CTED NEWER EDUCATIONAL A STUDY OF SELE S 21:. . 1.. r ._ 1.. y. .. 1.. , £12,... 5:15: VARIABLES AS COMPARED TO UPPER MEDIA ELEMENTARY STUDENT STANDARDIZED .k. I, ACHIEVEMENT scans Z :_ .1}: A ... 27....5 . \Il Thesis for the Degree of Ph. D. SITY MICHIGAN STATE UNIVER CLAIR ‘L. ROOD 3.3.53. a. In; Ixiv 1971 .A 5...: 0:: 9 3. . 2:55.45, . 7. .. 3.5. 1?‘r “Its This is to certify that the thesis entitled A STUDY OF SELECTED NEWER EDUCATIONAL MEDIA VARIABLES AS COMPARED TO UPPER ELEMENTARY STUDENT STANDARDIZED ACHIEVEMENT SCORES presented by Clair L. Rood has been accepted towards fulfillment of the requirements for Ph. D. degree inEdnsnLLQn— Date February 18, 0-7639 ?u3 S .. 2 ‘r‘ , r ‘T E_, a _‘ ;./’ ‘y, . I. .‘-. 4- .- d‘ .8 l \‘ .I Eflltz} U K}. dicltc University .' ffi' 3 «I (PM? (c ABSTRACT A STUDY OF SELECTED NEWER EDUCATIONAL MEDIA VARIABLES AS COMPARED TO UPPER ELEMENTARY STUDENT STANDARDIZED ACHIEVEMENT SCORES By Clair LaVern Rood This eXploratory field research develOped from involvment in exemplary programs of student instruction, which made use of New Educa- tional Media (NEM) as the tools for individualized learning. In order to bring about improved student achievement, educators must isolate the many environmental variables which affect students. It was the design of this study to select seven NEM variables, accept the remain- ing influencing variables as a part of normal classroom conditions, and attempt to measure their relationship to student achievement. Survey instruments were deve10ped and data gathered from admini- strators, principals and teachers on the following NEH Independent Variables: A. Does teacher ability to recognize behavioral objectives have an effect on student achievement? B. Does teacher attitude toward NEH have an effect on student achievement? C. Does the administrative attitude support of NE}! have an effect on student achievement? D. Does the amount of teacher training in NW have an effect on student achievement? E. Does the availability of NEM software have an effect on student achievement? Clair LaVern Rood .F. Does the availability of NEM hardware have an effect on student achievement? G. Does administrative financial support of NEM have an effect on student achievement? H. Do all of the preceeding seven NEM variables, taken as a whole, have an effect on student achievement? A weighting scale of relative value, was established for NEH which provided a single Standard Score value for identifing each school on MM. This value was compared to the Dependent Variable - Student Achievement. Student Achievement was established on a post-testing of 1,808 Lth, 5th, and 6th grade students from 13 rural school districts in the C00perative Educational Service Agency #11 of the State of Wisconsin. The Composite Grade Equivalent Score and the Student Study Skills Score, from a Spring 1970 teacher—administered California Comprehensive Test of Basic Skills- Level 1 test battery, was used as Dependent Variables. A Standard Composite Grade Equivalent Score was calculated across all schools. An Analysis of Variance statistical treatment of the data revealed that as a group the NEM Independent Variables had no significance to the Dependent Variables. Additional analysis of each Dependent Vari- able and each Independent Variable revealed two hypotheses, ”Teacher Training" and "Availability of Hardware," which did show a correlation of at least 1.56 at the .05 level of probability. The results of this investigation indicate a desperate need for the identification of the environmental factors which do have an effect on learning, and the effect of NEH in particular, which the instruments used in this investigation did not adequately identify. A STUDY OF SELECTED NEWER EDUCATIONAL MEDIA VARIABLES AS COMPARED TO UPPER ELEMENTARY STUDENT STANDARDIZED ACHIEVEMENT SCORES BY ‘ I L. {I (L. Clair L’f‘ Rood A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Instructional Deve10pment and TechnolOgy 1971 ACKNOWLEDGEMENTS The author wishes to express thanks to the members of his com- mittee; Dr. James L. Page, Chairman, Dr. Elwood Miller, Dr. Norman Bell, and Dr. William Sweetland, for their interest, encouragement and guidance while at Michigan State University as a doctoral student; for without their understanding concern, the program may never have been completed. A sincere thanks goes to the Director, Mr. Robert Tremain, Co- ordinators, and office staff of the Cooperative Service Agency #11, for it was with their helpful encouragement and assistance that the necessary contacts were made and data gathered. By_the same token, a thanks goes to all of the superintendents, principals and teachers, of CESAI#11, who responded c00peratively to the survey instruments. A special word of thanks is extended to the Director, Mr. Viggo Rasmusen and colleagues in the Audiovisual Center at La Crosse, without whose continued encouragement and support this program may not have been started and carried through. Finally, a very warm thank you to my family; my wife Doris, and children David, Susan and Jeffrey, in appreciation for their committment and encouragement during the tribulations and frustrations of seemingly endless years of schooling. C.L.R. ACKNOWLEDGMENTS . . . . LIST OF TABLES . . . . LIST OF APPENDICES . . CHAPTER I. II. III. THE PROBLEM . . Introduction . The Purpose of the Study Limitations of the Study Description of Terms Overview 121':va OF THE HTERATURE TABLE OF CONTENTS New Educational Media Status Project TREE Individualizing of Learning through Media-Rural Discussion of Previous Research DESIGN AND PROCEDURES . . . . . Apercu . . . . The POpulation Instrumentation Data Collection Analysis of Data Summary . . . . iii PAGE ii 10 10 12 12 22 26 30 33 33 33 35 37 39 AS CHAPTER PAGE IV. ANALYSIS OF RESULTS . . . . . . . . . . . . . . . . . . . . . A6 Descriptive Data . . . . . . . . . . . . . . . . . . . . . A6 Independent Variables . . . . . . . . . . . . . . . . . . A6 Dependent Variables . . . . . . . . . . . . . . . . . . . 63 Analysis of Data . . . . . . . . . . . . . . . . . . . . . 67 Summary of Data . . . . . . . . . . . . . . . . . . . . . . '75 V. DISCUSSION AND CONCLUSIONS . . . . . . . . . . . . . . . . . 80 Summary of Procedures . . . . . . . . . . . . . . . . . . . 80 Summary of Findings . . . . . . . . . . . . . . . . . . . . 81 Conclusion and Discussion . . . . . . . . . . . . . . . . . 82 Implications for Further Research . . . . . . . . . . . . . 84 E mmmmm O O O O O O O O O O O 0 O O O O O O O O O O O O O O O APPMI cm 0 O O O O O O O O O O 0 O O O O O O O O O O O C O O O O 92 iv TABLE 2-1. 4-1. A-Z. 4-3. h-A. A-S. 4-5. 4-6. 4-7. A-B. h-9. A-lO. A-ll. h-12. A-13. A-lh. h-Jho “-150 ($-15. 4-16. 14.17. LIST OF TABLES Instructional Fanctions of Various Media . . . Teacher Reaponse to NEM Instruments . . . . . NEM Software Weighting Index . . . . . . . . NEM Weighted Software Scores . . . . . . . . . NEM Hardware Weighting Index . . . . . . . . . NEM Weighted Hardware Scores . . . . . . . . . NEM Weighted Hardware Scores (continued) . . . Administrative Support - Attitude . . . . . . Administrative Support - Financial Allowances Mean Standard Scores (2) Independent Variables Weighting Index - Independent Variable . . . . Adjusted NEM Composite Standard Scores . . . . Compiled Student Grade Equivalent Scores . . . . . . Adjusted Achievement Scores (T-scores) on Dependent variables00000000000000.0000. Intercorrelations of all Independent Variables . . . Individual NEM Variables and Student Achievement T . Individual NEM Variables and Student Achievement T (continued) 0 O I O O O O O O O O O O O O I O O O 0 Individual NEM Variables and Student Study Skills T Individual NEM Variables and Student Study Skills T ( continued) 0 O O O C O O O O O O O O O O O O O O 0 Correlation of NEM Composite Standard Scores with mpendent variables 0 O O O O O O O O O O O O O O Ranking on NEM Compared to Dependent Variables . . . PAGE 15 A7 50 51 53 SA 55 57 58 60 61 62 6A 66 7O 71 72 73 76 77 APPENDIX A. Instructional Media Stimulus Relationships to Learning Objectives - Table I . . . . . . . . . . . . . . . . B. Request Letter to CESA #11 . . . . . . . . . . . . . . C. Response Letter from CESA #11 . . . . . . . . . . . . D. POpulation Identification - Table II . . . . . . . . . E. Introductory Letter to Teachers . . . . . . . . . . . F. Directions for Completing Teacher Survey Instrument . G. Teacher Personal Data Sheet . . . . . . . . . . . . . H. Teacher Behavioral Objectives Survey . . . . . . . . . I. Teacher NEM Attitude Inventory . . . . . . . . . . . . J. Compiled Teacher ReSponse to NEM Variables - Table III K. Introductory Letter to Para-professionals . . . . . . L.NEMSoftwareSurvey................. M. NEM Software Reaponse - Table IV . . . . . . . . . . . N. NEM Hardware Survey . . . . . . . . . . . . . . . . . O. NEM Hardware Reaponse - Table V . . . . . . . . . . . P. Introductory Letter to Administrators . . . . . . . . Q. Directions for Completing Administrator Survey Instrument R. Administrator Personal Data Sheet . . . . . . . . . . . . 8. Administrative Financial Support Instrument . . . . . . . T. Administrative NEM Attitude Inventory . . . . . . . . . . LIST OF APPENDICES PAGE 93 9A 95 96 99 100 102 108 110 111 112 113 114 115 116 117 118 119 TABLE PAGE h-18. Summary - Hypotheses Tested . . . . . . . . . . . . . . . . 79 APPENDIX TABLES I. Instructional Media Stimulus Relationships to Learning Objectives 0 O O O O O O C C O O O O O O O O O C O O O O 93 II. Popmtion Identification O O O O O O O O O O O O O O O O O 96 III. Compiled Teacher ReSponse to NEM Variables . . . . . . . . . 108 IV.NEMSoftwareRe3ponse...................112 V. NEM Hardware ReSponse . . . . . . . . . . . . . . . . . . . 11h CHAPTER I THE PROBLEM Introduction The American educational scene had been one of slow continuous change from the pre—World War II years to the present. With the return of great numbers of service men, the tenor of the educational progress quickened. The availability of Federal Funding, to the states and the local school districts, played an important roll in not only creating new educational programs, but also in providing new methods through which technology could be utilized as a teaching tool. Morris, writing in a position paper of a sub-committee of the NBA in 1963 which was created to study the function of media in the public schools, has defined educ- ational media as 'those things which are manipulated, seen, heard, read or talked about, plus the instruments which facilitates such activity.’1 It would seem that educational media could then be classified in the following several forms. (1) A better tool for teaching, (2) a more complete communicational tool, and (3) a more competent research report- ing method. Ely describes the role of media or technology in education in the following manner: Methodology based on the principle that a variety of audiovisual media and experiences correlated with other instructional materials lBarry Morris, "The Function of Media in the Public Schools,” (A Task Force Position Paper), Audiovisual Instruction, 8, No. 1 (January 1963), p. 11. overlap and reinforce the value of each other. Some of the material may be used to motivate interest; others, to commun- icate basic facts; still others to clear up misconceptions and deepen understanding.2 Investigation into teacher attitudes toward media utilization has been extensive since about 1954. In 1959, Kelly identified 16 factors related to teacher attitudes toward instructional media. In 1963, Knowl- ton found disagreement with other research findings that indicated additional preparation in the area of audiovisual instruction changed attitudes. Rather, he suggested that information concerning audiovisual instruction was instrumental only in slightly changing attitudes shown.3 Working with the same pOpulation in 1962, Knowlton and Hawes found that the negative attitudes were reflected by the barriers created through utilization and not alone through the lack of understanding of educational media. While reporting on Project Discovery in 1966, Eboch commented that teachers tend to use media as they are found available, but he did not comment on the effectiveness of media in the learning situation. With the increased availability of funds from the Office of Educ- ation, as well as such other sources as the Ford Foundation, there has appeared a great influx of software and hardware with which educators 2Donald Ely, "Alphabetical List' of Terminology " Audiovisual Communications Review, 11, No. 1, Supp. (January 19 33, p. AA. 3cnar1cs Aquino, "Teacher Attitudes Toward.Audiovisua1 Instruction as They are Influenced by Selection Factors Within Teaching Environments,” Audiovisual Communication Review. Vol. 18, No. 2, 1970. pp. 187-195. 3 needed to become proficient if they were, in fact, to be able to compete on an equal fboting with commercial distribution systems. Godfrey, in 1965, documented this growth of school inventories; while only a short time before, in 1963, Battram found that with the availability of soft- ware and hardware teachers tended to show greater interest in its use and tended to learn more. Previous researchers have studied various factors which could have an influence on teacher understanding and utilization of New Educational Media. (Abbreviated as NEM in the balance of this report). Over 1,000 physical barriers to media utilization were identified by Miller in 1965.h Fear of mechanization and the loss of self-importance were id- entified by Handleman in 1960 as negative influences by teachers for the lack of utilization of the NEM, specifically television. The major implication of the search of the literature is that educational NEM is utilized to a higher degree when there is also a higher availability ratio. However, Aquino says: there is little evidence to indicate that increased utilization arising from availability of audiovisual equipment and materials is linked with improved teacher attitudes toward such utilization. It may be assumed that improved attitudes imply a desire on the part of a user which not only leads to increased utilization, but also to more effective utilization of educational media. Since it is a tenet of those associated with audiovisual education that improved utilization methods and techniques must be employed by teachers if educational media are to have the desired impact on assisting teachers in reaching their educational objectives, the assumption that increased availability of educational media leads to improved utilization cannot be supported.5 “Ibid., p. 187. 5Ibid., p. 189. I. Torkleson inferred this same feeling when he addressed a Regional Research Conference by saying that the evidence seems to indicate that the present knowledge of NEM is not being applied by teachers, professors nor school administrators in their instructional programs.6 The preceeding paragraphs have highlighted the research of the past decade. The indications are that where E4 is available the util- ization trends are greater than where the availability of NE! is low. Also directly related to availability of N34 is the favorable attitude toward NB! utilization of educators. The studies in no way indicated a relationship between student achievement , teacher attitude, and avail- ability of NBA. The intent of this investigation is to attempt to determine the extent to which seven selected media factors (independent or predictor variable) are related to measured student achievement (dependent var- iable) . 