. 1...! .
5|. .itsiulhflurugi
hrg‘lilfl $.SIIEQJSA

2.3..

8:- .
1g; 1,531: In [.2
55-33.11 .1 | . .
. ..!.«!::z......... r... .a...:_. any! gun.
u (I
. 1.93.? , . .s
£11.91; .1 &r r
[1012. 3?. fit . at...
I509... . C... l I 1.‘
.5 :1... 3 .33.... b...
litflzl‘l-O {uni-I .I
it... i.
:g33n4Wifu.lfla.g.RV|fl| I I
. 1 2 Q . .. .
”$3...." «haflh‘ Sign; 1.2.531 s . z.
I‘ K

- Km-
3...»m....ufl..i..z
.5 .2. min; .7.
$21... 33.2
. i. ,
’25... .3... 1
$9.? 1...au.sn.l.. 5.3%....951
”liiallfi. .18} . ~91
n:.§3.!:.!$!9flnfirifluxa.lnart¢dt. u.
: Iii-t»!- ‘ {tzciu
3.... :Ju... ‘

Luann»... J. .
: "Br ._

a: {will}
till»!!! ..
Sinntl...‘

gang n‘i':
:.....i..v..h.....cs.; .Efiflt 12.. ..
o .‘I 3‘-

..cf‘! 11"9’3 0.!
ill". 1

 

 

THBS IS

1

’L
001’

This is to certify that the

dissertation entitled

THE IMPACT OF THE WISCONSIN COMPETENCY BASED ADMISSION
(CBA) PROGRAM ON COLLEGE ACCESS AND OUTCOMES

presented by

Clinton D. Gardner

has been accepted towards fulfillment
of the requirements for

Ph.D. . Educational Administration
degree in

 

 

 

MS U is an Affirmative Action/Equal Opportunity Institution 0-12771

 

 

LIBRARY
Michigan State
University

 

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE ' DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/01 cJCIRC/DateDuepss-p. 1 5

THE IMPACT OF THE WISCONSIN COMPETENCY BASED ADMISSION (CBA)
PROGRAM ON COLLEGE ACCESS AND OUTCOMES

By

Clinton D. Gardner

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Educational Administration

2002

ABSTRACT

THE IMPACT OF THE WISCONSIN COMPETENCY BASED ADMISSION (CBA)
PROGRAM ON COLLEGE ACCESS AND OUTCOMES

BY

Clinton D. Gardner

The purpose of this study was to evaluate the usefulness of the University
of Wisconsin Competency Based Admission program as a college admission
alternative to the Carnegie Unit admission program. To carry out this study, data
were gathered on both admission programs (i.e. Carnegie Unit and CBA) in the
areas of final admission decisions (e.g. admit and deny decisions); first semester
and first year college grades for matriculated students; and the time required by
admission counselors to make final admission decisions. These data were used
to test the impact of the CBA model and Carnegie Unit model on the levels of
admission access; the amount of decision-making efficiency associated with
each program; and the amount of college grade variation explained by each
program.

The aggregate data yielded results that showed the Carnegie Unit
program was more effective in maintaining higher levels of college access.
However, the disaggregated results of the data analysis showed that in four of
the ten universities studied, the CBA program generated higher college access

rates compared to the Carnegie Unit program.

An analysis of first semester college grades generated grade point
average results that indicated that each admission program explained similar
levels of variation in grades. However, differences were observed in the
explained grade variation in five subject areas. The CBA program explained
more of the grade variation in the subjects of social science and foreign
language, while the Carnegie Unit program explained more of the grade variation
in English, math and science.

The aggregate mean time required by admission officers to make final
application decisions for each program identified the Carnegie Unit program to be
more efficient than the CBA program by more than two minutes. A
disaggregated analysis found only one university that had an average CBA
decision time that was lower than the Carnegie Unit decision time.

The evaluation of these data resulted in the researcher establishing that
the CBA program, while not as effective in maintaining broad levels of access
(aggregate) and less efficient compared to the Carnegie Unit program, does hold

promise in its use as an alternative admission strategy.

Copyright by
Clinton D. Gardner

2002

DEDICATION

This study is dedicated to the memory of my late parents, Nellie and David

Gardner, and to my late sister, Rochelle.

ACKNOWLEDGMENT

The support of many people over the course of my life helped to make this
dream a reality. The early mentoring provided by Charles Thornton will always
be valued and never forgotten. Charles your unyielding support and friendship
has affected me in deeply profound ways.

Dr. Marylee Davis has provided immeasurable support in helping me
shape this work over many years. I could not have found a more supportive and
caring committee chairperson. The enthusiasm you show for your work and your
commitment to students is a high standard for all to try to emulate.

To the members of my committee, Dr. Richard Brandenburg, Dr. Lee June
and Dr. Marilyn Amey, thank you for all of your guidance, support and
assistance.

To Drs. Harry Reed, Sam Carter, James Jay and Marti Hesse, thank you
for being mentors, and consistent supporters.

To Dr. Bill Turner, your vision has helped me understand the importance
of college admissions.

To Albert Watson, Murray Edwards, Clayton Wheeler and Lisa Baggett,
thank you for your years of friendship and support.

To my children, Charles and Camille, you have changed and enriched my
life in so many positive and important ways. I hope that this work reminds you of

what is possible once you dedicate yourself to a goal.

vi

To my wife and life partner Pamela Sedwick, the road has finally come to
a successful conclusion. Thank you for being the same high quality, loving

person after close to twenty years of our commitment to each other.

vii

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................. x
LIST OF ABBREVIATIONS .............................................................................. xii
CHAPTER I: INTRODUCTION TO THE STUDY .............................................. 1
Background .................................................................................................. 1
Need for the Study ....................................................................................... 5
Purpose of the Study ................................................................................... 6
Research Questions .................................................................................... 8
Summary of Research Issues ...................................................................... 8
The CBA Program ....................................................................................... 9
Mathematical Knowledge and Reasoning ............................................... 13
Social Science ......................................................................................... 14
Definition of Key Terms ................................................................................ 16
Limitations ..................................................................................................... 18
Delimitations ................................................................................................. 19
Overview of the Remainder of the Dissertation ............................................. 19
CHAPTER II: LITERATURE REVIEW ............................................................... 21
Introduction ................................................................................................... 21
History of Access and Admission to Post-Secondary Institutions ................ 21
Redefining Access ........................................................................................ 27
Admission Requirements and Carnegie Units ............................................. 31
Admission Requirements .............................................................................. 33
Standardized Test Scores and Test Bias Issues .......................................... 34
Admission Decisions with Test Scores ........................................................ 39
Current Admission Challenges .................................................................... 41
Changes in High School Curricula ................................................................ 43
Home-Schooling Options ............................................................................. 45
Responding to Admission Challenges ......................................................... 46
CHAPTER III: METHODS ................................................................................. 48
Introduction ................................................................................................... 48
Research Questions .................................................................................... 48
Research Issues .......................................................................................... 49
The Research Study and Population ........................................................... 50
The CBA Pilot Design .................................................................................. 52
Multi-Attribute Utility Model (MAUT) .............................................................. 54
Admit Rates and the College Access Hypothesis ......................................... 63
Null Hypothesis 1 ................................................................................... 64

viii

Alternative Hypothesis 1 ......................................................................... 64

College Grades Hypothesis ......................................................................... 64
Null Hypothesis 2 ................................................................................... 65
Alternative Hypothesis 2 ......................................................................... 66

Admission Decision Times Hypothesis ........................................................ 66
Null Hypothesis 3 ................................................................................... 67
Alternative Hypothesis 3 ......................................................................... 67

Summary of Research Hypotheses ............................................................. 67

CHAPTER lV: RESULTS AND ANALYSIS OF DATA ...................................... 69

Introduction .................................................................................................. 69

Research Results ........................................................................................ 69
Hypothesis 1 ............................................................................................ 69
Hypothesis 2 ........................................................................................... 73
Hypothesis 3 ........................................................................................... 77

CHAPTER V: SUMMARY, CONCLUSIONS, IMPLICATIONS AND ................. 86
RECOMMENDATIONS FOR FUTURE RESEARCH

Introduction .................................................................................................. 86

Hypotheses .................................................................................................. 86

Findings and Conclusions ............................................................................ 87
Hypothesis 1 ........................................................................................... 87
Hypothesis 2 ........................................................................................... 92
Hypothesis 3 ........................................................................................... 94

Implications of the Study .............................................................................. 98

Direction for Future Research ...................................................................... 101

Summary of Areas for Future Research ...................................................... 103

Post-Pilot Summary Status .......................................................................... 105

APPENDICES
Appendix A — Competency Based Admission: ............................................. 110

The Wisconsin Model (Final Report)

