—what  happens  to  Sadava  et  al.’s  Fig.  8.13  within  the  Bio101  classroom  in  the  hands  of  the   instructors?  Is  Fig.  8.13  part  of  any  new  acts  of  reference?  In  other  words,  similar  to  the  work   accomplished  by  scientists  working  in  centers  of  accumulation/calculation,  do  the  instructors   engage  in  efforts  to  make  Fig.  8.13  even  more  mobile,  more  stable,  more  immutable,  more   combinable,  and  more  superimposable.  Do  they  endeavor  for  or  with  their  students  to  make   Fig.  8.13  even  more  abstract?   The  quick  answer  to  this  question  is:  Yes,  they  do.  The  Bio101  instructors  do  in  fact   transform  Fig.  8.13  into  other  visible,  material  forms.  In  Figure  4.10  we  can  see  what  may  be   the  furthest  upstream  visible,  material  form  used  by  the  Bio101  instructors.               156                           “Calvin  Cycle”     Figure  4.10.  “Calvin  Cycle”.  A  frequently  used  term  in  the  Bio101  classroom—both  in  spoken   and  written  forms—and  also  on  the  exams.     Once  again,  we  are  confronted  by  something  resembling  a  circuit  of  reference—which  in   this  instance  is  bounded  in  the  downstream  direction  by  Sadava  et  al.’s  Fig.  8.13  and  in  the   upstream  direction  by  a  written  phrase  commonly  used  by  the  Bio101  instructors  both  in  class   and  on  exams  (“Calvin  Cycle”).  I  encourage  readers  to  take  a  moment  and  briefly  revisit  Calvin’s   Fig.  20  for  the  explicit  purpose  of  reminding  themselves  that  this  circuit  continues  well  into  the   downstream  direction.  I  draw  reader’s  attention  to  Fig.  20  for  the  explicit  purpose  of  pointing   out  that  in  the  circuit  of  reference  we  have  constructed,  Sadava  et  al.’s  inscription   simultaneously  acts  as  matter  and  form,  thing  and  sign,  world  and  word.  When  a  product  of  the   transformation  of  Calvin’s  Fig.  20,  Sadava  et  al.’s  inscription  is  more  abstract,  more  wordy  than   Fig.  20.  However,  when  used  itself  as  the  raw  material  for  a  transformation  into  the  phrase   “Calvin  Cycle,”  Fig.  8.13  is  suddenly  more  concrete  and  worldlier  than  the  newly  produced,   more  abstract(ed)  sign.     The  remaining  two  chapters  in  my  dissertation  are  primarily  concerned  with  how  the   Bio101  instructors  transform  more  concrete  figures  such  as  Fig.  8.13  into  more  abstract  phrases   such  as  “Calvin  Cycle.”  In  particular,  I’m  interested  in  all  of  the  visible/material  intermediary   157       forms  that  the  instructors  deploy  as  they  move  between  thing-­‐y  signs  and  sign-­‐y  things.  Since  a   critical  feature  of  scientific  circuits  is  the  notion  of  reference,  I’m  also  deeply  interested  in  the   system  of  accounting  used  during  these  various  transformations:  do  the  instructors  create   accounting  systems  that  allow  their  students  to  move  fluidly  and  confidently  in  both  the   upstream  and  downstream  directions?  Finally,  I’m  interested  in  describing—in  strict  empirical   terms—the  ways  in  which  various  circuits  of  reference  created  in  the  class  overlap  and  intersect   to  create  abstract  concepts  within  the  classroom.  Among  other  affordances,  this  interest  in   abstraction  (but  also  concretion)  will  allow  me  to  revisit  abstract  conceptual  learning  theory   with  the  hope  of  rearticulating  it  in  accordance  with  a  non-­‐mental,  non-­‐psychological  horizon  of   expectations.         158       CHAPTER  5   HORIZONS  IN  ACTION         Unfortunately,  it  is  just  this  little  word,  this  slogan  of  the   enlightened—understand—that  causes  all  the  trouble.  It  is  this   word  that  brings  a  halt  to  the  movement  of  reason,  that  destroys   its  confidence  in  itself,  that  distracts  it  by  breaking  the  world  of   intelligence  in  two,  by  installing  the  division  between  the  groping   animal  and  the  learned  little  man,  between  common  sense  and   science.  From  the  moment  this  slogan  of  duality  is  pronounced,  all   the  perfecting  of  the  ways  of  making  understood,  that  great   preoccupation  of  men  of  methods  and  progressives,  is  progress   toward  stultification.   —Jacques  Rancière,  The  Ignorant   Schoolmaster       Looking  Back     In  the  first  half  of  Chapter  2,  I  documented  how  understanding  is  all  the  rage  in  the  Age   of  Reform  in  Science  Education.  And  how,  during  this  educational  era  which  began  in  the  late   1980s  and  continues  at  present,  many  individuals,  groups,  and  organizations  within  science   education  have  increasingly  promoted  a  particular  construction  of  understanding  known  as   “learning  with  understanding.”  Learning  with  understanding  is  generally  defined  in  terms  of   students  or  learners.  Those  who  learn  with  understanding  are  said  to  be  able  to  apply,  extend   or  transfer  a  knowledge  base  that  is  deep  in  content  and  rich  in  connections  to  situations   beyond  the  original  context  of  learning.  In  this  construction,  the  deep,  rich  knowledge  base  and   the  act  of  application/extension/transfer  are  both  routinely  characterized  as  mental  or   cognitive.  That  is,  both  knowing  and  doing  are  widely  reported  to  occur  in  the  minds/brains  of   159       learners.  When  executed  appropriately,  such  understanding  is  often  said  to  be  “conceptual,”   “meaningful,”  and  “enduring.”  This  particular  construction  of  learning  with  understanding  is   now  widely  acknowledged  by  many  groups  and  organizations  as  a  major  goal  of  science   teaching.  In  the  second  half  of  Chapter  2,  I  suggested  that  this  particular  mental/cognitive   construction  of  learning  with  understanding  has  strong  discursive  and  conceptual  continuities   with  what  Lemke  has  called  “conceptual  learning  theory.”  However,  I  added  a  minor   amendment  Lemke’s  work  and  used  the  term  abstract  conceptual  learning  theory  (or  ACLT)  to   reflect  and  emphasize  the  fact  that  educators  seem  to  value  abstract  concepts  above  and   beyond  all  other  types  of  concepts.     The  work  undertaken  in  Chapters  1  and  2  helped  make  at  least  three  statements   possible  about  the  construction  of  learning  with  and  teaching  for  understanding  in  the  Reform   Age:  First,  this  particular  construction  assumes  a  fundamentally  psychological  approach  to   teaching  and  learning.  Second,  it  belongs  to  the  tradition  of  mentalism.  And  third,  it  is  part  of  a   cognitive  model  of  science  education.  I’ve  suggested  that  this  particular  way  of  constructing   learning  with  and  teaching  for  understanding  aligns  it  more  closely  with  the  governing   principles  and  concepts  of  the  psychological  sciences  than  with  those  of  the  natural  sciences.   Popkewitz,  who  documents  a  similar  trajectory  in  other  educational  settings—for  example,  in   music  and  mathematics  education,  as  well  as  in  the  writing  of  educational  standards—uses  the   provocative  concept  of  “the  alchemy”  to  characterize  the  actions  and  events  by  which  the   academic  disciplines  are  transformed,  transmuted,  and/or  transmogrified  into  school  subjects.   By  extending  and  relating  the  ideas  of  Popkewitz  and  Lemke  to  the  discourse  of  learning  with   and  teaching  for  understanding,  I  tried  to  draw  critical  attention  to  what  I  feel  is  one  of  the   160       most  salient  outcomes  of  an  active  psychological  alchemy  in  Reform  Age  science  education:  To   take  a  mentalist  approach  to  entities  such  as  knowledge,  thinking,  reasoning,  and   understanding  is  to  make  a  choice  that  privileges  individuality,  secrecy,  clandestinity,   undocumentability,  and  universality  over  other  qualities.  In  order  words,  to  take  a  mentalist   approach  to  these  allies  is  to  be  selective  and  exclusive.  It  limits  our  conceptions  of  what  these   entities  can  be  to  a  culturally  and  historically  specific  set  of  values,  ethics,  assumptions,  and   beliefs.  More  often  than  not  in  the  Reform  Age,  students  from  backgrounds  outside  of  the   upper-­‐middle  class  are  more  likely  to  struggle  in  educational  moments  in  which  knowledge  and   understanding  are  defined  exclusively  as  mental  and  cognitive.  These  students  tend  not   participate  regularly  enough  in  networks  of  cultural  practices  that  promote,  develop,  and  value   psychologically  conceived  approaches  to  learning.   In  an  attempt  to  re-­‐define  entities  such  as  knowledge  and  understanding  as  something   other  than  mental  or  cognitive,  I  tried  to  disrupt  the  tenets  of  abstract  conceptual  learning   theory  in  Chapters  3  and  4  by  familiarizing  readers  with  the  anthropological  and  philosophical   work  of  Latour,  who  offers  us  vital  empirical  insight  into  how  scientists  confront  unfamiliar   phenomena.  This  disruption  was  meant  to  prepare  the  ground,  so  to  speak,  not  only  for  a   radical  revision  of  the  psychological  notions  such  as  concepts  and  abstraction,  but  also  for  the   specific  purpose  of  trying  to  make  ACLT  more  inclusive  and  less  constraining  for  teachers  and   students.  From  the  beginning,  my  contention  has  been  that  abstract  conceptual  learning  theory   doesn’t  have  to  be  so  individualized,  secretive,  clandestine,  rationalistic,  and  universalized.  This   historically  and  culturally  specific  formulation  is  not  inevitable.  It  can  be  different.  It  can  be   otherwise.  More  specifically,  it  can  be  more  inclusive,  more  empirical,  and  more  scientific.   161       In  summary,  a  problem  simultaneously  faced  by  students,  teachers,  professors,  and   researchers  can  be  distilled  as  follows:  in  the  context  of  the  Reform  Age,  understanding  has   become  a  form  of  learning  and  a  style  of  pedagogy  that  is  more  psychological  and  less  empirical.   Because  empirical  chains  of  reference  play  such  a  central  role  in  the  modern  natural  sciences,   we  might  also  say  that  understanding  has  become  a  form  of  learning  and  a  style  of  pedagogy   that  is  more  psychological  and  less  scientific.  From  certain  perspectives,  this  psychological   alliance  could  be  viewed  as  an  odd  choice  for  science  education  and  science  teacher  education.   Three  examples  might  help  illustrate  the  oddity  or  strangeness  of  this  choice.   Authenticity   For  a  good  part  of  the  past  30  years,  science  educators  have  heard  steady  calls  for   increased  authenticity  in  K-­‐16  science  education.  Although  this  term  has  at  least  three   meanings  within  science  education  discourse,  one  of  its  principle  meanings   158 communicates  the  desire  for  school  science  to  be  more  like  scientists’  science.   However,  if  authentic  disciplinary  science  undergoes  a  psychological  alchemy  on  its  way   into  the  spaces  of  schooling,  then  school  science  won’t  necessarily  be  more  like   scientists  science.  Thus,  it’s  possible  that  authenticity  boosters  could  view  the  activity  of   the  mental/cognitive  alchemy  as  problematic  to/for  their  aim  and  goals  of  making   school  science  more  like  scientists’  science.     Discipline-­‐Based  Educational  Research   Tertiary  science  educators  have  heard  recent  calls  in  their  domain  for  “Discipline-­‐Based   Educational  Research”  or  “DBER.”  One  of  DBER’s  principle  tenets  is  that  science                                                                                                                   158.  See  Buxton  2006.   162       education  reform  should  be  driven  by  educational  research  which  is  deeply  grounded  in   the  “priorities,  worldview,  knowledge,  and  practices”  found  in  disciplinary  science  and   engineering. 159  However,  if  scientific  and  engineering  research  undergoes  a   psychological  alchemy  on  their  way  into  the  spaces  of  schooling,  then  discipline-­‐based   education  research  won’t  necessarily  be  more  like  research  in  science  and  engineering.   Thus,  it’s  possible  that  DBER  boosters  could  view  of  the  activity  of  the  mental/cognitive   alchemy  as  problematic  to/for  their  aims  and  goals  of  making  educational  research   more  like  research  in  disciplinary  science  and  engineering.     Scientific  Teaching   Tertiary  science  educators  have  heard  recent  calls  in  their  domain  for  “scientific   teaching.”  One  of  the  principle  tenets  of  scientific  teaching  is  that  science  education   160 reform  should  be  approached  “with  the  same  rigor  as  science  at  its  best.”  However,   if  scientific  rigor  undergoes  a  psychological  alchemy  on  it  way  into  the  spaces  of   schooling,  then  rigor  in  the  classroom  teaching  won’t  necessarily  be  more  like  rigor  in   science.  Thus,  it’s  possible  that  scientific  teaching  boosters  could  view  the  activity  of  the   mental/cognitive  alchemy  as  problematic  to/for  their  aims  and  goals  of  making   educational  rigor  more  like  scientific  rigor.   It  follows  that  any  individuals,  groups,  or  organizations  working  within  or  outside  of   science  education  that  aspire  to  make  any  part  of  science  education  more  like  science  face  a   significant  challenge:  to  alchemize  something  authentic,  scientific,  or  disciplinary  in  accordance                                                                                                                   159.  NRC,  Discipline-­‐Based  Education  Research,  p.  9.   160.  Handelsman  et  al.,  “Scientific  Teaching,”  521.   163       with  the  governing  principles  and  concepts  of  the  psychological  rather  than  the  natural  sciences   is  not  to  create  something  which  is  more  authentic,  more  scientific,  or  more  disciplinary.  On  the   contrary,  it  is  to  create  something  that  is  decidedly  less  so.  Fortunately,  those  who  face  this   challenge  have  a  choice.  There  are  other  resources  on  which  to  base  the  alchemy  of  science   education  that  are  as  authentic,  as  disciplinary,  and  as  rigorous  as  science.   This  is  why  I  have  proposed  an  alternative  alchemy  for  learning  with  and  teaching  for   understanding.  This  new  alchemy  aligns  student  learning  and  teacher  pedagogy  with  governing   principles  and  key  concepts  from  the  natural  rather  than  the  psychological  sciences.  I  gathered   the  raw  materials  for  this  new  alchemy—that  is,  the  governing  principles  and  concepts—from   the  domain  of  Science  Studies.  Since  the  1970s,  a  diverse  and  loosely  organized  group  of   scholars  and  researchers  including  anthropologists,  sociologists,  historians,  economists,   philosophers,  and  political  scientists  (among  others),  have  turned  science  and  scientists  into   161 legitimate  objects  of  interest.  In  others  words,  they  have  studied  working  scientists  in  much   the  same  way  as  scientists  study  working  atoms,  circuits,  bacteria,  ecosystems,  and  galaxies.   Their  research—and  in  particular  the  work  of  Bruno  Latour—has  rendered  a  number  of  the   active  governing  principles  and  concepts  of  scientific  work  both  visible,  discussable,  and   available  for  use.  Some  of  these  principles  and  concepts  have  already  found  their  way  into   162 science  education  research.                                                                                                                   161.  These  scholars  have  also  turned  engineers  and  engineering  into  legitimate  objects  of   interest.   162.  The  greatest  density  of  work  in  science  education  has  been  brought  forth  by  Wolff-­‐Michael   Roth  and  his  extended  research  group.  The  work  with  the  most  relevance  to  my  research   includes  work  on  abstraction  (e.g.,  see  Pozzer  and  Roth  2003;  Roth  and  Hwang  2006);  on   inscriptions  (e.g.,  see  Roth  and  McGinn  1998;  Roth  and  Tobin  1997);  on  science  education  and   164       For  the  better  part  of  the  past  six  years  I’ve  been  working  arduously  to  try  and  align   something  that  people  within  my  field  care  deeply  about—that  is,  improving  learning  with  and   teaching  for  understanding—with  relevant  principles,  concepts,  ideas,  sensibilities,  and   methods  found  in  and  promoted  by  those  working  within  the  domain  of  Science  Studies.  Yes,   this  too  is  an  alchemical  act.  Yes,  this  too  will  lead  to  a  magical  transformation.  Yes,  this  too  will   lead  to  transmutation  and  transmogrification.  Yes,  this  too  will  lead  to  something  other  than   ‘real,’  authentic,  rigorous,  disciplinary  science.  After  all,  science  students  are  not  scientists.   However,  I  now  find  myself  in  the  exciting  and  challenging  position  to  hypothesize  that  by  re-­‐ structuring  pedagogical  practices  in  accordance  with  an  empirical  rather  than  a  mental  horizon   of  expectations,  my  sense  is  that  such  a  shift—albeit  a  dramatic  and  difficult  one—will  likely   result  in  substantial  improvements  in  students’  abilities  to  learn  with—as  well  as  teachers’   abilities  to  teach  for—deep,  rich,  conceptual,  meaningful,  and  enduring  understanding.   My  hope  is  that  others  will  see  this  alternative  alchemy,  as  I  do,  as  a  positive   contribution  to  the  field.  I  say  this  because  rather  than  subtract  the  mental/cognitive  horizon  of   expectations  from  science  education  discourse,  it  is  my  intent  to  add  an  empirical  one.  My   explication  and  communication  of  an  empirical  horizon  is  in  no  way  meant  to  deny  the   psychological  sciences  a  role  in  construction  of  learning  with  and  teaching  for  understanding.  In   fact,  once  again  I  remind  readers  that  I  do  not  care  whether  or  not  learning  with  understanding   actually  is  psychological,  mental,  and/or  cognitive.  Instead,  I  care  only  about  two  things:  First,   the  fact  that  I  am  an  active  member  of  and  participant  in  a  field  in  which  many  of  my  colleagues   and  peers  act  as  if  learning  with  understanding  is  psychological.  Second,  the  fact  that  I  am                                                                                                                                                                                                                                                                                                                                                                       Science  Technology  and  Society  (STS)  studies  (e.g.,  see  Roth  and  McGinn  1998);  and  on   alternative  approaches  to  cognition  (e.g.,  see  Roth  and  McGinn  1997).   165       persuaded  by  the  argument  that  empirical  traits  such  as  visibility,  materiality,  tangibility,   publicity,  specificity  contextuality,  locality,  and  historicality  can  play  important  and  productive   roles  in  the  goal  of  improving  students’  abilities  to  learn  with  and  teachers’  abilities  to  teach  for   understanding.     Addressing  a  Few  Unresolved  Issues     At  this  point  I  would  like  to  point  out  and  address  at  least  two  unresolved  issues  in  my   current  work.  The  first  issue  is  the  lack  of  a  more  descriptive  account  of  the  psychological   alchemy  in  action  within  the  context  of  Bio101,  and  especially  within  the  context  of  the  classes   leading  up  to  the  exam  upon  which  the  Mutant  Spinach  Question  appeared.  The  second  issue  is   the  lack  of  a  more  descriptive  account  of  the  empirical  alchemy  in  action  within  the  context  of   Bio101,  and  again,  especially  within  the  context  of  the  classes  leading  up  to  the  exam  upon   which  the  Mutant  Spinach  Question  appeared.  Without  these  two  descriptive  accounts,  readers   might  make  choices  that  they  might  not  otherwise  make.  For  example,  a  teacher  or  professor   might  have  difficulty  imagining  what  sorts  of  pedagogies  an  empirical  alchemy  might  lead  to   (and  I  wouldn’t  blame  them,  the  mind  is  not  to  entrusted  with  such  an  important  task!).   Without  this  image,  they  might  chose  the  sorts  of  pedagogies  that  psychological  alchemies   leads  to,  not  because  they  find  them  more  agreeable,  but  because  they  find  them  more  familiar.   There  is,  however,  one  significant  obstacle  standing  in  the  way  of  the  production  of  these  two   descriptive  accounts.  I  maintain  that  the  pedagogy  I  witnessed  in  Bio101  in  fall  2006  was,  at   least  for  the  most  part,  in  large  part  formed  by  a  psychological  alchemy.  In  other  words,  I   maintain  the  claim  that  the  Bio101  professors  approached  teaching  and  learning  science  as  if   they  were  primarily  mental/cognitive  tasks.  My  obstacle  arises  from  the  fact  that  I  have  no   166       example  of  the  Bio101  professors  approaching  teaching  and  learning  science  as  if  they  were   primarily  empirical  tasks.  And  so,  how  can  I  create  a  descriptive  account  of  an  empirical   alchemy  in  action  that  others  would  find  persuasive  and  useful  within  the  scope  and  sequence   of  this  dissertation?  How  can  I  bring  the  2006  versions  of  the  Bio101  professors,  the  application   moment,  and  the  Mutant  Spinach  Question  into  a  productive  relationship  with  my  alternative   (2013)  notion  of  empirical  teaching  and  empirical  learning?  In  other  words,  how  can  I  create  a   description  of  a  collection  of  actors  and  events  that  never  occupied  the  same  time  and  space?   There’s  only  one  way  I  can  think  of  to  accomplish  such  a  feat.     