6G. M. Torkleson, ”Implications of Research in Newer Educational Media for the Role of the Teacher and for Teacher Education", Regional Research Conference on Newer Educational Media. (Pennsylvania State University, 1 1. The Purpose of the Study The purpose of this study is to obtain descriptive data on six selected NEM variables which are commonly found in todays classroom en- vironment, and attempt to determine the extent to which they may be related to student achievement. It is also intended that inferences concerning the possible effects of NEM on student achievement would be drawn from the data gathered, such that other schools having a similar learning environment might be able to anticipate similar impact of NEM on achievement. To achieve these purposes, the study focused on the following questions:* A. Does teacher ability to recognize behavioral objectives have a relationship to student achievement? B. Does teacher attitude toward NEM have a relationship to student achievement? C. Does the amount of teacher training in NEM have a relation- ship to student achievement? D. Does the availability of NEM hardware have a relationship to student achievement? E. Does the availability of NEM software have a relationship to student achievement? F. Does the administrative support of NEM have a relationship to student achievement? *Selected by the researcher from the many environmental stimuli present which were felt to have a relationship to student achievement. 6 G. Do all of the preceeding six NEM variables, taken as a whole, have a relationship to student achievement? ‘ This study is designed to look critically at several selected NEM factors which have a common occurance in the classroom of todays schools and to determine to what extent they may contribute toward increased student achievement as measured by the California Comprehensive Test of Basic Skills - Level 2. Selected as participating schools in this survey were the schools of the COOperative Educational Service Agency #11, headquartered in La Crosse, Wisconsin. (For the Balance of this study, the agency will be referred to as CESA-#11). CESA-#11 is one of nineteen such service agencies which was created by Wisconsin State law in 1965 to replace the former county superintendents.7 The CESA‘#11 is composed of twenty-five school districts within a ten—county area, approximately L,000 teachers and h3,500 students. In the spring of 1967, 15 schools were surveyed by this writer to determine the extent of NEM facilities and the amount of NEM pre- paration the teaching personnel had received. Based on the results of this survey, a Central Planning Committee was formed to determine what might be done to improve the learning environment of the students. The Planning Committee and CESA-#11 sought and received a Planning Grant or 7Donald Jacobson, "The Effectiveness of C00perative Educational Service Agencies in Wisconsin", A Doctoral Thesis. University of Wisconsin 1970. 7 Mini-Grant under Title III PL89-10 to provide the necessary environmental changes. The grant provided for workshOps in ND! and for a detailed study of the teaching environment such that a three-year Operational Grant, entitled "Individualizing Learning Through Media-Rural", is now in its third year of Operation. The grant has provided summer workshOps in NEM for the faculties, additional NEM hardware and software, as well as para-professional and clerical assistance for each school team. A local Instructional Materials Center was created within each school to assist the project teachers and their students. Support for the local INC and consultation for the teachers, as well as Operation of the many summer and in-school NEM workshOps was provided through the guidance of the staff of the Audiovisual Center at Wisconsin State Universittha Crosse. The four major objectives upon which the Operational Grant was founded were: 1. To enable rural teachers to more nearly meet the intellectual needs of the individual learner through develOpment of an instructional program making the maximum use of instructional media in large group, small group, and individualized learn— ing situations. 2. To develOp teacher competency in the use of instructional media, preparing instructional objectives, and designing instructional sequences to accomplish the objectives. 3. To make instructional media readily available to rural area teachers and students. ‘ A. To bring about adeption of promising innovative procedures in the schools. Research of the past decade indicates that much concern and inp terest was generated regarding the availability of NEM as it affected 8CESA #11, La Crosse, Wisconsin, Operational Grant 1969-70. 8 teacher attitudes; also, how teacher training in ND! affected utilization. Present research has failed to indicate how the above and additional sel- ected um variables affect student achievement. In order to obtain data relevant to the selected environmental variables singled out for this study, a survey form was prepared. The several parts were so constructed as to measure teacher attitude toward NIH on a six-point Likert-type scale, ranging from agree strongly to dis- agree strongly; teacher ability to recognize behavioral objectives on a sixteen item instrument, reaponding yes or no; and the amount of teacher training in NEM as recorded on a personal inventory sheet. The amount of NEM hardware and software per school team was obtained through inven- tory completed by the para-professional. The amount of administrative support was determined through principal response to the same attitude inventory form used by the teachers and personal contact with each super- intendent, followed up with a letter requesting the necessary 1969 budget allocations for their project schools in grades K-8. This budget infor- mation.was also varified through the CESA #11 end of the year reports. The measure of student achievement was obtained from the CESA #11 office records of the 1969 administration of the California Comprehensive Test of Basic Skills—Level 2. The portion of concern was the Composite Grade Equivilent Score and the Study Skills Score of each student in the project school in the nth, 5th, and 6th grade whose teacher is a member of the project team. In summary, the data was gathered about six distinctly different selected NEM variables from a p0pulation consisting of 1,800 students, 80 teachers, 15 principals, and 15 superintendents of the project schools in CESA #11. Limitations of the Study There are certain limitations imposed on field research by its ex post facto nature. Kerlinger points out that: Ex post facto research may be defined as that research in which the independent variable or variables have already occurred and in which the researcher starts with the observation of a dependent variable or variables.9 This study deals with only the 4th, 5th, and 6th grade students, their teachers, principals, and superintendents within the project schools of CESA‘#11. The findings of this study may be generalized to other classrooms and schools only in as much as the learning environments are similar. The statistical procedures used in the study are restricted to the Analysis of Variance (F Test) based on student achievement tests as reported on the California Comprehensive Test of Basic Skills - Level 2. The differences which may be found in student achievement scores via this analysis would be hypothesized to parallel the differences between schools on the individual and the composite NEM variables. Both correlation and analysis of variance statistical techniques will be applied to the mean data for all schools studied, and if any significant mean differences are detected in the analysis of variance, then apprOpriate post hoc analysis will be performed. 9Fred Kerlinger, Foundations of Behavioral Research (New York: Holt, Rinehart and Winston, Inc., 196A), p. 369. 10 Description of Terms During the past twenty years, many new teaching aids have been develOped. Some of them are sufficiently elaborate to change or to re- place classroom communication and instructional patterns which, until their development, were limited to teacher and student. The following terms and definitions will assist in interpreting this study: New Educational Media Radio, television, motion pictures, slides, filmstrips, record players, tape recorders, teaching machines, programmed learning machines, and some computers will be considered New Educational Media. New Educational Media will be abbreviated as NEM. Equipment All projectors and other mechanical devices would be classified as equipment. They may also be referred to as "hardware". Materials All films and other visual diaplays are classified as materials. They may also be referred to as "software". Overview In the first chapter, an attempt has been made to present cagnate information about the statement of the problem. A brief description of the sample pOpulation, method of data collection, and a brief statement of data handling were also included. In the second chapter, pertinent related literature is reviewed which looks at the technology of NEM and research methods which govern field research. 11 In Chapter III, the methodology and procedures of the study are presented in detail, including a description of the pOpulation from which the sample pOpulation was taken, the develOpment of the survey instruments, and all statistical procedures for analyzing the data gathered. The analysis of data and statements of inference are provided in Chapter IV. Chapter V contains the summary of this study, any conclu— sions or inferencies reached, and recommendations for further research. CHAPTER II REVIEW OF THE LITERATURE New Educational Media Status The application of NEM, often referred to as technology, has only begun to affect education. It has become more evident since the Atomic Bomb and Sputnik that the survival and the rate of progress of our nation depends upon the widespread understanding and use of technology. Educa- tion, ranking as one of this nations largest businesses, and educational planners, must apply a cognizance of technology to the educational problems of underachievers irreSpective of the students age, nationality or economic background. Through the use of media, instructional units can be created in a permanent form that can be studied in detail utilizing apprOpriate research techniques. Learning from these instructional sequences can then be increased to a maximum by progressive improvement of the instructional message and prOper selection of the channels of communication. The resulting instructional material is generally superior to most instruction and potentially superior to the best instruction. Education must put technology to work for the cause of education.1 In 1962, the Department of Audiovisual Instruction of the NEA developed a position paper on the role of media in the public schools. In writing the paper, Morris2 suggests that there are many societial forces at work which encourage the use of technology in instruction. 1Loran Twyford, Jr., "Educational Communications Media," En clo die of Educational Research, (The MacMillan Co., 1969) 4th Ed., pp. 3 7-80. 2Barry Morris, "The Function of Media in the Public Schools," Audiovile Instruction, Vol. 8 (1963), pp. 9-14. 13 Two functions of media which were presented are, (1) media is to supple- ment the teacher by increasing his effectiveness in the classroom, and (2) media is utilized alone for instruction. The use of technology in these manners thus enriches present instruction as well as provides an instructional system which may operate effectively independent of the teacher. In whichever manner technOIOgy is used, the material presented must be directly related to the instructional goals of the learner en- volved. The trend today is to provide education to all learners, from pro-school to adult. The advent of television has provided communication with the masses. In addition to television, new courses are now taught via programmed texts, records, audio-tape, film, teaching machines, filmstrips, and by computer assisted instruction. The teacher of today scan receive support from a vast reserve of teaching and learning materials. The Educational Media Index, first created in 196A by the Educational Media Council, requires lb volumes and lists approximately 30,000 items. There are over 5,000 new films, filmstrips, tapes, recordings, models, and graphic materials which become newly available each year.3 This avalanche of instructional materials has been made readily available to all schools through the National Defense Education Act of 1958 and the Elementary and Secondary Education Act of 1965. Research on certain aspects of technology, mainly educational film, television and programmed instruction, has been supported through 3W0“: 22‘ 9.11;.” P- 367- 1A funds supplied by the Ford Foundation, Title VII of the National Defense Education.Act and the United States Department of Defense. While there have been voluminous research studies completed, the rate of adaption fer instructional uses has been disappointingly slow. - The gap from research to accepted classroom techniques was par— tially bridged by Gagne', writing in "The Conditions of Learning,” by his summary of media functions as shown in Table 2-1. The major varieties of media for instruction, as well as certain combinations of media were presented. The table indicates, for each medium, whether it could or could not perform the instructional duties requested of it. The examine ation of row one points out that both oral and printed verbal communications are limited in usefulness for presenting stimuli. This is true because they present only verbal material which often requires additional real objects or some form of pictorial representation for learning to rapidly take place. Row eight indicates that the media which is able to present information successfully provides limited feedback from the student. RasmussenA also attempted to bridge the gap between research and the learner in 1960. His writings on "Instructional Media Stimulus Relationships to Learning" support ideas that for improved learning, a stimulus should be a combination of many sensory perceptions and not designed to effect only one sensory organ. “Warren Rasmussen, "Instructional Process and Media Integration in the Creative Arts?, Instructional Process;and Media Innovation, edited by Robert Weisgerber, American Institute for Research, Palo Alto Calif- ornia (Rand McNally Co., Chicago 1960), p. 157. (See Appendix.A . 15 TABLE 2-1 INSTRUCTIONAL FUNCTIONS OF VARIOUS MEDIA5 Objects; Oral Still Moving Teach- Demon- Commu- Printed Pic- Pic- Sound ing Ma- Function stration nication Media; tures tures Movies chines Presenting Yes Limited Limited Yes Yes Yes Yes the stimulus Directing NO Yes Yes No No Yes Yes attention and other activity Providing Limited Yes Yes Limited Limited Yes Yes a model of expected perfor- mance Furnishing Limited Yes Yes Limited Limited Yes Yes external Prompts Guiding No Yes Yes No No Yes Yes thinking Inducing Limited Yes Limited Limited Limited Limited Limited transfer Assessing No Yes Yes No No Yes Yes attainp ments Providing Limited Yes Yes No Limited Yes Yes feedback J 5 Robert Gagne', The Conditions of Learnin , (Chicago: Holt, Rinehart and Winston, Inc., 19655, p. 284. 