Appendix B — The University of Wisconsin System ..................................... 118
Competency-Based Admission: Admission Competencies

Appendix C - Competency Based Admission: Standardized ...................... 138
Reporting Profile (SRP)

Bibliography ................................................................................................. 141

LIST OF TABLES

Table 1: Admission requirements of Colonial Colleges in 1800 ........................ 26

Table 2: Carnegie Unit admission requirements ............................................... 32
of selected institutions, 1915 to 1930

Table 3: Carnegie Unit admission requirements ............................................... 33
of selected institutions, 1930 to 1945

Table 4: Outcomes of high school rank and high school rank ........................... 40
plus SAT admissions policies at Dartmouth

Table 5: MAUT process, step 7 ........................................................................ 60

Table 6: Prior Admit Probabilities (Based on a five-year average ..................... 61
For each university)

Table 7: Estimated/Projected Carnegie Unit and CBA admits (Using ............... 61
Prior Admit Probabilities and observed admission applications)

Table 8: MAUT process, step 8 (Carnegie Unit Posterior Applications.) ........... 62
Admits and Admit Probabilities

Table 9: MAUT process, step 8 (CBA Posterior Applications, Admits) ............. 62
And Admit Probabilities

Table 10: Expectation Matrix ............................................................................ 68

Table 11: Expected MAUT college access utilities ........................................... 70
(Based on Prior Admit Probabilities)

Table 12: MAUT college access results (Based on Posterior ........................... 71

Admit Probabilities)
Table 13: Differences in Expected and Calculated MAUT utilities .................... 72

for the Carnegie Unit admission program

Table 14: Differences in Expected and Calculated MAUT utilities ................... 72
for the CBA admission program

Table 15: First semester correlation GPA weights by subject area ................... 74

Table 16: Comparison of SRP satisfactory ratings and .................................... 75
first year college GPA

Table 17: Comparison of SRP satisfactory ratings, GPA and ........................... 76
completed course credits

Table 18: Time needed to make decisions on Carnegie Unit ............................ 78
admission applications

Table 19: Time needed to make decisions on CBA admission applications ..... 80

Table 20: Aggregate admission application decision time ................................ 80
(Carnegie Unit and CBA)

Table 21: Results of ANOVA test of between-subject effects ........................... 81

Table 22: Results of Tukey’s multiple comparison of mean differences ............ 82

Table 23: Results of ANOVA test of CBA admission application ...................... 83
decision time for each institution

Table 24: Results of Expectation Matrix ............................................................ 84

Table 25: Alternative admission program policy decision-making matrix .......... 85

Table 26: Admit rates and variations in admit rates for the ............................... 88

Carnegie Unit model and the CBA model

xi

ACT

ANOVA

CBA

GPA

K-12

MAUT

SAT

SRP

LIST OF ABBREVIATIONS

American College Test

Analysis of Variance

Competency Based Admission

Grade Point Average

Kindergarten through 12th Grade

Multi-Attribute Utility Theory

Scholastic Aptitude Test

Standardized Reporting Profile

xii

CHAPTER I: INTRODUCTION TO THE STUDY

Background

The history of access to American higher education is centered on the
structured process called college admission. The college admission process, for
first-time freshmen, involves the use of structured criteria, including high school
grades, standardized test scores, and in some cases a personal statement and
letters of recommendation (Fetter, 1995). These items are the primary criteria used
to determine access to postsecondary education (Astin, 1991; Breland et al., 1995).

Although admission practices vary across colleges and universities, high
school grades and standardized test scores are criteria that are consistently
employed at competitive, “non—open-access” institutions. In screening and
evaluating each student applicant, universities with competitive admission practices
use structured criteria that primarily focus on high school grades and standardized
test scores to determine the applicant’s level of preparation and opportunity for
future academic success (Breland et al., 1995; Heamden, 1973; Maeroff, 1983).
Because students compete for space in the freshman class, these institutions are
competitive in their admission practices (Goren, 1962).

The continued reliance on test scores in making college admission decisions
has been and continues to be controversial. With minority students and women,
standardized tests continue to pose concerns related to the possibility of racial and

gender biases (Crouse 8 Trusheim, 1991; Rosser, 1989a). In recent years, some

highly selective colleges and universities expanded their admission criteria beyond a
dependency on test scores as a means to ensure the enrollment of a racially diverse
student body. The use of affirmative action strategies by some of these institutions,
starting in the 19703, resulted in an enormous increase in college enrollment of
minority students (Jones, 1998). The first major increase resulting from Affirmative
Action admission practices was observed when the college enrollment for Black
students rose from a total of 417,000 in 1970, including students enrolled in
Historically Black Colleges and Universities (HBCUs), to 1,033,000 in 1976 (US.
Department of Education, 1999). By 1994, the college enrollment of Black students
totaled 1,469,000 students (US. Department of Education, 1999). This rise in Black
student enrollment was occurring while the number attending HBCUs was only
increasing at a modest level. In 1976, there were 222,000 Black students enrolled
in HBCUs, and in 1994, a total of 280,000 Black students were enrolled in these
institutions (US. Department of Education, 1999). The enrollment of Black
students, at HBCUs and predominantly White colleges and universities, shows the
important gains in access to higher education for this ethnic group.

While important admission and enrollment gains were occurring among
Blacks, significant increases were observed among women and Hispanics. The
number of Hispanic students enrolled in college between 1988 and 1997 was
680,000 and 1,218,000, respectively (Weiger, 2000). This represents close to an

80% increase over this ten-year period.

An increased enrollment of women in higher education has been evolving for
close to twenty-five years. During the period from 1975 to 1997, the total enrollment
of women was 4,262,000 and 5,014,000, respectively (US. Department of
Education, 1999). While this increase is not as impressive as the gains observed for
Blacks and Hispanics, the increase of 25% represented a sizeable enrollment gain
for women.

While some colleges and universities deviated from the direct application of
making access decisions based solely on high school grades and test scores,
increasing political, and legal pressure is resulting in some of these institutions
returning to a strict interpretation and use of these criteria (Douglass, 1999; Jones,
1998; Karabel, 1999). In fact, the impact of these pressures is seen in recent
freshman admission and enrollment numbers in the state of California. In California,
with the passing of Proposition 209 (This proposition became a legal statute in
November 1996), which bars the use of affirmative action criteria in college
admission for public universities, the impact on access has been significant. The
enrollment of minority students on Califomia’s public university campuses had
steadily increased through 1996 (Douglass, 1999). With the passing of this
proposition in 1996, the data show a dramatic reduction in the enrollment of Black,
Hispanic and Native American freshman students (Jones, 1998; Karabel, 1999).
These results magnify the concerns that the strict admission criteria that are heavily
reliant on test scores will close the access door on significant numbers of minority

students. The maintenance of broad college access for minority students is an

important reason to examine alternative admission programs that could minimize the
importance of test scores in the college admission process.

Additional pressure on the current college admission criteria is being driven
by changes at the K-12 level. A number of curricular changes occurring in
secondary schools across the United States are threatening the fundamental
relationship that characterized educational access to higher education during the
majority of the twentieth century. As secondary schools implement standards that
make it more difficult for colleges and universities to evaluate college readiness,
new admission strategies need to be developed to meet these changing
requirements. The following are some of the K-12 curricular changes that challenge
the current college admission criteria:

. Elimination of letter grades in the high school assessment and

graduation process.

0 Development of block scheduling models where multiple courses (e.g.,

math and science) are taught as one course will alter the admission
process of counting Carnegie Units and make course-by-course grade

assessment in each subject more difficult.

In addition, home schooling options, resulting in an assessment of students’
skills without the benefit of course and subject grades, have an effect on the current
college admission criteria. Developing admission criteria to address each of these

curricular challenges require establishing new methods for evaluating student

achievement.

In essence, the Competency-Based Admission (CBA) program developed by
the University of Wisconsin System is an attempt to address these admission
challenges. Although CBA was designed to provide educational opportunities to
students graduating from high schools with nontraditional curricula, it could also
serve to eliminate the use of standardized test scores in the college admission
process. The benefits derived from developing this program must be compared with
any increased resource trade-offs. If these new demands translate into additional
admission-processing demands and increased resource use, then issues of access

at what expense becomes a relevant factor.

Need for the Study

Numerous curricular changes are occurring in K-12 education in America
and, more specifically, in the state of Wisconsin. A number of K-12 school districts
in Wisconsin are developing plans for non-grade assessment processes and block
scheduling options. These curricular changes could result in an increasing number
of students, using an unorthodox set of credentials, applying for admission to
University of Wisconsin institutions. These students will bring to the college
admission process an alternative set of achievement measurements that, if
examined in the light of current admission practices, could serve as barriers to
postsecondary educational opportunities. To address these current admission

challenges, the University of Wisconsin System developed an alternative admission

process called Competency-Based Admission (CBA: The Wisconsin Model, 1994).