I  need  to  treat  the  2006  versions  of  the  Bio101  professors,  the  application  moment,  and   the  Mutant  Spinach  Question  as  if  they  were  an  example  of  an  empirical  alchemy  in  action.  To   do  this,  I’ll  need  to  employ  a  tool  or  device  which  is  capable  of  reanimating  the  teaching  and   learning  that  actually  occurred  in  fall  2006  in  accordance  with  governing  principles  and   concepts  that  are  more  scientific  and  less  psychological.  Fortunately,  I  have  just  such  a  device  in   mind.  It’s  a  simulator  (or  emulator)  and  it  recruits  and  enlists  the  empirical  principles  and   concepts  I  developed  in  close  partnership  with  Latour  in  the  previous  chapter.  I  call  this  device   the  EmSIM  3000.     With  the  help  of  Latour  and  the  EmSIM  3000  I  intend  to  resolve  the  two  previously   unresolved  issues  stated  above.  I  will  generate  descriptive  accounts.  I  will  bring  the  2006   versions  of  the  Bio101  professors,  the  application  moment,  and  the  Mutant  Spinach  Question   into  a  productive  relationship  with  my  alternative  notion  of  empirical  teaching  and  empirical   learning.  I  will  manage  to  create  a  description  of  a  cadre  of  actors  and  events  that  never   occupied  the  same  time  and  space.  Using  the  data  I  collected  in  fall  2006  as  the  basis  for  both   167       accounts,  I  will  not  only  create  an  empirical  description  of  the  psychologically-­‐informed   practices  leading  up  to  question  “52,”  but  I  will  also—with  the  help  of  the  EmSIM  3000—create   an  empirical  description  of  the  empirically-­‐informed  practices  leading  up  to  question  “52.”  To   better  facilitate  the  reader’s  ability  to  compare  and  contrast  these  two  accounts,  I  will  present   the  two  accounts  as  a  single  narrative  in  which  both  the  psychological  (or  actual)  and  empirical   (or  hypothetical)  narratives  of  the  alchemies  unfold  side-­‐by-­‐side.  One  of  my  purposes  in   juxtaposing  these  two  narratives  in  this  way  is  so  that  they  may  be  of  greater  assistance  to   those  enthusiastic  readers  (should  there  be  any  still  left  at  this  point!)  who  may  already  be   tempted  to  tinker  and  experiment  with  the  existing  mental/cognitive  alchemy  of  learning  with   and  teaching  for  understanding.   I  would  like  readers  to  consider  these  two  descriptive  accounts  as  an  attempt  to   establish  empirical  profiles  or  baselines  for  two  pedagogical  substances,  or  rather,  pedagogical   practices.  The  first  practice,  a  much  more  widely  known  and  familiar  practice  shaped  by  a   psychological  alchemy,  I  will  hereafter  refer  to  as  Pedagogia  psychologicus  (P.  psychologicus).   The  second  practice,  a  much  less  widely  known  and  familiar  practice  shaped  by  an  empirical   alchemy,  I  will  hereafter  refer  to  as  Pedagogia  empiricus  (P.  empiricus).  If  this  particular  framing   of  what  is  about  to  come  sounds  rather  scientific,  that’s  because  it  is  meant  to  sound  this  way.  I   see  the  next  section  of  this  dissertation  as  a  genuine  experiment.  We  are  about  to  put  two   actors—one  more  known  and  one  less  unknown—through  a  series  of  trials  so  as  to  assess   characteristic  such  as  their  purity,  potency,  composition,  activity,  and/or  strength  relative  to   one  another.  In  science,  such  experiments  and  trials  constitute  something  called  an  assay.  In   biology,  such  events  are  called  bioassays.  Since  my  much  work  unfolds  within  the  context  of   168       biology  education,  I  will  call  this  particular  genre  of  experimentation,  the  bioeducational  assay.   By  the  end  of  this  particular  assay,  I  hope  to  be  able  to  generate  preliminary  answers  to   important  pedagogical  questions  such  as:     ● What  new  types  of  pedagogical  practices  are  made  possible  by  an  empirical  alchemy?     ● What  can  teaching  for  understanding  look  like  when  constructed  in  accordance  with  an   empirical  horizon?     ● What  can  teachers  actually  do  in  classrooms  in  which  empirical  practices  are  enacted?     As  well  as  to  important  questions  about  learners  and  learning  such  as:     ● What  new  types  of  learning  practices  are  made  possible  by  an  empirical  alchemy?   ● What  can  learning  with  understanding  look  like  when  constructed  in  accordance  with  an   empirical  horizon?     ● What  can  students  actually  do  in  classrooms  in  which  empirical  practices  are  enacted?     Furthermore,  the  use  of  the  EmSIM  3000  should  allow  us  to  generate  a  speculative  reality  in   which  we  can  see  a  (virtual)  Mutant  Spinach  Question  posed  to  an  (imaginary)  group  of   students  within  a  (simulated)  classroom  experiencing  an  (ostensibly)  empirically-­‐infused   pedagogy.  We  can  then  use  this  simulation  to  generate  a  preliminary  answer  to  yet  another   important  question:   169       ● What  is  the  likelihood  that  an  empirical  alchemy  of  pedagogy  could  have  led  to  a  higher   percentage  of  Bio101  students  in  fall  2006  able  to  successfully  demonstrate  the  ability   to  learn  with  understanding  on  question  “52”?   163   Since  this  is  assay  is  meant  to  be  a  type  of  experiment,  I  will  follow  some  of  the   protocols  of  scientific  research.  Thus,  before  presenting  the  two  descriptive  accounts  of  P.   psychologicus  and  P.  empiricus,  I  will  first  tend  to  a  number  of  the  other  important  conventions   characteristic  of  scientific  writing.  For  example,  after  stating  research  questions  I  will  include  a   “Methods”  section,  which  will  be  immediately  followed  by  a  “Results”  section.  I’ve  moved  part   the  “Discussion”  section  to  Chapter  6  and  it  serves  not  only  as  the  concluding  section  to  the   bioeducational  assay,  but  also  as  the  concluding  section  to  the  dissertation.     Research  Question       We  are  simultaneously  pursuing  three  research  questions  in  this  inquiry:     (A)  What  are  the  empirical  characteristics  of  the  psychologically-­‐informed  pedagogical   practices  that  led  up  to  the  exam  on  which  students  were  asked  the  Mutant  Spinach   Question?  In  other  words,  what  is  the  empirical  profile  of  a  pedagogical  practice  that  we   are  calling  Pedagogia  psychologicus?   (B)  What  are  the  empirical  characteristics  of  the  empirically-­‐informed  pedagogical   practices  that  led  up  to  the  exam  on  which  students  were  asked  the  Mutant  Spinach   Question?  In  other  words,  what  is  the  empirical  profile  of  a  pedagogical  practice  that  we   are  calling  Pedagogia  empiricus?                                                                                                                   163.  As  we  will  see  later,  however,  we  never  needed  to  go  so  far  into  a  virtual,  hypothetical   reality.  We  only  needed  to  travel  to  the  Bio101  classroom  a  mere  two  days  after  the  midterm   exam.   170       (C)  What  is  the  relative  ‘purity,’  ‘composition,’  ‘activity,’  and/or  ‘potency’  of  a  lesser   known  pedagogical  practice  (P.  empiricus)  relative  to  better  known  pedagogical  practice   (P.  psychologicus)?   Because  this  inquiry  is  a  descriptive  project,  is  it  not  hypothesis-­‐driven.  However,  I   intend  to  use  the  answers  to  all  three  questions,  and  especially  research  question  (C),  to   generate  hypotheses  regarding  past,  present,  and  future  uses  of  pedagogies  informed  by  the   psychological  and  natural  sciences.  This  speculation  and  hypothesis  generation  is  included  in   Chapter  6.   Methods     Practices  of  study     This  study  assumes  the  existence  of  two  practices,  Pedagogia  psychologicus  and   Pedagogia  empiricus.  Since  it  is  an  empirical  study,  this  means  that  I  am  interested  in   everything  that  can  be  seen,  heard,  touched,  tasted  and/or  smelled.  This  also  means  that  I  am   interested  in  both  subjects  and  objects,  or  rather,  humans  and  non-­‐humans.  In  other  words,  I   am  as  interested  in  those  things  contained  within  the  hands,  backpacks,  flash  drives,  and   notebooks  of  professors  and  students  as  I  am  in  the  professors  and  students  themselves.  I  am   not,  however,  interested  in  those  things  contained  within  the  minds,  heads,  hearts,  and/or  guts   of  professors  and  students  because  I  do  not  have  adequate  empirical  access  to  the  contents  of   these  places/spaces.     Equipment     The  data  used  in  this  bioeducational  assay  takes  the  form  of  1)  digital  video  tapes   containing  recordings  of  every  fall  2006  class  meeting,  2)  digital  audio  files  containing  a  number   171       of  interviews  with  the  course  instructors,  3)  a  collection  of  notebooks  filled  with  field  notes,  4)  a   copy  of  the  course  textbook,  and  5)  three-­‐ring  binders  containing  paper  artifacts  collected  from   the  course  (e.g.,  exams,  handouts,  course  syllabi,  lesson  plans,  homework  assignments  etc.).  To   collect  this  data,  I  used  a  digital  video  camera,  a  camera  tripod,  a  handheld  digital  voice   recording,  blank  field  notebooks,  a  computer  flash  drive  (or  memory  stick),  a  laptop  computer,   and  a  number  of  empty  three-­‐ring  binders.   To  perform  the  bioeducational  assay  required  the  use  of  both  hardware  and  software.   In  terms  of  hardware,  I  used  a  digital  video  camera  and  a  laptop  computer.  I  used  the  digital   video  camera  to  upload  the  digital  videotapes  onto  the  drive  of  my  laptop  computer  for  viewing   and  analysis.  I  used  Apple’s  Quicktime  Pro  (which  includes  viewing,  editing,  and  file  converting   capabilities)  for  this  portion  of  the  data  processing/analysis. 164  A  second  use  of  the  laptop   computer  was  to  facilitate  the  transcription  of  the  digital  video  of  classroom  instruction  into   two  types  of  transcripts.  I  generated  one  set  of  transcripts  of  the  auditory  classroom  discourse.   165 To  do  this,  I  used  Apple’s  Quicktime  Pro  and  Microsoft’s  Word  2010.  I  generated  another  set   of  transcripts  of  the  visual  classroom  discourse.  To  do  this,  I  used  Apple’s  Quicktime  Pro,   Microsoft’s  Word  2010,  and  Chimoosoft’s  Capture  Me. 166  The  Capture  Me  software  is  a  screen-­‐ capture  software  that  allowed  me  to  create  still  images  of  various  moments  during  the   playback  of  the  digital  video  files.  To  archive  all  of  this  digital  content  I  relied  upon  CD-­‐R/W  and                                                                                                                   164.  Quicktime  v.7  (http://www.apple.com/quicktime/).   165.  Mircosoft  Office  (including  Microsoft  Word)  (http://office.microsoft.com/en-­‐001/).   166.  Capture  Me  v1.3  (http://www.chimoosoft.com/products/captureme/).   172       DVD-­‐R/W  disks,  internal  and  external  hard  drives,  and  cloud  computing  storage  services  such  as   167 Google  Drive.   In  addition  to  some  of  the  equipment  mentioned  above  (e.g.,  the  laptop  computer,   Capture  Me,  Word  2010),  part  of  my  construction  of  the  EmSIM  3000  required  the  use  of   Google’s  Picasa  3  software. 168  In  addition  to  image  organizing,  viewing,  and  editing  capabilities,   Picasa  3  also  has  image  sorting,  tagging,  and  tracking  capabilities.  For  example,  in  addition  to   unique  filenames,  Picasa  3  users  can  also  assign  unique  or  overlapping  keywords,  captions,  tags,   folder  names,  and  other  metadata  (including  facial  and  color  recognition).  Users  can  use  a  built-­‐ in  search  bar  feature  to  track  photos  according  to  any/all  of  this  metadata.  The  EmSIM  3000   makes  use  of  Picasa  3’s  powerful  “tags”  feature,  which  I  discuss  in  greater  detail  in  my   Procedures  (below).     Procedures     (A)  Pedagogia  psychologicus     The  purpose  of  Trial  (A)  in  the  bioeducational  assay  is  to  generate  an  empirical  profile  of   Pedagogia  psychologicus  in  classes  that  I  determined  to  have  direct  relevance  to  students’   ability  to  answer  the  Mutant  Spinach  Question  (question  “52”)  correctly.  I  determined  the   relevance  of  the  classes  with  the  help  of  interviews  with  the  professors.  When  talking  about  the   Mutant  Spinach  Question  in  the  interviews,  the  professors  named  key  topics  and  concepts  such   as  “photosynthesis,”  “Z-­‐scheme,”  “thylakoid  membranes,”  “cyclic  photophosphorylation,”   “non-­‐cyclic  photophosphorylation,”  the  “light  reactions,”  and  the  “light-­‐dependent  reactions.”                                                                                                                   167.  Google  Drive  (https://drive.google.com/).   168.  Google  Picasa  v3.9  (http://picasa.google.com/).   173       This  discursive  constellation  of  topics/concepts  allowed  me  to  narrow  the  forty-­‐five  50-­‐minute   classes  down  to  four  “lectures”:  Lectures  11  (09-­‐25-­‐2006),  12  (09-­‐27-­‐2006),  13  (09-­‐29-­‐2006),   and  14  (10-­‐02-­‐2006).     I  recorded  all  the  Bio101  lectures  by  placing  a  single  digital  video  camera  in  the  same   general  area  in  which  the  Bio101  students  sat  during  lecture.  I  did  nearly  all  of  my  filming  from   the  first  row  of  student  seating  and  to  the  (left)  side  of  a  large  auditorium.  Although  at  times  I   directed  the  camera  toward  the  instructors  and  students,  most  of  the  time  I  trained  my  camera   on  what  the  professors  were  displaying  to/for  students  on  a  large,  theater-­‐sized  projection   screen  located  at  the  front  of  the  lecture  hall.  I  made  consistent  use  of  the  camera’s  zoom   feature  to  capture  any  and  all  empirical  activities  related  to  the  many  images  and  writing  that   appeared  on  the  projection  screen.  These  were  the  videos  of  these  lectures  that  I  watched   repeatedly,  eventually  deciding  to  transform  them  into  the  two  kinds  of  transcripts.  One  set  of   transcripts  contained  a  written  record  of  the  auditory  (or  verbal)  features  of  classroom   discourse  and  the  other  set  of  transcripts  contained  a  graphical  record  of  the  visual  (or  pictorial)   features  of  classroom  discourse.  This  second  set  of  transcripts  also  contained  a  graphical  record   of  the  material  (or  tangible)  features  of  classroom  discourse,  and  this  record  was  supplemented   by  entries  contained  within  my  field  notebooks.  Here,  I  use  the  term  “classroom  discourse”  to   refer  to  and  include  all  observable  classroom  agents—human  and  non-­‐human—which  appear   169 as  though  they  have  an  active  role  in  the  goal  of  making  biology  understandable.  When   required,  I  consulted  my  field  notebooks,  the  written  transcripts  of  interviews  with  the                                                                                                                   169.  This  definition  of  the  term  discourse  is  inspired  by  Fendler’s  description  of  Foucault’s  use   of  it  (see  Fendler  2010,  16).     174       professors,  the  course  textbook,  copies  of  the  exams  given  to  me  by  the  instructors,  and  other   available  empirical  artifacts  for  the  purpose  of  clarification  and/or  attempting  to  improve  our   accuracy/precision.     The  two  kinds  of  transcripts  were  then  used  to  construct  the  narrative  account  (or   “profile”)  of  the  psychologically-­‐informed  pedagogical  practice,  Pedagogia  psychologicus,  in  the   days  leading  up  to  the  Mutant  Spinach  Question.     (B)  Pedagogia  empiricus     The  purpose  of  Trial  (B)  in  the  bioeducational  assay  is  to  create  an  empirical  profile  of   Pedagogia  empiricus  in  classes  that  I  determined  to  have  direct  relevance  to  students’  ability  to   answer  question  “52”  (the  Mutant  Spinach  Question)  correctly.  The  procedures  for  Trial  (B)   were  exactly  the  same  as  those  used  in  Trial  (A),  but  included  the  construction  and  use  of  an   empirical  simulator,  the  EmSim3000.  Recall  that  there  is  no  existing  data  set  in  which  the  same   Bio101  professors  engaged  the  same  four  hundred  students  in  pedagogical  practices  that  were   a)  aimed  at  preparing  students  to  answer  question  “52,”  and  b)  structured  in  accordance  with   an  empirical  horizon  of  expectations.  Because  of  this  unfortunate  fact,  I  determined  that  an   empirical  simulator  is  needed  to  generate  a  hypothetical,  parallel,  or  virtual  reality  in  which  we   can  see  the  Mutant  Spinach  Question  posed  to  students  within  the  (simulated)  context  of  an   empirically-­‐infused  pedagogy.   I  undertook  the  construction  of  the  empirical  simulator  in  accordance  with  governing   principles  and  concepts  taken  from  the  research,  scholarship,  and  empirical  philosophy  of   Bruno  Latour.  Although  the  official  name  of  this  simulator  is  the  Latour  EmSIM  3000,  for   convenience  I  will  use  a  shortened  version,  the  EmSIM  3000.     175       How  to  construct  the  EmSIM  3000     PHASE  1   Every  time  something  visibly  new  appeared  on  the  projection  screen  at  the  front  of  the   lecture  hall  (as  seen  in  the  videotapes),  I  used  the  Capture  Me  screen-­‐capture  software   to  record  a  still  image  of  it.  On  those  occasions  in  which  the  professors  displayed  a   single  image  for  a  substantial  period  of  time  (for  example,  a  “figure”),  I  made  multiple   screenshots  of  what  appeared  on  the  projection  screen  for  the  purpose  of  documenting   what  the  instructors  had  done  to  the  image—e.g.,  added  written  annotation—for  and   with  their  students.  On  those  occasions  in  which  the  professors  projected  animations   onto  the  screen,  again  I  took  multiple  screenshots  of  what  appeared  on  the  projection   screen  for  the  purpose  of  documenting  the  different  stages  of  the  animation  that  were   visible  to  students.  At  the  end  of  this  phase,  I  printed  reproductions  of  each  of  the  still   images  onto  individual  ‘cards’  measuring  approximately  3”x5”.  Each  card  contained  a   color  reproduction  of  the  image,  metadata  (e.g.,  Lecture  no.,  date,  Figure  no.,  etc.),  and   blank  space  for  additional  inscribing/writing.       PHASE  2   With  the  entire  collection  of  imaged  cards,  I  then  used  a  combination  of  the  original   digital  video  tapes  and  the  two  types  of  transcripts  to  “tag”  the  still  images  with  single   words  and/or  short  phrases  reflecting  certain  auditory  (or  verbal)  features  of  classroom   discourse.  For  the  most  part,  these  tags  consisted  of  scientific  (or  ‘technical’)  tags.  That   is,  the  tags  were  meant  to  reflect  the  linguistic  and/or  semiotic  content  of  biology.  The   176       tags  themselves  were  generated  by  the  words,  phrases,  and/or  sentences  spoken   and/or  written  mostly  by  the  professors,  but  occasionally  by  the  students  (e.g.,  when   asking  one  of  the  professors  a  question  in  class).  Some  examples  of  the  content  tags   generated  by  the  classroom  discourse  include  (but  are  by  no  means  limited  to):   photosynthesis,  thylakoid(s),  permeability,  permeable,  membrane(s),  light  reactions,   light-­‐dependent  reactions,  proton(s),  plant(s),  electron  donor,  ATP,  NADPH,  H+,  sugar(s),   sunlight,  oxygen,  O2,  carbon  dioxide,  CO2,  and  spinach.  By  the  end  of  this  phase,  every   still  image  displayed  to/for  students  on  the  projection  screen  during  the  four   photosynthesis  lectures  had  been  assigned  (often  multiple)  tags.  Each  still  image—but   still  in  card  or  paper  form—was  assigned  tags  that  were  determined  to  be  reflective  of   the  classroom  discourse  in  circulation  while  the  image  was  on  display  (but  also   sometime  soon  before  and/or  soon  after  an  image  was  removed  from  actual  view).       PHASE  3   Each  of  the  original  still  images  was  then  imported  into  Google’s  Picasa  3  program.  The   image  cards  were  then  used  to  guide  the  digital  tagging  of  each  still  image  in  Picasa  3   using  the  software’s  built-­‐in  tagging  feature.  The  last  still  image  I  imported  into  the   software  was  the  image  of  question  “52,”  the  Mutant  Spinach  Question.  Just  as  I  did   with  the  other  images,  I  also  tagged  this  image  with  various  content  tags  (e.g.,  “spinach,”   “mutant,”  “thylakoid  membrane,”  etc.).  At  the  end  of  this  phase,  I  had  constructed  a   searchable  database  that  I  treated  as  if  it  were  a  visible,  material  knowledge  base.  I  saw   this  knowledge  base  as  not  only  deep  (in  terms  of  the  number  of  tagged  images  present),   177       but  also  rich  (in  terms  of  searchable  connections).  In  other  words,  I  considered  this  new   visible,  material  (and  digital)  knowledge  base  to  constitute  understanding  that  could  be   considered  conceptual,  meaningful,  and  enduring,  as  well  as  applicable,  extendable,   170 and/or  transferable  to  new,  unfamiliar,  unscripted  contexts.     In  conjunction  with  the  two  kinds  of  transcripts  already  produced  for  use  in  Trial  (A),  I   then  used  the  EmSIM  3000  to  help  construct  the  narrative  account  (or  “profile”)  of  the   empirically-­‐informed  pedagogical  practice,  Pedagogia  empiricus,  in  the  days  leading  up  to  the   Mutant  Spinach  Question.   Data  Analysis     Once  the  profiles  of  P.  psychologicus  and  P.  empiricus  were  constructed,  I  subjected   them  both  to  a  mode  of  analysis  derived  from  and  heavily  informed  by  the  work  of  Latour.  