16 Researchers have generally concerned themselves with indicators of effectiveness of media, while occasionally delving into student and teacher acceptance of media as a possible method of understanding the lack of media research implementation in instructional programs. From this start, a new concern, operational research, was develOped. It has been shown that while a form of media does have an effect on instruction it has not become a popular tool for instruction, due to the extreme cost involved to initiate a full scale program. An example of this phenomenon could be television, data banks, informational retrieval and computer assisted instruction. When Operational research is undertaken, the re- searcher expresses concern with many areas of knowledge and the interre- lationship each has with the other. Operations research concerns itself with the degree of change, or learning aquired, in realistic prOportion to the administrative committment required to carry out the program. In 1969, a conference sponsored by the Department of Audiovisual Instruction, NEA, was held at Syracuse University to explore Operational research.6 Coming out of that conference was not only concern with operational research, but also the design of learning or a systems analysis approach to solving learning problems. Since that 1964 conference, the systems approach has been adOpted by Michigan State University and other universities as the prOper procedure 6Eugene Oxhanler, "Operational Research and System Analysis as Applied to Media?, Rgpgrt of a Conference - Syracuse Universit , (1964) p. 102. h, 17 for the correct design Of learning units. Twyford states, in 1956, that there are characteristics of media which have little or no effect on learning which were identified by Carpenter and himself. They are: Music, optical effects, stereOSCOpic projection, attention-gaining devices, dramatic sequences, motion, and realistic settings often result in little improvement in learning. While preparing learning units through a systems approach, an awareness of the foregoing media characteristics must be considered so that only the form or forms of media whose attributes indicate the greatest likelyhood of success should be included. When this is accomp- lished, the teacher will be permitted to become a resource person, counselor of learners, or a supervisor of instructional patterns. To fully capitalize on media advantages, educational efficiency must be considered. Twyford says "that instructional efficiency can be obtained if the time saved through the use of media is used to teach additional matter."8 One of the more important aspects of media application to instru- ctional patterns is that of administrative committment. Twyford talking about administrative committment in his writings says: The more successful media applications are usually characterized by a firm administrative policy supporting the use of media backed up by an adequate supporting program of personnel, equipment, and materials. One cannot expect a sizeable change in instructional methods without 7Twyford, 93. 933., p. 372. 81bid. , p. 372. 18 a comprehensive plan to bring about change. Often initial costs may greatly exceed current Operational costs.9 This, then, presents administrative reasoning concerning the degree of financial support which a school may give any innovative and creative approach to the instruction of its' students. The acceptance of technology as a method of assisting communi- cations for instructional purposes is very important because the degree of acceptance determines, in large part, the extent to which the unique advantages of media will be used. Erickson states: When instructors develOp penetrating insights into the breadth and variety of teaching objective, when they understand better the difficulties in communication, and when they come to feel a real concern for student achievement in both large and small groups, they will recognize more clearly the need for help that audiovisual materials can give, help for the teacher that is rewarded in help for the student, help that is urgently needed if the learning process is to proceed efficiently. Morris says, "that the environment which contributes to the pro- blems of education also contains the elements that can help to solve them."11 Discussing the acceptance of technology, Norberg states: The newer educational media are means which will be accepted or re— jected as a means to ends. PeOple who try new tools do so to accomplish new tasks or to perform old tasks in a new and possibly better way . . . . These are not just strong and ingenious tools; they are also means that will be used to accomplish some purpose beyond their own use, implement some prOgram. They challenge educators to take another look at their goals, both eXplicit and implicit, to determine whether the goals are still sound, to decide whether the new media 91bid., p. 373. 10Carlton Erickson, Fundamentals of TeachinggWith Audiovisual Technology, (New York: The MacMillan 00., 1965), p. 2S. 11Barry Morris, "The Function of Media . . . . ," p. 11. 19 will help to implement them, possibly to change the course of the instructional program as well as the lives of the teachers and students who are involved. Since no clear evidence appears showing patterns of influence within the schools, some Observers have drawn the conclusion that there are no institutional change agents in the public schools. Carlson says: the change agent counterpart of the county extension agent has no office in our public school enterprise. And, as has been indicated, many attribute the slowness of change in educational practices to the absence of a change agent. Others feel that administrators control media acceptance in the public schools. Brickell observes that "two distinct groups of peOple might be expected to influence structural change in the local schools",14 the public which is outside the school system, and the professional staff itself. New types of instructional programs are introduced by adminstra- tors. Rearrangements of structural elements of the institution depend almost exclusively upon administrative initiative5 Teachers are not change agents for innovations of a major scape. It is suggested by Brickell that administrators act as gate keepers for the innovative process within their jurisdiction; " the administrator 12Kenneth Norberg, Media and Educational Innovation, Meierhenry (ed.), (University of Nebraska Press, Lincoln, Nebraska, 1964), pp.368—9. 13Richard Carlson, §t_gl., Chan e Process in the Public Schools, (Eugene: The Center for Advanced Study of Educational:Administration, university of Oregon, 1965), p. 4. 1“Henry Brickell, "State Organizations for Educational Change: A Case Study and a PrOposal", Innovation in Education, (ed.) Miles (New YOrk: Bureau of Publication, Teachers College, Columbia University, 1966), p. 1695. ~ 151mm, p. 503. 20 may promote or prevent innovation. He cannot stand aside, or be ignored."16 An example of this is shown by Kelly17 who studied several points of influence on teachers' attitude toward the adOption 0f audiovisual materials. Having collected data from over 900 teachers in the Boston area, he found a significant relationship between teacher attitude toward audiovisual materials and whether or not they had had the encouragement of their various administrative personnel in the school system and the availability of materials, as a factor in determining teacher attitude toward the use of audiovisual materials.18 From this, we deduce there are several extenuating factors that not only affect the degree of change within a given school, but also affect the rate of innovation. Aquino19 points out that previous researchers have identified various factors which influence teacher utilization of educational media. These factors range from the amount of media in teacher training to fear of mechanization and the reduction of self-importance. This range of factors is further 16Ibid. 17Gaylen Kelly, "An.Analysis of Teachers' Attitudes Toward the Use of Audiovisual Materials" (unpublished Ph. D. dissertation, Boston University, 1959). . 18Gaylen Kelly, "A Study of Teachers' Attitudes T0ward.Audio-Visual Materials," Educational Screen and Audiovisual Guide, March, 1960. p. 119. 19Charles Aquino, "Teacher Attitudes Toward Audiovisual Instruc- tion as They are Influenced by Selected Factors Within Teaching Environments," AV Communications Review, Vol. 18,2 (Summer 1970) p. 187. 21 pointed out by Aquino in his summation of the investigations of Eboch, Godfrey, and Battram. Aquino states: Eboch (1966), in reporting on Project Discovery, noted that teachers will utilize audiovisual materials when they are available but did not comment on the effectiveness with which educational media were applied to the teaching-learning process. The growth of educational media inventories within schools and school districts was documented by Godfrey (1965) who noted that teacher requests were among the more influential channels for having school boards provide more audio-visual equipment and materials; while Battram (1963) found that teachers who perceived audio-visual materials to be readily available tended to learn more about the effective use of those tools.20 A major implication of the literature is that educational media usage is in direct relationship to its availability. There is some evidence to support the postulate that teacher attitude toward media is linked to availability; however, "the assumption that increased avail- ability of educational media leads to improved utilization cannot be supported."21 The availability of media was studied by Aquino, who attempted to determine differences between attitudes on the part of the teachers who perceived various degrees of availability and accessability of 22 The resultant educational media within their teaching environments. implication of his research points out a need for future investigation intoteacher attitudes toward media as compared to teacher utilization of media in the learning environment when considering the availability of media. 201bid., p. 188. lehiéo. p- 189- 2222i2.. pp. 189-19h. 22 Operational research, of the type described on the preceeding pages, is being undertaken in two areas in Wisconsin. Project TREE (Teacher Research in Elementary Education)23 was designed to investigate the affect of high media availability upon teachers and students at the Ames Laboratory School at Wisconsin State University — River Falls, Wis- consin; while the CESA #11, of the State of Wisconsin, is completing the third year of a Title III Grant for the "Individualizing of Learning Through Media-Rural."2h A closer examination of each of these research areas provided the incentive and partial background for this investigation. Project TREE: The Ames Laboratory School, River Falls, Wisconsin is a member of the Wisconsin State University System. The Lab School is charged with the education of students, K-9, as well as providing for the training of prospective teachers from the State University at River Falls. The role of the Lab School is described more adequately by Dr. Krueger, who served as Chairman of the TREE Executive Committee. Ames Laboratory School instructors assist in the training of student teachers within their classrooms, as well as providing further input into the teacher-training process by teaching at least one elementary methods class each academic year. Student Observers also enter the classrooms as a required portion of their psychology of learning sequence. With this total teachernstudent exposure to media utilization, it was felt that teacher attitudes and evaluations would be reflected 23Robert Krueger, "Project.TREE -.A FOur Year Study on the Impact of Media Availability 0n Teachers and Students", (River Falls: Wisconsin State University, 1969) (Mimeographed.) 2[‘Roland Solberg, "Individualizing Learning Through Media-Rural", (La Crosse: CESA #11., 1970) (MimeOgraphed.) 23 in the end product of the College of Education, the beginning teacher. The intimate teacher~student relationship would have to result in similar reactions. The initial research project was conceived around grades K-3 at the Ames School. The original program was based on a three-year study of instructional media and the affect on learning which would be created through ultimate classroom use of media. The develOpment of this pro- ject was a joint venture of EncyclOpaedia Britannica Films Department of Education and Dr. Eugene Kleinpell, President of Wisconsin State University - River Falls. The initial year of Operation was 1964-65. In 1965-66, Project TREE was eXpanded to include the hth grade. Later Project TREE was to include grades K-9. With this expansion, Project TREE became the only K-9 Media Availability Study on a univer- 26 sity campus in the United States. Data was gathered from the faculty and students involved in the project through a Summary and Evaluation Form, which was completed periodically throughout the project. The Teacher Summary and Evaluation Form asked responses to the following questions: 1. 2. 3. A. In what ways has Project TREE affected your teaching approaches and procedures? In what way has Project TREE affected your pupils' interests and attitudes? In what ways has Project TREE affected your pupils' learning? In what ways has Project TREE been valuable to you as a teacher? 25Robert Krueger and Alton Jensen, "High Media Availability in The Teacher Education Process," (River Falls: Wisconsin State Univer- sity, 1970) (Mimeographed.) 26Krueger, gp.‘git., p. 41. 2A 5. In what ways has Project TREE created difficulties for you as a teacher? 6. What wouldzyou recommend to increase the effectiveness of Pro- ject TREE? The student teachers working within the project were not solicited, although reSponses were obtained from grades 3 through 8 by using modified questions similar to those above. The Teacher Media Attitude Inventory, which was completed in Sept- ember and May of each school year, consisted of a Likert-reSponse—type check list. The choices ranged from Essential to Not Applicable. While the above independent variables provided data of a subjective nature, the data of a dependent nature (student achievement) was also gathered through the administration of standardized achievement tests and intelligence tests. The Revised Stanford-Binet Intelligence Scale, the MetrOpolitan Readiness Test, the Large-Thorndike Intelligence Test, the Harrison-Stroud Reading Readiness Profiles and the Stroud-Hieronymus Primary Reading Pro- file were used in K-2. Grades 3-9 used the Large—Thorndike Intelligence 8 The evaluation was com- Test as well as the Iowa Tests of Basic Skills.2 plated on each of the four years of the project. The information gathered on the independent and dependent variables provided data through which the following two hypotheses could be examined. Hypothesis 1: There is no significant difference in achievement of children in high and low media availability programs. 27Krueger and Jenson, 22, cit., pp. 1-2. 28Krueger, 92. £13., p. 19. 25 Hypothesis 2: There is no significant difference in achievement of children in study skills, language skills, and arith- metic in high and low media availability programs.29 The Teacher Media Attitude Inventory assessed Project TREE on the print and non-print media involved in the project. In summary, teachers' ratings of traditional materials used in the teaching of reading, ap- peared lower than the ratings of teaching with media as introduced in Project TREE.30 Standardized test data, which indicated the effectiveness of Pro- jest TREE, provided the dependent variable used in the study to determine the effectiveness of high media availability on student achievement. An analysis of covariance and t-tests were used to determine any significant gains in student achievement due to Project TREE. The conclusions reach- ed from the investigation are explained by Dr. Krueger as: The achievement test data obtained from the MetrOpolitan Readiness Tests, Stroud-Hieronymous Primary Reading Profiles, and the Iowa Tests of Basic Skills support the effectiveness of the Ames School program during the four years 196h-65 -— 1967-68. It was clear that the children profitted well during the years of Project TREE. It was difficult however, to demonstrate a clear statistical advantage for Project TREE children, but in each instance in which a signifi- cant difference was obtained, that difference favored Project TREE. The noinREE children may very well have been favorably influenced by the experimental or Hawthorne effect. It was not possible to insulate the control group from the pervasive influence of a mass- ive media program. Teachers of non-TREE groups were able to avail themselves of media in excess of normal availability levels and general discussion of teaching strategy could easily have influenced control group teachers to higher levels of performance. It appears unlikely that the measuring instruments used in the study permitted 29Ibid., p. 9. 3°Ibid., p. 16. 