The literature indicates that no comprehensive examination of the Wisconsin
CBA program has been undertaken to answer key admission decision and resource-
efficiency questions. Such an investigation may help to further validate the use of
the CBA evaluation process as an effective admission decision-making model and a
resource-efficient alternative method for determining college access and college
readiness. The present study was undertaken to address that need.

The researcher is hopeful that the results of this study will provide some
evidence to determine if the CBA program has a broader application and use that

could minimize concerns with the use of test scores in college admission.

Purpose of the Study

As changes in K-12 education continue to blanket the landscape, the
establishment of new college admission strategies, similar to the CBA program, will
play an important role in defining college access in the current century. The CBA
program was designed as an alternative approach to the current college admission
criteria and a way of maintaining broad postsecondary educational access (CBA:
The Wisconsin Model, 1994). Given this intention, CBA as an admission process
could serve to meet societal needs by maintaining educational access during a time
of numerous K-12 curricular reforms. In addition, when one examines CBA purely

from a policy perspective, questions related to resource allocations must be

explored to determine whether the program is effective in achieving these important
educational-access outcomes.

Therefore, the researcher’s purpose in this study was to determine (1) how
CBA admission decisions compare with the current admission process, and (2) the
level of resources expended by universities in processing and rendering admission
decisions on CBA applications. The research compared admission-decision rates
and first year college grade outcomes for CBA and the traditional admissions
process (Carnegie Unit) and the time required to make decisions on CBA and
traditional application materials (Camegie-based applications).

In focusing on the aforementioned areas of research, the researcher
evaluated CBA as an alternative admission practice. Therefore, CBA admission-
decisions and resource allocations (time requirements) were compared and
evaluated against those admission-decisions and resource allocations (time
requirements) associated with the use of the traditional admission program (e.g.,
high school grades and test scores). The instrument used to examine and compare
admit decisions forthese two admission programs is a Multi-Attribute Utility (MAUT)
model (Edwards, Guttentag & Snapper, 1975). The MAUT model is often used to
help policy makers formulate program review decisions (Edwards, 1977). The use
of the MAUT model in this analysis will provide a method for evaluating and
determining the impact of the CBA program on access to college, while comparing

and contrasting these results with the traditional admission program.

Research Questions

To facilitate and develop this study, the researcher established topics that
centered on the following questions:

. Do admission decisions using CBA result in similar access outcomes
(Admit Rates) when compared to the traditional admission (Carnegie
Unit) process?

. Do predictive relationships exist between the CBA process and first
semester college grades? If such a relationship exists, how does it
compare to college grades predicted from the traditional admissions
(Carnegie Unit) process?

0 When compared to Carnegie Unit, does CBA represent a time-

efficient process for making college admission decisions?

Summary of Research Issues

. The CBA program was designed by the University of Wisconsin System as
an alternative admission program (CBA: The Wisconsin Model, 1996). This
implies that CBA should lead to comparable admission decisions and
predicts similar levels of success in college when compared to the traditional
admission process (Carnegie Unit). Admission decision rates and first

semester college grades are used to examine this assumption.

. The CBA program has been cited and hailed as an alternative process that
will allow admission offices to render decisions in a timely manner consistent
with the time involved in making decisions on traditional admission (Carnegie
Unit) application materials (e.g., grades and test scores). The CBA program
implies that the use of a Standardized Reporting Profile (SRP) form will allow
university admission offices to evaluate application materials and render
timely admission decisions. This research was undertaken to examine
whether this time-efficiency assumption has merit.

o The researcher conducted this study to determine whether the CBA
processing time expended by university admission offices compared
favorably with the processing time associated with processing traditional
application (Carnegie Unit) materials. In carrying out this phase of the study,
the researcher analyzed the time expended by universities in processing
traditional admission applications, as compared to the time expended by

universities in making CBA decisions.

The CBA Program

In October of 1992, a task force was convened by the University of Wisconsin
President’s Office to explore the prospects of developing a supplemental admission
process for maintaining college access opportunities for students enrolled in
nontraditional curricula and to develop an admission process that would meet the

needs of students enrolled in high schools undergoing curricular changes (CBA: The

Wisconsin Model, 1994). The task force met for several months to explore the
viability of developing a new admission procedure (CBA: The Wisconsin Model,
1994). At the conclusion of an eight-month process, the task force submitted its
recommendations to the University of Wisconsin’s Board of Regents for the creation
of the Competency Based Admission (CBA) program (CBA: The Wisconsin Model,
1994). In June 1993, the Board of Regents endorsed CBA and asked the
President’s Office to develop a strategy to make CBA a viable admission program in
all of the four-year, public universities (CBA: The Wisconsin Model, 1994).
Shortly after the approval from the Board of Regents, the President’s Office
appointed a steering committee to define the parameters needed to make CBA a
reality (CBA: The Wisconsin Model, 1994). Working in partnership with the steering
committee were six subcommittees made up of seventy-five faculty members from
all of the public universities and the two-year technical colleges (Community
Colleges in Wisconsin), teachers from various K-12 school districts, and
administrators from the University of Wisconsin President’s Office (CBA: The
Wisconsin Model, 1994). These committee members started work on this initiative
in November of 1993 (CBA: The Wisconsin Model, 1994). Committee members
maintained continuous contact as they focused on the charge assigned to each
group (CBA: The Wisconsin Model, 1994). Five of the six subcommittees worked on
developing core competency requirements needed for admission and necessary for
students to achieve academic success on any of the University of Wisconsin four-

year campuses (CBA: The Wisconsin Model, 1994). The members served on

10

committees that established CBA admission requirements in the subject areas of
English, math, science, social science and foreign language (CBA: The Wisconsin
Model, 1994). The final documents developed by these committees became known
as the CBA-Subject Competencies (CBA: The Wisconsin Model, 1994).

The sixth subcommittee focused its attention on developing a process for
summarizing the competency levels attained in each subject (CBA: The Wisconsin
Model, 1994). The work of this committee resulted in the development of the
Standardized Reporting Profile (SRP) form (CBA: The Wisconsin Model, 1994). The
SRP is the form used by high schools to summarize student competency scores in
each academic subject (CBA: The Wisconsin Model, 1994). This form is submitted
to the university admission office for a final admission decision on each applicant
(CBA: The Wisconsin Model, 1994).

The subcommittees completed their assignments in May 1994 (CBA: The
Wisconsin Model, 1994). Their collective work resulted in the development of a five-
subject set of competency requirements to be used in making college admission
decisions, thereafter called the Competency Based Admission Program/T he
Wisconsin Model (CBA: The Wisconsin Model, 1994).

The CBA program was established as the formal, alternative college
admission criteria for students graduating from high school curricula that could not
easily be evaluated using the traditional Carnegie Unit admission criteria (CBA: The
Wisconsin Model, 1994). The potential use and impact of the CBA program in the

college admission process could be significant. For example, standardized college

11

admission tests have been continuously cited as an important college enrollment
barrier for minority students and in some cases female students (Medina & Neill,
1990; Rosser, 19893). This argument points out a concern that college access
decisions made solely on the use of high school grades and test scores could have
a negative effect on these two groups. By its design, the CBA program could
minimize the importance and reliance on standardized test scores in college
admission. As a result, CBA has the potential to expand access to college for
students of color and women.

The CBA program asks high school teachers to evaluate each student's
competency in each subject area (CBA: The Wisconsin Model, 1994). An
understanding of how this process works can be obtained by looking at the subject
of math. Math teachers are asked to determine how well a student is able to
complete math problems ranging from elementary algebra to more complex levels of
trigonometry and analytical geometry (CBA: Admission Competencies, 1995).
These math problems were selected as containing the necessary knowledge each
student must possess in order to be successful in math courses on a University of
Wisconsin campus (CBA: The Wisconsin Model, 1994). The following represents
some examples of CBA competency statements that high school math teachers are

asked to provide as a formal evaluation of each student’s skill level:

12

Mathematical Knowledge and Reasoning
1. Use of Constraints:

3. Perform arithmetic operations in proper order, represent real
numbers in a variety of forms and simplify arithmetic expressions
involving radicals. Use arithmetic operations to model problem
situations. Use mental arithmetic and estimation.

b. Construct and read charts, tables and graphs that summarize data
from real world situations.

2. Use of Variable in Linear Situations:
a. Solve linear systems of equations in two or more variables and
interpret solutions both symbolically and graphically.

b. Use matrices to represent and analyze linear situations.

3. Use of Variables ln Algebraic Situations:
a. Add, subtract, multiply, divide and exponentiate polynomial,
rational, complex fractional and radical expressions and simplify
the results.

b. Solve algebraic equations and inequalities in one variable,
including those which can be factored into linear and quadratic
expressions, or which contain fractional expressions, absolute
values, radicals or fractional exponents.