P.   psychologicus  and  P.  empiricus  were  compared  and  contrasted  in  regards  to  their  ability  to   create  (or  not)  coherent,  visible,  material  “circuits  of  reference,”  a  concept  that  features   171 prominently  in  a  number  of  Latour’s  empirical  studies  of  science  in  action.  This  concept   depends  on  other  Latourian  concepts,  such  as  “acts  of  reference,”  “chains  of  reference,”   172 “translation,”  “inscription,”  and  “amplification/reduction.”  All  of  the  concepts  play  an  active   role  in  my  statements  about  the  educational  or  pedagogical  ‘purity,’  ‘potency,’  ‘composition,’                                                                                                                   170.  Functional  caveat:  this  knowledge  base  will  be  considered  ‘enduring’  for  as  long  as  my   laptop  and  external  hard  drives  remain  in  working  order,  as  well  as  for  as  long  as  Google’s   Picasa  remains  a  well-­‐supported,  functioning,  multi-­‐platform,  bug-­‐free  software  program.     171.  For  example,  see  Latour  1986;  1987;  1999.   172.  These  are  discussed  at  length  in  Chapter  4.   178       ‘activity,’  and/or  ‘strength’  of  the  lesser  known  P.  empiricus  relative  to  the  better  known  P.   psychologicus.   Results     The  results  or  findings  of  this  bioeducational  assay  are  divided  into  three  major  sections   that  reflect  the  three  main  pedagogical  practices  enacted  in  Bio101.  These  three  major   practices  are  each  named  after  the  most  visible,  material  element  present  in  the  practice.  For   example,  the  first  practice,  “Figures,”  is  so  named  because  of  the  significant  presence  of  the   figures  displayed  by  the  two  professors  to/for  their  students  during  this  practice.  Each  of  these   three  practices  is  then  divided  into  three  main  sections.  The  first  main  section  contains  a   detailed  empirical  description  of  the  pedagogical  practice.  The  second  and  third  main  sections   consist  of  two  perspectives.  The  first  perspective  develops  an  empirical  profile  of  P.   psychologicus  for  that  practice.  That  is,  it  describes  the  pedagogical  practice  when  it  is   constructed  and  executed  in  accordance  with  a  mental  horizon  of  expectations.  The  second   perspective  develops  an  empirical  profile  of  P.  empiricus  for  that  same  practice.  That  is,  it   describes  the  pedagogical  practice  when  it  is  constructed  and  executed  in  accordance  with  an   empirical  horizon  of  expectations.  The  juxtaposition  of  these  two  perspectives  within  each  of   the  three  major  pedagogical  practices  should  help  facilitate  a  comparison  of  their   characteristics  and  qualities  relative  to  one  another.                   179       Practice  1:  Figures       During  the  four-­‐day  photosynthesis  unit,  Bio101  professors  and  students  spent  the   majority  of  their  class  time  together  looking  at  and  talking  about  “figures.” 173  On  the  first  day   of  the  unit,  the  professors  displayed  ten  figures.  On  the  second,  they  displayed  twenty-­‐one   figures.  On  the  third,  they  displayed  twenty-­‐two  figures.  On  the  fourth  day,  a  day  in  which  only   half  the  period  was  devoted  to  the  topic  of  photosynthesis,  they  displayed  seven  figures.  In   total,  the  Bio101  professors  displayed  no  less  than  sixty  visible,  material  figures  to/for  students   during  the  four-­‐day  unit.  Two  of  these  sixty  figures  are  shown  in  Figure  5.1.                                                                                                                 173.  “Figures”  are  discussed  briefly  in  Chapter  3,  and  at  length  in  Chapter  4.   180           A.  A  figure  of  the  “Calvin  Cycle”  shown  to  students  on  Day  3  (Lecture  13,  09-­‐29-­‐2006).     Figure  5.1.  Photographs  of  two  figures  (A  and  C)  shown  to  undergraduate  students  by  the  course  instructors  during  the   photosynthesis  lectures.  Because  the  images  and  text  shown  in  photographs  A  and  C  may  be  difficult  to  see/read,  the  original   images  (B  and  D)  are  presented  with  the  ones  used  in  the  photosynthesis  lectures.  A  figure  of  the  “Calvin  Cycle”  shown  to  students   on  Day  3  (Lecture  13,  09-­‐29-­‐2006)  (A);  the  figure  of  the  “Calvin  Cycle”  as  it  appears  in  the  instructional  materials  (B);  a  figure  of  the   “Z-­‐scheme”  shown  to  students  on  Day  2  (Lecture  12,  09-­‐27-­‐2006)  (C);  and  the  figure  of  the  “Z-­‐scheme”  as  it  appears  in  the   instructional  materials  (D).  (Reprinted  with  permission  by  the  copyright  holder.) 181       Figure  5.1.  (cont’d)     B.  The  figure  of  the  “Calvin  Cycle”  as  it  appears  in  the  instructional  materials.       182         Figure  5.1.  (cont’d)     C.  A  figure  of  the  “Z-­‐scheme”  shown  to  students  on  Day  2  (Lecture  12,  09-­‐27-­‐2006).         183         Figure  5.1.  (cont’d)       D.  The  figure  of  the  “Z-­‐scheme”  as  it  appears  in  the  instructional  materials.     184         In  Figure  5.1(A),  we  can  see  visible  evidence  of  the  manual  addition  of  annotations  to   the  published  figure.  For  example,  we  can  see  where  certain  elements  already  inscribed  into   the  figure  are  circled  or  underlined.  These  additional  annotations  are  not  the  work  of  the   company  who  created  them;  they  are  the  work  of  the  professors.  This  activity  is  representative   of  the  type  of  visible,  material  work  that  the  Bio101  professors  do  on  a  daily  basis  to  many  of   the  figures  they  project  for  students  onto  a  large  projection  at  the  front  of  the  classroom.  In   Figure  5.1(C),  we  can  see  that  figures  are  not  always  pre-­‐printed  by  companies.  In  other  words,   some  figures  are  drawn  in  their  entirely  by  the  professors  themselves  from  scratch.  This  is  a   nearly  completed  figure  of  the  “Z-­‐scheme”  drawn  for  students  on  the  second  day  of  instruction   during  the  photosynthesis  unit.   While  the  professors  display,  annotate,  and  create  figures,  they  are  in  almost  constant   verbal  communication  with  the  students.  More  often  than  not,  they  are  speaking  to  the   students  at  the  same  time  as  they  are  annotating  and/or  drawing  the  figures.  The  professor’s   spoken  discourse  contains  many  scientific  or  technical  terms.  For  example,  while  displaying   Figure  5.1(A)  for  students,  one  of  the  Bio101  professors  spoke  no  less  than  57  content-­‐related   terms  while  annotating  it.  While  displaying  Figure  5.1(C),  one  of  the  Bio101  professors  spoke  no   less  than  88  content-­‐related  terms  while  drawing  it.  Table  5.1  (below)  contains  a  complete   manifest  of  the  terms  spoken  by  the  professors  while  they  were  annotating  and/or  drawing   them.  The  manifest  in  Table  5.1  is  not  meant  to  include  the  terms  that  are  visible  within  the   figures  themselves  in  Figure  5.1.  Nevertheless,  readers  will  likely  not  be  surprised  to  see  that   there  is  a  significant  degree  of  overlap  between  them.   185       In  the  table,  I’ve  adopted  the  use  of  the  “#”  symbol  to  help  signal  the  beginning  (and   end)  of  each  content-­‐related  term.  However,  while  functional,  this  decision  is  also  conceptual.   In  many  digital  social  networking  services  (e.g.,  Twitter,  Tumblr,  Instagram,  and  Google+),  when   the  “#”  symbol  is  added  to  a  word  or  phrase  as  its  prefix,  the  term  becomes  a  “hashtag”  which   can  then  be  used  as  a  form  of  metadata  tag.  Especially  in  digital  environments,  such  tags  can   help  facilitate  analytical  tasks  such  as  grouping,  searching,  and  identifying  trends.             186       Table  5.1.  A  table  showing  the  content  related  terms  spoken  by  the  instructors     while  two  figures  were  visible  to  students.     FIGURE         Content-­‐related  terms  used  by  the  instructors  while  the  figure  was   (Total  number  of   visible  to  students   content-­‐related  terms)           Figure  5.1(A):   Calvin  Cycle   (57)   #phosphoglycerate,  #three  phosphoglycerate,  #reduction,  #sugar   production,  #glyceraldehyde  three  phosphate,  #energy,   #reduction  reactions,  #endergonic,  #ATP  (molecules),  #NADPH,   #CO2  (molecules),  #three-­‐carbon  sugar(s),  #carbon(s),   #reaction(s),  #step(s),  #molecule(s),  #glyceraldehyde  three   phosphate  production,  #reduction  step,  #acid,  #sugar,  #high-­‐ energy  intermediates,  #light-­‐dependent  reactions,  #reduction   phase,  #glycolysis,  #phosphoenolpyruvate,  #conversion,   #pyruvate,  #polymerize(d),  #reverse,  #glycolysis  steps,  #glucose,   #calvin  cycle,  #glucose  (molecule),  #ribulose  bisphosphate,  #five-­‐ carbon  molecule,  #three-­‐carbon  RuBP(s),  #RuBP,  #starting     material,  #rearrangement,  #photosystem  I,  #cyclic  (photosystem),   #ATP  surplus,  #ATP  use,  #CO2  fixation,  #photosynthesis,  #three-­‐ carbon  photosynthesis,  #atmosphere,  #three-­‐carbon  acid,   #carbon  fixation,  #carbon  reduction,  #cell,  #chloroplast,  #plant   cell,  #exit,  #mechanism,  #carbon-­‐fixing  reactions,  #light-­‐ independent  reactions                                       187       Table  5.1  (cont’d)               Figure  5.1(C):   Z-­‐Scheme   #photosynthesis,  #light  reactions,  #Z-­‐scheme,  #(energy)  scale,   #free  energy,  #axis,  #chlorophyll  (molecules),  #reaction  center(s),   #chlorophyll  groups,  #cooperation,  #photon  ‘trapping’,  #photon,   #photon  absorption,  #(light)  energy  absorption,  #(large)   molecules,  #energy  level,  #electron  shell(s),  #excited  chlorophyll,   #electron  ‘bumping’,  #energy  state,  #electron,  #energized   chlorophyll,  #excited  electron(s),  #electron  transfer,  #electron   acceptor,  #plastoquinone,  #missing  electron(s),  #electron   ‘getting’,  #oxidized  chlorophyll,  #electron  loss,  #oxidizing  agent,   #water,  #ground  state,  #water  ‘taking’,  #H2O,  #electron  stripping,   (88)   #oxygen  ions,  #hydrogen  ions,  #(molecular)  oxygen,  #O2,  #water   ‘splitting,’  #breathing,  #origin,  #Earth,  #atmosphere,  #plants,     #ancient  Earth,  #respiration,  #high-­‐energy  electron(s),  #NADH,   #process,  #electron  transport  chain,  #energy  ‘lowering’,  #proton   gradient,  #proton  ‘pumping,’  #membrane,  #concentration   (gradient),  #battery,  #ATP  synthase,  #ATP  production,  #electron   passing,  #cytochromes,  #plastocyanin,  #hydrogen  ion  ‘pumping’,   #hydrogen  ion  ‘building’,  #photosystem  (I  &  II),  #photo   excitement,  #enzyme,  #NADP  reductase,  #electron  ‘adding’,   #NADP+,  #NADPH  production,  #phosphate  group,  #NAD,  #NADP,   #electron  ‘trapping’,  #hydrogen  ion  gradient,  #ATP  synthesis     At  the  end  of  each  of  the  four  photosynthesis  lectures,  both  the  professors  and  students   place  all  of  the  figures  they  collected,  annotated,  and/or  created  in  class  into  various  folders,   books,  binders,  shoulder  bags,  and  backpacks.  They  do  not  leave  them  behind.  These  items  are   taken  with  them  as  they  leave  the  lecture  hall.     Perspective  1A  -­‐  P.  psychologicus     Recall  that  in  P.  psychologicus,  learning  with  understanding  is  treated  as  if  it  were  a   mental  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  mentally  apply,   extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning.  What  follows  is  an  empirical  profile  of  how  professors  teach  photosynthesis  for   understanding  when  learning  photosynthesis  for  understanding  is  construed  as  mental.   188       When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  figures  as  one  of  the  primary  pedagogical  devices  to  help  students  develop  a  mental   knowledge  base.  Structurally,  the  figures  displayed  to/for  students  mainly  consist  of  various   visible,  material  symbolic  (or  semiotic)  linguistic  elements—for  example,  words,  numbers,   arrows,  geometric  figures,  and  other  symbolic  elements.  During  class,  the  professors  often  add   additional  visible,  material  linguistic  elements  to  them—for  example,  circles,  lines,  arrows,  and   more  words.  The  figures  on  display  are  constantly  supplemented  by  spoken  or  verbal  linguistic   elements.  Compared  to  the  symbolic  elements  of  the  figures,  these  verbal  elements  are  much   less  visible  and  much  less  material.  Although  the  professors  transform  some  of  these  verbal   elements  into  a  symbolic  form  as  they  annotate  the  figures,  they  do  not  transform  all  of  them.   Those  students  who  decide  to  “take  notes”  also  do  this  transformational  work.  However,  the   sheer  number  of  verbal  elements  spoken  during  the  display  of  a  single  figure  ensures  that  very   few  of  the  Bio101  students  could  ever  hope  to  copy  all  of  these  elements  down  onto  paper. 174   The  coherency  feature  of  the  knowledge  base  is  addressed  in  part  by  the  presentation   of  the  figures  in  a  particular  order  or  sequence,  but  it  is  also  addressed  by  the  presentation  of   the  verbal  element  in  a  particular  order  or  sequence  (and  also  with  changes  in  the  use  of  the   voice).  One  of  the  most  common  strategies  used  by  the  Bio101  professors  to  promote  the   coherency  of  the  knowledge  base  is  to  proceed  from  the  ‘whole’  of  a  concept  to  its  constituent   ‘parts.’  For  example,  the  overarching  concept  of  “photosynthesis”  is  broken  up  into  two  parts                                                                                                                   174.  Occasionally,  some  students  can  be  seen  putting  tape  recording  devices  on  their  desks   during  class.  Some  students,  then,  have  devised  a  way  of  capturing  a  greater  percentage  of  the   verbal  elements.  Exactly  what  they  do  with  the  digital  forms  of  these  elements  once  they  leave   the  classroom  I  do  not  know.   189       or  “reactions.”  These  two  reactions  are  then  broken  up  into  yet  other  parts.  For  example,  the   “light  independent  reactions”  are  divided  into  “phases,”  “stages”  and/or  “steps.”     In  P.  psychologicus,  the  figures  on  display  are  treated  as  if  they  were  the  visible  shadows  or   projections  of  the  Idea  or  Concept  of  Photosynthesis. 175  In  P.  psychologicus,  The  Concept  of   Photosynthesis  (or  Photosynthesis)  is  treated  in  class  as  if  it  was  always  already  an  abstract   reality  in  the  world  and,  the  professors  hope,  soon  to  be  an  abstract  reality  within  students’   minds/brains.  The  work  done  by  professors  and  students  in  class  with  figures  are  pedagogical   practices  designed  to  help  students  develop  the  abstract  Concept  of  Photosynthesis  in  their   minds.  To  do  this,  the  professors  rely  on  their  students’  ability  to  generalize  from  the  different   instances  and  aspects  of  photosynthesis  shown  in  the  figures.  In  these  figures,  students  are   supposed  to  ‘see’  the  conceptual  unity  of  the  abstract  Concepts  of  Photosynthesis  across  the   176 use  of  the  many  figures  presented  during  the  four-­‐day  unit.  The  professors’  spoken  words   are  meant  to  help  facilitate  this  particular  way  of  ‘seeing’  (seeing-­‐as-­‐generalizing,  seeing-­‐as-­‐ abstracting).  By  the  end  of  the  photosynthesis  unit,  the  professors  expect  their  students  to  have   assembled  the  abstract  Concept  of  Photosynthesis  in  their  minds.  Furthermore,  they  expect   their  students  to  be  able  to  ‘see’  and  recognize  those  instances  outside  of  their  minds  in  which   the  corresponding  abstract  Concept  of  Photosynthesis  is  present.  In  P.  psychologicus,  the   transfer  of  learning  is  seen  as  the  ability  of  students  to  ‘leap’  to  situations  in  which  abstract   Ideas  or  Concepts  are  always  already  present.                                                                                                                     175.  This  helps  explain  why  professors  often  refer  to  figures  as  “visual  representations.”  The   visual,  material  figures  are  meant  to  re-­‐present  what  is  seen  as  an  original  or  authentic   presentation  of  an  abstract  Idea  or  Concept.   176.  This  helps  explain  why  professors  often  refer  to  figures  as  “visual  aides.”  The  visual,   material  figures  are  meant  to  help  students  develop  abstract  Ideas  or  Concepts.   190       During  the  four  days  in  which  the  Bio101  professors  taught  photosynthesis  for  understanding,   they  used  figures  so  that  their  students  might  develop  the  mental  forms  of  certain  Concepts,   which  would  allow  them  to  ‘see’  the  presence  of  these  same  abstract  Concepts  within  or   behind  phenomena  as  strange  and  unfamiliar  as  a  “mutant  strain  of  spinach.”  The  professors   acknowledge  that  seeing,  hearing  about,  and  writing  down  (or  on)  the  figures  used  in  class  will   not  be  enough  to  develop  the  abstract  Concepts  they  require  for  the  exam.  This  is  why  the   professors  encourage—and  sometimes  require—students  to  engage  in  other  Concept-­‐ developing  activities.  For  example,  among  other  actions,  students  are  told  to  “read  the   textbook  before  class,”  “do  the  homework  problems,”  “take  notes  during  class,”  “take  notes   outside  of  class,”  “recopy  notes  outside  of  class,”  “reorganize  notes  outside  of  class,  “make   flash  cards,”  “write  down  definitions,”  “form  a  study  group,”  and  “review  the  material   presented  in  lecture.  After  a  certain  amount  of  practice  and  repetition,  it’s  postulated  that  the   students  will  ‘get’  the  Concepts  at  abstract  level  that  they  need.  All  of  these  means  are  directed   towards  a  particular  end:  the  complete  internalization  of  a  coherent  knowledge  base  which  can   be  mentally  extrapolated  and  applied  to  new,  different  contexts.     Perspective  1B  -­‐  P.  empiricus     Recall  that  in  P.  empiricus,  learning  with  understanding  is  treated  as  if  it  were  an   empirical  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  empirically   apply,  extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original   context  of  learning.  What  follows  is  a  virtual,  simulated,  and  empirical  profile  of  how  professors   teach  photosynthesis  for  understanding  when  learning  photosynthesis  for  understanding  is   construed  as  empirical.   191       When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  figures  as  one  of  the  primary  pedagogical  devices  to  help  students  develop  an   empirical  knowledge  base.  In  particular,  they  exploit  some  of  the  structural  features  contained   within  them.  First,  they  ask  their  students  to  pay  close  attention  to  the  visible,  material   symbolic  (or  semiotic)  linguistic  elements  within  the  figures  (words,  numbers,  arrows,   geometric  figures,  etc.).  The  instructors  tell  the  students  to  consider  putting  the  words  present   in  the  figures  into  a  basic  table  with  empty  rows  and  columns.  They  recommend  that  students   think  of  these  content-­‐related  terms  as  “hashtagged”  terms  (just  like  the  ones  used  on  Twitter).   They  tell  students  that  these  tagged  terms  might  be  useful  when  doing  the  homework   assignments  or  answering  clicker  questions  in  class.  By  suggesting  that  students  begin  to  find   ways  to  ‘tag’  both  the  written  and  spoken  content-­‐related  terms,  the  professors  are  helping   students  develop  the  notion  of  a  connected  and  coherent  knowledge  base.  During  class,  the   professors  often  add  additional  visible,  material  linguistic  elements  to  the  figures—for  example,   circles,  lines,  arrows,  and  more  words.  The  instructors  tell  the  students  to  pay  close  attention  to   the  content-­‐related  terms  in  the  figures  that  they’ve  underlined,  circled,  and/or  otherwise   emphasized  during  lecture.  They  encourage  their  students  to  then  consider  highlighting  these   same  content-­‐related  terms  to  their  tables  to  indicate  a  certain  density  of  emphasis/use.     The  Bio101  professors  are  constantly  supplementing  the  displayed  figures  with  spoken   or  verbal  linguistic  elements.  The  professors  know  that  these  verbal  elements  are  much  less   visible  and  much  less  material  when  compared  to  the  symbolic  elements  in  the  figures.  They   know  that  many  of  these  verbal  content-­‐related  terms  will  never  make  their  way  onto  students’   papers  in  a  written  form  unless  they  find  a  way  to  help  facilitate  this  process.  They  do  this  in   192       two  different  ways:  First,  they  record  their  lectures  and  make  the  recordings  available  to  their   students  on  a  course  website.  Students  can  listen  to  the  lecture  for  the  purpose  of  going  back   to  the  figures  and  creating  another  set  of  content-­‐related  terms  to  add  to  their  (now   expanding)  tables.  Second,  while  the  professors  speak  about  a  particular  figure,  one  of  the   teaching  assistants  keeps  a  record  of  the  content-­‐related  terms  they’ve  used.  They  then  make   these  lists  available  through  the  course  website.  In  this  way,  the  Bio101  professors  and  their   assistants  help  keep  their  students  from  becoming  overwhelmed  by  the  sheer  volume  of  verbal   elements  spoken  during  the  display  of  the  figures.  For  their  part,  the  students  begin  to  see  the   knowledge  base  growing  before  their  very  eyes.  They  can  touch  it.  They  can  grasp  it.  They  begin   to  see  patterns  and  trends.  Some  even  find  ways  to  begin  transforming  the  table  into   something  different.  As  the  lectures  begin  to  pile  up,  however,  the  organization  and  coherence   of  the  knowledge  base  becomes  more  difficult.  New  strategies  of  organization  must  be  adopted.   