26 a real answer to the question of the value of a high media avail- ability program. Therefore, the evalugiion design for the future study of Project TREE will be reVIsed. Individualizing 0f Learninnghrough Media-Rural: The CESA-#11 Agency of the State of Wisconsin was awarded a Planning Grant, in 1967 under Title III P.L.89—10, for the purpose of determining the status of media, media utilization, and media facilities within its rural school pOpulation. The CESA #11 Agency is composed of 25 school districts, within a 10 county area, approximately A,OOO teachers and 43,500 students. The Planning Grant provided a sixrweek summer workshOp in media for teacher teams from 15 of the 25 school districts. Also provided was in—service training within the participating schools. This researcher was commissioned by CESA #11 to survey and an- alyze the results of the survey.32 Using the results of the initial investigation into media application, a Central Planning Committee was formed. The Committee sought and secured a 3-year Operational Grant. The Title III Operational Grant was awarded in 1968, resubmitted in 1969, and is presently in its last year of Operation. There were four principle objectives under which the Operational Grant was funded and is now 0p- erating. They are as follows: 1. To enable rural area teachers to more nearly meet the intel- lectual needs of the individual learner through develOpment of an instructional program making the maximum use of in- structional media in large groups, small groups, and 31Ibid., p. 24 and p. 26. 32Richard Peterson, "Operational Grant Title III, P.L.89—10" (La Crosse: CESA-#11), pp. 12-13. (Mimeographed.) 27 individualized learning situations. 2. To develOp teacher competency in the use of instructional media, preparing instructional objectives, and designing instructional sequences to accomplish the objectives. 3. To make instructional media readily available to rural area teachers and students. A. To bring about adoption of promising innovative procedures in the schools.3 The participating schools committed classroom space, equipment, and allocated funds to support an experimental team within each school. This team was composed of one 4th, one 5th, and one 6th grade classroom, students and teachers in each of the buildings. Also provided was the service of one full-time para-professional and one clerical assistant. To assure media software availability, a semi-weekly truck route was established between the Agency IMO in La Crosse, the Audiovisual Center at Wisconsin State University at La Crosse, and each of the schools. A local IMC, within each school, and under the guidance of the para-professional, was created to coordinate the production, supply, and utilization of media software and equipment. The CESA #11 Agency evaluated the first year of the program through the use of several instruments which were designed with the assistance of the Research and DeveIOpment Center of the University of Wisconsin. The second year, some of the same measures were used, while some additional instruments were created by the Agency. The evaluation report was completed in.March of 1970, covering 33min. , p. 14. 28 the second year of Operation. That report was intended to do the follow- ing: 1. 2. 3. h. 1. 2. 3. Establish an assessment of the project thus far in terms of how well the project objectives are being met and how well program activities are being carried out. Establish a pattern for continuing evaluation of the project. Suggest areas within the project which should be examined to a greater degree than has been accomplished by this report. Provide information which can be utilized by project planners in considering changes in the Operational format and in submitting the application for continuing support.34 The complete evaluation report indicated the following: During this past year the local IMC's were expanded to meet the demands created by the addition of fourth, fifth, or sixth grades in eight schools of the original thirteen plus the addition of one new school. Four schools did not increase their program to include additional grades, two of which did not have any'addp itional grades to expand into, and one school was drOpped from the project. Two additional schools added an individualized prOgram in accordance with project Specifications in grades four, five and six without financial support from the project itself. Sufficient interest was created on the junior high school level in five schools to cause them to initiate a partial individualized program in that area.3 Teachers new to the program demonstrated a strong ability to re- ognize behavioral obggctives correctly. This was attributed to the summer workshOp. An agency level IMC was established and a truck route delivered 16mm films, filmstrips, records, tapes, and transparencies to schools bi-weekly. Production services from the central IMC to WSU-La Crosse in the areas of graphics and photography were utilized very much by participating teachers. . . . The Evalu- ation Report showed a tremendous increase in the use of media 3“Solberg, 93. gi_t_., p. 15. 35Ibid., p, 6. 36Ibid. A. 5. 29 by project teachers, eSpecially in the areas of English and mathematics with science and reading increasing this year as compared to the first year of the project.37 The availability of software and hardware increased greatly, with the largest gains in materials for tape recorders, filmstrip projectors, viewers, listening stations and head sets, as well as overhead projectors. This supported the tendency of the teacher teams to provide greater individualized instruction for their students. A four—week summer workshOp was conducted in 1968 and 1969, which was designed to develOp the following: 2a the use of instructional media, b the writing of instructional objectives, EC the designing of learning experiences, d the evaluation and selection of instructiona media, and (a working effectively with para-professionals. 9 The workshOp participants also developed behavioral objectives for the grade levels involved in the project, selected media to be used, and designed the learning eXperiences in which students will participate for the academic year 1970—71. 6. During the past year delivery and pick up services were main- tained from the central IMC. The utilization of 16mm films and filmstrips from the central IMC increased, but there was a slight drOp in utilization of production service. Production services centered Brimarily around photographic and dry mount- ing needs. . . . A A program of consultant visitations and the dissemination of information was initiated, to inform not only CESA #11 area educators of the projects demonstrated contributions to student learning, but to statewide and national educators. 37Ibid., p. 7. 38Ibid. 39Ibid., p. 8. “OIbid., p. 9. 30 It is the aim of CESA #11 to motivate and encourage adOption of the "innovative practice demonstrated through team teaching, independent study using media, the use of para-professionals, and maximum utilizatiOn of the resources provided through the instructional materials center."l+1 Discussion of Previous Research Chapter II has sought to provide the research framework within which this study should be examined. The Review of Literature presented basically two divergent points of view on media research. There are those who favor a clinical-type research on the contributive value of media. These researchers are able to demonstrate that, as a tool of communication, media is as able a tool for teaching content as material taught in nonpmedia environments. The Opposite view is supported by Kittross, who in reviewing MacLean says: I have said that we seem to be wasting much fine research talent on trivial matters. We frequently use high prestige methods where they are not apprOpriate to our level of knowledge or theory. We control unimportant factors and leave important ones uncontrolled and un- defined . . . . We become so encumbered by elaborate manipulations and by unwieldy organization of research that we find little time to ask where we are going and why. This emphasis on educational research was emphasized by Saettler, who said: It has tended to focus on seperate disciplines already established “Ibid. , p. 11.. thllen Koenig and Ruane Hill (ed.), The Farther Vision -5§T! Today (Madison: University of Wisconsin Press, 1967), p. 216. 31 in the curriculum and to ignore or give scant attention to the develOpmentat processes of learners or to their social or cultural backgrounds. 3 The update of subject matters by teachers has been tied to school reorganizational plans. Thus administrators have played a very important role as a change agent. Too often, the assumption has been made that new content, new organizational theories, new media and new facilities are all that is required for improved learning to take place. The principle point of diSpute between the two extremes of researchers in that on one hand, the research has been done in a sterile environment and is not easily applicable to actual classroom procedure, while on the other hand, the researchers have arrived at the conclusion of NSD. Kittross elaborates on meaningful research and the NSD findings by suggesting there are three ways of looking at them: When considering the question of "meaningful research," there are at least three ways of looking at these NSD findings. First, we should try to isolate the factors in the learning situation that might cause these results. Williams, for example, suggests that the atti- tudes, ability, and personality of the classroom teacher may be the most important missin variable. Schramm has speculated as to whether the Hawthorne effect increased effort from the students due to being in the limelight as part of an experiment) or a novelty effect may have been important factors for NSD findings in a closely allied field. Also, there is little agreement as to what constitutes "conventional classroom teaching," and there are so many uncontrolled variables in the classroom situzkion that it is of little value to compare the two modes of teaching. The TREE Project and the CESA-#11 Project described in the preceed- ing pages has been an attempt at applying research to actual classroom LBPaul Saettler, A Histogy of Instructional Technology (New Y0rk: “*Koenig and Hill, pp. 993., p. 218. 32 conditions. While the evaluation of each project showed that a favorable attitude toward media had been created, the TREE Project reflected NSD when measured by a dependent variable (student achievement). It was be— cause of a desire to seek the application of educational research on media that this investigation was develOped. The investigation, as presented in the remaining portion of this study, was instigated under certain environmental conditions and with the knowledge that in as much as the results would indicate a relationship between certain media variables and student achievement, inferences could be drawn concerning the value of media to learning only within the pOp- ulation sampled, however, the findings of the investigation may be found applicable to other learning situations which reflect similar pOpulations and learning environments. The methodology and procedures of this invest- igation are presented in detail in Chapter III. CHAPTER III DESIGN AND PROCEDURES lens This dissertation records an eXploratory field study, which can be defined as an ex post facto investigation of the relationships between NEM independent variables and student achievement (dependent) variables, which are present in todays' educational environment. Specifically, descriptive information related to seven NEM variables was gathered from each of 15 schools. The analysis of this data provided a rank ordering of the schools on the NEM variables. The same schools provided student data through the results of student achievement in two areas, (1) general subject matter achievement, and (2) study skills scores as measured by the Comprehensive Test of Basic Skills - Level 2 produced by the Calif- ornia Test Bureau. Analysis of variance procedures were used to indicate systematic student achievement differences among the several schools, which were known to differ in terms of their respective NEM characteristics. The Population The CESA-#11 Agency is composed of 25 school districts encompass- ing a ten-county area, in the state of Wisconsin. There are approximately A,000 teachers, 25,000 elementary (K-6) and 18,500 secondary (7-12) students. The school districts range from a city of 50,000 pOpulation with many city and urban schools to rural districts with single or con- solidated buildings. The 25 school districts were provided the Opportunity to 3A participate in a three-year Title III project, entitled "Individualizing Learning Through Media-Rural." There were 15 schools that indicated an interest and joined in the project. Each of these schools committed a minimum of one 4th, one 5th, and one 6th grade class, its' teacher and room to the project. The pOpulation, from which the data was gathered, was basically rural schools and all members of the Title III project. The prOposed independent or "predictor" variables upon which information was to be gathered were: A. Teacher ability to recognize behavioral objectives. B. Teacher attitude toward NEM. C. The amount of teacher training in NEM utilization. D. The availability of NEM software. E. The availability of NEM hardware. F. Administrative attitude toward NEM. G. Administrative financial support for NEM. The several instruments were constructed to gather NEM data from 15 superintendents, 15 elementary principals, and 78 elementary teachers. The criterion measure, or dependent variable, was assessed from teacher-administered standardized student achievement tests. The Calif- ornia Testing Bureaus' Comprehensive Test of Basic Skills - Level 2, was administered to all tth, 5th, and 6th grade students in the project schools in the spring of 1970. These 1,800 student achievement scores were available through the CESA #11 office. 35 Instrumentation Instruments were prepared and distributed to four closely re- lated pOpulations consisting of superintendents, elementary principals, teachers, and para-professionals within the 15 project schools of CESA #11. The school SUperintendents were contacted through a personal tele- phone conversation. These were followed with a survey instrument which requested information relative to budget expenditures within the project schools for 1969. The net Operating costs for each school and the amount Spent for NEM software and NEM hardware in 1969 was obtained. The school enrollment figures were obtained from the CESA #11 office with which the cost per student for NEM was computed. The elementary school principals were surveyed with a series of two instruments. Part One requested personal data and Part Two was an NEM Attitude Inventory Instrument consisting of A7 items to which the respondent replied using a Likert-type scale ranging from "1 - agree strongly" to "6 - disagree strongly." Twenty—two of the 47 items were reversed scored to avoid the ambiguities caused by the negative phrasing of some statements. Therefore, a strong disagreement with a negative item was scored as a high positive attitude response. Those items mark- ed with "R" in Appendix I indicate the reversed scored items. The form of this instrument had its inception with Ramsey, who devised an instrument which discriminated between respondents possessing positive attitudes toward NEM and those respondents having a negative attitude.1 Having initially selected 375 statements which indicated 1Ramsey, A Research Project for the DevelOpment of a Measure to Assess Attitudes . . . . 36 positive or negative attitudes toward NEM, Ramsey reduced the final selected list to 39 statements through testing and revision. Ramsey's instrument was later modified by Guba and Synder in their 1964 research on MPATI telecasting.2 The instrument was further modified by Katser in 1969, when the Attitudes of Building Coordinators were studied.3 Katser's 23-item form was further modified for this investigation. A L7-item form was determined through pre-testing and revision using peer groups of audiovisual persons. The teachers received a survey packet consisting of three separ- ate instruments. Instrument One requested personal data; Instrument Two was the same A7-item NEM Attitude Inventory Form described fer the principals. Instrument Three was a 16-item instrument which was designed to determine the reSpondents ability to recognize behavioral objectives as described by Mager. There were six of the 16 items that were written in behavioral terms, while the remaining 10 items were not in behavioral form. A total of the correct responses ranging from 16, for correctly identifing all items, to O for being unable to make any correct identi- fication, was tallied for each respondent. The para—professionals received two instruments which were designed to inventory both the amounts of NEM software and NEM hardware available ZArthur D. Katser, "Activities and Attitudes of Instructional Media Building Coordinators: A Follow-up to Two M.S.U. Summer Institutes." (unpublished doctorial thesis, Michigan State University, East Lansing, 1969), p. 56, citing Guba and Synder, 196A, ITV and the Classroom Teacher, 9. 