4. Use of Variables In Transcendental Situations:
a. Manipulate and simplify expressions involving exponentials or
logarithm. Solve equations and inequalities involving
exponential and logarithmic expressions.

13

b. Use the language, notation and properties of exponential,
logarithmic and trigonometric (sine, cosine, tangent) functions
and their graphs.

5. Geometry:
a. Visualize and sketch points, lines, planes and simple solids in
three-dimensional space and find volumes of boxes and cylinders.

b. Use knowledge of parallelism, perpendicularity and associated
angle properties to analyze and construct figures and represent
problem situations (with or without coordinates).

In the subject area of social science, the following examples are represented

in the competency evaluation process:

Social Science

1. Knowledge:

a. Students should be able to distinguish among the powers
assigned to the executive, legislative, and judicial branches of the
government in the US. Constitution, and between the areas of
responsibility assigned to the state and federal governments;
identify significant changes that have altered the foregoing through
judicial interpretation and other developments.

b. Students should be able to discuss the concepts of class, race,
ethnicity, and gender in the analysis of society, and describe how
the following have affected the status of women in various cultures

14

of the world, including the United States: 1) increasing numbers of
women in the economy; 2) the rebirth of an organized women’s
movements; 3) traditional definitions of women’s roles.

0. Students should be able to recognize the principal eras in the
history of western civilization from Greek and Roman times to the
present, identifying elements used in conventional periodizations,
show a knowledge of the basic chronologies of world history.

2. Skills and Methods:
a. Students should be able to demonstrate ability to use geographic

tools and resources (e.g., maps, atlases, data bases, and spatial
data).

b. Students should be able to show awareness of the variety of
sources used as evidence by social scientists and humanists,
including print material, statistics, paintings, sculpture,
architecture, film, photographs, and other artifacts.

3. Integrative Applications:

3. Students should be able to demonstrate their knowledge and skills
through critical analyses in which, for example, they compare and
contrast the impact of race, class, ethnicity, and gender on the
histories of US. and other cultures.

b. Students should be able to demonstrate their knowledge and skills
through critical analyses in which, for example, they apply
economic reasoning to help explain historical and current
developments and issues,distinguishing between and showing the
interaction of the US. domestic economy and the global economy.

15

The CBA process uses a similar approach in asking teachers of English,
science, and foreign language to evaluate competency levels for each student

applicant.

Definition of Key Terms

The following terms are defined in the context in which they are used in this
dissertation:

Cameme Unit: The name Camegle Unit is derived from the Carnegie
Foundation for the Advancement of Teaching. In 1909, the Camegle Foundation
provided the leadership for the creation and development of a systematic process
for quantifying the academic achievement of K-12 students (Tompkins & Gaumnitz,
1954). By quantifying the number of class hours and the grades received in college-
preparatory courses, Camegle Units are the standard criteria used to evaluate
learning outcomes (Tompkins & Gaumnitz, 1954). Over the course of their 92-year
history, Carnegie Units have continued to be an important part of college admission
criteria.

Carnegie Unit Admission: The process of using Camegle Units and
standardized test scores (American College Test—ACT and Scholastic Aptitude
Test—SAT) as the primary criteria for making college admission decisions (CBA: The
Wisconsin Model, 1994; Wechsler, 1977). The Camegle Unit admission criteria
commonly used by most colleges and universities requires four years of college-

preparatory English; three years each of social studies, math, and science; and two

16

years of foreign language coursework (Tompkins 8: Gaumnitz, 1954).

Commtengy Based Admission (CBA): An admission process that uses newly
developed University of Wisconsin System competencies as the primary basis for
making admission decisions. This process allows high school teachers, using a
Standardized Reporting Profile (SRP) form, to evaluate students” competencies in
each academic subject (e.g., English, math, science, social science, and foreign
language). The CBA process was developed and designed to serve as a direct
alternative and substitute for the traditional Camegle Unit admission process.

Standardized Repgrting Profile (SRP) form: The form used to summarize the
level of subject-specific competencies for each admission applicant. Teacher
evaluations for all academic subjects (English, math, science, social science, and
foreign language) are listed on the SRP form.

Traditional admission applications: Applications that require high school
transcripts, listing grades and standardized test scores, as the material needed in
the admission decision-making process. This term is another way of denoting an
admission process that requires Camegle Unit.

Traditional college admission: The admission process that uses criteria that
rely on Carnegie Units and standardized test scores as the basis for making final

admission decisions (Often referred to as Camegle Unit Admission).

17

Limitations

The examination of admit decisions (access) and the resources expended in
processing CBA applications has important implications for higher education in
Wisconsin, as well as other states. Although gaining a better understanding of
college access decisions and the time expended in processing these admission
applications will provide useful insights, this examination is not without limitations.

A limitation of the study results from the data being collected during a pilot
phase study of the impact of CBA. Some of the observed results could vary during
a full program implementation.

The second limitation is that data on the Camegle Unit and the CBA
programs were collected by the University of Wisconsin System. As a result, the
analysis in this study utilized secondary data sources.

The third limitation is that Carnegie Unit and CBA admission decisions are
made by two separate admission officers at each university. Since all admission
officers at each university review and make Camegle Unit decisions on a regular
basis, the lack of a full dissemination process for CBA applications to these same
officers could result in a directional bias (potentially positive or negative) for CBA

admit rates.

18

Delimitations
An explanation of the participant data used to make admission decisions will
be limited to the following areas:
0 High School Grades
0 CBA — Standardized Reporting Profile scores
0 University Admit Decisions
. University Deny Decisions
0 Admit Decision Times
. Deny Decision Times
. First Semester College Grades

0 First Year College Grades

Based on the number of admission decisions made during the pilot phase,
the study will be limited to analyzing data from ten of eleven University of Wisconsin
institutions (One institution had insignificant admission data which could not be

evaluated).

Overview of the Remainder of the Dissertation

To begin, research on access to college and the history and evolution of
college admission criteria is discussed in Chapter II. The traditional admission

applications (Carnegie Unit) and the rationale behind the development of the CBA

19

program are also discussed in Chapter II. In Chapter III, the research procedures
and methodology are explained, and a discussion of how the Multi-Attribute Utility
(MAUT) process is used in making program review decisions in comparing which
admission program is better at maintaining levels of college access (i.e., Camegle
Unit versus CBA). Also listed in Chapter III is the establishment of hypotheses
related to college grades and the time needed to make college admission decisions
based on Camegle Unit and CBA applications. The results of these analyses are
presented in Chapter IV. In Chapter V, the summary, conclusions, implications and

recommendations for future research are outlined.

20

CHAPTER II: LITERATURE REVIEW

Introduction

Chapter II explores the history of access to postsecondary education in
America, beginning with the founding of Harvard College and other early colonial
colleges. Chapter II details how access to American higher education changed after
the passage of the Morrill Act of 1862 and 1890. Also discussed is the historical
development of Camegle Units and standard test scores, as well as the evolution of
structured college admission criteria. Important challenges and threats facing
traditional admission criteria are highlighted in this chapter. In addition, curricular
changes in K-12 schools, high school scheduling innovations, and home schooling

options are discussed as important issues leading to the development of the CBA

program.

History of Access and Admission to Postsecondary Institutions

The history of access to American colleges and universities can be
summarized by examining two key periods. These periods can be characterized as
the pre-Morrill Act period and the post-Morrill Act period. Many historians have
designated these periods in higher education as the pre-Civil War period and the
post-Civil War period (Allmendinger, 1971 ; Axtell, 1971 ; Potts, 1971 ).

The period before 1862 has been described as a time of limited educational

21

access. In this pre-Morrill Act period, education was available to a limited number of
wealthy young men whom faculty members admitted to a number of elite colleges
(Wechsler, 1977). The vast majority of these institutions were small, private liberal
arts colleges (Axtell, 1971). Harvard College, founded in 1636, established a
standard policy of limited access by educating only a select, elite class of young
men.

Research conducted by historian Ronald Story (1975a, 1975b) indicated that
students from private preparatory schools in Massachusetts and other New England
states constituted the vast majority of the Harvard student body during the period
from 1801 to 1845. The inclusion of significant numbers of public high school
students at Harvard was not seen until after 1846. Story (1975b) summarized
Harvard’s admission policy during this period by noting that “the proportion of
Harvardians from private boarding schools-institutions providing preparatory
instruction to boarders for profit-was about the same in the twenty years after 1820
as in the twenty years before” (p. 286).