New  transformations  of  the  knowledge  base  must  be  performed.   In  P.  empiricus,  the  figures  on  display  are  not  treated  as  if  they  were  the  visible  shadows   or  projections  of  the  Idea  or  Concept  of  Photosynthesis.  The  Concept  of  Photosynthesis  (or   Photosynthesis)  is  not  treated  as  if  it  were  always  already  an  abstract  reality  in  the  world  or  an   abstract  reality  within  students’  minds/brains.  The  work  done  by  professors  and  students  in   class  with  figures  are  pedagogical  practices  designed  to  help  students  develop  a  more  concrete   (i.e.,  visible,  material)  Concept  of  Photosynthesis  outside  of  their  minds.  To  do  this,  the   professors  encourage  their  students  to  ‘tag’  a  number  of  linguistic  features  of  the  different   instances  and  aspects  of  photosynthesis  shown  in  the  figures.  From  these  figures,  students  are   supposed  to  physically  assemble  and  align  conceptual  unity  by  performing  a  variety  of  carefully   193       linked  visible,  material  transformations.  These  actions  render—in  visible  and  material  forms—a   concrete  Concept  of  Photosynthesis  across  the  use  of  the  many  figures  presented  during  the   four-­‐day  unit.  The  professors’  insistence  that  students  learn  how  to  tag  content-­‐related  terms  is   meant  to  help  facilitate  a  particular  way  of  ‘seeing’  (seeing-­‐as-­‐tagging,  seeing-­‐as-­‐aligning,   seeing-­‐as-­‐arranging).  By  the  end  of  the  photosynthesis  unit,  the  professors  expect  their   students  to  have  assembled  a  concrete  Concept  of  Photosynthesis  outside  of  their  minds.   Furthermore,  they  don’t  expect  their  students  to  be  able  to  automatically  ‘see’  and  recognize   those  instances  outside  of  their  minds  in  which  other  say  a  corresponding  abstract  Concept  of   Photosynthesis  is  present.  In  P.  empiricus,  the  transfer  of  learning  is  seen  as  the  ability  of   students  to  construct  or  assemble  visible,  material  bridges  to  situations  those  where  others   have  said  abstract  Ideas  or  Concepts  exist.   Practice  2:  Clicker  Questions       Once  or  twice  each  class  period,  the  professors  display  something  other  than  a  figure   like  the  ones  shown  in  Figure  5.1.  On  these  occasions,  the  students  are  shown  a  multiple-­‐choice   question  on  the  large  projection  screen  at  the  front  of  the  lecture  hall.  These  questions  almost   never  contain  any  of  the  figures  that  so  often  precede  and  follow  them.  Most  of  the  time,  the   professors  display  the  questions  and  choose  to  read  the  stem  question  and  the  4-­‐5  answer   choices  out  loud.  A  wireless  microphone  worn  by  the  professors  helps  them  project  their  voice   with  ease  throughout  the  large  lecture  hall.  Typically,  students  are  then  encouraged  to  talk  to   one  another  (“discuss  it  with  your  neighbor”)  for  a  minute  or  so.  At  the  end  of  the  discussion   period,  one  of  the  professors  or  a  teaching  assistant  activates  a  software  program  on  a   computer  located  at  the  front  of  the  classroom.  The  computer  is  connected  to  a  radio   194       frequency  (Rf)  receiver  through  one  of  its  USB  ports.  This  receiver  allows  the  Bio101  students  to   send  the  professors  their  answers  to  the  multiple-­‐choice  question  displayed  on  the  projection   screen.  They  do  this  via  the  use  of  small,  handheld  Rf  transmitting  units  which  these  professors   and  student  call  “clickers.”  Students  are  given  a  predetermined  amount  of  time  in  which  to   answer  these  questions  (usually  two  minutes).  According  to  its  default  setting,  the  clicker   software  program  places  a  small  timer  in  the  lower  right  corner  of  the  question  on  the  screen.   The  instructors  place  few  limitations  on  students’  actions  during  this  brief  window  of  time.  They   can  speak  to  each  other  as  much  or  as  little  as  they  choose  (which  many  of  them,  especially   those  setting  within  the  first  ten  or  so  rows,  often  do).  They  can  also  use  any  of  the  items   typically  found  in  front  of  them,  e.g.,  their  textbooks,  handouts,  notes,  and  figures.  Examples  of   two  of  these  clicker  questions  are  shown  in  Figure  5.2. 195                 Figure  5.2.  (At  left):  A  clicker  question  shown  to  students  on  Day  2  of  the  photosynthesis  unit  (Lecture  12,  09-­‐27-­‐2006).  (At  right):  A   clicker  question  shown  to  students  on  Day  3  of  the  photosynthesis  unit  (Lecture  13,  09-­‐29-­‐2006).  The  full  text  of  the  clicker  question   at  left  reads  as  follows:  “If  H2O  labeled  with  18O  is  added  to  a  suspension  of  photosynthesizing  chloroplasts,  which  compound  will   first  become  labeled  with  18O?  A.  ATP    B.  NADPH    C.  O2    D.  3PG.”  The  full  text  of  the  clicker  question  at  right  reads  as  follows:  “The   energy  derived  from  the  “light  dependent”  reactions  is  used  to:  A.  drive  endergonic  reactions  in  the  cytoplasm    B.  fix  inorganic  C  into   organic  molecules    C.  polymerize  CO2  and  H2O  into  glucose    D.  covert  NADPH  into  ATP  using  a  proton  gradient.”  The  bargraphs  seen   in  the  corners  of  the  two  figures  contain  information  that  is  not  relevant  to  my  analysis. 196           In  both  of  the  images  included  in  Figure  5.2,  we  can  see  one  other  important  empirical   feature  of  the  clicker  questions.  We  can  see  that  there  are  a  number  of  the  content-­‐related   terms  present  within  the  stem  portions  of  the  (two)  questions,  as  well  as  in  their  (eight)  answer   choices.  In  this  way,  we  can  see    some  visual,  material  continuity  between  the  clicker  questions   and  the  figures:  they  both  contain  a  number  of  content-­‐related  terms  that  take  written  forms   (e.g.,  words,  symbols,  numbers,  geometric  figures).     Just  as  they  did  when  speaking  about  the  figures  they  were  busy  annotating  and   creating,  the  two  professors  also  routinely  spoke  to  students  (as  well  as  to  each  other)  while   displaying  the  clicker  questions  on  the  projection  screen.  Here,  then,  we  see  another  continuity   between  the  clicker  questions  and  the  figures:  they  both  involve  a  number  of  content-­‐related   terms  that  take  verbal  or  auditory  forms.  Table  5.2  (below)  contains  a  complete  manifest  of  the   written  and  verbal  content-­‐related  terms  in  circulation  during  the  use  of  each  of  the  two  clicker   questions.  Once  again,  I’ve  used  the  hashtag  format  so  as  to  allow  readers  the  opportunity— should  they  wish  to  do  so—to  take  notice  any  similarities  in  the  use  content-­‐related  terms   between  the  manifests  seen  in  Tables  5.1  and  5.2.       197       Table  5.2.  A  table  showing  the  content  related  terms  spoken  by  the  instructors     while  two  clicker  questions  and  their  answers  were  visible  to  students.     FIGURE         Content-­‐related  terms  used  in  the  question  and  by  the  instructors   (Total  number  of   while  the  clicker  question  was  visible  to  students   content-­‐related  terms)     Written  terms:  9       18   #H2O,  # O,  #suspension,  #photosynthesizing  chloroplasts,   Figure  5.2  (at  left)   #compound,  #ATP,  #NADPH,  #O2,  #3PG     Day  2  Clicker  Question     Spoken  terms:  4     #water,  #heavy  water,  #isotope,  and  #sugar       (13)                 Figure  5.1  (at  right)   Day  3  Clicker  Question   (38)   Written  terms:  13     #energy,  #light-­‐dependent  reactions,  #endergonic   reactions,  #cytoplasm,  #inorganic  (carbon),  #fix(ing),   #organic  molecules,  #CO2  polymerization,  #H2O,  #glucose,   #NADPH  conversion,  #ATP,  #proton  gradient       Spoken  terms:  25     #chloroplast(s),  #organelle(s),  #ATP  production,     #mitochondria,  #ATP  export,  #cellular  respiration,   #cytoplasm,  #transport  system,  #plant  cell(s),  #work,   #photosynthesis,  #formula,  #CO2,  #C6H12O6,  #carbon   dioxide,  #water,  #glucose,  #carbon,  #atmosphere,   #inorganic,  #organic,  #energy,  #second  phase  of   photosynthesis,  #sugar  production,  #reactions       198       Unlike  many  of  the  figures,  the  course  textbook  does  not  contain  any  of  the  clicker   questions  used  by  the  professors.  This  is  because  the  professors  either  construct  them   themselves  or  else  they  get  from  other  colleagues.  This  makes  them  different  from  the  pre-­‐ produced  figures,  but  similar  to  the  figures  the  professors  create  from  scratch.  That  is,  if   students  want  to  take  a  visible,  material  copy  of  a  clicker  question  with  them  away  from  class,   they  must  either  write  it  down  in  their  notebooks  by  hand  or  take  a  photograph  of  it  with  a   digital  device  (e.g.,  an  iPad®  or  a  smartphone).  Many  of  the  students  I  observed  did  exactly  this   and  thus  found  a  way  to  take  visible,  material  copies  of  the  clicker  questions  away  from  class   with  them. 177  At  the  end  of  each  of  the  four  photosynthesis  lectures,  both  the  professors  and   students  place  all  of  their  materials—including  those  clicker  questions  they’ve  acquired—into   various  folders,  books,  binders,  shoulder  bags,  and  backpacks.  They  do  not  leave  them  behind.   These  items  are  taken  with  them  as  they  leave  the  lecture  hall.     Perspective  2A  -­‐  P.  psychologicus     Recall  that  in  P.  psychologicus,  learning  with  understanding  is  treated  as  if  it  were  a   mental  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  mentally  apply,   extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning.  What  follows  is  an  empirical  profile  of  how  professors  teach  photosynthesis  for   understanding  when  learning  photosynthesis  for  understanding  is  construed  as  mental.                                                                                                                   177.  In  fall  2006,  the  Bio101  instructors  also  often  made  their  Microsoft  PowerPoint   presentations  available  to  students  either  before  or  soon  after  each  class.  The  slides  of  these   presentations  almost  always  contained  the  clicker  questions,  and  so  this  constituted  yet   another  way  for  students  to  acquire  visible,  material  copies  of  them.   199       When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  clicker  questions  as  one  of  their  pedagogical  devices.  They  use  them  for  at  least  two   purposes.  First,  they  use  them  to  help  students  continue  to  develop  a  coherent  mental   knowledge  base.  In  other  words,  the  professors  see  the  clicker  questions  as  yet  another  useful   way  of  helping  students  develop  the  abstract  Concept  of  Photosynthesis.  Second,  they  use   them  to  determine  for  themselves  the  degree  to  which  their  students  have—at  that  moment— developed  some  of  the  foundations  of  a  coherent  knowledge  base.  In  the  professors’  own   words,  they  use  the  clicker  questions  as  a  way  of  “checking  for  understanding.”  Many  of  the   clicker  questions  check  for  understanding  by  posing  questions  that  are  similar  to  the  context  of   instruction.  That  is,  in  these  questions  there  tends  to  be  much  overlap  in  the  content-­‐related   words  used  in  the  text  of  the  clicker  question  and  those  used  in  the  series  of  figures  immediate   preceding  its  appearance.  This  is  not  always  the  case,  however,  as  sometimes  the  professors   use  clicker  questions  that  are  different  from  the  context  of  instruction.  These  clicker  questions   usually  have  a  different  linguistic  relationship  with  the  figures  that  preceded  them.  That  is,  in   these  questions  there  tends  to  be  less  overlap  in  the  content-­‐related  words  used  in  the  text  of   the  clicker  question  and  those  used  in  the  series  of  figures  immediate  preceding  its  appearance.   Thus,  while  the  professors  use  some  clicker  questions  to  determine  the  degree  to  which   students  have—at  that  moment—begun  to  develop  coherent  mental  knowledge  bases,  they   use  others  to  determine  the  degree  to  which  students’  with  knowledge  bases  can—at  that   moment—mentally  extrapolate  them  to  contexts  with  differing  degrees  of  contextual   178 familiarity.                                                                                                                     178.  Because  the  students  can  see  how  they  did  on  the  clicker  questions  almost   200       Structurally,  the  clicker  questions  displayed  to/for  students  are  similar  to  figures  in  the   sense  that  they  consist  of  symbolic  (or  semiotic)  linguistic  elements.  Unlike  figures,  however,   which  almost  always  contain  a  greater  diversity  of  elements,  the  clicker  questions  mostly   contain  only  words  (and  occasionally  numbers).  The  clicker  questions  almost  never  contain   figures  in  them.  One  of  the  reasons  for  this  is  because  some  of  the  clicker  questions  are  used  to   see  what—if  any—conceptual  features  of  the  figures  preceding  the  clicker  questions  students   have  successfully  managed  to  abstract  to  their  minds/brains.  The  professors  teach  as  though   certain  key  words  and  phrases  within  the  text  of  the  clicker  questions  can  trigger  or  activate  the   use  of  the  abstract  Concept  of  Photosynthesis.  When  students  do  this  successfully,  some   science  educators  say  that  the  students  have  managed  to  structure  their  mental  knowledge   179 base  in  meaningful  or  useful  ways.  This  is  one  of  the  ways  that  the  Bio101  professors  and   others  speak  to  the  coherence  feature  of  the  knowledge  base.   As  they  did  with  figures,  the  professors  also  acknowledge  that  reading,  answering,   talking  about,  and  writing  down  the  clicker  questions  used  in  class  is  not  sufficient  practice  for   adequately  internalizing  the  most  important  aspects  of  them.  Again,  this  is  why  the  professors   encourage  their  students—but  sometimes  requires  them—to  engage  in  a  number  of  different   learning  activities.  All  of  them,  however,  are  directed  towards  a  particular  end:  the  complete   internalization  of  a  coherent  knowledge  base  which  can  be  mentally  extrapolated  and  applied   to  new,  different  contexts.                                                                                                                                                                                                                                                                                                                                                                       instantaneously,  I  should  add  that  these  questions  allow  for  students  to  determine  for   themselves  the  degree  to  which  they  have,  at  that  moment,  begun  to  develop  a  coherent   mental  knowledge  base  that  can  be  mentally  extrapolated  to  contexts  with  varying  degrees  of   contextual  familiarity.   179.  This  seems  to  me  the  main  idea  behind  mental  or  cognitive  “frameworks.”     201       Perspective  2B  -­‐  P.  empiricus     Recall  that  in  P.  empiricus,  learning  with  understanding  is  treated  as  if  it  were  an   empirical  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  empirically   apply,  extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original   context  of  learning.  What  follows  is  a  virtual,  simulated,  and  empirical  profile  of  how  professors   teach  photosynthesis  for  understanding  when  learning  photosynthesis  for  understanding  is   construed  as  empirical.   When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  clicker  questions  as  one  of  their  pedagogical  devices.  They  use  them  for  at  least  two   purposes.  First,  to  continue  helping  students  develop  a  coherent  empirical  knowledge  base.  In   other  words,  the  professors  see  the  clicker  questions  as  yet  another  useful  way  of  helping   students  develop  the  concrete  Concept  of  Photosynthesis  (or  Photosynthesis).  Second,  to  begin   to  determine  the  degree  to  which  their  students  have—at  that  moment—developed  the   foundations  of  a  coherent  knowledge  base.  In  the  professors’  own  words,  they  use  the  clicker   questions  as  a  way  of  “checking  for  understanding.”  Just  as  they  did  with  students  when   showing  them  figures,  the  Bio101  professors  ask  the  students  to  tag  the  concept-­‐related  terms   seen  in  the  text  of  the  clicker  questions.  Right  there  in  the  lecture  hall,  students  put  these  terms   into  a  table  with  empty  rows  and  columns.  Next  to  this  new  table,  they  have  the  one  they’ve   created  for  keeping  track  of  the  content-­‐related  terms  used  in  the  figures.  Placed  side-­‐by-­‐side   on  the  tops  of  their  desks,  students  begin  noticing  linguistic  continuities  between  the  figures   and  the  clicker  questions.  By  suggesting  that  students  begin  to  find  ways  to  tag  and  compare   202       the  content-­‐related  terms  in  both  the  figures  and  the  clicker  questions,  the  professors  are   helping  students  develop  the  notion  of  a  connected  and  coherent  knowledge  base.     Many  of  the  clicker  questions  used  in  Bio101  check  for  understanding  by  posing   conditions  that  are  very  similar  to  the  context  of  instruction.  The  professors  work  hard  to  show   their  students  how  to  see  and  measure  this  feature  in  terms  of  amount  of  overlap  present  in   the  use  of  content-­‐related  terms.  They  do  the  same  for  and  with  their  students  with  clicker   questions  that  are  very  different  from  the  context  of  instruction.  These  clicker  questions  usually   have  a  different  type  of  linguistic  relationship  with  the  figures  that  preceded  them.  That  is,   there  is  less  overlap  present  between  the  content-­‐related  words  seen  in  the  clicker  question   and  those  seen  and/or  spoken  in  the  series  of  figures  immediate  preceding  the  it.  In  this  way,   students  learn  how  to  empirically  extrapolate  to  contexts  with  differing  degrees  of  contextual   familiarity.  Once  at  home,  students  begin  to  add  layers  to  the  tagging  techniques.  They  begin  to   create  families  of  related  terms.  To  these  families  they  add  additional  diagrams  from  their   textbooks,  definitions  of  unfamiliar  terms,  and  simplified  drawings  of  some  of  the  figures   presented  in  class.  The  students  see  their  knowledge  base  growing  now.  They  can  touch  it,  but   it  no  longer  fits  neatly  in  their  folders.  They  can  grasp  it,  but  it  takes  two  hands  and  even  then   part  of  the  knowledge  base  falls  to  the  floor.  There  is  more  work  to  be  done.  There  is  more   organization  to  accomplish.  There  are  more  connections  to  be  made.  There  are  more  patterns   and  trends  to  see.  The  concrete  Concept  of  Photosynthesis  is  starting  to  take  shape.   Practice  3:  Exam  Questions     Approximately  once  every  three  to  four  weeks,  students  come  to  class  to  take  an  exam.   The  professors  told  the  Bio101  students  that  the  material  covered  during  the  four   203       photosynthesis  lectures  would  be  assessed  on  “Exam  2.”  Just  as  they  did  during  the  lectures,   many  students  bring  book  bags  and  backpacks  into  the  classroom  on  examination  days.   However,  one  of  the  major  differences  between  lectures  and  examination  days  is  that  much  of   what  students  have  in  their  bags  and  backpacks  is  never  removed  from  them.  The  only   empirical  allies  students  are  allowed  to  remove  from  their  bags  and  put  to  use  during  the   exams  include  paper  (in  the  form  of  an  already  inscribed  paper  exam  given  to  them  by  the   Bio101  professors  or  their  teacher  assistance),  a  pencil  (only  No.2  pencils,  however),  a   wristwatch  (but  there  is  also  a  clock  for  use  on  the  classroom  wall),  and  a  university-­‐issued   photographic  ID,  but  that  is  all.   While  the  paper,  pencils,  and  wristwatches  are  used  during  the  examination,  students   typically  use  the  photographic  ID  only  after  the  completion  of  it.  It  turns  out  that  the  professors   don’t  trust  their  own  mental  faculties  to  remember  the  names  and  faces  of  their  nearly  four   hundred  undergraduate  students—a  number  of  whom  only  occasionally  show  up  for  classes.  So,   the  professors  ask  each  of  their  students  to  prove  their  identity  by  means  of  triangulation.  Each   student’s  true  identity  is  held  between  three  visible,  material  objects:  the  photographic  ID   (which  contains  a  photograph  of  the  student,  their  legal  name,  and  a  one-­‐of-­‐a-­‐kind  9-­‐digit   alphanumeric  code  or  “student  number”),  a  paper  class  roster  provided  by  the  university   Registrar’s  office  (which  contains  each  student's  legal  name  and  student  number),  and  the   actual  (physical)  face  of  the  student.  Besides  these  three  allies,  the  enlistment  of  all  other   empirical  allies—including  other  students—is  strictly  forbidden.  In  fact,  right  before  distributing   the  paper  exams  to  their  students,  the  professors  often  remind  those  present  to  tuck  all   unapproved  empirical  allies  safely  away  underneath  their  chairs  and/or  place  them  into  folders,   204       purses,  shoulder  bags,  backpacks,  etc.  As  a  final  way  of  dissuading  students  from  enlisting  any   other  student’s  exam  paper  as  an  ally,  the  professors  also  usually  tell  students  to,  “Keep  your   eyes  and  hands  on  your  own  exam.”  Figure  5.3  (below)  shows  an  example  of  an  exam  question   from  Exam  2.  