59. 3Ibid., p. 54. 37 to each teaching team. A tally of the responses provided the total amounts required in this investigation. Data Collection The initial thrust of the research was to determine to what exp tent NEM variables, present in todays classroom environment, affect student achievement. Having worked with the CESA #11 Agency and the Title III Project from its inception, a letter dated August 12, 1970, requesting permission to survey the project schools was sent to Mr. Ro- bert B. Tremain, Coordinator of CESA #11. (See Appendix By) Mr. Tremain replied on August 17, 1970, that the request to use the project schools for this investigation was granted. (See AppendixCL) Mr. Tremain also offered the services of the CESA #11 office staff and the area coordina- tors should such assistance be required in order to complete this investigation. A listing of the personnel of the project schools, who were a part of the project, as well as their principals and superintendents, was provided by the CESA #11 office. This document provided the names of 15 superintendents, 15 principals, and 80 teachers. Each school was assigned a number that was recorded to be used later to identify them in the analysis of the data, such that all re- sponses would remain confidential. (See Appendix D.) The several packets, administrator and teacher, of survey instru- ments were readied and addressed to each project school team leader for distribution. On September 9, 1970, a meeting was held with the southern half of the project schools, at which time the packets of survey forms 38 were distributed to the team leader. The completion and return of the instruments was discussed. The team leader returned to the project school, distributed the packets to fellow team members and to the prin— cipal. Each packet contained a cover letter with instructions on completing the several instruments, as well as the method by which they were to be returned to the researcher. (See Appendix F.) A similar meeting was held on September 10, 1970, at which time the packets were distributed and eXplained to the team leaders of the northern half of the project schools. The reSpondents, who had not returned the completed instruments at the requested time, were contacted again through the CESA #11 service route driver. All of the 80 teacher reapondents completed and returned the survey instruments to this researcher by October 15, 1970. There was a 100% return for the teachers and para-professionals. The 15 principals received their survey instruments from the team leader of their school. A cover letter provided the instructions nec- essary to complete the data form and the NEM Attitude Survey Form (see Appendix Q) which was enclosed. Those principals who did not complete and return the instruments were contacted by a personal letter request— ing their c00peration in expediting the returns. By November 15, 1970, all of the principals had responded. There was 100% return of the principal's instruments, although this was not done within the requested time table. The 15 superintendents were contacted by telephone during the month of November, 1970. It was found that the report of the school 39 budgeting was not constant within all 15 school districts; therefore, a personal telephone conversation was apprcpriate because of the two budget questions which the follow-up survey instrument would ask. The superintendents were very helpful and prompt in returning their responses to the survey instruments. On December 1, 1970, 100% of the superinten- dents had replied. The statistical responses on the criterion measure, student achievement, were obtained through reviewing the files on student achieve- ment testing in the CESA #11 office. All but one of the project schools utilized the California Test of Basic Skills - Level 2, in the spring of 1970, to determine the achievement levels of their Ath, 5th, and 6th grade students in the project classrooms. One school did not evaluate with the same measure, therefore, it was necessary to remove that school from consideration in the general analysis. However, comparisons may still be made which may be of interest. Analysis of the Data The survey instruments, as received by the respondents, requested information in seven areas: 1. Teacher Ability to Recognize Behavioral Objectives (See Apr pendix H) was determined by identification of responses to 16 statements, six of which were correctly stated in behavioral terms. Each school was identified by number, so that a record of each response could be compiled. The compiled responses determined the mean reSponse for that school. (See Table 4-1, p.h7.) 2. Teacher and administrative attitude toward NEM innovation was A0 determined through an instrument having A7 items to which replies were recorded on a Likert-type scale ranging from "1 agree-strongly" to "6 disagree-strongly." (See Table 4-1, p.1fi'.) Twenty two of the A7 items were reversed scored so that a strong reSponse to a negative item was re- corded as a highly positive reply. The use of code numbers for the respondent allowed for the separation of replies into administrative and teacher. The mean score of each group is recorded in Table A-1, p.L7 and Table 4-6, p.57 . 3. The amount of teacher training in NEM was obtained from the data sheet which was attached to each packet of instruments. The replies indicated the number of courses or institutes in NEM each reSpondent had attended. The mean number of courses for each school was recorded. (See Table A-1, p. 47-) A. The availability of NEM software to each project school team was determined by para-professional reSponse to the NEM Software Survey Form. The chart contained 15 items of NEM software commonly found in todays learning environments. A numerical type inventory response was made to each item, such that the numbers of each item could be tallied. (See Appendix In) The reSponses were identified by number so that the total amount of each reSponse could be determined for each school. It was necessary to determine an arbitrary weighting system for the software items, such that the responses could be combined into a single number which would represent the software responses for a given school. This was done by ranking the 15 items in ascending order of im— portance to a learning situation as determined by the investigator. A1 (See Table A-2, p.5x).) The weighting ranged from the language laboratory assigned a value of one, to 16mm films having an assigned value of forty. A weighted software score was determined for each school on each item by dividing the number of items, of each type, by the total number of items for all schools and multiplying that number by the weight assigned to that item. (See Table A-3, p.5fl..) From this, a weighted software num— ber was determined which represented each school on each item. The weighted numbers were totaled to provide a Weighted Composite Software Score for each school. (See Table 4-3, p» 51.) 5. The availability of NEM hardware was determined in a manner similar to that of NEM software. The para-professional for each project school replied in inventory fashion to the NEM Hardware Survey Form. There were 22 items of hardware for which each respondent indicated the number available in their project school. (See Appendix N.) The coded responses were identifiable by school. The items, all being of different types and having different ed- ucational values, made it necessary to establish a weighting procedure such that a single number would identify each school in NEM hardware. This was accomplished by ranking the 22 items of NEM hardware in ascend- ing order, from the public address sound system, weighted one, to the 16mm projector with an assigned weight of forty. A weighted hardware score was determined for each school by dividing the number of each item at a given school by the total number of that item for all schools, (see Table 1.4., p. 53 ) and multiplying that number by the weight assigned that item. From this weighted hardware number, a weighted 42 composite hardware number was determined for each school. (See Table 4-5, p- 51..) 6. The amount of administrative support for NEM was ascertained first on the NEM Attitude Survey, which was previously described. 7. A personal telephone conversation with each superintendent was combined with a follow-up Budget Survey Instrument. The personal contact with each Superintendent was deemed apprcpriate as budget report- ing procedures, in terms of what the instrument asked, were not readily available to provide consistent data. Each school was identified by a number which indicated the net amount of dollars required to Operate the project school in 1969-70. Also, recorded for each school, was the amount of money expended by that school district, within the project school, on NEM software and hardware for a similar period. (See Appendix 8.) The number of students enrolled in each school was determined through State Yearly Reports available in the CESA #11 office. In order to compute the amount of money spent in 1969-70 by each project school per student, the total amount of money spent for NEM was divided by the number of students enrolled for that period. (See Table A-7, p. 58.) The raw scores, which represent the project schools reSponse to the NEM variables, were tabulated. It should be noted that school #11. was omitted from further anaylsis as they had not used the CalifOrnia Comprehensive Test of Basic Skills - Level Two, as a means to determine their student achievement, and school.#18 because it was the first year of their participation in the project, therefore, their data reSponses A3 would not be compatable to the other schools. The remaining thirteen project schools were analyzed on their responses to the NEM variables. The seven independent variables were ranked in ascending order and assigned a weight relative to the importance each has as a contributor to the learning environment, with teacher training weighted one, and teacher attitude assigned twenty, as arbitrarily determined by the investigator. (See Table A-9. p. 61.) A Standard Score or z-score was generated for each school on each independent variable. All of the z-scores were in- spected. It was noted that higher numerical scores on all NEM measurement scales, except those for administrator and teacher attitude, indicated a high and positive response to, or value of, NEM. The z-scores for admini- strative and teacher attitude were therefore reversed in sign, because the lower the score the higher the value of NEM, while the higher score in- dicated a low value of NEM. Thus, in order that the z-scores on all independent variables would be comparable in meaning, the z-scores were reversed from negative to positive and positive to negative. (See Table A-1, p.A7 and Table A-6, p. 57.) The Standard Score for each NEM variable for each school was multi- plied by the weight assigned and the resulting Weighted Standard Scores were summed to determine the NEM Composite Standard Score. (See Table A-lO, p. 62.) Noting that some of the resulting NEM Composite Standard Scores were negative, an arbitrary constant of AO was added to each school's ND! Composite Standard Score so that all such Standard Scores were in the positive range. From this data, a simple rank order compiled with the school ranking in the number one position being the most favorable to NEM on all of the seven variables examined and school #13 being the least favorable toward the NEM variables investigated. The dependent variable data, student achievement, was compiled from Administrative State Reports on file in the CESA #11 office. The data available for this study were the results of the California Comprehensive Test of Basic Skills - Level 2, which had been administered in March of 1970 to each Ath, 5th, and 6th grade student in the project. The data collected on each of the 1,800 students indicated their performance on that test in achievement and on study skills. The measures used in this investigation are the Composite Grade Equivalent Score and the Study Skills Score for each student. It was noted that school.#2A had not administered their tests during the testing period pertaining in all other schools. Therefore, to correct for additional learning and hence increment in measured achieve- ment which may have taken place between the times of testing, .2 was subtracted from each student score gathered during late testing. An example of this would be a Ath grade student's grade equivalent score of 5.6 would, for the purpose of this study, be recorded as 5.A. Each school was identified by a code number, so that identification was possible in both of the areas in question. It was possible to analyze these scores by grade as well as by school when compared to the school's NEM scores. A5 Summagy Descriptive information indicating the degree of support given to seven selected NEM independent variables was gathered from 15 school districts within the CESA #11 district of the State of Wisconsin. The sample pOpulation consisted of 15 superintendents, 15 elementary princi- pals, and 78 elementary teachers from primarily a rural environment. Their several responses were tallied, and converted to z-scores for comparison. The z-scores for each school, on each of the independent variables, were weighted and summed to create one composite number which would represent each school's level of support for NEM. Data on student achievement, the dependent variable, was gathered on 1,800 Ath, 5th, and 6th grade students from the records on file in the CESA #11 office. The students data indicated their achievement as measured by the California Comprehensive Test of Basic Skills - Level 2 in the area of Composite Grade Equivalent Score and Composite Study Skills Score. An IBM 1130 computer was used to provide the statistical analysis required. The statistical treatment used was an analysis of variance (F test) based on two student achievement variables measured by the California Test (dependent variables.) Differences among schools on such student achievement data were examined for their correspondence to differences among schools on NEM Composite Standard Scores. CHAPTER IV ANALYSIS OF RESULTS Descriptive Data Indegdent Variables: This chapter contains statements and tables which present the data gathered by this investigation. In the first section, descriptive data relating to the NEM Independent Variables and the Dependent Variables are presented. The second section presents an analysis of that data, and section three summarized the analysis of that data. The Independent Variables which were measured were: A. Teacher ability to recognize behavioral objectives. B. Teacher attitude toward NEM. C. The amount of teacher training in NEM utilization. D. The availability of NEM software. E. The availability of NEM hardware. F. Administrative attitude toward NEM. G. Administrative financial support for N34. H. A composite score, combining all seven of the above. Table A-1 presents the combined data gathered on NEM variables A, B, and C. Variable A, teacher recognition of behavioral objectives, was measured by a 16-item instrument (see Appendix H) which required a yes or no reSponse to indicate whether or not a statement was written in behavioral terms according to Mager. There were 83 teachers surveyed with 100% return. The reSponses by individual teachers are shown, by school, in Appendix H. Table A-1 indicated the mean school response on TABLE 4-1 TEACHER RESPONSE TO NEM INSTRUMENTS A7 Behaviors Attitude NEM Teacher School Objectives (Raw Score) (Converted Score) Training (courses) X X X 10 14.00 102.80 57.20 4.33 11 12.00 107.00 53.00 3.00 12 14.17 119.08 40.92 4.00 13 14.60 98.80 61.20 3.40 14* 14.00 94.17 1.89 15 8.67 109.00 51.00 2.67 16 14.67 124.50 35.50 1.33 17 13.50 103.38 56.62 2.25 18* 12.33 131.83 2.00 19 15.00 111.38 48.62 2.50 20 15.00 86.10 73.90 3.60 21 14.58 88.08 71.92 2.67 22 14.00 82.00 78.00 2.50 23 13.00 104.33 45.67 3.33 2A 14.13 107.56 52.4A 3.75 X 13.64 103-39 55.85 3.03 s 1.71 12.35 12.35 .82 N 13.00 13.00 13.00 13.00 *Omitted from analysis **Converted to indicate high value to mean high support of NEM Formula used I . 