The establishment of the College of William and Mary in Virginia in 1693
resulted in a continuation of the limited-access trend started by Harvard. Whereas
Harvard focused attention on educating leaders across many disciplines, the
mission of William and Mary was to prepare young men for careers in the clergy
(Rudolph, 1990). The precedent established by William and Mary spread through
eariy colonial America, resulting in the establishment of other secular-based

educational institutions during the eighteenth century (Herbst, 1974; Tewksbury,

22

1965). The establishment of Yale, Princeton, Dartmouth, and Brown perpetuated
the tradition of educating future clergymen (Rudolph, 1990). According to traditional
historians, these institutions maintained a commitment to the limited-access
ideology established by Harvard and William and Mary (Herbst, 1975; Story, 19753,
1975b). This entrenched philosophy of educating society’s financially elite class
established a precedent for all institutions founded during the eighteenth century
and the first half of the nineteenth century.

Although traditionalist historians have characterized these institutions as
catering to wealthy citizens, certain evidence indicates an expansion and
broadening of educational access to less prosperous students (Angelo, 1983).
Historian David Allmendinger (1971, 1975) noted that this shift, which originated in
eastern colleges, occurred long before the establishment of universities. According
to revisionist historians, these nineteenth-century colleges exhibited many
egalitarian characteristics by providing educational access to a broad segment of
society (Burke, 1982; Potts, 1975, 1977). Although the time frame of this

transformation has not been fully established, Allmendinger (1971) wrote,

It began almost imperceptibly at the time of the American Revolution and
then assumed unprecedented proportions after 1800. Into New England
colleges there came a flood of students from poor families. Never before had
these families sent sons to college, nor could they afford to do so now; their
sons came voluntarily to higher education, for the most part having made
their own decisions. All ten New England colleges founded before 1822
experienced influxes of these poor young men, especially the newer,
provincial institutions outside New Haven and Cambridge. (pp. 381-382)

The debate between traditionalists and revisionists concerning educational

access for poor Americans during the 19th century continues today. Although more

23

research is needed on educational access for this group, to determine when and
why these young men enrolled in college and what challenges they faced, Blackburn
and Conrad (1986) concluded, “Whether the revisionists’ data of student
backgrounds proves that the colleges were aristocratic or not is another matter. The
less privileged may have attended college for any of a number of reasons, in spite of
discrimination they may have suffered” (p. 223).

If the revisionists are correct, the experience of these early New England
colleges was more an exception than the general rule in American higher education.
Most colleges maintained a policy of restrictive access during this early period.
Moreover, the process of limiting access to these institutions constituted the earliest
form of college admission criteria (Story, 1975a, 1975b). These criteria allowed
institutions to pick the choicest of society’s elite. Students seeking admission to
these schools often were required to interview with faculty members and pass the
institutions’ qualifying exams (Wechsler, 1977). In this eariy period in American
higher education, a process of restricted access was perpetuated, with educational
opportunities accruing to the wealthiest segment of society.

Whereas at Harvard great emphasis was placed on the social and economic
background of prospective students, other important admission criteria also were
established. The initial criterion was for students to interview with Harvard’s
president so that he could assess issues of character and knowledge (Fine, 1946).
Once a dialogue was established, the student was required to demonstrate verbal

proficiency in both Greek and Latin. As early as 1643, the following admission

24

statement appeared in Harvard’s publications:

When any scholar is able to read Tully or such like classical Latin author
extempore, and make and speak true Latin in verse and prose at sight, and
decline perfectly the paradigms of nouns and verbs in the Greek tongue, then
may he be admitted into the college, nor shall any claim admission before
such qualifications. (Broome, 1903, p. 18)

The College of William and Mary established a similar admission statement,
indicating that before matriculation a student “must first undergo an examination
before the president and masters” (Fine, 1946, p. 15). When Columbia was
established in 1754, it took Harvard’s admission policy and expanded its

requirements, stating:

None shall be admitted (unless by a particular act of the Governors) but such
as can read the first three of Tully’s Select Orations, and the three final
Books of Virgil’s Aeneid into English, and the ten first chapters of St. John’s
Gospel into Greek, and such as are well versed in all the rules of Clark’s
introduction so as to make true Grammatical Latine, and are expert in
arithmetic as far as the rule of reduction to be examined by the president.
(Fine, 1946, pp. 15-16)

In addition, other early New England colleges followed Harvard’s lead by
establishing admission criteria with proficiency in Greek and Latin as their core
requirement. The admission requirements at Yale, Princeton, and Brown were all
developed using Harvard’s criteria as a guide. The similarities in admission

requirements among these early colleges are noteworthy, as Broome (1903)

suggested:

Uniformity was the striking characteristic of college admission requirements
during the Colonial Period. First of all there was a uniform aim; secondly,
there was a uniform course of study, with absolutely no flexibility; thirdly, the
grammar school had a single purpose-to prepare for the college-and
consequently the same condition existed there. Uniformity in admission
requirements was, therefore, a natural consequence. (pp. 38-39)

25

In addition to requiring grammar and composition skills in Latin and Greek,
math (arithmetic) proficiency was a consistent admission requirement for most
colonial colleges by 1800. Interestingly, in 1800, Harvard College was the notable
exception to the math requirement established by many colonial colleges (Broome,

1903). (See Table 1.)

Table 1: Admission requirements of colonial colleges in 1800.

 

 

 

 

 

 

 

 

Admission Requirement
Latin Latin Greek Greek Math/
College Grammar Composition Grammar Composition Arithmetic

Brown Yes Yes Yes Yes Yes
Columbia Yes Yes Yes Yes Yes
Harvard Yes Yes Yes Yes No
Princeton Yes Yes Yes Yes Yes
Yale Yes Yes Yes Yes Yes
William and Mary Yes Yes Yes Yes Yes

 

 

 

 

 

 

 

 

Note: From A Historical and Critical Look at Collge Admission Reguirements,
by E. C. Broome, 1903, New York: MacMillan.

 

The influence of Harvard’s admission policy spread far beyond these early
colonial colleges. The policy itself, as well as its component parts, had a profound
influence on college admission requirements throughout the United States. When
the University of Michigan opened in 1841, it adopted the following admission

statement:

26

Applicants for admission must adduce satisfactory evidence of good moral
character, and sustain an examination in geography, arithmetic, the elements
of algebra, the grammar of English, Latin, and Greek languages, the exercise
and reader of Andrews Cornelius Nepos, Vita Washingtonii, Sallust, Cicero’s
Orations, Jacobs’ Greek Reader, and the Evangelist. (Farrand, 1885, p. 47)

Seven years later, these initial criteria were changed to include:

English Grammar, Geography, Arithmetic, Algebra through simple equations,
Kreb’s Guide for the writing of Latin, Latin Reader, Cornelius Nepos, Cicero's
Orations, Virgil's Bucolics and six books of the Aeneid, Greek Reader
through, Latin and Greek Grammar, Keightley’s (or Pinnock’s, Goldsmith’s)
Grecian History to the time of Alexander the Great, and Roman to the time of
the Empire. (Broome, 1903, pp. 44-45)

Regardless of the institution being considered, the admission requirements
developed at Harvard were the prototype criteria during the eighteenth century and

the first half of the nineteenth century. '

Redefining Access

Passage of the Morrill Act of 1862 (Land Grant Act of 1862) served as a
critical point of departure by redefining the idea of educational access in American
society (Axtell, 1971). This legislation gave public land to existing colleges, while
establishing new institutions with the singular mission of providing a much larger
segment of society with access to educational opportunities (Roderick & Stephens,
1979). Today, these institutions are profiled as large (student enrollment), public
(taxpayer supported), and research-intensive universities (commonly referred to as

1862 land grant universities).

27

The Land Grant Act of 1862 did not provide an access provision for newly
freed slaves following the Civil War. Therefore, in an attempt to reestablish a
society of educational inclusion and access for all citizens, the US. Congress
passed the Morrill Act of 1890 (Land Grant Act of 1890), which established a group
of black colleges to educate emancipated slaves. These 1890 land grant colleges
and universities were designed to parallel the 1862 land grant universities by
embodying similar principles of educational access.

With the establishment of universities, the latter part of the nineteenth century
can be viewed as the classical period in American higher education (Axtell, 1971;
Herbst, 1975). Highlighting this period was the vast educational opportunities
provided to students in every state with little regard to socioeconomic status. During
this period, access to higher education became a reality for the vast majority of high
school graduates.