It  is  question  “52,”  the  Mutant  Spinach  Question.     52)  Suppose  you  discovered  a  mutant  strain  of  spinach  in  which  the  thylakoid   membranes  were  slightly  permeable  to  H+  ions,  thus  allowing  a  slow  leakage   (remember  that  in  normal  membranes,  H+  is  not  permeable  at  all).  What  change     in  the  reactions  of  photosynthesis  might  occur  in  compensation  for  this  defect?     F) cyclic    photophosphorylation  would  increase   G) non-­‐cyclic  photophosphorylation  would  increase   H) O2  production  would  decrease   I) cyclic  photophosphorylation  would  decrease   J) non-­‐cyclic  photophosphorylation  would  decrease         Figure  5.3.  Question  “52,”  the  Mutant  Spinach  Question,  from  Bio101  Exam  2     (fall  2006)   A  quick  glance  at  question  “52”  makes  visible  a  common  characteristic  of  most  exam   questions—with  very  few  exceptions,  the  questions  contain  almost  no  visible,  material  figures   within  them.  In  this  way  they  have  much  in  common  in  terms  of  their  visible  and  material   features  with  the  clicker  questions.  Both  are  laden  with  content  related  terms.  The  content-­‐ related  terms  in  question  “52”  include:  #mutant,  #strain,  #spinach,  #thylakoid,  #membrane(s),   #permeable,  #H+,  #ions,  #leakage,  #normal  membrane(s),  #reactions,  #photosynthesis,   #compensation,  #defect,  #cyclic  photophosphorylation,  #non-­‐cyclic  photophosphorylation,  #O2   production.  In  total  there  are  17  content-­‐related  terms  contained  with  the  text  of  question  “52.”   Unlike  either  of  the  two  previous  pedagogical  practices,  during  exams  questions  like  question   205       “52”  almost  never  receive  and  verbal  addressing  by  the  professors.  The  only  time  any  verbal   addressing  usually  occurs  is  if  there  is  something  found  to  be  wrong  with  the  question  (e.g.,  a   misspelled  or  misplace  word).  The  professors  and  students  are  noticeably  silent  during  exams,   and  this  makes  the  practice  rather  unlike  the  figure-­‐  and  clicker  question-­‐based  practices.     When  finished,  the  students  turn  in  their  exams  and  scoring  sheets  to  the  professors  or   teacher  assistants.  They  do  not  take  it  home  with  them.  They  do,  however,  tend  to  take  all  of   the  other  items  they  brought  with  them  into  the  exam  (e.g.,  folders,  books,  binders,  shoulder   bags,  and  backpacks),  which  the  students  never  removed  from  them.  In  these  un-­‐accessed   items  were  many  of  the  figures  and  clicker  questions  the  students  had  collected,  created,  and   annotated—and  on  behalf  of  whom  so  much  verbal  activity  had  been  espoused—during  the   four  days  of  the  photosynthesis  unit.   A  few  days  after  the  exam,  the  Bio101  professors  receive  the  results  of  the  exam  from   the  university  scoring  office.  The  results  for  question  “52”  quickly  grab  their  attention.   According  to  the  report,  only  twenty  percent  of  the  Bio  101  students  answered  the  Mutant   Spinach  Question  correctly.  It  was  the  most  missed  question  on  entire  exam.  Over  three   quarters  of  the  Bio101  students  failed  to  apply  their  existing  knowledge  to  the  novel   phenomenon  as  the  professors  had  hoped  they  would.  In  other  words,  more  than  three   quarters  of  the  students  failed  to  demonstrate  that  they  had  learned  the  concept  of  the  “light   reactions  of  photosynthesis”  in  a  way  that  could  be  considered  deep,  rich,  conceptual,   meaningful  and/or  enduring.           206       Perspective  3A  -­‐  P.  psychologicus     Recall  that  in  P.  psychologicus,  learning  with  understanding  is  treated  as  if  it  were  a   mental  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  mentally  apply,   extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original  context  of   learning.  What  follows  is  an  empirical  profile  of  how  professors  teach  photosynthesis  for   understanding  when  learning  photosynthesis  for  understanding  is  construed  as  mental.   When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  exam  questions  to  assess  whether  or  not  students  have  learned  with  photosynthesis   with  understanding.  Structurally,  the  exam  questions  are  almost  identical  to  clicker  questions.   They  too  mostly  contain  only  words  (and  occasionally  numbers)  and,  like  clicker  questions,  the   exam  questions  almost  never  contain  figures  in  them.  The  exam  questions  serve  at  least  two   purposes.  First,  they  are  used  to  determine  the  degree  to  which  students  have—at  that   moment—developed  coherent  mental  knowledge  bases.  Second,  they  are  used  to  determine   the  degree  to  which  students’  with  knowledge  bases  can—at  that  moment—mentally   extrapolate  them  to  contexts  with  differing  degrees  of  contextual  familiarity.  In  both  cases,   students  are  not  allowed  to  use  any  of  the  visible,  material  figures  or  clicker  questions  as  allies.   In  other  words,  students  are  not  allowed  to  use  any  of  the  shadows  of  the  Idea  or  Concept  of   Photosynthesis.  On  the  exams,  all  students  have  to  rely  on  are  mental  allies  such  as  the  abstract   Concept  of  Photosynthesis  in  their  minds/brains.     Although  no  (visible,  material)  figures  or  clicker  questions  are  permitted  for  use  on  the   exam,  the  Bio101  professors  allow  students  to  bring  with  them  a  number  of  mental  allies.  In   addition  to  abstract  concepts,  students  can  rely  upon  such  mental  allies  as  logic,  reason,  facts,   207       induction,  deduction,  analytical  skills,  critical  thinking  skills,  and  abstract  thinking  skills.  In   addition,  the  professors  encourage  students  to  perform  all  kinds  of  mental  operations  on   factual  knowledge.  For  example,  students  are  encouraged  to  integrate  and  assemble  it;  to  put  it   together  and  pull  it  apart;  to  tie  and  fit  it  together;  to  organize  and  reorganize  it;  and  to  use  it   (in  the  service  of  actions  such  as  “making  predictions,”  “drawing  explanations,”  and  “gaining   insights”).  On  the  Mutant  Spinach  Question,  however,  only  twenty  percent  of  the  Bio101   students  were  able  to  demonstrate  that  they  could  trigger/activate  the  mental  allies  needed  to   demonstrate  learning  with  understanding.  Only  one  fifth  of  the  students  were  able  to  mentally   extrapolate  abstract  concepts  such  as  the  Concept  of  the  Light  Dependent  Reactions  and  the   Concepts  of  Cyclic  and  Non-­‐Cyclic  Photophosphorylation  and  apply  them  correctly  to  the   unscripted  context.     Perspective  3B  -­‐  P.  empiricus     Recall  that  in  P.  empiricus,  learning  with  understanding  is  treated  as  if  it  were  an   empirical  activity.  Students  who  learn  with  understanding  are  said  to  be  able  to  empirically   apply,  extend  or  transfer  their  deep,  rich  knowledge  base  to  situations  beyond  the  original   context  of  learning.  What  follows  is  a  virtual  or  simulated  empirical  profile  of  how  professors   teach  photosynthesis  for  understanding  when  learning  photosynthesis  for  understanding  is   construed  as  empirical.   When  teaching  photosynthesis  for  understanding,  the  Bio101  professors  use  visible,   material  exam  questions  to  assess  whether  or  not  students  have  learned  with  photosynthesis   with  understanding.  On  exam  day,  the  professors  know  that  they  can’t  ask  their  students  to   place  the  bulk  of  their  trust  in  mental  allies.  Although  the  professors  would  like  for  students  to   208       be  able  to  rely  purely  on  mental  allies  such  as  the  abstract  Concept  of  Photosynthesis,  they   know  from  their  own  work  as  biologists  that  learning  with  understanding  in  science  often   depends  on  the  successful  execution  of  a  wide  variety  of  well  coordinate,  empirical  strategies.   Therefore,  they  encourage  their  biology  students  to  bring  a  collection  of  empirical  allies  with   them  for  use  during  the  exam  including  their  empirical  knowledge  base.     Because  the  exam  questions  are  structurally  similar  to  clicker  questions,  the  Bio101   students  tend  to  take  a  similar  (empirical)  approach  to  them.  The  first  thing  they  do  is  identify   the  key  content-­‐related  terms  and  extract  (rather  than  abstract)  them  away  from  the  question.   These  terms  don’t  travel  far—only  as  far  as  a  table  of  blank  rows  and  columns  placed  next  to   the  exam,  where  they  remain  both  visible  and  material.  Once  isolated  from  the  exam  question,   the  students  check  these  content-­‐related  terms  against  other  completed  tables  in  their   empirical  knowledge  bases.  Many  of  them  begin  to  see  overlap  between  the  terms  used  in  one   exam  question  (question  “52”),  two  clicker  questions,  and  three  figures  used  in  class.  Soon,   students  have  used  their  empirical  knowledge  bases  to  identify  two  figures  and  a  single  clicker   question.  They  then  use  these  graspable  items  to  help  them  select  one  of  the  five  answer   choices.     Because  the  Bio101  professors  trust  empirical  allies  more  so  than  mental  ones  in  much   of  their  work  as  biologists,  they  allow  students  to  bring  with  them  into  the  exam  a  number  of   empirical  allies.  In  addition  to  more  concrete  concepts,  students  call  upon  allies  as  logic  and   reason,  but  these  ‘skills’  are  done  with  things  like  hands  and  eyes.  In  addition,  the  professors   encourage  students  to  perform  all  kinds  of  empirical  operations  on  factual  knowledge.  For   example,  students  are  encouraged  to  integrate  and  assemble  it;  to  put  it  together  and  pull  it   209       apart;  to  tie  and  fit  it  together;  to  organize  and  reorganize  it;  and  to  use  it  (in  the  service  of   actions  such  as  “making  predictions,”  “drawing  explanations,”  and  “gaining  insights”).  On  the   Mutant  Spinach  Question,  the  results  are  rather  promising:  sixty  percent  of  the  students  are   able  to  demonstrate  that  they  could  mobilize/recruit  the  empirical  allies  needed  to   demonstrate  learning  with  understanding.   Discussion  -­‐  Part  A     The  design  of  the  bioeducational  assay  proposed  three  research  questions.  The  first   research  question  was:  What  is  the  empirical  profile  of  a  pedagogical  practice  that  we  are   calling  Pedagogia  psychologicus  (P.  psychologicus)?   180 Empirical  profile  (A)  -­‐  P.  psychologicus     In  this  undergraduate  biology  course,  P.  psychologicus  takes  the  empirical  form  of  three   main  pedagogical  practices  so  named  for  the  empirical  actors  most  commonly  found   within  them:  “figures,”  “clicker  questions,”  and  “exams.”  In  P.  psychologicus,  teaching   for  and  learning  with  understanding  can  be  described  across  these  three  pedagogical   practices  as  a  progression  from  the  empirical  to  the  mental.  In  the  four  days  of   instruction  leading  up  to  an  exam,  teachers  directed  much  of  their  students’  visual  and   auditory  attention  toward  an  almost  continuous  presentation  of  visible,  material   “figures”  and  “clicker  questions.”  These  two  empirical  actors  were  at  the  center  of  much   of  what  goes  on  in  the  classroom  on  a  daily  basis.  However,  these  two  actors  mainly   played  the  part  of  “visual  aids”  and/or  “visual  representations.”  That  is,  they  were                                                                                                                   180.  Readers  may  notice  similarities  between  this  empirical  profile  and  the  anthropologist’s   report  of  the  “pedagogical  expedition”  from  Chapter  3.   210       enlisted  by  the  professors  in  the  service  of  the  development  of  a  more  important  set  of   student  allies,  a  group  of  mental  actors  called  abstract  science  concepts  (or  Concepts).   In  P.  psychologicus,  Concepts  are  treated  as  if  they  were  always  already  abstract   realities  in  the  world.  The  work  done  by  professors  and  students  with  figures  and  clicker   questions  in  the  classroom  are  practices  designed  to  help  students  develop  (abstract)   Concepts  in  their  minds—for  example,  the  Photosynthesis.  In  P.  psychologicus,  the   professors  accomplish  this  by  relying  on  their  students’  ability  to  generalize  from  the   different  instances  and  aspects  of  the  Concept  of  Photosynthesis  (re)presented  in  the   figures  and  clicker  questions.  In  these  empirical  objects,  students  are  supposed  to  ‘see’   the  conceptual  unity  of  Photosynthesis  across  the  use  of  the  many  figures  and  clicker   questions  presented  and  used  during  the  four-­‐day  unit.  The  professors’  speech  is  meant   to  help  facilitate  this  particular  way  of  ‘seeing’  (seeing-­‐as-­‐generalizing,  seeing-­‐as-­‐ abstracting).  By  the  end  of  the  four-­‐day  unit,  the  professors  expected  their  students  to   have  adequately  assembled  the  abstract  Concept  of  Photosynthesis  in  their  minds.   When  examination  day  arrived,  they  expected  their  students  to  be  able  to  see  and   recognize  instances  of  it  outside  of  their  minds/brains,  and  in  which  the  corresponding   abstract  Concept  of  Photosynthesis  was  simultaneously  present—for  example,  in  a   “mutant  strain  of  spinach.”  On  exams  questions,  learning  with  understanding  is   demonstrated  when  students  successfully  extrapolate  their  mental  understanding  and   use  it  to  ‘leap’  to  situations  or  phenomena  in  which  the  abstract  Ideas  or  Concepts  are   always  already  present.  To  summarize,  within  the  context  of  this  undergraduate  biology   course,  P.  psychologicus  can  be  described  as  a  set  of  practices  whose  ultimate  trajectory   211       is  the  successful  transformation  or  transfiguration  of  vast  numbers  of  empirical  allies   into  mental  ones.  If  there  were  one  word  that  could  characterize  P.  psychologicus,  that   word  would  be  “INNERstanding.”   The  second  research  question  was:  What  is  the  empirical  profile  of  a  pedagogical   practice  that  we  are  calling  Pedagogia  empiricus  (P.  empiricus)?   181 Empirical  profile  (B)  -­‐  P.  empiricus     In  this  undergraduate  biology  course,  P.  empiricus  takes  the  empirical  form  of  three   main  pedagogical  practices  so  named  for  the  empirical  actors  most  commonly  found   within  them:  “figures,”  “clicker  questions,”  and  “exams.”  In  P.  empiricus,  teaching  for   and  learning  with  understanding  can  be  described  across  these  three  practices  as  a  four-­‐ day  engagement  with  empirical  allies.  Although  it  would  be  silly  to  deny  that  the  science   students  must  engage  in  mental/cognitive  practices  such  as  thinking  and  reasoning,  the   professors  do  not  feel  that  it  is  necessarily  to  consider  these  important  actions  as   exclusively  psychological  practices.  When  confronted  by  a  phenomena  known  as  the   Concept  of  Photosynthesis  (or  Photosynthesis)—an  abstract  concept  which  they  could   not  understand  at  first  glance  or,  for  that  matter,  at  second,  third  or  fourth  glance—the   professors,  who  happened  to  be  research  scientists  themselves,  taught  their   undergraduate  students  how  to  make  sense  of  a  perplexing  Concept  by  asking  them  to   deliberately  shifting  the  weight  of  responsibility  from  their  internal,  mental  faculties  to  a   network  of  empirically  observable  objects  and  practices.  Rather  than  the  students’                                                                                                                   181.  Readers  may  notice  similarities  between  this  empirical  profile  and  the  anthropologist’s   report  of  the  “scientific  expedition”  from  Chapter  3.   212       minds/brains,  it  appears  as  though  the  professors’  primary  expectation  of  their  students   is  that  they  each  find  ways  to  efficiently  and  effectively  externalize  the  confusing   Concept  of  Photosynthesis.  To  summarize,  within  the  context  of  this  classroom,  P.   empiricus  learning  with  understanding  can  be  described  as  a  set  of  practices  whose   ultimate  success  depends  upon  the  students’  abilities  to  learn  how  to  coherently  and   carefully  coordinate  a  vast  army  of  empirical  allies.  In  the  heat  of  an  epistemological   engagement,  the  professors’  pedagogical  mantra  is  this:  mental  allies  can’t  be  trusted.  If   there  were  one  word  that  could  characterize  P.  empiricus,  that  word  would  be   “OVERstanding.”     The  third  research  question  was:  What  is  the  relative  purity,  composition,  activity,   and/or  potency  of  a  lesser  known  pedagogical  practice  (P.  empiricus)  relative  to  better  known   pedagogical  practice  (P.  psychologicus)?   An  answer  to  this  final  research  question  is  given  at  the  beginning  of  Chapter  6   (Discussion  -­‐  Part  B).         213       CHAPTER  6   NEW  HORIZONS  FOR  SCIENTIST  TEACHERS         I  could  not  think  without  writing.       —Jean  Piaget     “Thinking  is  hand-­‐work,”  as  Heidegger  said,  but  what  is  in  the   hands  are  inscriptions.   —Bruno  Latour       Discussion  -­‐  Part  B     In  scientific  assays—for  example,  in  bioassays—recording  mechanisms  such  as   myographs  or  gamma  counters  are  connected  to  organisms,  whether  to  cells,  muscles,  or   whole  animals,  so  as  to  produce  easily  readable  traces. 182  In  this  next  section,  I  use  a  device  of   my  own  making—the  bioeducational  assay—to  produce  readable  traces  of  the  two  pedagogical   practices  named  in  Chapter  5,  P.  psychologicus  and  P.  empiricus.  The  practices  are  evaluated   according  to  traits  or  characteristics  such  as  purity,  composition,  activity,  and  potency.  However,   I  have  taken  these  scientific  characteristics  and  re-­‐contextualized  them  for  use  in  my  study.     The  research  question  I  asked  in  Chapter  5  is:  What  is  the  educational  or  pedagogical   purity,  composition,  activity,  and  potency  of  the  lesser  known  Pedagogia  empiricus  relative  to   Pedagogia  psychologicus?  Sections  6.1-­‐6.4  contain  the  discussion  of  and  interpretations  for   these  four  pedagogically  reformulated  traits.                                                                                                                       182.  Latour,  Laboratory  Life,  58.   214       6.1  Purity     The  scientific  concept  of  purity  draws  our  attention  to  the  degree  of  homogeneity   and/or  uniformity  in  character  or  constitution.  In  this  bioeducational  assay,  I  interpret  “degree   of  homogeneity”  and  “degree  of  uniformity”  as  referring  to  the  number  and  types  of   pedagogical  modes  of  expression  enacted  in  the  classroom.     In  terms  of  purity,  P.  empiricus  should  be  considered  as  purer  than  P.  psychologicus.  P.   empiricus’s  greater  purity  is  derived  from  the  fact  that  its  pedagogical  expression  remains   entirely  within  an  empirical  mode  during  the  four-­‐day  photosynthesis  unit.  For  example,  in  P.   empiricus  the  Bio101  professors  constantly  drew  their  students’  attentions  to  visible,  material   figures  and  clicker  questions  and  encouraged  students  to  tag  the  figures  and  questions  with  yet   other  visible,  material  objects  (for  instance,  with  hashtagged  terms  such  as  “#light  reactions”   and  “#cyclic  photophosphorylation”).  P.  psychologicus’s  lesser  purity  is  due  to  the  fact  that  it   does  not  remain  in  a  single  pedagogical  mode  during  the  unit.  Instead,  P.  psychologicus   demands  that  students  shift  constantly  from  empirical  to  mental  modes  of  expression.  For   example,  the  Bio101  instructors  constantly  drew  their  students’  attention  to  visible,  material   figures  and  clicker  questions  while  in  P.  psychologicus.  Furthermore,  they  expected  students  to   transform  the  figures  and  questions  into  mental  or  cognitive  objects  (for  example,  into  the   Concept  of  the  Light  Reactions  and  the  Concept  of  Cyclic  Photophosphorylation).  The  effects  of   these  continuous  modal  shifts  between  psychological  and  empirical  modes—which  is  one  of  the   defining  features  of  teaching  for  understanding  in  P.  psychologicus—could  have  any  number  of   significant  consequences  on  students’  ability  to  learn  with  understanding  and  deserves  further   investigation.  If  research  scientists  spend  much  of  their  time  learning  with  understanding  in  a   215       single  mode—an  empirical  one—then  what  does  it  mean  for  science  teachers  to  ask  their   science  students  to  be  ‘bimodal?’  In  term  of  modal  practices,  does  this  mean  that  science   teachers  demand  more  of  novice  science  students  than  expert  scientists  demand  of   themselves?  In  other  words,  does  this  mean  that  science  education  demands  more  of   undergraduate  science  students  than  science  demands  of  its  Nobel  Prize-­‐winning  researchers?   6.2  Composition     The  scientific  concept  of  composition  draws  our  attention  to  the  type  of  matter  that   makes  up  an  object,  as  well  as  the  arrangement  of  the  matter  in  the  object.  In  this   bioeducational  assay,  I  interpret  “type  of  matter”  as  referring  to  the  number  and  types  of   human  and  non-­‐humans  involved  in  a  pedagogical  practice.  I  interpret  “arrangement  of  the   matter”  as  referring  to  how  those  human  and  non-­‐humans  are  arranged  in  time  and  space.     