160 - Mean Raw Score 48 Variable A. Although data was gathered from 15 schools, it was necessary to omit schools 14 and 18 from consideration, because of incomparable data on certain dependent variables. The highest possible mean reSponse was 16. The actual range was from 15.00 to a low of 8.67. The mean of all schools, or grand mean, was 13.64 with a standard deviation of 1.71 and an N of 13. Variable B, teacher attitude toward NEM, was measured by a 48 item Likert-type instrument (see Appendix I) which required a response ranging from "agree strongly" to "disagree strongly." There were 20 items which were reversed scored so that a reSponse of "disagree strong- ly" with a negative statement would be scored as an "agree strongly",so that all total reSponses were finalized in the positive. Any statement to which there was no response made was scored as a 3.5 or middle reSponse. There were 83 teachers surveyed with 100% return. Appendix J shows the individual teacher responses, while Table 4-1, columns 2 and 3 indicate the mean school response. It should be noted that the mean school re- Sponse was reported in raw score form with a low numeric response indicating a high attitude toward NEM and a high numeric response indicating a low attitude toward NEM. Therefore, it was necessary to convert the mean raw score for each school to a converted score, which would then indicate a high numeric reSponse as having a high attitude toward NEM and a low numeric response as having a low attitude toward NEM. Table 4-1 indicates the converted Scores which were obtained by using the formula 2 - 160 - mean raw score. The converted school mean reSponses ranged from 78.00, high attitude toward NEM, to 35.5, low 49 attitude toward NEM. The grand mean of all schools was 55.85 with a standard deviation of 12.35 and an N of 13. Variable C, teacher training, was indicated by the respondent on a personal information sheet. (See Appendix G.) There were 83 instruments circulated with 100% return. The individual teacher response, by schools, is found in Appendix J. Table 4-1, column 4, indicates the mean number of training courses per teacher by school. These range from 4.33 courses to 1.33. The grand mean of all schools was 3.03 courses with a standard deviation of .82 and an N of 13. variable D, availability of software, was determined through para-professional response to a 15-item inventory-type listing of soft- ware. (See Appendix L.) The para-professionals tallied all software available to each teaching team within each school surveyed. Each item was assigned a relative weight index value (Table 4-2) by the researcher, in terms of value toward instruction, with the item considered least im- portant to instruction assigned a 1. The balance of items were assigned values on a relative scale to 1 and ranging to a value of 40 fer 16mm films. The total number of items were calculated across all schools. In order to determine a number which would identify each school on software, the number of each item per school was divided by the total number of items and then multiplied by the weight assigned. The weighted total for all items per school is found in Table 4-3. These weighted totals, on each item, were totaled to create a weighted composite software score across all items for each school. TABLE 4-2 NEM SOFTWARE WEIGHTING INDEX 50 “ Item * Weighted Value 16mm films 8mm, super 8mm lOOp films 35mm filmstrips 2x2 slides audio recordings audio-tape recordings overhead transparencies realia maps globes models study prints overhead masters 3%-x 4 slides language labs #0 30 20 15 10 10 H O we P4 r- t- o~ 0‘ O\ a: Total - 15 items *Relative to value of 1 for least valued. macaques ea bounded“ pom naooeomtta e.uoen sen nonemwozva . sowaomnm Hesaooe swoon 3mm unawaeoos onoow onmsamom sownoasoc o e o 0 Se H 00 80 e e j. n emH MP. Namepl NQOMH @QOJ vogfiflgl e 80 o o 80 8e 80 o e 80 o 0N 80 80 80 80 “HHS-H e e e .0 8o 80 80 o e 8. HM. 80 80 80 8o . 8. . 8. jluddl . . 8. S. 8. 8. 8. an. nausea o 80 H o 80 80 no. 80 e O 80 80 80 80 80 OH. . 8. e . o . 8. o . 8. . S. o . 84 8A 8. 8. a? enema e 80 o 80 80 80 8e MHO No. 80 Neda Nude 80 30 80 e 8 MM. ”0 mo. dque 80 o o e 0 e 80 80 00. em. ”a He 80 o 0 Ho. 80 80 @HO 80 30 80 OH 80 Ofle 80 j 8. 8318. fill: om. 8. en. 8 8. S. 8. 3588mm ma. CO. 00. mm. OH. <0. 00. . mo. 00. mo. 00 00. ha. 00. j 8. .3. 8. S. 8. a; 8. 8. m. 8. . Ed em. 88.8.11! 8. 8. 8. 8. 8. S. 8. bu. 8. 8. mm. 8. 8. m... 8. essences .843 8. 8. 8. 13. 8. 2. 8 8. 1N. 8. 2385 HH. o0. HO. m0. NO. ON. 00. IWHH HH. 00. 40. PH 00. . oo. vmonhowm 84 84 8. an. 8. 8. 8. 8a 88 8. SA 8 N. 8. . mxm 2. 8. .8. 8. 8. 8. 8. 8. 8. 8. 8. 8 8. 8. 2. 80 80 8. HNO «Noe 80 80 8e 80 80 8e 8 80 80 80 NJ um «m 80 80 8. HNO @Fe 80 8e 80 80 80 80 8 80 80 80 1n. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8 8. 8. 8. no: 8% d. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8 8. 8. 8. as. .8. an. 84 8. .3. 8. S. 8 2. 8.8 8. 8. 8. 8. monsoon mo. 00. mo. OH. HO. #0. 00. NO. NO HO. we. go. 00. NO. 00. mm. 8.. on; 8. 8. 8. 8. on. Ms 18. 8A 8. 8. mm. 8. 3 00. m0. HH. no. mo. no. 00. m0. m0. m0. OH. OH. 00. @0. m0. Rd was 2.. 84 8. 84 8. we. 84 8. and 8. 8. Rd 8. mad 8. 8.. 8. 8. 8. 8. 8. 8.1%. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8.8 2.8 8. 8. one 814 8. 8. 8. on. on.” 8. nfiaommmmm CO. CO. 00. 04. OH. 00. OO. ma. 8H. 00. CO. 00. HO. Ha. 00. o O o O o O o OoeN N00 80 80 ON. H OH OHOH 80H 0 ”Ham 0 o .312. EH“ EQH 8. 8. 8. s. 8. 8. 8. 8. 8. 3. 8. 3. 8. 8. 3. . em mm am am on as ...mH mwooeamH ms arses mm «H as on oneseeon mmmoom mm<3bmom amaonmz.xmz mud mgm.m4 Om.mm >m.m4 mo.m4 mm.o4 >N.o vopanoz 8. 8. 8. 8 8. 8.m 8. 8. 8 8. 8. 8. 8. 8. 8. 85.43.6408 8. 8. 8. 8. 8. 8.4 8. 8. 8. 8. 8. 8. 8. 8. 8. 044 N4. 8.4 44.. 8. 8. 8. 8. 8. mm. mm. «44 8. 8. 444. So... 32. «4. 4o. «4. 8. 8. 8. 8. 4o. 8. 8. [8. M4. 8. 8. 8. .... 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8244894 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 843.643 8.4 8. 8. 8. 8. 8. 8. 8. 8. 8.4 8. 8. 8. 8. 8. 44.4.4.4 cm. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8. 8.4 8. 8. 8. 84 8. 8. 8. 8. 8. >48 ’8. 8. 8. 8. 8. 8. 8. 8. 8. cm 8. 8. 8. 8. 8. 118.4. 8. 8. .44.. 8. 8: an. 8.. 8. 84. 44.4 8. 8. a. 8. I. «494.48 8. 8. Jm4. m4. 8. 8. 44. 8. 8. .40. 8. 8. 8. 44. 8. .. .834. 4a 8 8. 4N om 4.4 $84 4.4 84 m4 $.44 M4 N4 44 04 naoonom unmsoum: 888 B44343. 94.48444: 4442 2.02.4483 8.4 44.443. 56 was noted that two schools had replies from more than one administrator. For these two schools, the raw scores were tallied and a mean score de- termined which was used to indicate the administrative attitude for that school system. Two schools, 14 and 18, were also omitted from analysis of administrative data, because some data returned (dependent variables) was found to be incomparable. Table A-6, column 3, shows the mean reSponse per school for administrators. The raw form of the score in- dicates a low value, or score, as having a high attitude toward NEM, while a large value, or score, as having a low attitude toward NEM. Column A shows the converted scores used, which were attained through the fbrmula X = 160 - mean raw score. These converted scores allowed a high numerical response to indicate high attitude toward N194, while a low numerical re- Sponse indicated a low attitude toward NEM. The converted score mean response ranged from 78.00, high attitude toward NEM, to 9.50, low at- titude toward NEM. The mean for all schools was 57.12 with a standard deviation of 23.h9 and an N of 13. Variable G, administrative financial support for NEM, was deter- mined through personal telephone contact with all school superintendents followed by a financial survey instrument through the mail. (See Appen- dix S.) Table 4-7 indicates the amount spent in 1969-70 per school ranged from a high of $26.03 per pupil to a low of $3.41 per pupil. It was noted that school #19 actually had a higher per pupil expenditure than reported here, due to involvement in other funded activities, as an example, a "Talking Typewriter" computerized terminal. Variable H, combining the preceeding independent variables A, B,, 57 TABLE 4-6 ADHNISTRATIVE SUPPORT -ATTITUDE- Attituae_.- *** School # Admin. # Raw Score Converted Score Rank 10 1 36.0 74.0 5 11 5 144.0 16.0 12 12 123.0 37.0 11 13 16 82.0 78.0 2 14* 23 91.0 15 33 114.0 h6.0 10 16 37 85-0 75.0 3 17 Al 91.0 69.0 6 18* 46 159.0 19 50 80.0 80.0 1 20 55 85.0 75.0 a 21 61 119.0 7 J. . 62 88.5 J ‘ " 56.0 9 22 75 93.0 67.0 7 23 80 150.5 9.5 13 24 87 115.0 J 100.0 88 85.0 60.0 8 Total - 17 Administrators 15 *Omitted from analysis 2 a 57.12 MAverage reSponse S = 23.1.9 N - 13 m Converted to indicate high value to mean high support of ND! Formula used it = 160 - mean raw score. 58 TABLE h-7 ADMINISTRATIVE SUPPORT -FINANCIAL ALLOWANCES— Net—Budget "Ahount‘épént ‘ ' ilment‘ "” per School # 1969 on NEM 1969 1969“ Student 10 $ 349.280 $3,500 269 $13.01 11 268,240 2.420 519 4.66 12 313,926 6,015 474 12.69 13 263.250 2.800 435 6.44 14* 210,000 7,500 482 15.56 15 496,640 4,800 593 8.09 16 386,692 3,500 220 15.91 17 510,384 2.500 679 3.68 18* 163,372 2,520 215 11.72 19 171.715 6.377 245 26.03 20 451,675 6.900 422 16.35 21 1,151,766 7,700 942 8.17 22 450.523 3.362 57b 5.86 23 608,780 1,972 578 3.41 24 406.875 3.905 426 9.17 *Not included in the analysis of data **0btained from CESA.#11 State Reports for 1969-70. 3 = $6.44 N . 13 X :- $10.27 per student 59 C, D, E, F and G as one independent variable, was accomplished by totalp ing each mean school response on each independent variable. Table 4—8 shows the mean reSponse per school on each independent variable converted to Standard Scores (2 scores) to allow for the differences in sample size. It was necessary to create a weight index for the independent variables, (see Table 4—9) so that a Composite Standard Score which would represent each school could be calculated. (See Table 4-10.) Table 4-10 presents the raw Composite Standard Score and an adjust- ed Composite Standard Score. The adjusted Standard Score was determined for each school by the following formula. Adjusted NEM Comp. 5.3. a 40 + [3(Var.1S.S.) + 20 (var.23.s.) 8.8.) + 10 (Var. 8.8.) + 1 (Var. + 1.5 (Var. 5.3.) + 10 (Var.6S.S.) 3 h 5 + 12 (Var. s.s.)] 7 The arbitrary value of 40 was added to all Composite Standard Scores so that all of the values would be positive and therefore more easily ranked. The Composite Standard Score, for each school included in this investigation, represents the numerical value which identifies each schools responses to the survey instruments concerning NEM. The Grand Mean Com- posite Scores were used to determine the relationships that NEM (independent variables) had with student achievement (dependent variables I and II. TABLE 4-8 MEAN STANDARD SCORES (2) INDEPENDENT VARIABLES School Behavioral Attitude Attitude Teacher Soft Hard Finance #‘ Objectives Teacher Admin. Train. Ware Ware 10 +0.21 +0.05 +0.72 +1.59 -1.13 -0.93 +0.43 11 -0.96 -O.29 -1.75 —0.04 +0.35 +0.46 —0.87 12 +0.31 -1.27 -0.86 +1.18 '-0.85 -O.43 +0.38 13 +0.56 +0.37 +0.89 +0.45 -0.83 +0.40 -O.59 15 -2.91 -O.45 -O.47 -O.44 -1.26 -0.08 -0.34 16 +0.60 -1.71 +0.76 -2.07 +1.39 —O.70 +0.88 17 -0.08 +0.00 +0.51 -0.95 +0.65 -1.07 -1.02 19 +0.80 —O.65 +0.97 ~O.65 -0.32 +1.69 +2.45 2O +0.80 +1.40 +0.76 +0.70 -0.03 -0.82 +0.94 21 +0.55 +1.24 -0.05 —O.44 +2.24 +1.97 -0.33 22 +0.21 +1.73 +0.42 -0.65 -0.07 -0.67 -0.68 23 -0.37 -0.08 -2.03 +1.37 -0.34 -0.63 -1.07 24 -+0.29 -O.34 +0.12 +0.88 +0.14 +0.81 -O.17 W TABLE 4-9 WEIGHTING INDEX - INDEPENDENT VARIABLE 61 W variable value Assigned A Recognizing Behavioral Objectives 3.0 B Teacher Attitude 20.0 C Administrative Attitude 1.5 D Teacher Training 1.0 E Software 10.0 F Hardware 10.0 G Financial Support 12.0 Note: Values assigned subjectively by investigator relative to value of contribution toward student learning. 62 TABLE 4-10 ADJUSTED NEM COMPOSITE STANDARD SCORES Composite Standard Scores School # SS SS+40* Rank Order 10 ~11.14 28.86 7 11 -13.69 26.31 8 12 _ -32.82 7.18 12 13 ~0-52 39.48 6 15 ~36-36 3.64 13 16 -15.87 24.13 9 17 -16.87 23.13 10 19 +33.31 73.31 3 20 +35.62 75.62 2 21 +64.08 104.08 1 22 +19.65 59.65 4 23 ~27.93 12.07 11 24 +2.59 42.59 5 X 8 40.00 S I 30.15 N - 13 *Add 40 to give all positive values Nets: Adjusted Comp.S.S. = 3(Var.18.S.) + 20(Var. 5.5.) + 1.5(Var. 5.5.) 2 5.5.) + 10(Var.6S.S.) + 12(Var. 3 + 1(Var. 5.5.) + 10(Var. 3.5.) 7 W 4 5 63 Merit Variables: The dependent variables used in this study are two forms of student achievement as determined by the California Compre- hensive Test of Basic Skills - Level 2, which was administered in the Spring of 1970. The fact that all tests were administered by the class- room teacher was accounted for in the environmental conditions under which most achievement testing takes place. The actual Student achieve- ment raw scores are not included in the Appendix of this study, as the large sampling of 1,808 students would fill many additional pages; how- ever, all of the raw scores used were obtained from the files of the CFSA #11 office. Student achievement was measured in two manners: (a) composite student achievement score, and (b) student'study skills score. These are designated Variable I and Variable II, respectively. Table 4-11 indicates student grade equivalent scores, in raw terms, for each grade across all schools. The fourth grade mean "grade-equi- valent" score on composite student achievement was 5.10, with a standard deviation of 1.31 and a amnple size of 620 students. The fourth grade "study skills" mean score was 5.67, with a standard deviation of 1.90 and a sample of 620 students. The fifth grade mean “grade equivalent“ score on composite student achievement was 6.13, with a standard deviation of 1.61 and a sample of 653 students. The fifth grade ”study skills" mean score was 6.85, with a standard deviation of 2.19 and a sample of 653 students. The sixth grade mean"grade equivalent“ score on composite student achievement was 7.20 with a standard deviation of 1.78 and a sample of 538 students. The sixth grade mean "study skills" score was 8.00, with a standard deviation of 2.28 and a sample of 538 students. TABLE 4-11 COMPILED STUDENT GRADE EQUIVALENT SCORES* Dependent Sample Grade Variables Mean SD Size 4th Composite Stud. Achieve. 5.10 1.31 620 Study Skills 5.67 1.90 620 5th Composite Stud. Achieve. 6.13 1.61 653 Study Skills 6.85 2.19 653 6th Composite Stud. Achieve. 7.20 1.78 538 Study Skills 8.00 2.28 538 *California Comprehensive Test of Basic Skills - Level 2, Spring 1970, expressed as 'grade-equivalent' scores. 65 The sample size for each reporting school varied.within each grade level. It was therefore necessary to interpret the student raw scores on Variable I and Variable II in terms of a converted score, a Standard Score. (See Table 4-12.) The T—score was calculated on the mean and standard deviation of each grade across all schools. Table 4-12 indicates the mean T-score for each school, standard deviation, and sample size on each dependent variable. A correlation between the school means for Variable I and Variable II was calculated. The results indicated a correlation or r12 - +0.74, where 1 - mean student achievement T-score; 2 - mean student study skills T—score; and N a 13. The correlation value +0.74 indicated a high degree of overlap between the two dependent variables of student achievement and.student study'sk1112. £118, a student who scored high in. grade equivalent also tended to score high in measured study skills and vice versa. TABLE 4-12 Variable I* ADJUSTED ACHIEVEMENT SCORES (T-SCORES) 0N DEPENDENT VARIABLES Variable II** 66 School # Sample . Sample Mean SD Size Mean SD Size 10 52.48 9.38 95 53.06 8.88 95 11 48.01 11.79 78 45.83 9.17 78 12 51.03 9.30 160 51.37 8.91 160 13 52.79 10.96 146 52.20 9.31 146 15 49.70 10.91 51 49.42 10.40 51 16 49.94 9.19 83 48.41 9.62 83 17 47.18 10.65 107 47.85 10.74 107 19 50.79 9.84 113 50.07 8.81 113 20 48.58 10.18 163 49.77 9.77 163 21 48.63 10.43 354 48.21 9.67 354 22 47.39 11.01 83 49.88 11.68 83 23 52.60 10.92 183 50.48 9.81 183 24 50.55 10.88 192 52.35 11.05 192 13 schools 1808 students 1808 students *Variable I is Grade Equivalent Score on all students in sample. **Variable II is Study Skill Score on all students in sample. 