In the twentieth century, two major pieces of federal legislation impacted and
shaped the direction of college access. The first boost to college access came after
the end of World War II. Colleges and universities experienced increased
enrollments from World War II veterans. In 1944, the federal government enacted
legislation called the Servicemen’s Readjustment Act (commonly called the GI. Bill)
which provided veterans the financial benefits needed to pay for a college education
(Duffy & Goldberg, 1998). The impact of this legislation on college enrollment was
unprecedented in the history of American higher education (Olson, 1974). In 1945,

88,000 veterans were enrolled in college, representing 5.2% of all students (total

28

enrollment was 1,676,851) enrolled during that year (Olson, 1974). By 1946,
veterans represented 48.7% (1,013,000 veteran enrollment) of the total college
enrollment of 2,078,095 students (Olson, 1974). The enormous impact of veterans
enrolling in college was observed on the University of Wisconsin-Madison campus
starting in 1946. The total enrollment at the University of Wisconsin-Madison
increased to 18,598 in 1946 compared to 9,028 during the 1945 academic year
(Olson, 1974). During that period, veteran enrollment increased to 11,076 in 1946
from a total of 1,347 in 1945 (Olson, 1974). After World War II, the vast majority of
colleges exercised an open door admission policy to accommodate the enrollment
of veterans (Duffy & Goldberg, 1998; Olson, 1974).

The second major impact on college access in the twentieth century came
after the legislative enactment of the Civil Rights Act of 1964. By ending legalized
segregation, the act helped to pave the way for African American students to enroll
in White colleges and universities (Duffy & Goldberg, 1998). In addition, the act
helped to increase the total number of African American students enrolled in
colleges and universities immediately after the passage of the legislation (Cross &
Slater, 1999).

The Civil Rights Act of 1964, was followed by additional legislation in the
early 19703 that gave rise to the use of Affirmative Action strategies in college
admission (Cross & Slater, 1999; Orfield, 1998). The use of Affirmative Action
allowed colleges and universities to consider factors such as race, gender and

ethnicity in making admission decisions (Bryant, 1996; Duffy & Goldberg, 1998).

29

This expanded the admission criteria beyond the use of grades and test scores and
opened the door to the enrollment of a large number of African American, Hispanic
and female students (Bryant, 1996; Cross & Slater, 1999; Orfield, 1998). Between
1964 and 1970, enrollment of African American students in higher education
increased from 274,000 to 522,000 (US. Department of Education, 1999). African
American student enrollment in 1975 increased to 927,000 students (US.
Department of Education, 1999). After 1975, the enrollment of African American
students in higher education continued to increase reaching a high of 1,415,000
students in 1996 (US. Department of Education, 1999). During the period from
1975 to 1996, Hispanic student enrollment in higher education grew from 41 1 ,000 to
1,039,000 (US. Department of Education, 1999). The enrollment of women during
the period from 1965 to 1970 grew from 2,139,000 to 2,962,000 (US. Department of
Education, 1999). The period from 1970 to 1997 resulted in a 110% increase as the
enrollment of women grew to 6,252,000 (US. Department of Education, 1999).
Since the current legislative and legal challenges to Affirmative Action have focused
almost exclusively on race-based admission practices, there has been very little
impact on the enrollment of women (Bryant, 1996; Hu-DeHart, 1997; Jones, 1998;
Pusser, 2001 ). In addition, while the aggregate African American and Hispanic
enrollment has continued to reach record levels, the elimination of Affirmative Action
consideration in college admission has had a negative effect on these populations in
states like California and Texas (Bok, 2000; Chapa & Lazaro, 1998; Douglass, 1999;

Karabel, 1999).

30

Admission Requirements and Camegle Units

The end of the nineteenth century gave rise to numerous challenges for the
emerging industrialized American society. During the early part of the twentieth
century, many new colleges and universities were established to prepare workers to
meet the demands of business and industry for skilled laborers. One problem these
institutions faced was the lack of a uniform standard and the absence of an agreed-
upon procedure for evaluating students” high school records (Broome, 1903).
According to Broome, the lack of an admission standard across American colleges

and universities placed a significant burden on preparatory schools’ resources:

Schools which send students to several colleges have been compelled to
maintain more classes than they othewvise would, because the several
colleges failed to agree on any policy of admission requirements, and petty
and non-essential differences were insisted on, even in the more common
subjects. (p. 127)

To address this admission issue, the Carnegie Foundation for the
Advancement of Teaching established a blue-ribbon committee in 1909. This
committee, whose members included a number of distinguished college presidents,
formulated a set of admission requirements called Carnegie Units. The Carnegie
Units are a measurement of high school work in terms of credit based on time spent
in the classroom (Tompkins & Gaumnitz, 1954). These units of evaluation provides
higher education admission offices a method for counting and evaluating high
school coursework to determine each student’s college-readiness skills. The
Carnegie Units take the four-year high school as a basis and assumes that (a) the
length of the school year was 36 to 40 weeks, (b) a class period was 40 to 60

minutes long, and (c) a subject was studied for four or five periods a week

31

(Tompkins 8 Gaumnitz, 1954). For example, four years of English would be equal
to four units, a year of algebra one unit, a year of plane geometry another unit, a
year of history one unit, and two years of a foreign language two units (Fine, 1946).

Development of the Carnegie Units had an immediate and widespread effect
on college admission standards. Colleges and universities expressed and
publicized their admission requirements based on the recommendations of the
Carnegie Foundation. For example, in 1911, students seeking admission to the
University of Chicago needed a minimum of 12 Carnegie Units of high school
coursework (Reeves & Russell, 1933). By 1941, the vast majority of colleges and

universities used 15 Carnegie Units as the minimum benchmark and standard

admission requirement (see Tables 2 and 3) (Emanuel, 1953).

Table 2: Carnegie Unit admission requirements of selected institutions,
1 91 5 to 1930.

 

 

 

 

 

 

 

 

 

 

 

 

 

Number of Carnegie Units Required
Social Foreign
College/University English Math Science Science Language Other
Ohio University 2 2 1 1 — —
Ohio Wesleyan 3 3 2 1 4 -
Wayne State Univ. 3 2 —- 1 2 -
Wooster College 3 2 1 2 2 -

 

 

The work of the Carnegie Foundation allowed colleges and universities to
specify their admission requirements directly and unambiguously. The process of

counting and totaling units was a key innovation that established modem—day

32

admission criteria. The significance of the Carnegie Units is evidenced by its
longevity, spanning more than nine decades—close to 90 years of continuous use in

college and university admission.

Table 3: Carnegie Unit admission requirements of selected institutions,
1930 to 1945.

 

 

 

 

 

 

 

Number of Carnegie Units Required
Social Foreign
College/University English Math Science Science Language Other
Univ. of California Berkeley 3 2 1 1 2 3“I
3b

Iowa State Univ. 3 2 2 2 Reading -

Speaking

Proficiency
Michigan State Univ. 3 2 3 4 Background 3°
Univ. of Missouri 3 2 1 1 2 6d

 

 

 

 

 

 

 

 

Note. From A Historical and Criticfllgok at College Admission Requirements, by E.
C. Broome, 1903, New York: Macmillan; A Historvof the Iowa State Colleg_e_, by E.
D. Ross, 1942, Ames: The Iowa State College Press; The University of California
1868-1968, by V. Stadtmann, 1970, New York: McGraw-Hill; A History of 4&9
University of Missou_ri, by F. F. Stephens, 1962, Columbia: University of Missouri
Press.

aCoursework in English, math, science, and foreign language.
General electives.

:Vocational coursework.
Academic electives (maximum of 3 vocational units).

Admission Requirements

In stark contrast to the nineteenth century, the second half of the twentieth

century represented a time of qualified access to higher education (Fetter, 1995;

33

Trow, 1981). During this period, college admission and educational access was
defined through the use of high school grades in academic subjects (Carnegie Units
with specific numbers of requirements in math, English, science, social science, and
foreign language). These subjects are considered important ingredients in
predicting future college success. At the same time, the Scholastic Aptitude Test
(SAT) and the American College Test (ACT) were commonly used in assessing the
level of quantifiable student knowledge. Taken together, grades and test scores
constitute the most commonly used four-year college admission criteria and it is
designed to limit and restrict access to postsecondary education (Bracey, 1990;

Heamden, 1973; Powell & Steelman, 1996).

Standardized Test Scores and Test Bias Issues

The SAT gained acceptance as a college admission criterion during the early
part of the twentieth century (Grossman, 1935). In contrast, the ACT was developed
in 1959 and gained widespread use and acceptance during the 1960s. In the early
1930s, 26% of postsecondary schools used the SAT (Grossman, 1935). By 1992,
more than 90% of four-year colleges and universities used the SAT or the ACT as a
primary admission requirement (Breland et al., 1995).

Before and even after validation of the SAT and ACT as standardized tests,
most colleges and universities continued to administer an institutional examination

to evaluate students’ knowledge across a range of subject matter prior to making

34

final admission-decisions. The oral and written examinations used for admission to
early colonial colleges were viewed as psychological tests (Fine, 1946). While these
tests were used in the admission process, they were not standardized tests but
instead represented exams that were specific to each institution. Much later, many
universities described the institution’s test as a “comprehensive examination"
(Michigan State College, 1941, p. 42). These institutional tests were eliminated as
colleges and universities incorporated the ACT and SAT tests as part of their
admission criteria.