6.2a  Number  and  type  of  humans     The  unconventional  design  of  this  bioeducational  assay  makes  it  difficult  to  detect   compositional  differences  between  P.  empiricus  and  P.  psychologicus  in  terms  of  the  number  of   humans  present.  That  is,  the  number  of  humans  in  both  trials  was  exactly  the  same:  two   professors  and  four  hundred  or  so  students.  However,  the  assay  reveals  a  compositional   difference  in  the  types  of  humans  present.  In  P.  empiricus,  the  Bio101  professors’  commitment   to  teaching  their  students  empirical  practices  similar  to  those  commonly  used  in  scientific   research  means  that  we  must  simultaneously  acknowledge  the  professors  as  scientists.  Rather   than  as  science  teachers,  we  might  instead  consider  them  as  scientist  teachers.  This  title  draws   attention  to  their  firm  commitment  to  empirical  practices  in  both  science  and  science  education.   In  P.  psychologicus,  the  Bio101  professors  made  a  firm  commitment  to  teaching  their  students   216       psychological  practices,  which  in  their  work  as  research  scientists  outside  of  the  classroom  they   typically  eschew  at  the  insistence  of  their  colleagues.  Thus,  we  can  conclude  that  P.  empiricus   and  P.  psychologicus  have  different  ways  of  constructing  their  professors:  P.  empiricus  tends  to   construct  its  professors  as  scientists  whereas  P.  psychologicus  tends  to  construct  its  professors   as  something  other  than  scientists.  The  irony  in  P.  psychologicus  should  already  be  apparent.   College  professors  of  science  are  discouraged  from  acting  like  scientists  while  teaching  science.   6.2b  Number  and  type  of  non-­‐humans     It  is  relatively  easy  to  detect  a  compositional  difference  between  P.  empiricus  and  P.   psychologicus  in  terms  of  the  number  and  type  of  non-­‐humans  present.  In  both  P.  empiricus   and  P.  psychologicus  we  see  equal  numbers  of  figures  and  clicker  questions  used  in  class.  We   also  see  equal  number  of  exam  questions  used  on  the  exams.  However,  one  significant   difference  is  that  in  P.  empiricus  we  see  the  birth  of  an  entirely  new  type  or  genre  of  empirical   objects  in  the  “tables”  used  by  students  to  track  the  presence  of  both  the  written  and  spoken   content-­‐related  terms.  In  P.  empiricus,  students  used  these  tables  to  add  depth  and  coherence   to  their  empirical  knowledge  bases.  This  depth  and  coherence  took  forms  that  were  visible,   material,  tangible,  public,  and  documentable.  In  P.  psychologicus  we  never  see  the  birth  of  an   entirely  new  genre  of  empirical  objects  because  students’  knowledge  bases  are  treated  as  if   they  were  entirely  mental  or  cognitive.  When  treated  psychologically,  the  depth  and  coherence   of  mental  knowledge  base  take  forms  that  are  significantly  less  visible,  less  material,  less   tangible,  less  public,  and  less  documentable.  In  other  words,  they  take  forms  that  are  more   secretive,  more  clandestine,  and  more  universal.  Thus,  we  can  conclude  that  P.  empiricus  and  P.   psychologicus  have  different  ways  of  constructing  knowledge  bases  defined  by  qualities  such  as   217       depth  and  coherence:  P.  empiricus  tends  to  construct  knowledge  bases  empirically  whereas  P.   psychologicus  tends  to  construct  knowledge  bases  as  something  other  than  empirical.  Again,   the  irony  in  P.  psychologicus  should  be  apparent.  College  professors  of  science  are  discouraged   from  teaching  their  students  how  to  assemble  the  same  kinds  of  empirical  knowledge  bases   that  they  find  so  useful  in  their  work  as  research  scientists.     6.2c  How  humans  and  non-­‐humans  are  arranged  in  time  and  space     The  bioeducational  assay  also  reveals  a  significant  compositional  difference  in  how   humans  and  non-­‐humans  are  arranged  in  time  and  space.  In  this  example,  I  will  focus  on  how  a   non-­‐human—the  concept  of  photosynthesis  (or  Concept  of  Photosynthesis)—is  temporally  and   spatially  arranged  in  Bio101.     In  P.  psychologicus,  the  Concept  of  Photosynthesis  is  treated  as  if  it  existed  outside  of  all   language  including  representational  systems  such  as  images,  symbols,  and  actions  in  at  least   three  places.  First,  the  Concept  of  Photosynthesis  is  treated  as  if  it  existed  in  phenomena  in   nature  (i.e.,  ‘out  there’). 183  Second,  the  Concept  of  Photosynthesis  is  treated  as  if  it  existed  in   184 the  mind  of  the  scientist  or  professor  (‘in  there’).  It’s  important  to  note,  however,  that  the   Concept  of  Photosynthesis  out  in  nature  is  treated  as  if  it  were  exactly  the  same  as  the  Concept   of  Photosynthesis  in  the  mind  of  the  scientist/professor.  In  other  words,  these  two  concepts  are   treated  as  if  they  were  one-­‐and-­‐the-­‐same  Concept,  as  if  they  shared  a  one-­‐to-­‐one   correspondence,  as  if  they  were  mimetic.  Third,  the  Concept  of  Photosynthesis  is  treated  as  if  it   existed  in  the  minds  of  students  who  have  successfully  learned  with  understanding.  Here  again,                                                                                                                   183.  Lemke  characterizes  this  view  as  philosophical  realism  (see  Lemke  2002).   184.  Lemke  characterizes  this  view  as  an  updated  form  of  Plato’s  idealism  (see  Lemke  2002).   218       it’s  important  to  note  that  the  corresponding  Concept  of  Photosynthesis  out  in  nature  and  in   the  mind  of  the  scientist/professor  are  treated  as  if  they  were  exactly  the  same  as  the  Concept   of  Photosynthesis  in  minds  of  accomplished  students.  In  other  words,  these  three  concepts  are   all  treated  as  if  they  were  one-­‐and-­‐the-­‐same  Concept,  as  if  they  shared  a  one-­‐to-­‐one-­‐to-­‐one   185 correspondence,  as  if  they  were  mimetic.  Here,  we  can  see  that  P.  psychologicus  constructs   the  Concept  of  Photosynthesis  as  if  it  had  three  distinct  features.  First,  it  constructs   Photosynthesis  as  if  it  were  invisible.  In  other  words,  P.  psychologicus  treats  Photosynthesis  as   if  it  were  simultaneously  hiding  just  behind  natural  phenomena  and  also  within  mental   phenomena.  Second,  it  constructs  Photosynthesis  as  if  it  were  universal.  In  other  words,  P.   psychologicus  treats  Photosynthesis  as  if  it  were  exactly  same  both  out  in  nature  and  in  the   mind.  Third,  it  constructs  Photosynthesis  as  if  it  were  ahistoric  (or  timeless).  In  other  words,  P.   psychologicus  treats  Photosynthesis  as  if  it  had  always  been  out  in  nature  awaiting  discovery  by   scientists  and  students.  This  particular  conceptual  scenography  is  precisely  what  makes  it   possible  for  professors  to  expect  their  students  to  be  able  to  a)  discover  the  Concept  of   Photosynthesis  for  themselves,  b)  generalize  from  different  figures  and  clicker  questions  and   ‘see’  (internally)  the  conceptual  unity  of  the  various  representations  of  the  abstract  Concept  of   Photosynthesis,  and  c)  leap  to  the  abstraction  in  situations  beyond  the  context  of  instruction  (in   other  words,  cognitive  transfer  is  possible  because  the  abstract  Concept  of  Photosynthesis  is   real  and  therefore  always  already  naturally  there  as  a  target  two  which  one  can  leap).                                                                                                                     185.  Latour  characterizes  this  view  as  a  product  of  a  “Kantian  scenography,”  where  phenomena   are  said  to  “reside  at  the  meeting  point  between  the  inaccessible  things  in  themselves  and   categorizing  work  made  by  the  Active  Ego”  (see  Latour  1999,  72).     219       In  P.  empiricus,  the  concept  of  photosynthesis  is  not  treated  as  if  it  existed  outside  of  all   language.  It  is  not  treated  as  if  it  resided  in  the  face-­‐to-­‐face  confrontation  of  scientific  minds   with  natural  objects  and  phenomena.  Instead,  the  concept  of  photosynthesis  is  treated  as  if  it   186 was  what  routinely  circulates  through  cascades  of  visible,  material  transformations.   Although  in  science  these  transformations  often  proceed  from  the  more  concrete  to  the  more   abstract—i.e.,  from  things  to  signs,  from  matter  to  form,  from  the  worldly  to  the  more  wordly— a  critical  feature  of  the  transformations  is  that  the  upstream  movement  must  be  reversible  and   traceable  in  the  downstream  direction.  In  other  words,  scientists  must  be  able  to  trace  the   concept  of  photosynthesis  both  upstream  and  downstream,  but  regardless  of  their  location  in   stream  (or  circuit)  the  concept  must  always  remain  visible  and  material.  Even  when  put  into   one  of  its  more  abstract  forms  in  Bio101—for  instance,  as  when  one  of  the  professors  wrote   the  abbreviation  “PS”  during  a  lecture—this  form  remained  both  visible  (students  could  see  it   on  the  projection  screen)  and  material  (students  could  touch  it  if  they  picked  up  the  overhead   transparency  on  which  it  was  written  in  green  ink).  Where  and  when  do  these  attitudes  and   assumptions  locate  the  concept  of  photosynthesis?  In  P.  empiricus,  photosynthesis  is  still   treated  as  if  it  were  real,  but  in  a  different  sense.  P.  empiricus  doesn’t  treat  photosynthesis  as  if   it  re-­‐presented  a  pre-­‐existing  reality.  It  also  doesn't  treat  photosynthesis  as  if  it  were  some  pre-­‐ destined  mentality.  Instead,  P.  empiricus  treats  photosynthesis  as  if  it  were  that  which  is  held   187 constant  through  a  series  of  visible,  material,  and  empirically  traceable  transformations.  In   other  words,  P.  empiricus  draws  attention  away  from  (on  the  one  hand)  that  which  is  hidden                                                                                                                   186.  See  Latour  1999,  69.   187.  See  Latour  1999,  58.   220       ‘behind’  trees  growing  on  a  sunny  hillside  and  ‘within’  mind  of  students,  and  toward  (on  the   other  hand)  all  of  the  visible,  material  practices  found  in  between  these  two  extreme  poles.  The   written  abbreviation  “PS”  may  be  abstract  in  the  sense  that  it  has  lost  some  of  its  visibility  and   materiality  compared  to  when  it  is  written  as  “photosynthesis,”  and  even  more  of  its  visibility   and  materiality  compared  to  when  it  is  written  as  “light  energy  +  CO2  +  H2O  !  C6H12O6  +  O2   +H2O”,  but  the  photosynthesis  cannot  not  afford  to  lose  all  visibility  and  materiality  because  to   lose  all  of  these  two  traits—at  least  in  the  natural  sciences—is  not  to  exist!  In  P.  empiricus,   abstraction  is  a  relative  quality,  which  means  that  even  abstract  concepts  can  still  be   considered  concrete.     Here,  I  think  Lemke’s  treatise  on  concepts  is  perhaps  even  more  instructive  than  I  can   communicate,  but  I  have  taken  the  liberty  of  re-­‐contextualizing  his  treatise  on  the  concept  of   energy  to  fit  with  our  current  discussion  of  photosynthesis.   The  concept  of  [photosynthesis]  is  not  a  single  anything;  it  is  a  whole  system  of   disparate  but  linked  practices,  ways  of  talking,  ways  of  measuring,  ways  of  calculating,   ways  of  seeing.  To  learn  this  concept  is  to  learn  how  to  apply  it  in  ever-­‐widening  circles   of  practical  contexts,  to  learn  how  exactly  our  culture,  our  historical  scientific  tradition,   constructs  connections  between  this  situation  and  that,  that  and  the  next.     You  cannot  "grasp"  a  concept  like  [photosynthesis];  to  teach  that  you  can  is  to  promote   an  intellectually  and  socially  dangerous  illusion.  You  can  construct  a  higher-­‐order   pattern,  a  pattern  in  the  strategies  by  which  our  culture  connects  situations  of  different   types,  but  this  will  not  enable  you  to  anticipate  how  the  concept  of  [photosynthesis]  will   apply  to  a  totally  new  situation—or  even  whether  or  not  it  can  usefully  be  made  to.   Historically,  and  in  the  intellectual  recapitulation  of  culture  that  grounds  the  educational   process,  it  has  always  taken  new  work,  new  insight,  new  ways  of  constructing  new  kinds   of  connections  to  apply  the  concept  of  [photosynthesis]  to  new  domains.  In  each   successful  instance  the  concept  of  [photosynthesis]  itself  was  changed,  was  extended.     221       The  same  is  true  for  all  abstractions,  all  concepts,  all  categories,  but  especially  for  the   most  abstract  ones,  those  that  apply  to  the  most  superficially  dissimilar  instances.  They   are  not  singular,  not  unitary.  The  "concept"  is  not  the  same  in  any  real  sense  from  one   situation  to  another  very  different  one:  to  use  the  concept  we  must  do  very  different   things,  use  different  discourses  and  construct  different  semantic  patterns  in  language,   draw  different  diagrams,  perform  different  manipulations  of  objects.  That  we  have  a   "concept"  merely  means  that  we  ALSO  have  ANOTHER  set  of  procedures  for  connecting   what  we  do  in  one  case  with  what  we  did  in  the  other.     This  means  that  the  similarities  on  which  abstract  concepts  are  based  are  not  "there"  for   all  to  see.  Either  they  are  entirely  cultural  constructions,  or  even  if  not,  the  ones  on   which  a  particular  concept  is  based  are  indistinguishable  from  the  infinite  other  possible   similarities  that  may  be  construed  between  any  two  objects,  until  we  are  taught  how  to   attend  to,  pick  out,  and/or  construe  the  ones  our  culture,  our  physics  wants  us  to  see.   Consequently,  there  is  no  reason  to  expect  "transfer  of  learning"  from  one  situation   type  to  another.  We  must  be  taught,  separately  in  each  case,  how  to  apply  "a  concept"   to  that  case.  In  fact,  we  must  be  taught  two  things:  how  to  operate  in  the  new  context,   and  how  to  construct  a  conventional  similarity  between  that  operation-­‐in-­‐context  and   188 all  the  others  to  which  our  culture  gives  the  same  name.       The  conceptual  scenography  articulated  by  Lemke  is  precisely  what  makes  it  possible  to   expect  professors  to  teach  their  students  how  to  talk,  how  to  measure,  how  to  calculate,  and   how  to  see.  These  can  be  understood  as  empirical  practices.  It  is  also  what  makes  it  possible  to   expect  professors  to  teach  their  students  how  to  construct  higher-­‐order  patterns  and  how   scientists  connect  situations  of  different  types.  These  too  can  be  understood  as  empirical   practices.  It  is  also  what  makes  it  possible  to  expect  professors  to  teach  their  students  how  to   engage  in  the  types  of  work  that  they  do  as  scientists,  including  how  they  operate  in  new   contexts  and  how  they  construct  conventional  similarities  between  situations  to  which  the                                                                                                                   188.  Lemke,  “The  Missing  Context,”  para.  16-­‐19.   222       scientific  culture  gives  the  same  name  (but  only  retroactively!).  Again,  these  too  can  be   understood—as  they  already  have  by  Lemke,  Latour,  and  others—as  empirical  practices.     6.3  Activity     Among  other  characteristics,  the  scientific  concept  of  activity  draws  our  attention  to  the   189 types  of  action  or  movement  enacted  by  substances.  In  this  bioeducational  assay,  I  interpret   “substances”  as  referring  to  the  types  of  action  or  movement  enacted  by  humans  and  non-­‐ humans  involved  in  a  pedagogical  practice.  Let  us  briefly  consider  the  two  types  of  actions  or   190 movements  enacted  by  students:  saltation  and  ambulation.   P.  psychologicus  often  draws  attention  to  the  need  for  students  to  enact  conceptual   “leaps”  over  yawning  “gaps.”  Such  movement  can  be  characterized  as  saltatory  (from  Latin   saltare,  ‘to  hop’  or  ‘to  leap’).  This  was  the  case  with  the  Mutant  Spinach  Question,  when   students  had  to  leap  from  the  context  of  classroom  instruction  to  the  strange,  unfamiliar   context  of  a  test  question  about  a  “mutant  strain  of  spinach”  with  leaky  membranes.  Of  the   Bio101  students  who  could  not  make  this  abstract  leap  successfully,  it  might  be  said  of  them   that  the  reason  they  could  not  make  this  leap  is  because  they  were  not  thinking  abstractly   enough.  In  other  words,  it  might  be  said  of  them  that  they  were  thinking  too  concretely.     P.  empiricus  often  draws  attention  to  an  entirely  different  type  of  movement  altogether.   Instead  of  leaps  and  gaps,  which  are  discursive  artifacts  of  a  commitment  to  a  one-­‐to-­‐one   theory  of  correspondence,  P.  empiricus  draws  attention  to  student  and  teacher  movements   that  can  be  characterized  as  ambulatory  (from  Latin  ambulare,  ‘to  walk’  or  ‘to  step’).                                                                                                                   189.  For  example,  the  scientific  concept  of  activity  also  draws  attention  to  the  capacity  of  a   substance  to  undergo  change.   190.  See  Latour  1999,  Chapter  2.   223       Ambulatory  movement  is  action  that  is  aligned  with  the  principles  of  circulating  reference.   While  it  may  be  true  that  the  Mutant  Spinach  Question  requires  a  large  leap  from  the  context   of  classroom  instruction  to  the  strange,  unfamiliar  context  of  a  test  question,  it’s  not  necessarily   true  that  students  must  a)  make  use  of  only  mental  allies  in  this  task,  and  b)  do  it  all  at  once.   Instead,  students  can  cross  the  yawning  chasm  by  means  of  circulating  reference,  which  a)   makes  use  of  empirical  allies,  and  b)  requires  students  to  take  small,  carefully  articulated  and   well  aligned  steps.  The  former  action  is  cognitive  transfer;  the  later  action  is  empirical   transformation.  The  former  action  is  a  common  characteristic  of  contemporary  school  science;   the  later  action  is  a  common  characteristic  of  scientists’  science.   6.4  Potency     The  scientific  concept  of  potency  draws  our  attention  to  the  capacity  or  potential  of  a   substance  to  produce  strong  effects.  In  this  bioeducational  assay,  I  interpret  “strong  effects”  as   referring  to  the  capacity  of  a  pedagogical  practice  to  enable  Bio101  students  to  answer  the   Mutant  Spinach  Question  correctly.     Exam  2,  question  “52”  served  as  a  way  of  testing  the  potency  of  P.  psychologicus.  In  fall   2006,  P.  psychologicus  was  only  able  to  produce  a  strong  effect  in  twenty  percent  of  the  Bio101   students.  In  other  words,  eighty  percent  of  the  Bio101  students  could  not  demonstrate  that   they  had  learned  with  understanding.  In  this  non-­‐simulated  reality,  students  could  first  turn   their  attention  to  the  visual,  material  text  of  question  “52.”  Here,  they  could  register  the   content-­‐related  terms  within  the  stem  and  answer  choice  components  of  the  question,  but   soon  after  that  they  quickly  needed  to  switch  to  their  mental/cognitive  faculties.  For  reasons   that  surely  vary,  but  that  may  have  a  good  deal  to  do  with  a  student’s  particular  cultural   224       background,  a  majority  of  the  Bio101  students  were  unable  to  perform  the  necessary  abstract   psychological  operations.  In  this  particular  instance,  the  potency  of  P.  psychologicus  was  weak.   To  assess  the  potency  of  P.  empiricus,  I  had  to  use  the  EmSIM  3000.  Recall  that  the   EmSIM  3000  was  used  to  tag  all  of  the  visible,  material  elements  used  by  the  Bio101  professors   with  students  during  class.  The  EmSIM  3000  not  only  allows  us  to  act  as  if  the  professors  had   done  this  type  of  empirical  work  with  their  students,  but  also  to  act  as  if  the  students  had  been   allowed  to  keep  the  products  of  their  empirical  work  in  front  of  them  when  confronting   question  “52.”  If  this  was  the  reality  of  Bio101,  then  one  of  the  first  tasks  to  which  students   would  turn  their  immediate  attention  are  the  numerous  content-­‐related  terms  present  in  the   text  of  the  stem  of  the  question.  In  P.  empiricus,  although  these  terms  are  some  of  the  more   abstract  forms  that  students  encountered  during  instruction,  they  are  still  visible  and  still   material.  Rather  than  have  students  shift  their  attention  from  an  empirical  to  a  mental  mode   (as  is  required  in  P.  psychologicus),  P.  empiricus  has  its  students  shift  their  attention  from  one   empirical  element  (e.g.,  a  single  content-­‐related  term  such  as  “#mutant”  or  “#spinach”)  to   other  empirical  elements  that  have  visible,  material  connections  to  the  content-­‐related  terms  in   the  stem  of  the  question.   I’ve  used  the  EmSIM  3000  to  model  what  this  process  might  look  like.  Table  6.1  shows   what  happens  when  students  begin  looking  within  their  visible,  material  knowledge  bases  for   elements  that  overlap  with  the  content-­‐related  terms  found  in  the  stem  of  question  “52.”           225         Table  6.1:  A  table  showing  the  number  of  content-­‐related  hits  generated  by  the  EmSIM  3000.     