67 Analysis of Data The research hypothesis of this investigation was that there was a relationship between the environmental conditions under which learning takes place and measured student achievement. Data was gathered which described selected NEM independent variables. Table 4-13 shows the intercorrelations of all the Independent Variables. The mean intercorrel- ation of all variables was +0.10. This indicated that there was little correlation between the NEM variables. At the .05 level of probability an r 2'? 0.55 is required for significance with 13 pairs of measures. The low mean intercorrelation did, then, indicate that distinctly dif- ferent NEM variables were measured. When considering the selected NEM variables investigated, in com-6 parison to the dependent variable (student achievement) the conclusion derived was that under the conditions of this investigation the selected variables, as a group, had no more effect on student achievement than conventional environmental conditions. Analysis of each independent variable in relation to student achievement indicated a slightly different conclusion. Table 4-14 pre- sents Individual NEM Variables and Dependent Variable I, student achieve- ment, correlations. Table 4-15 presents the Individual NEM Variables and Dependent Variable II, student study skills, correlations. Column 1 in Table 4-14, indicates the ranking of all schools on NEM variable A, "recognizing behavioral objectives," and corresponding student achievement T scores (Dependent Variable I). School;#19 ranked 1 and school.#l5 ranked 13. The Grand Mean Response was 13.64 and the Variable I; E: =:-.- TABLE 4-13 INTERCORREIATIONS OF ALL INDEPENDENT VARIABLES 1 2 3 4 5 6 7 1 +1.00 +0. 18 +0.51 +0.07 +0.36 +0.12 +0.42 2 +1.00 +0.30 +0.13 +0.16 +0.09 -0.22 3 +1.00 -0.19 +0.07 +0.02 +0.35 1, +1.00 —0. 57 -0.08 —0.06 5 +1.00 +0.33 -0.06 6 +1.00 +0.25 7 +1.00 Mean Intercorrelation .. +0. 10 Note: 1. 2. 3. 4. 5. 6. 7. Key to Independent Variables Behavioral Objectives Teacher Attitude Administrative Attitude Teacher Training Software Hardware Finances 69 correlation of +0.12 was not significant. Table 4-15 shows the ranking and correlation between Independent Variable A and Dependent Variable II, student study skills. The Grand Mean ReSponse was 13.64. The correlation of +0.27 was not significant. The correlation between Independent Variable B and Dependent Variable I is shown in Table 4-14, column #2. The Grand Mean ReSponse was 55.85. The correlation of -0.44 was not significant. Table 4-15, column #2, shows the relationship of Variable B with Dependent Variable II. The Grand Mean ReSponse was 55.85. The correlation of -0.03 was not significant. The correlation between Independent Variable C and Dependent Var- iable I is shown in Table 4-14, column #3. The Grand Mean Response was 57.12. The correlation of -0.04 was not Sigiificant. Table 4-15, column #3, shows the relationship of Variable C with Dependent Variable II. The Grand Mean Reaponse was 57.12. The correlation of +0.31 was not sigh- nificant. The correlation between Independent Variable D and Dependent Var- iable I is shown in Table 4-14, column #4. The Grand Mean Response was 3.03. The correlation of +0.50 approaches statistical significance, but is not sufficiently high to indicate a correlation which may have occurred other than by chance. Table 4-15, column #4, shows the relationship of Variable D with Dependent Variable II. The Grand Mean Response was 3.03. The correlation of +0.66 was of sufficient value to indicate a significant correlation (p405) between the availability of software and Student Study Skills. Appraising only Independent Variable D and Dependent Variable II , 70 TABLE 4-14 INDIVIDUAL NEM VARIABLES AND STUDENT ACHIEVEMENT T Sch. '2 Ach. Sch. '2 Ach. Sch. TI Ach. Sch. ‘2 Ach. mm 1 T Rmk2* T mm 9 T Rmk4 T 19 15.00 50.79 22 78.00 47.39 19 80.00 50.79 10 4.33 52.48 20 15.00 48.58 20 73.90 48.56 13 78.00 52.79 12 4.00 51.03 16 14.67 49.94 21 71.92 48.63 16 75.00 49.94 24 3.75 50.55 13 14.60 52.79 13 61.20 52.79 20 75.00 48.58 20 3.60 48.58 21 14.58 48.63 10 57.20 52.48 10 74.00 52.48 13 3.40 52.79 12 14.17 51.03 17 56.62 47.18 17 69.00 47.18 23 3.33 52.60 24 14.13 50.55 23 45.67 48.01 22 67.00 47.39 11 3.00 48.01 10 14.00 52.48 11 53.00 50.55 24 60.00 50.55 15 2.67 49.70 22 14.00 47.39 24 52.44 49.70 21 56.00 48.63 21 2.67 48.63 17 13.50 47.18 15 51.00 50.79 15 46.00 49.70 19 2.50 50.79 23 13.00 52.60 19 48.62 52.60 12 37.00 51.03 22 2.50 47.39 11 12.00 48.01 12 40.92 51.03 11 16.00 48.01 17 2.25 47.18 15 8.67 49.70 16 35.50 49.94 23 9.50 52.60 16 1.33 49.94 3'6 13.64 I 55.85 I 57.12 I 3.03 S 1.71 3 12.72 S 23.49 S 0.82 N 13.00 N 13.00 N 13.00 N 13.00 r= +0.12 r- -O.44 rs -0.04 r- +0.50 r- Correlation based on Individual NEM Scores and mean Study Skill Score across all schools. *Converted to indicate high value to mean high support of NEM. W 71 TABLE 4—14 (Continued) INDIVIDUAL NEM VARIABLES AND STUDENT ACHIEVEMENT T E Ach. Sch. 3? Ach. Sch. E Ach. Sch. Rank 5 T Rank 6 T Rank 7 T 21 25.21 48.63 21 31.34 48.63 19 26.03 50.79 16 20.11 49.94 19 29.19 50.79 20 16.35 48.58 17 15.15 47.18 24 22.54 50.55 16 15.91 49.94 11 13.82 48.01 11 19.85 48.01 10 13.01 52.48 24 12.53 50.55 13 19.37 52.79 12 12.69 51.03 20 11.87 48.58 15 15.72 49.70 24 9.17 50.55 22 11.31 47.39 12 13.01 51.03 21 8.17 48.61 19 9.81 50.79 23 .11.57 52.60 15 8.09 49.70 23 9.64 52.60 22 11.22 47.39 13 6.44 52.79 13 6.73 52.79 16 10.98 49.94 22 5.86 47.39 12 6.57 51.03 20 10.12 48.58 11 4.66 48.01 10 4.89 52.48 10 9.27 52.48 17 3.68 47.18 15 4.14 49.70 17 8.19 47.18 23 3.41.52.60 I 11.71 3'6 16.34 I 10.27 S 6.03 S 7.61 S 6.44 N 13.00 N 13.00 N 13.00 rs -0.52 'ru +0.04 r- +0.19 r=Correlation based on Individual NEM Scores and mean Study Skill Score across all schools. TABLE 4-15 INDIVIDUAL NEM VARIABLES AND STUDENT STUDY SKILLS T 72 Sch. “ii 5.8. Sch. 3'6 S.S. Sch. SE 3.3. Sch. I 5.8. Rank 1 t T Rank 2* T Rank 3* T Rank 4 T 19 15.00 50.07 22 78.00 49.88 19 80.00 50.07 10 4.33 53.06 20 15.00 49.77 20 73.90 49.77 13 78.00 52.20 12 4.00 51.37 16 14.67 48.41 21 71.92 48.21 16 75.00 48.41 24 3.75 52.35 13 14.60 52.20 13 61.20 52.20 20 75.00 49.77 20 3.60 49.77 21 14.58 48.21 10 57.20 53.06 10 74.00 53.06 13 3.40 52.20 12 14.17 51.37 17 56.62 47.85 17 69.00 47.85 23 3.33 50.48 24 14.13 52.35 23 45.67 50.48 22 67.00 49.88 11 3.00 45.83 10 14.00 53.06 11 53.00 45.83 24 60.00 52.35 15 2.67 49.42 22 14.00 49.88 24 52.44 52.35 21 56.00 48.21 21 2.67 48.21 17 13.50 47.85 15 51.00 49.42 15 46.00 49.42 19 2.50 50.07 23 13.00 50.48 19 48.62 50.07 12 37.00 52.37 22 2.50 49.88 11 12.00 45.83 12 40.92 51.37 11 16.00 45.83 17 2.25 47.85 15 8.67 49.42 16 35.50 48.41 23 9.50 50.48 16 1.33 48.41 3? 13.64 I 55.85 I 57.12 I 3.03 s 1.71 S 12.72 S 23.49 S 0.82 N 13.00 N 13.00 N 13.00 N 13.00 r= +0.27 r- -0.03 r- +0.31 r- +0.66 r= Correlation based on Individual NEM Scores and mean Study Skill Score across all schools. *Converted to indicate high value to mean high support of N34. TABLE 4-15 (Continued) INDIVIDUAL NEM VARIABLES AND STUDENT STUDY SKILLS T 73 Rank 5 T Rank 6 T Rank 7 T 21 25.21 48.21 21 31.34 48.21 19 26.03 50.07 16 20.11 48.41 19 29.19 50.07 20 16.35 49.77 17 15.15 47.85 24 22.54 52.35 16 15.91 48.41 11 13.82 45.83 11 19.85 45.83 10 13.01 53.06 24 12.53 52.35 13 19.37 52.20 12 12.69 51.37 20 11.85 49.77 15 15.72 49.42 24 9.17 52.35 22 11.31 49.88 12 13.01 51.37 21 8.17 48.21 19 9.81 50.07 23 11.57 50.48 15 8.09 49.42 23 9.64 50.48 22 11.22 49.88 13 6.44 52.20 13 6.73 52.20 16 10.98 48.41 22 5.86 49.88 12 6.57 51.37 20 10.12 49.77 11 4.66 45.83 10 4.89 53.06 10 9.27 53.06 17 3.68 47.85 15 4.14 49.42 17 8.19 47.85 23 3.41 50.48 I 11.71 I 16.34 I 10.27 S 6.03 S 7.61 S 6.44 N 13.00 N 13.00 N 13.00 ra -0.60 rs -0.10 r- +0.20 r-Correlation based on Individual NEM Scores and mean Study Skill Score across all schools. W 74 the conclusion was drawn that within the restrictions of this investi- gation, the presence of NEM software does have a positive effect on student achievement. (Study Skill Score.) The correlation between Independent Variable E and Dependent Variable I is shown in Table 4-14, continued, column #1. The Grand Mean Response was 11.71. The correlation of -O. 52 was not significant. Table 4-15, continued, column #1 shows the relationship of Variable E and Dependent Variable II. The Grand Mean was 11.71. The correlation of -0.60 was of significant value to report as a negative correlation be- tween the availability of ND! hardware and Student Study Skills. Appraising only Independent Variable E, the conclusion was drawn that within the restrictions of this investigation, the presence of NEM hardware had a negative effect on student achievement. (Student Stumr Skills Score.) The correlation between Independent Variable F and Dependent Var- iable I is shown in Table 4-14, continued, column #2. The Grand Mean Response was 16.34. The correlation of +0.04 was not significant. Table 4—15 continued, column #2, shows the relationship of Variable F and Dependent Variable II. The Grand Mean was 16.34. The correlation of -0. 10 was not significant. The correlation between Independent Variable G and Dependent Var- iable I is shown in Table 4-14, continued, column #3. The Grand Mean Response was 10.27. The correlation of +0.19 was not signigicant. Table 4—15, continued, column #3, shows the relationship of Variable G and Dependent Variable II. The Grand Mean was 10.27. The correlation of 75 +0.20 was not significant. Table 4-16 shows the correlation coefficient of the ND! Composite Standard Scores with Dependent Variable I and Variable II. The correlation coefficient of —O.3O for NEM and Variable I indicates that no significant correlation was found, at the .05 level of probability, when NEM variables were present at the levels measured in the student learning environment. Also shown in Table 4-16, is the correlation coefficient of —0. 10 for NE! and Variable II. This indicates that no significant correlation was found, at the .05 level of probability, when NFM Variables and Student Study Skills were compared. . This fact is supported in Table 4-17. Visual inapection indicates that if school #21, which ranked 1 in NEM, had also ranked 1 in Dependent Variable I and Dependent Variable II instead of ranking 10 and 11 re- Spectively, there would have been an indication that the hypothesis of this investigation was supported. School #15 which was 13th in ranking on NB! ranked 8th on Dependent Variable I and 9th on Dependent Variable II. Visual inspection showed no pattern of ranking between the Indepen- dent and Dependent Variables. The apparent random ranking shown in Table 4—17, supported by the correlational analyses reported previously, in- dicated that no additional examination of data as suggested in Chapter III should be undertaken. Summagz of Data A summary of the decisions reached on the NEM hypotheses is shown in Table 4-18. Of the 16 hypotheses tested, there were two hypotheses which indicated a significant correlational value between NEM and the 76 TABLE 4-16 CORRELATION OF NEM COMPOSITE STANDARD SCORES WITH DEPENDENT VARIABLES r12 = -O.3O Where 1 = NEM Composite Standard Score; and N = 13 2 a Mean Student Achievement T NSD from r = 0 at Papmouo one ca downwawoch were: one uncooam HecowposnpneH: .conmssmem .H sense: an confine .dowpm>ocsH mapoz.usm neoconm HmcowpoSEpmcH assess. snaps: 36H snaps: 36H scape: cofiumuSOmoum Hmuo snaps: .soH snaps: Scans: and seeps: axoonuxoa pmucwum snaps: snaps: swam 36H Snares. 36H cowumuuncosmn coauusuumcu assoc: ,soH rqu eases: eases: Esteem seemswoua abacus 30H Emacs: 30H 30H Eswpmx mwcwouoOom pr=< 36H sol sol 36H :on Sol auooflno n-m scape: sea sawed: muH: snaps: sawpoz scanw>mama .ESSpmz saunas. mUHm.. :uHx :on adept: maneuuwm coHuoz 36H 36H segues. seeps: . scum sawpoz maneuuwm "kum r neoaucpanoz_ - some case: a snowmamo muo< acuoz_ measm ecu fichMuusuumcH .uovsuuuum Hanumoouom announce mcofiumoamaucopu cowumsuowcH massages: poauaxm . mouseoooum noamuocuum Hennw> aneuomm mm>auoomno maumoHo>on wauauowuom .wcwcumma wcucumoa usucumon magnumma mewcuemA H Mama. n. @5830 02% DH. mmHmmonag mDADZHBm SHE: AgogosmamzH < anzmmm< APPENDIX B REQUEST LETTER TO CESA #11 . . . . 94 WISCOflSII‘I State Umversnfy - La Crosse La Crosse, Wisconsin 54601 August 12, 1970 Mr. Robert B. Tremain, Coordinator Cooperative Educational Service Agency Court House La Crosse, Wisconsin Dear Mr. Tremain: As a. member of the Audiovisual Center staff I have had the pleasure of working with your agency, for the past several years, as a consultant in the Title III, ESEA project, Individ- ualizing Learning Through Media-Rural. We had discussed informally the possibility of my working with your agency on a. predictive survey involving new educational media and its rela- tionship to student achievement scores. Last year, 19 69-70, I was a. doctoral student at Michigan State University. I have now returned to Wisconsin State Uni- versity—LaCrosse to complete my dissertatiOn and continue as a. member of the Audiovisual Staff. I request your permission to work with your agency in pursuit of information for the disserta- tion. Of course, all such information would be confidential and the results and implications for CESA #11 would be available to you. I should like to meet with you or your representative as soon as convenient to formalize the procedures to be followed while administering the survey instruments. Thank you for your consideration and assistance. Sincerely, Clair L. Rood, Assistant Professor Audiovisual Center CLR:lf APPENDIX C STATE ‘ 95 COOPERATIVE EDUCATIONAL SERVICE AGENCY NO. II County Cou rt House LA CROSSE, WISCONSIN 54601 TELEPHONE 764-0518 R. B. TREMAIN. COORDINATOR RESPONSE IETTER FROM CESA #11 August 27, 1970 Mr. Clair Rood La Crosse State University La Crosse, Wisconsin 54601 Dear Mr. Rood: In reply to your recent letter asking permission to use the project schools of CESA #11 for subjects for a Predictive Survey relative to the newer educational needs. We are most happy to have you make this survey and will assist you in any possible way that is necessary. Yours very truly, . Pflflrflfln R.B. Tremain, Coordinator RBT/eb APPENDIX D POPULATION IDENTIFICATION - TABLE II Number Of 96 School Assigned Stu. Total # Superin. Princ. Teachers in Stu. Proj. Alma-Center 10 1 l 3 95 269 Bangor 11 1 1 3 78 519 Blair 12 l 1 6 160 47h Cashton 13 1 1 5 146 ABS Cathedral 1A* 1 1 9 -—- h82 Cochrane— 15 1 1 3 51 593 FOuntain City De Soto 16 1 1 3 83 220 Holman l7 1 1 h 107 679 Independence 18* 1 1 3 -—- 215 La.Farge 19 1 1 A 113 2A5 ldelrose— 2O 1 1 5 163 h22 Mindoro Tomah 21 1 2 12 35h 9L2 West Salem 22 1 1 h 83 57h Westby 23 1 1 6 183 578 Whitehall 2h 1 2 8 192 L26 Total: 1808 Students 15 schools 15 Superin. l7 Princ. 78 Teachers *Not included in analysis. APPENDIX E INTRODUCTORY IET’I'ER TO TEACHERS To: Faculty Members Of CESA #11 Schools From: Clair L. Rood, Doctoral Student, Michigan State University and Assistant Professor, Audiovisual Center, Wisconsin State University-La Crosse Re: Participation in New Educational Media Survey of CESA #11 schools, grades 4, 5 and 6. At the present time I am in the process Of instituting survey instruments to attempt to predict achievement scores of students in relation to the availability and utilization Of the new educational media available to today's teachers. I would like to enlist your aid. as a concerned 2 e a c h e r i n CESA #11 schools. As you will note I have attached several survey forms. Would you please complete these forms within the next week and return them to me via Mr. Ralph Whiting or mail them in the enclosed envelope to me at the Audiovisual Center. Wisconsin State University, La Crosse. Your responses will be confidential and utilized by me only for the completion Of this survey. At the culmination Of this investigation the resulting implications will be made available to you. Thank you very much for your assistance in completing this survey. APPENDIX F 93 DIRECTIONS FOR COMPLETING THE SURVEY FORMS Teachers: Please complete ALONE all areas which pertain to you with the following exceptions . 