Although most colleges and universities have defended the use of the SAT
and ACT as admission criteria, these standardized tests have come under much
scrutiny from multiple segments of society (Crouse & Trusheim, 1991; Heamden,
1973; Nettles & Nettles, 1999). The arguments for retaining standardized tests
focus on the reliability of the instruments in evaluating students’ current levels of
knowledge and learning. Alternatively, critics have argued a persuasive case for
discontinuing the use of these tests by citing empirical evidence that casts doubt on
their predictive validity (Crouse & Trusheim, 1988; Rosser, 1989a).

Over the past three decades, concerns about the administration and use of
standardized test scores in college admission decisions has been the subject of
critical examination by numerous researchers and scholars. Much of the concern
centers on whether or not these exams are culturally biased and underestimate the
abilities of students from minority groups (Medina & Neill, 1990). A similar concern
has focused attention on the possibility that these exams have a gender bias

(Rosser, 19893). In exploring the issue of bias, a number of scholars have

35

examined three primary categories that may serve to devalue the skills and abilities
of students in these groups. These three areas of interest are social bias,
measurement bias, and predictive bias (Jacobs, 1991; Medina & Neill, 1990;
Rosser, 1989a).

The social bias argument points to differences in socio—economic and cultural
distinctions between men and women and members of ethnic groups (Taylor & Lee,
1987; Willie, 1985). Walter Jacobs defines social bias as the ”bias that extends a
notion of unfairness when test score differences by demographic groups are more
rooted to differences in society" (Jacobs, 1991, page 23).

The cultural differences argument states that the vast majority of White
students live and are raised in a familiar, popular and dominant environment that
nurtures their personal development (Stewart, 1993). It has been noted that White
students are raised in a singular, monolithic environment that fosters a clear vision
of their role and place in society (Helms, 1992). By extension, some argue that
standardized tests are constructed based on issues and activities related to
American popular culture and are more user friendly to White students
(Scheuneman, 1987).

By contrast, scholars argue that women and minority students are raised in
dualistic cultural environments (Rosser, 1989a). As evidence of this duality,
scholars note that many minority students live and interact in two distinctly separate
worlds on a daily basis (Rosser, 1989a). African American students may encounter
the cultural values of the larger society on a daily basis, however, their primary
cultural values are often shaped by the ethnic and gender composition of their

community. A case in point is the test score gap that exists between African

36

American students who reside in predominantly African American communities and
those African American students who live in mostly white communities (Nettles &
Nettles, 1999). The test score gap between these two group is large, with the
scores of African American students who reside in predominantly White
communities coming close to the scores achieved by Whites on these tests (Lyman,
1998). While issues related to the quality of schools, stability of family structure and
a number of other factors may contribute to these test score differences, the social
bias factor is viewed as being an important reason for some of the variation in test
scores (Scheuneman & Oakland, 1998).

The differences in Hispanic test scores and Whites are argued based on
cultural distinctions (Codina, 1991 ). Scholars have noted that for large numbers of
Hispanics, Spanish is the dominant language spoken in the home and in
predominantly Hispanic communities (Sandoval & Duran, 1998). For these
students, taking tests written in English may still result in many challenges. This fact
is referenced in research conducted by Scheuneman and Oakland (1998).
Scheuneman and Oakland noted that students’ success and their overall
“performance on tests requiring the use of language may be affected even for
bilingual examinees who are competent in English” (Scheuneman & Oakland, 1998,
page 87).

While English is an important language for Hispanic students, it will
sometimes take on the role of a second language in these communities (Codina,
1991; Cortada, 1984). It has been estimated that close to half (48%) of the Hispanic
population who are fluent in Spanish are much less proficient in English (Sandoval &

Duran, 1998). As with African American students, the test score gap is similar

37

between Hispanic students who reside in predominantly Hispanic communities and
those who live in predominantly White communities (Pennock-Roman, 1990).

Some scholars and critics argue that social bias in these tests invariably
result in a measurement and predictive bias (Crouse & Trusheim, 1991; Rosser,
1989a). For women and minority students, test scores have less validity in
predicting levels of success in college (Rosser, 1989a). The consequence of the
measurement bias is the underperformance of students from minority populations on
these tests when compared to White student.

In relation to women and standardized tests, some researchers have pointed
out that these exams under predict the true abilities of girls (Rosser, 1989a). Phyllis
Rosser noted that “the biggest sex differences in SAT score averages-much larger
than the national averages for the test as a whole-occurred at the lowest GPA level”
(Rosser, 1989b, Page 61).

The argument of test bias is compelling when you consider that on average
females have lower SAT and ACT scores but consistently receive higher grades in
both high school and college (Fleming & Garcia, 1998; Rosser, 19893). These
results highlight the challenges that females from various ethnic groups face on SAT
and ACT tests. A number of studies comparing the test scores of men and women
have observed that women perform less well on multiple choice tests than essay
based assessment instruments (Bell & Hay, 1987; Bolger 8. Kellaghan, 1990).
These gender test score differences have been observed within various ethnic
groups (Mazzeo, Schmitt & Bleistein, 1993). The results have prompted some to
conclude, “minority female high school students are doubly penalized by both

gender and racial biases of the SAT” (Rosser, 1989a, page 14).

38

Admlssion Decisions with Test Scores

The presumption of test bias serves to limit and reduce college choices
available to women and minority students (Navarro, 1984; Powell & Steelman,
1996). Test scores are an important part of the current college admission criteria.
Students with lower test scores have limited opportunities to gain admission to a
host of highly selective colleges and universities (Cole, 1987).

While these tests play a critical role in controlling access to college, their
ability to predict success in college has come under much scrutiny (Crouse &
Trusheim, 1991). For all student populations, the best predictors of success in
college are high school grade point average and class rank (Crouse & Trusheim,
1991). When test scores are added to these two measurement units, a small,
incremental increase is observed in the model that explains the variation in college
GPA. The research conducted by James Crouse and Dale Trusheim (1991)
focused attention on college admission decisions at highly selective colleges and
universities. They examined the high school grade point average, class rank and
SAT scores for the 1985 and 1986 Dartmouth College freshman class. Based on
the data provided by Dartmouth, Crouse and Trusheim constructed a cross
tabulation table of predicted grade point averages. The results of their study found
no significant difference in average GPA when SAT scores were added to high

school grades and class rank (Crouse & Trusheim, 1991).

39

Table 4: Outcomes of high school rank and high school rank plus SAT admissions
policies at Dartmouth.

 

 

 

Outcome High School Rank High School Rank Plus SAT
Average Freshman 3.28 3.28
GPA

 

 

 

 

Source: Crouse and Trusheim, 1991.

The research conducted by Crouse and Trusheim, Rosser, and Codina
shows that test scores have a limited ability to predict success in college (Crouse &
Trusheim, 1991 ; Rosser, 1989a, 1989b; Codina, 1984). If these studies have merit,
then an important question is: Why do colleges and universities use test scores in
the admission decision-making process? The research tends to suggest that the
following two explanations are answers to this question:

1 . Test scores help the admission officer confirm the applicant’s ability to

perform college level work.

2. Test scores help to regulate access to college.

For many college admission officers, the use of test scores provide an
additional set of data from which they are able to analyze and draw comparisons
with the information gained from high school grades and class rank. In this respect,
admission officers are using these tests to confirm whether or not the applicant’s
scores are consistent with the level of ability that is indicated from examining the

high school record (Bracey, 1990).

40

In their book, “The Case Against The SAT,” Crouse and Trusheim concluded
that in cases where the SAT altered the admission decision, it usually served to
reject African American students and students from low income families (Crouse &
Trusheim, 1988).

Given the concerns about bias in these tests, their limited predictive ability,
and their role in controlling access to college, calls for changes in the college
admission criteria continue to be heard (Douglass, 1999; Powell & Steelman, 1996).
In addition, challenges with evaluating, in a thorough and effective manner, students
who are enrolled in schools with block scheduling curricula and schools with
restricted or limited grade assessment processes (e.g., traditional letter grades) are
key factors that require an admission alternative to the Camegle Unit program. The
development and validation of the Competency Based Admission program could
result in an admission procedure that might serve to reduce or eliminate the reliance
on test scores in college admission decisions, while effectively assessing the college

readiness skills of students.

Current Admission Challenges

Starting in the later part of the 19905, numerous curricular changes began to
emerge in K-12 education. The demand from employers for high school graduates
who possess basic competencies, parental demands for practical and applied
learning skills, and societal concerns about eroding educational standards are the

catalysts behind these curricular changes (Newman, 1985).