Content-­‐related  term  (Q52)   Number  of  hits   Distribution  of  hits     #mutant     2   —   —   2  on  09-­‐29-­‐06   #strain   0   —   #spinach   0   —     #thlakoid(s)     5   1  on  09-­‐25-­‐06   3  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #membrane(s)     11   3  on  09-­‐25-­‐06   7  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #thylakoid(s)  membrane(s)     4   1  on  09-­‐25-­‐06   2  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #permeable  or  #permeability       0     —     #ions     3   —   2  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #H+  ion     4   —   3  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #hydrogen     5   —   4  on  09-­‐27-­‐06   1  on  09-­‐29-­‐06     #reaction(s)     27   4  on  09-­‐25-­‐06   10  on  09-­‐27-­‐06   13  on  09-­‐29-­‐06     226       Table  6.1  (cont’d)     #photosynthesis     53   10  on  09-­‐25-­‐06   21  on  09-­‐27-­‐06   22  on  09-­‐29-­‐06     #photosynthesis  reactions     28   4  on  09-­‐25-­‐06   10  on  09-­‐27-­‐06   14  on  09-­‐29-­‐06     As  an  example  of  how  to  interpret  the  table,  students  looking  for  figures  and  clicker   questions  in  their  knowledge  bases  having  to  do  with  “#photosynthesis”  would  have  their   attention  drawn  to  at  least  fifty-­‐three  visible,  material  elements  presented  during  the  four-­‐day   photosynthesis  unit.  Ten  of  these  elements  were  presented  during  Lecture  1  (09-­‐25-­‐06),   twenty-­‐one  of  these  elements  were  presented  during  Lecture  2  (09-­‐27-­‐06),  and  twenty-­‐two  of   these  elements  were  presented  during  Lecture  3  (09-­‐29-­‐06).  These  same  students  might  be   overwhelmed  by  the  results  of  the  large  number  of  ‘hits’  produced  when  searching  their   knowledge  base  for  “#photosynthesis,”  so  they  might  instead  try  looking  in  the  direction  of   other  content-­‐related  terms  that  result  in  fewer  hits.     If  students  were  to  then  shift  their  attention  to  the  collection  of  content-­‐related  terms   that  initially  produced  a  more  manageable  number  of  hits,  say,  between  three  and  eleven,  then   their  attention  would  be  drawn  to  terms  such  as  “#thylakoid(s),”  “#membrane(s),”  “#  thylakoid   membrane(s),”  “#ions,”  “#H+  ion,”  and  “#hydrogen.”  If  they  were  to  then  pursue  the  identities   of  the  figures  and  clicker  questions  associated  with  these  particular  hits  within  their  knowledge   bases,  they  will  quickly  find  that  their  pool  of  potentially  useful  visible,  material  allies  consisted   of  a  total  of  fourteen  numbered  elements.  Of  these  fourteen  numbered  elements,  they  would   quickly  see  that  there  was  a  higher  density  of  hits  on  just  seven  of  these  fourteen  numbered   227       elements  (specifically,  Elements  23,  15e,  20,  12b,  9c,  17,  and  6).  Of  these  seven  filtered   elements,  students  would  quickly  see  that  Element  6,  which  is  a  copy  of  Figure  10.16  from   Lecture  3  (09-­‐29-­‐06),  had  the  greatest  number  of  total  hits  (six),  and  that  Element  17,  which  is  a   still  image  made  from  an  animation  shown  to  students  in  Lecture  2  (09-­‐27-­‐06),  had  the  second   greatest  number  of  total  hits  (four).  Elements  6  and  17  are  shown  in  Figures  6.1  and  6.2. 228             A.  Figure  10.16  shown  by  the  Bio101  professors  during  Lecture  3  (09-­‐29-­‐06).     Figure  6.1:  Two  versions  of  Element  6,  which  was  identified  by  the  EmSIM  3000  as  having  the  most  relevance  to  question  “52.”  Two   versions  of  Element  6  are  included  because  the  images  and  text  in  the  photographed  version  may  be  difficult  to  read/see.  Figure   10.16  shown  by  the  Bio101  professors  during  Lecture  3  (09-­‐29-­‐06)  (A);  and  a  non-­‐annotated  version  of  Figure  10.16  as  it  appears  in   the  instructional  materials  (B).  (Reprinted  with  permission  by  the  copyright  holder.)   229               Figure  6.1.  (cont’d)   B.  A  non-­‐annotated  version  of  Figure  10.16  as  it  appears  in  the  instructional  materials.               230         A.  A  still  image  made  from  an  animation  shown  by  the  Bio101  professors  during  Lecture  2  (09-­‐27-­‐06).     Figure  6.2:  Two  versions  of  Element  17,  which  was  identified  by  the  EmSIM  3000  as  having  the  second  most  relevance  to  question   “52.”  Two  versions  of  Element  17  are  included  because  the  images  and  text  in  the  photographed  version  may  be  difficult  to  read/see.     A  still  image  made  from  an  animation  shown  by  the  Bio101  professors  during  Lecture  2  (09-­‐27-­‐06)  (A);  and  a  still  image  made  from   the  animation  as  it  appears  in  the  instructional  materials  (B).  (Reprinted  with  permission  by  the  copyright  holder.)     231     Figure  6.2.  (cont’d)     B.    A  still  image  made  from  the  animation  as  it  appears  in  the  instructional  materials.   232       The  EmSIM  3000  identified  Element  6  (Figure  6.1(A)  and  (B))  and  Element  17  (Figure   6.2(A)  and  (B))  as  the  visible,  material  elements  most  likely  to  aid  Bio101  students  in  their   attempts  to  answer  question  “52”  correctly. 191  However,  in  the  unsimulated  version  of  Bio101   the  students  were  not  allowed  to  have  the  visible,  material  form  of  either  element  with  them   when  attempting  to  answer  the  exam  question.  In  other  words,  we  have  no  way  of  simulating   whether  the  possession  of  visible,  material  copies  of  these  two  figures  would  have  helped  more   than  twenty  percent  of  the  Bio101  students  demonstrate  that  they  had  learned  with   understanding.  Thus,  it  appears  as  though  we  have  no  way  of  evaluating  and/or  validating  the   EmSIM  3000’s  selection  of  these  two  figures.  Fortunately  for  us,  just  two  days  after  Exam  2  one   of  the  Bio101  professors  offered  us  a  way  of  doing  just  this.  They  offered  a  real  time  example  of   the  very  scenario  that  the  EmSIM  3000  identified.   Exam  2  Review:  Lecture  20     Two  days  after  Exam  2,  the  Bio101  professors  decided  to  re-­‐visit  the  Mutant  Spinach   Question  with  the  students  during  class.  This  was  a  relatively  common  practice  in  Bio  101.  The   instructors  often  identified  one  or  two  of  the  most  missed  questions  on  an  exam  and  discussed   them  in  some  detail  with  students  in  class.  Question  “52”  was  the  most  missed  question  on   Exam  2,  and  one  of  the  professors  took  this  opportunity  to  lead  the  students  through  an   exercise  that  I  had  never  seen  him  do  before.  As  the  professor  framed  the  task,   Professor  2:  There  were  a  couple  particularly  difficult  questions  that  I’d  like  to  go   over…this  is  one  of  them,  number  “52,”  that  asked  you  about  a  leaky  thylakoid   membrane.  OK.  And  I  want  to  take  some  time  to  show  you  the  kind  of  logic  that  you                                                                                                                   191.  Interestingly,  when  I  searched  all  at  once  for  a  combination  of  all  the  content-­‐related   terms  found  within  the  stem  of  the  Mutant  Spinach  Question,  the  EmSIM  3000  spit  out  a  single   hit:  Element  6,  Figure  10.16,  09-­‐29-­‐06.   233       might  use…I’m  not…there  might  be  other  ways  of  solving  the  problem…I  want  to  show   you  the  way  I  might  step  through  that  problem  to  get  to  the  correct  answer,  OK.  And  I’m   going  to  do  that  by  using  the  clicker.  All  right?  So  everybody  get  your  clickers  out  and   let’s  begin.  All  right? 192     Making  use  of  the  same  technology  used  to  ask  clicker  questions  of  students  prior  to   Exam  2,  the  professor  broke  question  “52”  down  into  six  different  clicker  questions  designed  to   help  students  see  how  they  should  have  approached  the  Mutant  Spinach  Question.  Unlike  any   of  the  clicker  questions  used  in  the  four  days  leading  up  to  Exam  2,  four  of  these  six  clicker   questions  made  use  of  written  text  combined  with  the  use  of  one  of  two  figures.  The  two   figures  used  in  the  four  sequential  clicker  questions  are  shown  in  Figure  6.3.                                                                                                                 192.  Lecture  Transcript  (October  18,  2006):  00:01:26  -­‐  00:01:56.   234                 Figure  6.3.  (At  left):  The  first  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review  session.  The  text  contained  within,  on  top,   and  underneath  the  vertical  arrow  to  the  far  left  of  the  figure  appearing  within  the  clicker  question  reads  as  follows:  “Energy  Level”   (within),  “High”  (on  top),  and  “Low”  (underneath).  (At  right):  The  second  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review   session.  The  text  in  the  upper  (blue)  portion  of  the  figure  contained  within  the  clicker  question  reads  as  follows  (starting  in  the  top   left  of  this  upper  portion  and  proceding  in  a  clockwise  direction):  “thylakoid  space,”  (multiple)  “H+,”  and  “FO  unit.”  The  text  in  the   lower  (orange)  portion  of  the  figure  reads  as  follows  (starting  in  the  top  left  of  this  lower  portion  and  proceding  in  a  clockwise   direction):  “stroma,”  “H+,”  “Stalk,”  “H+”  “F1  unit,”  “ATP,”  and  “ADP  +  Pi.” 235     We  first  need  to  focus  our  attention  on  the  figure  embedded  in  the  first  of  the  six  clicker   questions  used  by  the  professor  during  the  post-­‐Exam  2  review  session—in  other  words,  the   “N”-­‐shaped  figure  at  left  of  Figure  6.3.  This  is  a  figure  that  the  professor  spent  a  substantial   portion  of  time  discussing  with  students  when  showing  them  “the  kind  of  logic”  that  they  might   use  to  solve  question  “52.”  If  we  juxtapose  this  figure  with  Element  6  (Figure  6.1),  which  was   one  of  the  two  images  identified  by  the  EmSIM  3000,  then  it  appears  we  have  taken  a  positive   step  in  validating  the  empirical  simulator’s  performance.  This  juxtaposition  is  done  for  you  in   Figure  6.4. 236         A.  Figure  10.16  shown  by  the  Bio101  professors  to  students  during  Lecture  3  (09-­‐29-­‐06),  but  also  the     element  (Element  6)  identified  by  the  EmSIM  3000  as  having  the  most  relevance  to  question  52.     Figure  6.4.  Juxtaposition  of  Element  6  and  a  figure  used  with  Bio101  students  during  the  post-­‐Exam  2  review  session.  Figure  10.16   shown  by  the  Bio101  professors  to  students  during  Lecture  3  (09-­‐29-­‐06),  but  also  the  element  (Element  6)  identified  by  the  EmSIM   3000  as  having  the  most  relevance  to  question  52  (A);  A  non-­‐annotated  version  of  Figure  10.16  as  it  appears  in  the  instructional   materials.  Notice  the  Z-­‐  (or  N-­‐shaped)  scheme  visible  in  the  image.  (B);  and  a  close-­‐up  of  the  image  used  in  the  first  of  six  clicker   questions  asked  during  the  post-­‐Exam  2  review  session.  Notice  the  Z-­‐  (or  N-­‐shaped)  scheme  visible  in  the  image.  The  text  contained   within,  on  top,  and  underneath  the  vertical  arrow  to  the  far  left  of  the  figure  reads  as  follows:  “Energy  Level”  (within),  “High”  (on   top),  and  “Low”  (underneath)  (C).  (Reprinted  with  permission  by  the  copyright  holder.)   237                         Figure  6.4.  (cont’d)   B.  A  non-­‐annotated  version  of  Figure  10.16  as  it  appears  in  the  instructional  materials.     Notice  the  Z-­‐  (or  N-­‐shaped)  scheme  visible  in  the  image.   238         Figure  6.4.  (cont’d)     C.  A  close-­‐up  of  the  image  used  in  the  first  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review  session.  Notice  the  Z-­‐  (or  N-­‐ shaped)  scheme  visible  in  the  image.    The  text  contained  within,  on  top,  and  underneath  the  vertical  arrow  to  the  far  left  of  the   figure  reads  as  follows:  “Energy  Level”  (within),  “High”  (on  top),  and  “Low”  (underneath).   239         Despite  the  appearance  of  more  information  in  the  figure  at  left,  the  two  figures  are   clearly  related. 193  This  means  that  the  professor  chose  to  show  students  a  figure  during  his   Exam  2  review  that  was  similar  to  the  first  figure  selected  by  the  EmSIM  3000.     If  we  now  to  our  attention  instead  to  the  figure  embedded  in  the  second  of  the  six   clicker  questions  used  by  the  professor  during  the  post-­‐Exam  2  review  session—in  other  words,   the  figure  with  the  large,  green  apparatus  at  right  of  Figure  6.3—then  we  get  a  similar  result.   The  juxtaposition  of  this  figure  with  Element  17  shows  that  we  have  taken  another  positive  step   in  validating  the  empirical  simulator’s  performance.  This  juxtaposition  is  done  for  you  in  Figure   6.5.                                                                                                                 193.  The  Bio101  professors  might  describe  both  figures  as  representations  of  the  “Concept  of   the  Light-­‐Dependent  Reactions  of  Photosynthesis.”     240         A.  A  still  image  made  from  an  animation  shown  by  the  Bio101  professors  during  Lecture  2  (09-­‐27-­‐06),  but  also  the     element  (Element  17)  identified  by  the  EmSIM  3000  as  having  the  second  most  relevance  to  question  “52.”     Figure  6.5.  Juxtaposition  of  Element  17  and  a  figure  used  with  Bio101  students  during  the  post-­‐Exam  2  review  session.  A  still  image   made  from  an  animation  shown  by  the  Bio101  professors  during  Lecture  2  (09-­‐27-­‐06),  but  also  the  element  (Element  17)  identified   by  the  EmSIM  3000  as  having  the  second  most  relevance  to  question  “52”  (A);  a  still  image  made  from  the  animation  as  it  appears  in   the  instructional  materials  (B).  Notice  the  (orange)  pear-­‐shaped  structure  visible  in  the  center  of  image;  and  a  close-­‐up  of  the  image   used  in  the  second  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review  session  (C).  The  text  in  the  upper  (blue)  portion  of   the  figure  contained  within  the  clicker  question  reads  as  follows  (starting  in  the  top  left  of  this  upper  portion  and  proceding  in  a   clockwise  direction):  “thylakoid  space,”  (multiple)  “H+,”  and  “FO  unit.”  The  text  in  the  lower  (orange)  portion  of  the  figure  reads  as   follows  (starting  in  the  top  left  of  this  lower  portion  and  proceding  in  a  clockwise  direction):  “stroma,”  “H+,”  “Stalk,”  “H+”  “F1  unit,”   “ATP,”  and  “ADP  +  Pi.”  Notice  the  similarities  between  the  (green)  structure  in  the  center  of  the  image  and  the  (orange)  pear-­‐shaped   in  the  previous  image.   241       Figure  6.5.  (cont’d)     B.  A  still  image  made  from  the  animation  as  it  appears  in  the  instructional  materials.  Notice  the  (orange)  pear-­‐shaped  structure   visible  in  the  center  of  image.         242     Figure  6.5.  (cont’d)     thylakoid space   stroma     C.  A  close-­‐up  of  the  image  used  in  the  second  of  six  clicker  questions  asked  during  the  post-­‐Exam  2  review  session.  The  text  in  the   upper  (blue)  portion  of  the  figure  contained  within  the  clicker  question  reads  as  follows  (starting  in  the  top  left  of  this  upper  portion   and  proceding  in  a  clockwise  direction):  “thylakoid  space,”  (multiple)  “H+,”  and  “FO  unit.”  The  text  in  the  lower  (orange)  portion  of   the  figure  reads  as  follows  (starting  in  the  top  left  of  this  lower  portion  and  proceding  in  a  clockwise  direction):  “stroma,”  “H+,”   “Stalk,”  “H+”  “F1  unit,”  “ATP,”  and  “ADP  +  Pi.”  Notice  the  similarities  between  the  (green)  structure  in  the  center  of  the  image  and   the  (orange)  pear-­‐shaped  in  the  previous  image.   243         194 Despite  differences  in  the  two  figures,  they  are  clearly  related.  This  means  that  the   professor  chose  to  show  students  a  figure  during  his  Exam  2  review  that  was  similar  to  the   second  figure  selected  by  the  EmSIM  3000.     To  summarize,  when  showing  students  “the  kind  of  logic”  they  might  use  to  solve   question  52,  and  when  showing  students  the  way  he  might  “step  through  that  problem  to  get   the  correct  answer,”  Professor  2  relied  not  on  mental  allies,  but  instead  on  two  empirical   allies—two  visible,  material  figures—both  of  which  had  been  identified  by  an  empirical  tagging   (or  circuit-­‐building)  exercise  facilitated  by  the  EmSIM  3000.  Therefore,  in  this  particular  instance   the  potency  of  P.  empiricus  was  particularly  strong.  The  tagging  techniques  used  by  the  EmSIM   3000  helped  us  choose  two  visible,  material  elements  from  a  pool  of  over  from  over  fifty-­‐three   visible,  material  elements  presented  to  students  during  a  four-­‐day  photosynthesis  unit.  Most   importantly,  these  happened  to  be  the  same  two  empirical  elements  selected  by  one  of  the   Bio101  professors  when  showing  his  students  how  to  apply  their  newfound  scholarship  to  a   problem  students  didn’t  think  they  knew  how  to  solve.     Conclusions     I’ve  used  a  device  of  my  own  making—the  bioeducational  assay—to  produce  readable   traces  of  two  pedagogical  practices,  P.  psychologicus  and  P.  empiricus.  These  practices  were   evaluated  according  to  their  relative  purity,  composition,  activity,  and  potency.  One  of  the  main   purposes  of  this  experiment  was  to  not  only  to  further  delineate  the  boundaries  of  a   pedagogical  practice  constructed  in  accordance  with  a  mental/cognitive  horizon  of  expectations,                                                                                                                   194.  The  Bio101  professors  might  describe  both  figures  as  representations  of  the  “Concept  of   the  Proton  Gradient”  (or  “Proton  Transport”)  and/or  the  “Concept  of  ATP  Production.”     244       but  also  to  begin  sketching  and  elaborating  an  envelope  of  a  pedagogical  practice  constructed   in  accordance  with  an  empirical  horizon.   P.  empiricus,  which  I’ve  tried  to  align  with  the  governing  principles  and  concepts  of   science  rather  than  those  of  psychology,  should  be  viewed  as  yet  another  way  that  professors   can  help  their  students  find  ways  to  learn  with  understanding.  To  be  sure,  I  have  enacted  an   alchemy  that  distorts  and  oversimplifies  many  of  the  complexities  and  purposes  of  scientific   practices.  To  make  matters  worse,  I  have  begun  modifying  the  five  defining  features  associated   with  learning  with  understanding.  In  the  scenography  that  I  have  developed  thus  far,  students   who  learn  with  understanding  are  still  said  to  possess  a  coherent  knowledge  base,  but  this   knowledge  base  can  take  more  visible,  material  forms.  Students  who  learn  with  understanding   are  still  said  to  be  able  to  apply,  extend  or  extrapolate  their  deep,  rich  knowledge  base  to   certain  types  of  situations,  but  to  do  so  they  must  rely  on  circulating  reference  instead  of   cognitive  transfer.  Furthermore,  I’ve  used  the  ideas  of  Popkewitz,  Lemke,  and  Latour  to  help  me   re-­‐imagine  the  ways  that  abstract  conceptual  learning  theory  can  operate  in  university  biology   classrooms.  One  of  my  prime  motivations  is  to  try  and  find  ways  to  exclude  fewer  students   from  meeting  the  goals  of  science  education.  A  brief  anecdote  will  help  illustrate  why  I  think   this  sort  of  action  is  needed.   A  Student’s  Plea  for  Help       In  fall  2007,  I  interviewed  a  number  of  Bio101  students  regarding  their  answers  to  three   application  questions  related  to  the  topic  of  photosynthesis.  The  students  were  each  offered  a   decent  sum  of  money  for  an  hour’s  worth  of  their  time.  However,  one  student,  whom  I’ll  call   “Louisa,”  wasn’t  interested  in  coming  to  the  interview  for  the  money.  Louisa’s  interest   245       stemmed  from  the  fact  that  she  had  seen  me  videotaping  the  lectures  during  parts  of  the   semester  from  the  rear  of  the  lecture  hall.  She  reasoned  that  I  must  be  one  of  the  instructors   and  she  thought  she  might  be  able  to  use  this  interview  to  ask  for  advice.  “You  see,”  she  told   me  before  the  formal  portion  of  the  interview  commenced,  “I’ve  done  horrible  on  the  first  two   Bio101  midterm  exams  and  I’m  worried  that  I  might  fail  the  course.”  When  I  asked  her  about   things  like  whether  or  not  she  attended  class  regularly,  completed  the  homework  assignments,   did  the  course  readings,  etc.  she  quickly  convinced  me  that  this  was  not  a  case  of  personal   irresponsibility,  disinterest,  or  neglect.  On  the  contrary,  she  had  a  perfect  attendance  record,   sat  near  the  front  of  the  room,  completed  all  the  readings  before  class,  and  formed  study   groups  with  her  peers.  In  other  words,  Louisa  was  doing  many  of  the  things  her  Bio101   professors  hoped  their  students  would  do.  It  was  soon  after  we  established  these  facts  that  she   then  surprised  me.  She  began  to  cry.     As  tears  ran  down  her  cheeks  Louisa  apologized  profusely,  but  what  she  did  next  caught   me  by  complete  surprise.  She  unzipped  her  backpack  rather  hurriedly  and  began  stacking  a   series  of  colorful,  spirally  bound  notebooks  on  the  small  interview  table.  As  she  began  opening   them,  one  by  one,  and  flipping  through  them  page  by  page,  her  sadness  quickly  became  mixed   with  anger  and  frustration.  “Do  you  see  these?”  She  said  while  continuing  to  flip  through  the   individual  pages—and  then  through  the  larger  tabbed  sections—of  her  notebooks,  “Nobody  in   this  class  works  as  hard  as  I  do.”  