1. N.E.M. Software Survey 2. N.E.M. Hardware Survey The above 2 forms may be completed by your team para-profes- sional and reflect your physical arrangements as well as the materials and equipment available within your local I.M.C . When you have completed your portion of the survey please have your paraprofessional complete the above mentioned forms , gather all completed forms from your team, place them in their envelOpes and return them tO me via Mr . Whiting and the service route . Please return the completed survey by September 22. Thank you . APPENDIX G 99 TEACHER PERSONAL DATA SHEET Your name Sex Name of your school Position: (circle One) teacher principal superintendent Highest degree earned Total years teaching experience Years in administration Years in present system The number of media courses taken OR The number Of media institutes attended Are you a participant in CESA #11 "Individualized Learning Through Media-Rural" project" Yes NO. Of years NO Your answers tO these survey instruments will be kept strictly confidential. Only you and members Of the study team will see your responses. Thank you for your COOperation. ... ‘ .....- .. 100 RECOGNIZING BEHAVIORAL OBJECTIVES SURVEY Place an (X) before any Of the instructional Objectives which are properly stated in behavioral terms, according tO Mager. There are six (6) correct answers. NO 12. N0 13. Give ten finite sets, the student is able to name the number Of each set with 100 per cent accuracy. Given twenty subtraction problems, the student will work them with 90% accuracy. Given a matching test, the pupil will correctly match both columns. (100 '70) Given 10 (10) rectangles, the student will be able to compute the area Of each with 80% accuracy. The student will prefer sewing to cooking. Given chapter 10, the student will grasp the significance Of the Treaty Of Versailles with 80% accuracy. Given ten true and false statements, the student will answer by true or false. (90%) Given orally a list of one-syllable words containing short vowel sounds, the student is able to write the vowel letter and mark the vowell letter long or short according to the sound heard in the word. (80%) Given a demonstration, you will pay attention as the teacher demonstrates the use Of the lathe. Given paragraphs to which a conclusion or prediction must be supplied, you will be able to select the most logical con- clusion or prediction from each paragraph. (90%) Given a list Of words, some Of which are proper nouns, the student will be able to capitalize those words that are prOper nouns. (80%) The student will be able to develOp a sense Of the cultural unity Of man with 90% accuracy. The student must pass a test Of vocabulary with 100% accuracy. 101 N9 14. Given a history Of World War I, the student will know the important battles. N9 15. Given 10 algebra problems, the student will appreciate the key importance Of algebraic approaches. 125— 16. Given two whole numerals that name whole numbers not greater than nine thousand, nine hundred ninety-nine, the student is able to compute and list the products of 20 such pairs with 80% accuracy. YOU HAVE NOW COMPLETED THE SURVEY INSTRUMENTS. I WISH TO THANK YOU FOR YOUR TIME AND CONSIDEATION CONCERNING NEW EDUCATIONAL MEDIA. WOULD YOU PLEASE PLACE THE COMPLETED INSTRUMENTS IN THE ENCLOSED BROWN ENVELOPE AND RETURN THEM TO ME AT THE FOLLOWING ADDRESS. THANK YOU. Mr. Clair L. Rood Audiovisual Center Wisconsin State University La Crosse, Wisconsin 54601 APPENDIX I TEACHER NEM ATTITUDE INVENTORY 102 NEWER EDUCATIONAL MEDIA ATTITUDE INVENTORY During the past twenty years or so, many new teaching aids have been develOped. Some Of these are sufficiently elaborate to change, or even to replace temporarily, the classroom communication processes which were formerly pretty much limited to children and teachers. Radio, television, motion pictures, slides and filmstrips, and phonograph and tape recorders, certain types of teaching machines and programed learning methods - - all are examples Of what might be termed the "Newer Educational Media". (NEM) In American education today, there is some controversy concerning this NEM. The following statements represent various points of view on this question. Please indicate the extent Of your agreement or disagreement with each statement. Please don't make efforts to be consistent or to select the "right answer" -- there are none. Simply enter the proper number in the space before each sentence according to the following code. DE FINIT IONS EQUIPMENT refers to projectors and other mechanical devices. ' MATERIALS refers to films and other audio-visual displays. _ .‘._..__ NEW EDUCATIONAL MEDIA will be abbreviajiedm in this questionnaire as NEM. The following statements represent varrying points Of view about which there is some controversy in American education today. Respond rapidly according to the degree Of agreement with the statements listed below. Mark your answers in the blank Space on the right according to the code shown below: 1. Agree strongly . Agree moderately . Agree slightly . Disagree slightly . Disagree moderately 2 3 4 5 6 Disagree strongly 103 Please indicate the extent Of your agreement or disagreement with each statement . 10. ll. Agree strongly Agree moderately Agree slightly Disagree slightly . Disagree moderately . Disagree strongly O‘UlpthI—I The widespread use Of the NEM will revolutionize the process Of instruction as we know it now. The possible uses Of the NEM are limited only by the imagination Of the person directing the usage. The wide resources Of the NEM stimulate the creative student. There are nO educational frontiers in the NEM-~just new gadgets . Most children see the NEM mainly as entertainment, rather than as education. Most teachers lose the gratification Of personal accomplishment when the child is taught by machine . Use Of the NEM constitutes a major advance in providing for individual differences in the learning needs Of students. Much wider usage Of the NEM is needed. The vicariousness Of learning by NEM aids is not conducive to the most effective learning. If surplus funds exist which could be spent only for supplementary books or for more NEM equipment, the latter should be chosen. Children can learn the basic value Of a good education only when taught by conventional methods -- not by the NEM. Note: "Open" responses scored 3.5 101+ Please indicate the extent Of your agreement or disagreement with each statement. R 12. R 13. R 14. R 15. 16. R 17. R 18. R 19. R 20. 21. Agree strongly Agree moderately Agree slightly Disagree slightly . Disagree moderately . Disagree strongly O‘U‘IEP-UONI-n O The problems Of getting materials and equipment when you need it, darkening rooms, setting up the equipment, and otherwise disrupting classes tend to counteract the value of most NEM. The "authoritative” presentations Of most Of the NEM tend tO produce an uncritical acceptance on the part Of most children. The passive quality Of learning by NEMis not conducive to the most effective learning. The prOper student attitudes for effective learning are not develOped as well by the NEM as by conventional methods of teaching . Only through the NEM can vicarious learning experiences be provided in the classroom. The expense Of most Of the NEM is out Of all prOportion to their educational value. The NEM give little Opportunity to provide for individual differences Of children. NEM materials are so Specific as tO have little adaptability tO different teaching requirements or situations. With increased usage Of the NEM, the teaching role may be downgraded to clerical work, proctoring, grading, and other simple administrative tasks. The development Of NEM centers in every school unit should be encouraged and facilitated. 105 Please indicate the extent Of your agreement or disagreement with each statement. 23. 26. 27. 29. 30. 31. l . Agree strongly 2 . Agree moderately 3 . Agree slightly 4. Disagree slightly 5 . Disagree moderately 6. Disagree strongly The NEM do not suitably provide for the special needs Of either slow learners or brighter children. Provision for the purchase of NEM should be included in every school's instructional budget. The educational value of broadcast (commercial) television is practically nil. The educational value Of Closed Circuit Television is practically nil. The use Of such aids as the bioscope, electric microscope, and science films can revolutionize the teaching Of science. New teachers would be more inclined to use NEM if there were wider usage of these aids in teacher-training programs. Most media persons (10 not use the mass communications media enough in developing a favorable public attitude toward NEM. The percentage Of teachers using newer educational media has increased greatly in recent years . The personal relationship between teacher and student is essential in most learning situations . NEM machines instructing ability cannot be evaluated solely on the basis Of standardized scholastic achievement Of students using them. NEM materials have little adaptability to different teaching requirements or situations. 106 Please indicate the extent of your agreement or disagreement with each statement. 33. 34. 35. 36. 37. 39. 40. 41. 42. 43. Agree strongly Agree moderately Agree slightly Disagree slightly . Disagree moderately . Disagree strongly O‘U'ItprI—a O The newer educational media improves the teacher's ability to communicate with students . Wider use Of newer educational media will uitirnately mean that instructional costs can be reduced. The widespread use Of teaching machines will revolutionize the process Of instruction as we know it now. All teachers should have a central training NEM room where the equipment is permanently installed and available for use there. All teachers in training should take a course in the use Of NEM aids . Learning through new educational media is a passive experience . Wider acdeptance Of currently known NEM aids is needed. PrOper use Of NEM materials can go a long way toward providing for individual differences in the learning needs Of children. Most professional educators have viewed newer educational media in the Specific context Of machines and Operations rather than in the more general point Of view Of a medium for communication. The development Of new NEM aids is a waste Of time and resources . Recent technological trends in education demand a changing teacher role. 107 Please indicate the extent Of your agreement or disagreement with each statement. Agree strongly Agree moderately Agree slightly Disagree slightly . Disagree moderately . Disagree strongly C‘UTVFUJNH R 44. NEM materials and educational media usage should be the province Of NEM specialists. R 45. The creative student is apt to be stifled by the extensive use of NEM instructional media. 46. A basic problem Of NEM education is to change the attitude Of many teachers who look upon NEM aids simply as frills tacked on to their regular teaching. 48. One Of the most satisfactory ways to provide adequate educational Opportunities for the increasing mass Of students is through wider usage Of NEM aids . "R" Represents those items reverse scored. APPENDIX J COMPILED TEACHER RESPONSE TO NEM VARIABLES - TABLE III c hOOl # Teacher # Behavioral Attitude Number of QC Objectives Survey NEM Courses 10 02 14 078.0 05 1° 03 16 117.5 05 10 0a 12 113.0 03 11 06 11 101.0 03 11 07 11. 123.0 02 11 08 11 09a.0 04 12 10 11 099.5 07 12 11 16 156.0 02 12 12 11+ 126.0 02 12 13 1h 101.0 02 12 11+ 16 096.0 03 12 15 14 136.0 03 13 17 14 088.0 03 13 18 16 091.0 06 13 19 16 095.0 03 13 20 13 108.0 01 13 21 14 112.0 04 14 26 14 103.0 01 14 25 14 090.0 01 1“ 26 16 081.0 03 1h 27 16 103.0 09 14 28 11 078.5 01 1“ 29 In 089.5 02 14 30 14 096.0 01 14 31 14 105.0 01 16 32 10 101.5 04 15 3h 12 112.0 01 15 35 1A 100.0 03 15 36 00 115.0 04 16 38 In 128.5 _ 01 16 39 11 133.0 02 16 #0 16 112.0 01 17 42 15 124.0 03 17 43 15 115.5 01 17 AA 12 095.0 03 17 [+5 12 079.0 02 109 COMPILED TEACHER RESPONSE T0 NEM VARIABLES - TABLE III (continued) Behavioral Attitude Number Of S°h°°1 # Teacher #' Objectives Survey NEM Courses 18 17“ 13 081.5 02 18 L8 12 150.0 03 18 A9 12 164.0 01 19 51 16 086.5 03 19 52 16 093.0 01 19 53 14 115.5 05 19 51 14 150.5 01 20 56 12 099.5 01 20 57 16 086.0 05 20 58 16 091.0 05 20 59 16 081.0 on 20 60 15 073.0 03 21 63 15 097.0 02 21 6h 16 079.0 02 21 65 16 082.0 02 21 66 1A 106.5 03 21 67 12 089.5 03 21 68 1A 080.0 03 21 69 16 086.0 02 21 7o 16 077.0 02 21 71 14 093.0 05 21 2 16 076.0 02 21 73 lb 085.0 04 21 7A 1A 106.0 01 22 76 16 073.0 0A 22 77 14 079.0 02 22 78 14 088.0 02 22 79 16 088.0 02 23 81 1A 107.0 04 23 82 1h 072.0 01 23 83 12 134.0 03 23 BA 12 127.5 02 23 85 IA 080.0 03 23 86 12 105.5 07 2A 89 1A 130.0 08 24 90 11 095.0 03 2h 91 16 129.5 04 24 92 13 192.0 03 2b 93 IA 102.0 07 21 , 9A 12 - 096.0 02 2A 95 1A 105.0 01 2A .96 16 111.0 02 15 schools 78 teachers APPENDIX K 110 Wisconsin State University - La Crosse La Crosse, Wisconsin 54601 INTRODUCTORY LETTER TO PARA—PmFESSIONAIS Dear Paraprofessional: In order to complete the survey Of Newer Educational Media of which your project school is a part, it is necessary to ask for additional specific information. Using the enclosed forms please complete the survey using numbers to indicate quantities . The Software form asks for numbers of 16m films you have rented or purchased the last year of the project. The balance of the questions refer tO materials purchased either with district funds or through the CESA #11 project, which are now in your I.M.C. and used by all of the project teachers . The Hardware form asks for numbers Of equipment purchased either with district funds or CESA #11 funds and presently housed in the I.M.C. or classrooms of the project teachers. The central sound system may be a part of the classrooms, if so, mark it as a one (1). Thank you very much for your assistance. Will you please return this form through the CESA #11 driver? Thank you again. Sincerely, Clair Rood , Wisconsin State Univer sity- LaC ros se CR:lf Enc . APPENDIX L NEW EDUCATIONAL MEDIA. SOFTWARE SURVEY ”111 Materials Provided School # Rented From FilIn Libraries Pur cha 3 ed 16mm films - number used last yr 8mm films Loop of single concept films Filnistrips Classroom use Tape Recordings Classroom use Disk Recordings A AClassroom use Language Lab Tapes and Disk Recordings Slides 3-1/4" x 4" or lantern slides 2" x 2" slides Overhead transparency master a Overhead tran spar encie s Study prints Maps P“Globes Dioramas Models Realia (live specimens) 112 3 o o N m o o o o o o m o o o o SHE: NNH o o H o m m o NH 00H 0 N o .o 4 NH . mHoeoa ms m o m a o a o o H a N m o N m AAAOHN NEH EN 0 m HH N NH o NN NH 6 N NH o NH N mass NEH NN o o On 4H 6 o N N 0 NH o 0 EN 0 mchAa Nessa mowocouodmcdhp NHNH NNH om NH om mm QON o NNN o oN smN oNH om sen 4m omosto>o savanna NON ooH om NH om NH omH o oNH 00H 0 Nm cmH 0 mm o eaost0>o moo ow ON NN EN 0 an 0 ma NHN 0 ms 0 ON o oo mosHHm NAN oHH o o 0 EN NN o o o o o o o o o o AoeHHm sxwm cm NH 0 o o a N o o o Nm 0 o o o o mnNH owmsmamH NomH No 0 N8 04H NH ow 0 MN Nm 2H NNN NH 0 EN 0 meteomt mmcwpuoooa HNNH NNH ms smN om NoH om o ooH ONH He NNH NOH NoH 46H NN mass NNNN can NNN HNH ONN msH NNN o NoH mom NHH oNN OON ooH Nam NEH mNHAsm EHHH 00H 0 o o 02 NH o 0 NH 4H 0 o o H HH 0 msHHH AooH mHeN mHN NHN OHN 06m ONH NNN o HEN oHN NN ON oHH NN NNH on AeHHH esoH mEOOH Hmpoe ON mm mm HN ON ma 0H ma ma mm NH Ha OH A 5809 Hoonom onmspmom 00 H [\- H >H mqm6 NNH 0 NH HH N NH oH H N NH N NH N N N NH .NNAA NHANNEHHN NN N N N N N N N N N N N N N NH N .Nota NHANNEHHH Hogoonond NH 0 o H N H H H o H H o N H H o aoOH EEN AOQOONONO NN N N H N H N N N H H N N N N H Ncsom EENH NENNH HNNoN NN NN NN HN 0N NH NH NH NH NH NH NH NH HH oH % same Hoonom OANEOHN: > mqm<5 I mmzommmm mm<3nm