Indeed,  Louisa’s  notebooks  were  impressive.  They  were  neat,   thorough,  extensive,  organized,  highlighted,  and  underlined.  These  were  not  the  notebooks  of  a   lazy  or  an  unmotivated  student.  “I  just  don’t  understand,”  she  added,  “No  matter  what  I  do   246       outside  of  class...no  matter  how  hard  I  work...I  just  can’t  seem  to  make  it  pay  off  on  the  exams.   I  don’t  know  what  else  I  can  do.  Can  you  help  me?”   From  Innerstanding  to  Overstanding     There  are  many  ways  we  could  read  Louisa’s  situation,  but  I  want  to  move  away  from   the  psychological  or  cognitive  readings  of  it  and  propose  something  entirely  empirical.  What  if   Louisa’s  main  problem  stems  from  the  fact  that  she  is  routinely  asked  by  her  college  science   professors  to  place  nearly  all  of  her  trust  in  her  mind/brain?  What  if  she  were  allowed  to  enlist   more  allies  that  were  something  other  than  mental?  What  if  she  could  be  taught  how  to  re-­‐ organize  the  contents  of  her  notebooks  according  to  the  principles  of  circulating  reference   instead  of  those  such  as  ‘chunking’  information  and  improving  short-­‐term  memory?  What  if  she   were  expected  to  engage  in  chains  of  transformation  instead  of  instances  of  transfer?  In  other   words,  what  if  she  were  allowed  to  be  more  like  research  scientists  when  it  came  to  learning   with  understanding?   P.  empiricus  can  get  us  closer  to  a  point  in  science  education  where  it  becomes  possible   to  ‘think’  and  to  ‘reason’  with  both  hands  and  eyes. 195  With  a  substantial  amount  of  work  and   almost  constant  maintenance,  it  can  get  us  closer  to  a  point  in  science  education  where  it   becomes  possible  to  shift  the  attention  from  the  mind  to  the  surface  of  visible,  empirical   resources  that  can  be  moved  more  freely—and  with  more  integrity—through  both  space  and   time.  It  can  get  us  closer  to  a  point  in  science  education  where  it  becomes  possible  to  treat  logic   196 as  if  it  were  about  logistics.  And,  it  can  get  us  closer  to  a  point  in  science  education  where  it                                                                                                                   195.  See  Latour  1986.   196.  See  Latour  1987,  Chapter  6.   247       becomes  possible  to  treat  understanding  less  as  innerstanding—where  understanding  tends  to   remain  secretive  can  clandestine—and  more  as  overstanding—where  it  can  be  rendered  more   public,  more  accessible,  and  more  equitable.  Latour,  always  skeptical  of  the  special  powers  so   often  attributed  to  the  human  mind,  reminds  of  us  the  power  of  empirical  practices,   The  role  of  the  mind  has  been  vastly  exaggerated,  as  has  been  that  of  perception   (Arnheim,  1969).  An  average  mind  or  an  average  man,  with  the  same  perceptual   abilities,  within  normal  social  conditions,  will  generate  totally  different  output   depending  on  whether  his  or  her  average  skills  apply  to  the  confusing  world  or  to   inscriptions. 197       Perhaps  the  presence  of  P.  empiricus  in  this  dissertation—despite  its  clear  need  of   further  trials,  additional  strengthening,  and  much  more  extensive  elaboration—signals  the   beginning  of  an  era  in  science  education  in  which  the  psychological  sciences  can  be  made  to   loosen  their  historically  tightened  grip  on  the  notions  of  teaching  for  and  learning  with   understanding.  To  open  up  these  notions  to  the  reach  and  influence  of  the  natural  sciences   would  not  only  make  room  for  more  authenticity  in  science  education,  but  also  for  more   inclusion.  It  is  possible  that  transforming  science  via  a  more  scientific  or  empirical  alchemy   would  result  in  a  much  greater  percentage  of  college  students  demonstrating  that  are  capable   of  learning  with  understanding.  As  I  said  before,  to  take  a  mentalist  approach  to  classroom   allies  is  to  be  selective  and  exclusive.  It  limits  our  conceptions  of  what  these  entities  can  be  to  a   culturally  and  historically  specific  set  of  values,  ethics,  assumptions,  and  beliefs—mostly  those   of  “upper-­‐middle  class”  cultural  backgrounds.  By  taking  a  mentalist  approach,  those  students   from  backgrounds  outside  of  the  upper-­‐middle  class  are  more  likely  to  struggle  in  educational                                                                                                                   197.  Latour,  “Visualization  and  Cognition,”  22.   248       moments  in  which  knowledge  and  understanding  are  defined  exclusively  as  mental  and   cognitive.     Shifting  the  alchemy  from  the  psychological  sciences  to  the  natural  or  empirical  sciences   also  means  that  science  professors  are  reconnected  to  their  ‘other’  lives  as  research  scientists.   Instead  of  living  schizophrenic  lives  as  empirical  practitioners  outside  of  the  classroom  and   psychological  practitioners  inside  of  it,  through  the  magic  of  a  more  scientifically  informed   alchemy  the  two  split  selves  are  reunited  in  the  form  of  a  single  person—the  scientist  teacher.   Rather  than  having  to  leave  their  most  treasured  research  practices  and  sensibilities  at  the  door   to  the  classroom,  like  a  checked  overcoat  or  a  bulky  piece  of  luggage,  these  habits  and   sensibilities  would  be  allowed  to  flood  the  space  of  the  classroom  each  and  every  day.     This  stance  does  not  deny  that  there  are  such  entities  as  “reasoning,”  “thinking,”   “minds-­‐on”  learning,  “abstract  concepts,”  and  “understanding  by  design.”  Nor  does  it  deny  the   existence  of  discursive  features  such  as  knowledge  base,  coherence,  transfer,  extrapolation,   and  cognition.  On  the  contrary,  it  endorses  all  of  these  actors  but  with  one  vital  caveat:  none  of   these  actors  must  be  defined  in  accordance  to  a  mental/cognitive  horizon  of  expectations.   There  can  be  such  things  as  reasoning,  thinking,  minds-­‐on  learning,  abstract  concepts,  and   understanding  by  design,  and  there  can  such  entities  as  knowledge  base,  coherence,  transfer,   extrapolation,  and  cognition,  but  they  can  also  be  defined  by  logistical  practices  instead  of  (or  in   addition  to)  logical  practices.  It  is  a  matter  of  choice.  It  is  a  matter  of  taste.  It  is  a  matter  of   preference.  It  is  a  matter  of  importance.  It  is  a  matter  of  alchemy.   249       But  wouldn’t  it  be  an  interesting  new  reality  in  contemporary  science  education  if   average  students—in  partnership  with  their  scientist  teachers—could  routinely  perform   extraordinary  deeds?       250                                         BIBLIOGRAPHY             251       BIBLIOGRAPHY       American  Association  for  the  Advancement  of  Science  (AAAS).  “About  Project  2061,”  AAAS   Project  2061.  Accessed  August  10,  2013,   http://www.project2061.org/about/default.htm.   ———.  Benchmarks  for  Science  Literacy.  New  York:  Oxford  University  Press,  1993.     ———.  Science  for  All  Americans.  New  York:  Oxford  University  Press,  1990.   Anderson,  Charles  (Andy).  “Designing  Systems  to  Support  Learning  Science  with  Understanding   for  All.”  Project  2061.  Last  modified  January  2001.   http://www.project2061.org/events/meetings/textbook/science/anderson.htm.     Bloom,  Benjamin  S.,  Max  D.  Englehart,  Edward  J.  Furst,  Walker  H.  Hill,  and  David  R.  Krathwohl.   Taxonomy  of  Educational  Objectives,  The  Classification  of  Educational  Goals:  Handbook  I:   Cognitive  Domain.  New  York:  David  McKay  Company,  Inc.,  1956.   Bowker,  Geoffrey  C.  Memory  Practices  in  the  Sciences.  Cambridge,  MA:  MIT  Press,  2005.   Buxton,  Cory  A.  “Creating  Contextually  Authentic  Science  in  a  ‘Low-­‐Performing’  Urban   Elementary  School.”  Journal  of  Research  in  Science  Teaching  43,  no.  7  (2006):  695–721.   Callon,  Michel.  “Some  Elements  of  a  Sociology  of  Translation:  Domestication  of  the  Scallops  and   the  Fisherman  of  St.  Brieuc  Bay.”  In  Power,  Action  and  Belief:  A  New  Sociology  of   Knowledge?  Edited  by  John  Law,  196-­‐223.  London:  Routledge,  1986.   Calvin,  Melvin.  “The  Path  of  Carbon  in  Photosynthesis  [Nobel  Prize  Lecture].”  Paper  presented   at  the  Nobel  Prize  Award  Ceremonies,  Stockholm,  Sweden,  December  11,  1961.  Retrieved   from  http://www.nobelprize.org/nobel_prizes/chemistry/laureates/1961/calvin-­‐ lecture.pdf.     Carpenter,  Thomas  P.,  and  Richard  Lehrer.  “Teaching  and  Learning  Mathematics  with   Understanding.”  In  Mathematics  Classrooms  that  Promote  Understanding,  edited  by   Elizabeth  Fennema  and  Thomas  A.  Romberg,  19-­‐32.  Mahwah,  NJ:  Erlbaum,  1999.   Center  for  Education  (CFE).  Improving  Undergraduate  Instruction  in  Science,  Technology,   Engineering,  and  Mathematics:  Report  of  a  Workshop.  Washington,  D.C.:  The  National   Academies  Press,  2003.   Crary,  Jonathan.  Suspensions  of  Perception:  Attention,  Spectacle  and  Modern  Culture.   Cambridge,  MA:  MIT  Press,  1999.   ———.  Techniques  of  the  Observer:  on  Vision  and  Modernity  in  the  Nineteenth  Century.   Cambridge,  MA:  MIT  Press,  1990.   252       Daston,  Lorraine  J.,  and  Peter  Galison.  Objectivity.  New  York:  Zone  Books,  2007.   DeBoer,  George  E.  A  History  of  Ideas  in  Science  Education.  New  York:  Teachers  College  Press,   1991.   Dewey,  John.  How  We  Think.  Boston:  D.C.  Heath  &  Co.  Publishers,  1910.   Fendler,  Lynn.  “The  Magic  of  Psychology  in  Teacher  Education.”  Journal  of  the  Philosophy  of   Education,  46,  no.  3  (2012):  332-­‐51.   ———.  Michel  Foucault.  Continuum  Library  of  Educational  Thought,  Vol.  22,  Richard  Bailey,   (Series  Ed.).  London:  Continuum,  2010.   ———.  “Others  and  the  Problem  of  Community.”  Curriculum  Inquiry  36,  no.  3  (2006):  295-­‐318.   ———.  “Teacher  Reflection  in  a  Hall  of  Mirrors:  Historical  Influences  and  Political   Reverberations.”  Educational  Researcher  32,  no.3  (2003):  16-­‐25.     ———.  “Why  Generalisability  is  Not  Generalisable.”  Journal  of  the  Philosophy  of  Education  40,   no.  4  (2006):  437-­‐449.   Fennema,  Elizabeth,  and  Thomas  A.  Romberg.  Preface  to  Mathematics  Classrooms  that   Promote  Understanding,  edited  by  Elizabeth  Fennema  and  Thomas  A.  Romberg,  ix-­‐xi.   Mahwah,  NJ:  Erlbaum,  1999.   Giere,  Ronald  N.  “How  Models  are  Used  to  Represent  Reality.”  Philosophy  of  Science  71,  no.  5   (2004):  742-­‐52.   Handelsman,  J.,  D.  Ebert-­‐May,  R.  Beichner,  P.  Bruns,  A.  Chang,  R.  DeHaan,  J.  Gentile,  S.  Lauffer,   J.  Stewart,  S.  M.  Tilghman,  and  W.  B.  Wood.  “Scientific  Teaching.”  Science  304,  (Apr  2004):   521-­‐22.   Latour,  Bruno.  “Drawing  Things  Together.”  In  Representation  in  Scientific  Practice,  edited  by   Michael  Lynch  and  Steve  Woolgar,  19-­‐68.  Cambridge,  MA:  The  MIT  Press,  1990.   ———.  “Give  Me  a  Laboratory  and  I  Will  Raise  the  World.”  In  Science  Observed:  Perspectives  on   the  Social  Study  of  Science,  edited  by  K.D.  Knorr-­‐Cetina  and  M.  Mulkay,  141-­‐70.  London:   Sage  Publications,  1983.   ———.  “On  the  Partial  Existence  of  Existing  and  Nonexisting  Objects.”  In  Biographies  of   Scientific  Objects,  edited  by  Lorraine  J.  Daston,  247-­‐69.  Chicago:  University  of  Chicago  Press,   2000.   ———.  Pandora’s  Hope:  Essays  on  the  Reality  of  Science  Studies.  Cambridge,  MA:  Harvard   University  Press,  1999.     ———.  “The  “Pédofil”  of  Boavista:  A  Photo-­‐Philosophical  Montage.”  Common  Knowledge  4,  no.   1  (1995):  144-­‐87.   253       ———.  Science  In  Action:  How  to  Follow  Scientists  and  Engineers  Through  Society.  Cambridge,   MA:  Harvard  University  Press,  1987.   ———.  “Visualization  and  Cognition:  Thinking  with  Hands  and  Eyes.”  Knowledge  and  Society  6   (1986),  1-­‐40.   ———.  We  Have  Never  Been  Modern.  Translated  by  Catherine  Porter.  Cambridge,  MA:  Harvard   University  Press,  1993.   Latour,  Bruno,  and  Steve  Woolgar.  Laboratory  Life:  The  Construction  of  Scientific  Facts.  2nd  ed.   Princeton,  NJ:  Princeton  University  Press,  1986.   Law,  John.  “Actor  Network  Theory  and  Material  Semiotics.”  Working  paper,  Centre  for  Science   Studies,  Department  of  Sociology,  Lancaster  University,  Lancaster,  UK,  2007.  Retrieved   from   http://www.heterogeneities.net/publications/Law2007ANTandMaterialSemiotics.pdf.   ———.  “The  Materials  of  STS.”  Working  paper,  Centre  for  Science  Studies,  Department  of   Sociology,  Lancaster  University,  Lancaster,  UK,  2008.  Retrieved  from   http://www.heterogeneities.net/publications/Law2008MaterialsofSTS.pdf.     ———.  “On  the  Methods  of  Long  Distance  Control:  Vessels,  Navigation,  and  the  Portuguese   Route  to  India.”  In  Power,  Action  and  Belief:  A  New  Sociology  of  Knowledge?  Edited  by   John  Law,  234-­‐63.  London:  Routledge,  1986.   ———.  “On  Sociology  and  STS.”  Working  paper,  Centre  for  Science  Studies,  Department  of   Sociology,  Lancaster  University,  Lancaster,  UK,  2008.  Retrieved  from   http://www.heterogeneities.net/publications/Law2008OnSociologyAndSTS.pdf.     Lemke,  Jay  L.  “The  Missing  Context  in  Science  Education:  Science.”  Paper  presented  at  the   Annual  Meeting  of  the  American  Educational  Research  Association,  Atlanta,  GA,  April  1992.   Arlington  VA:  ERIC  Documents  Service  (ED  363  511),  1994.  Retrieved  from  http://www-­‐ personal.umich.edu/%7Ejaylemke/papers/gap-­‐sci.htm.   ———.  “Multiplying  Meaning:  Visual  and  Verbal  Semiotics  in  Scientific  Text.”  In  Reading   Science:  Critical  and  Function  Perspectives  on  Discourses  of  Science,  edited  by  J.R.  Martin   and  Robert  Veel,  87–113.  London:  Routledge,  1998.  Retrieved  from   http://academic.brooklyn.cuny.edu/education/jlemke/papers/mxm-­‐syd.htm.     ———.  “Semiotics  and  the  Deconstruction  of  Conceptual  Learning.”  Journal  of  Accelerative   Learning  and  Teaching  19,  no.  1  (1994):  67-­‐110.  Retrieved  from  http://www-­‐ personal.umich.edu/~jaylemke/papers/jsalt.htm.   ———.  Talking  Science:  Language,  Learning,  and  Values.  Westport,  CT:  Ablex  Publishing,  1990.   ———.  “Teaching  All  the  Languages  of  Science:  Words,  Symbols,  Images,  and  Actions.”  In   Science  Education:  Ideas  to  Improve  Your  Practice,  edited  by  Montse  Benlloch,  159-­‐86.   Barcelona:  Paidos  Iberica  Ediciones  SA,  2002.  Retrieved  from  http://www-­‐ personal.umich.edu/~jaylemke/papers/barcelon.htm.   254       ———.  Textual  Politics:  Discourse  and  Social  Dynamics.  London:  Taylor  &  Francis,  1995.   Lynch,  Michael.  “Discipline  and  the  Material  Form  of  Images:  An  Analysis  of  Scientific  Visibility.”   Social  Studies  of  Science  15  (1985):  37-­‐66.   ———.  “The  Externalized  Retina:  Selection  and  Mathematization  in  the  Visual  Documentation   of  Objects  in  the  Life  Sciences.”  Human  Studies  11  (1988):  201-­‐34.   ———.  “Representation  is  Overrated:  Some  Critical  Remarks  About  the  Use  of  the  Concept  of   Representation  in  Science  Studies.”  Configurations  2,  no.  1  (1994):  137-­‐49.   Lynch,  Michael,  and  Steve  Woolgar,  eds.  Representation  in  Scientific  Practice.  Cambridge,  MA:   The  MIT  Press,  1990.   Michigan  State  University  College  of  Education.  “A  New  Model  for  Teacher  Education:  MSU   Selected  to  Participate  in  Landmark  Initiative.”  New  Educator  (Spring  2003):  ii-­‐iii.   http://www.educ.msu.edu/neweducator/spring03/NewEdInsert.pdf.   Moore,  Elizabeth  A.  “Human  Brain  Has  More  Switches  Than  All  Computers  on  Earth,”  CNET   Health  Tech.  Posted  November  17,  2010.  http://news.cnet.com/8301-­‐27083_3-­‐20023112-­‐ 247.html.     National  Center  for  Improving  Student  Learning  and  Achievement  in  Mathematics  and  Science   (NCISLA).  “Learning  with  Understanding.”  Program  Overview.  Accessed  August  10,  2013.   http://ncisla.wceruw.org/publications/reports/TFUconcept.pdf.   ———.  “Program  Overview”  (emphasis  added).  Accessed  August  10,  2013,   http://ncisla.wceruw.org/whatwedo/index.html.   National  Research  Council  (NRC).  BIO2010:  Transforming  Undergraduate  Education  for  Future   Research  Biologists.  Washington,  DC:  The  National  Academies  Press,  2003.     ———.  Discipline-­‐Based  Education  Research:  Understanding  and  Improving  Learning  in   Undergraduate  Science  and  Engineering.  Washington,  DC:  The  National  Academies  Press,   2012.   ———.  “Executive  Summary.”  Next  Generation  Science  Standards  (June  2013):  1-­‐3.   http://www.nextgenscience.org/sites/ngss/files/Final%20Release%20NGSS%20Front%20M atter%20-­‐%206.17.13%20Update_0.pdf.   ———.  How  People  Learn:  Brain,  Mind,  Experience,  and  School:  Expanded  Edition.  Washington,   DC:  The  National  Academies  Press,  2000.   ———.  How  People  Learn:  Bridging  Research  and  Practice.  Washington,  DC:  The  National   Academies  Press,  1999.   ———.  Learning  and  Understanding:  Improving  Advanced  Study  of  Mathematics  and  Science  in   U.S.  High  Schools.  Washington,  DC:  The  National  Academies  Press,  2002.   255       ———.  National  Science  Education  Standards.  Washington,  DC:  The  National  Academies  Press,   1996.   ———.  Science  Teaching  Reconsidered:  A  Handbook.  Washington,  DC:  The  National  Academies   Press,  1997.   Pathe,  Simone.  “Obama  Hopes  Mapping  Project  Reveals  Brain’s  Mysteries.”  PBS  NewsHour   Extra.  Posted  April  8,  2013.  http://www.pbs.org/newshour/extra/2013/04/obama-­‐ launches-­‐project-­‐to-­‐understand-­‐the-­‐human-­‐brain/.     Popkewitz,  Thomas  S.  “The  Alchemy  of  the  Mathematics  Curriculum:  Inscriptions  and  the   Fabrication  of  the  Child.  American  Educational  Research  Journal  41,  no.  1  (2004):  3-­‐34.   ———.  “Dewey,  Vygotsky,  and  the  Social  Administration  of  the  Individual:  Constructivist   Pedagogy  as  Systems  of  Ideas  in  Historical  Spaces.”  American  Educational  Research  Journal   35,  no,  4  (1998):  535-­‐70.   ———.  “How  the  Alchemy  Makes  Inquiry,  Evidence,  and  Exclusion.”  Journal  of  Teacher   Education  53,  no.  3  (2002):  262-­‐67.   Pozzer,  Lilian  Leivas,  and  Wolff-­‐Michael  Roth.  “Prevalence,  Function,  and  Structure  of   Photographs  in  High  School  Biology  Textbooks.”  Journal  of  Research  in  Science  Teaching  40,   no.  10  (2003):  1089–1114.     Project  to  Advance  Science  Education  (PASE).  “Interactive  Timeline  –  Science  Education  in  the   U.S.A.”  University  of  Arkansas.  Last  accessed  on  August  10,  2013.   http://coehp.uark.edu/pase/itseusa/.     Richmond,  Gail,  Brett  W.  Merritt,  Mark  Urban-­‐Lurain,  and  Joyce  M.  Parker.  “The  Development   of  a  Conceptual  Framework  and  Tools  to  Assess  Undergraduates’  Principled  Use  of  Models   in  Cellular  Biology.”  CBE  Life  Science  Education  9,  no.  4  (2010):  441-­‐52.   Roth,  Wolff-­‐Michael,  and  Sung  Won  Hwang.  “On  the  Relation  of  Abstract  and  Concrete  in   Scientists’  Graph  Interpretations:  A  Case  Study.”  Journal  of  Mathematical  Behavior  25   (2006):  318-­‐33.   Roth,  Wolff-­‐Michael,  and  Michelle  K.  McGinn.  “Graphing:  Cognitive  Ability  or  Practice?”  Science   Education  81,  no.  1  (1997):  91-­‐106.   ———.  “Inscriptions:  Toward  a  Theory  of  Representing  as  Social  Practice.”  Review  of   Educational  Research  68,  no.  1  (1998):  35-­‐59.   ———.  “Knowing,  Researching,  and  Reporting  Science  Education:  Lessons  from  Science  and   Technology  Studies.”  Journal  of  Research  in  Science  Teaching  35,  no.  2  (1998):  213-­‐35.   ———.  “Science  in  Schools  and  Everywhere  Else:  What  Science  Educators  Should  Know  about   Science  and  Technology  Studies.”  Studies  in  Science  Education  29  (1997):  1-­‐44.   256       Roth,  Wolff-­‐Michael,  and  Kenneth  Tobin.  “Cascades  of  Inscriptions  and  the  Re-­‐Presentation  of   Nature:  How  Numbers,  Tables,  Graphs,  and  Money  Come  to  Represent  a  Rolling  Ball.”   International  Journal  of  Science  Education  19,  no.  9  (1997):  1075-­‐91.   Rudolph,  John  L.  “Reconsidering  the  'Nature  of  Science'  as  a  Curriculum  Component.”  Journal  of   Curriculum  Studies  32,  no.  3  (2000):  403-­‐19.   ———.  Scientists  in  the  Classroom:  The  Cold  War  Reconstruction  of  American  Science  Education.   New  York:  Palgrave  Macmillan,  2002.   Sadava,  David  E.,  H.  Craig  Heller,  H.  Gordon  Orians,  William  K.  Purves,  and  David  M.  Hillis.  Life:   The  Science  of  Biology.  8th  ed.  Sunderland,  MA  :  Sinauer  Associates,  Inc.  and  W.H.   Freeman  &  Co..,  2007.   Toulmin,  Stephen.  Cosmopolis:  The  Hidden  Agenda  of  Modernity.  Chicago:  University  of  Chicago   Press,  1990.   ———.  Return  To  Reason.  Cambridge:  Harvard  University  Press,  2001.   U.S.  Department  of  Education.  A  Nation  at  Risk:  An  Imperative  for  Educational  Reform.   Washington,  D.C.:  The  Commission  on  Excellence  in  Education,  1983.   Wickman,  Forrest.  “Your  Brain’s  Technical  Specs:  How  Many  Megabytes  of  Data  Can  the  Human   Mind  Hold?”  Slate  Magazine  Health  and  Science.  Posted  April  24,  2012.   http://www.slate.com/articles/health_and_science/explainer/2012/04/north_korea_s_2_ mb_of_knowledge_taunt_how_many_megabytes_does_the_human_brain_hold_.single.ht ml.     Wilson,  Christopher  D.,  Charles  W.  Anderson,  Merle  Heidemann,  John  E.  Merrill,  Brett  W.   Merritt,  Gail  Richmond,  Duncan  F.  Sibley,  and  Joyce  M.  Parker.  “Assessing  students'  ability   to  trace  matter  in  dynamic  systems  in  cell  biology.”  CBE  Life  Science  Education  5,  no.4   (2006):  323-­‐31.   Wiggins,  Grant,  and  Jay  McTighe.  Understanding  by  Design  (Expanded  2nd  Ed.).  Alexandria,  Va.:   Association  for  Supervision  and  Curriculum  Development,  2005.         257