41

In the future, postsecondary institutions will recognize that high school
curricular changes necessitate concomitant modifications in college admission
practices. Some states such as Wisconsin and Oregon already have discovered the
importance of devising a strategy for establishing alternative admission criteria.
These states understand the importance of developing a process or method of
evaluating a nontraditional high school performance record in order to maintain a
plan of educational accessibility.

To address curricular changes in secondary schools, the Higher Education
Governing Board in Wisconsin developed an alternative college admission process
called competency-based admission (CBA; University of Wisconsin System, 1994).
At the same time, Oregon has focused on college admission by developing a
proficiency-based admission standards system (Oregon State System of Higher
Education, 1996). These two state-based initiatives have been the driving force
behind the development of alternative admission criteria that could serve as a
catalyst in redefining college admission and access to higher education in the
twenty-first century.

Today, most admission offices use Carnegie Unit and standardized test
scores as the primary criteria to determine students’ access to and probability of
success in college (Crouse & Trusheim, 1991). The Carnegie Unit, focusing on high
school grades and the number of years of coursework completed in predictor
courses, has been commonly accepted as important factors in college admission

decisions. Although the use of standardized test scores in admission decisions is as

42

widespread as the use of Carnegie Units, the application of such criteria is more
controversial. The use of standardized test scores in the college admission process
has been vigorously debated during the last 30 years.

In addition, the continued use of Camegle Units in admission decisions is
facing challenges as a result of curricular changes in secondary schools. A number
of colleges have recognized this dilemma and have adapted their criteria to allow
students to submit personal portfolios for admission consideration (Needle, 1991).
The portfolio often requested by colleges require students to complete the
admission application; submit a current high school transcript; provide a personal
statement of interest; and submit any supplemental material that may build a case
for a positive admission decision (Needle, 1991). While the use of portfolios has
been gaining popularity in undergraduate admission, they are becoming increasingly
popular in graduate school admission (Hagedom & Nora, 1996; Johnson & Gentry,
2000). In future years, the use of portfolios may play an increasing role in both

undergraduate and graduate school admission.

Changes in High School Curricula

Recent changes in high school curricula are creating tension in the traditional
college admission and assessment process. Two primary changes pose key

challenges to the perpetuation of this admission model:

43

Changes in grading and graduation requirements. Some K-12 school
districts are altering the course requirements for graduation from high school.
A number of these requirements have focused on developing specific
academic competencies. These school districts are implementing changes in
the student evaluation process at lower grade levels (Guskey, 1994;
Sperling, 1994; Wiggins, 1994). In a number of these districts, alternative
assessment practices that exclude historical grading scales (letter grades
ranging from A to F) are used to evaluate learning (Guskey, 1994; Kenney &
Perry, 1994). The establishment of any system that disrupts the fundamental
college admission balance that relies on letter grades will pose a major
challenge to colleges and universities. Any continued shift away from the
use of grades to evaluate student success will require new college admission
strategies to maintain broad levels of institutional accessibility.

Block scheduling. An increasing number of high schools across the United
States are implementing block-scheduling programs that are both inner
disciplinary and interdisciplinary in academic composition (Eineder & Bishop,
1997; Skrobarcek et al., 1997). Block scheduling is designed to provide
students with an extended class period, thus increasing the probability of
their learning the subject and course material. The positive effect of block
scheduling on learning has been documented in subjects such as math and
science (Fitzpatrick & Mowers, 1997; Skrobarcek et al., 1997). Under most

block-scheduling plans, students can complete one year of academic

44

coursework in just one semester. Block scheduling alters the historical
calculation of high school grades and the number of completed Carnegie
Units. This issue is further complicated when two academic disciplines are
combined in one distinct class block. Here college admission questions arise
concerning how to evaluate the grade received (Should the same grade be
assigned to each course?) and how to assign Carnegie Units (Should one
unit or one-half unit be assigned to each course?) As a result of these
structural alterations, block-scheduling issues could provide admission

challenges well into the twenty-first century.

Home-Schooling Options

More parents across the United States have decided to forsake the traditional
practice of sending their children to established K-12 school districts, in favor of
educating their youngsters at home. By 1994, more than 250,000 students are
educated at home, compared with 15,000 students who were home schooled during
the 19703 (Gordon, Russo, & Miles, 1994). This trend toward home schooling is
expected to continue well into the first half of the twenty-first century.

During the last decade, the concept of home schooling has gained popularity
among parents, the public, and politicians. Some states have developed legislative
strategies designed to recognize the growing number of students who are being
educated in home environments. In Oklahoma, the state legislature enacted a law

providing protection for home schools. This law provides a mechanism for

45

monitoring and regulating the educational environment of every home school
(Klicka, 1995). In addition, many states have adopted and currently maintain
regulations for home schooling. In fact, twelve states allow home schools to
register, operate, and become certified as private schools (Klicka, 1995).

The trend toward home schooling represents a return to the classical period
of education in America. As Whitehead and Bird (1987) noted, “From the beginning
of this country, education was an area of concern left to parents through home
education” (p. 23). In fact, the development of a broad-based public educational
system evolved from the early period of private, home-schooling concepts (Klicka,
1995; Whitehead & Bird, 1987).

Whereas the aforementioned changes or innovations were designed to
provide academic-enrichment opportunities for students, they place an additional
burden on existing resources. This is particularly true when considering the effect
that these changes will have on college admission. The increased focus on home
schooling and the elimination of grades in secondary schools served as a catalyst

for the establishment of the Wisconsin CBA program.

Responding to Admission Challenges
The Wisconsin Model was developed in 1994 by a group of 75 faculty

members representing each University of Wisconsin two-year and four-year
institutions (University of Wisconsin System, 1994). College-competency

matriculation requirements were developed in five disciplinary areas: English, math,

46

science, social science, and foreign language.

The Wisconsin Model provides high school teachers with the means to
evaluate the college-readiness skills of student applicants using the CBA criteria. A
form called the Standardized Reporting Profile (SRP) is used to summarize these
competencies.

While CBA was established as an alternative to the use of the Carnegie Unit
admission criteria, little attention has been focused on decisions comparing
admission rates, first semester college grades, and the time required to make
admission decisions associated with each admission process. These outcomes are
important to the decision making process for policy makers as they consider a broad

implementation strategy for a program like CBA.

47

CHAPTER III: METHODS

Introduction

The researcher’s purpose in this study was to examine and compare
admission rates, first year college grades and the level of resources expended
(time) by universities in processing and rendering admission decisions on Carnegie
Unit and CBA applications. Chapter III details the methodology used to analyze
these data. In addition, this chapter discusses the use of the Multi-Attribute Utility
(MAUT) model to determine if CBA results in similar college access outcomes
(Admit Rates) when compared to the Carnegie Unit admission program. The MAUT
development process for admission decisions and its utility ranking procedure is
described in this chapter. The research hypotheses that highlight the relationship
between admit decisions and grades in college, and the time required to make
admission decisions are discussed. Finally, the expected outcomes associated with

each research hypothesis are summarized in an expectation matrix.

Research Questions

. Do admission decisions using CBA result in similar access outcomes
(Admit Rates) when compared to the traditional admission (Carnegie
Unit) process?

. Do predictive relationships exist between the CBA process and first

semester college grades? If such a relationship exists, how does it

48

compare to college grades predicted from the traditional admission
(Carnegie Unit) process?
0 When compared to Carnegie Unit, does CBA represent a time-

efficient process for making college admission decisions?

Research Issues

To determine if the CBA program is an effective, alternative to the Carnegie
Unit admission model, specific outcomes must be measured. The primary
comparative outcome for CBA and Carnegie Unit focus on an analysis of admit
rates. The secondary comparative outcomes of this study are an analysis of the
correlation of first semester college grades and the processing time associated with
final admission decisions. These two secondary issues attempt to answer efficiency
and resource allocation questions. In total, these comparative outcomes should
provide evidence of which program provides the broadest access to college; which
program most effectively predicts how well admitted students will perform during
their first semester in college; and which program is most efficient in rendering final
admission decisions. The results of this study could provide evidence concerning
the impact a program like CBA might have in maintaining high levels of college
access for women and minority students. In addition, as political pressure continues

to mount against the use of Affirmative Action strategies in maintaining access to

49

public universities for a diverse group of students, these institutions will face
legislative mandates requiring them to use a more stmctured college admission
criteria (e.g., Califomia’s Proposition 209). If the current results in California are any
indication of the impact these political pressures will have on access to college for
minority students, then higher education will need to continue to explore alternative
admission programs as a way of maintaining high levels of diversity. Since the CBA
program moves away from the traditional criteria used to determine college
readiness skills, it has the potential to move the issue of access out of the political

spotlight.

The Research Study and Population

The University of Wisconsin System developed a pilot program to evaluate
the effect of CBA on college admission practices. This pilot program was designed
to provide evaluative data with which to compare the CBA process to the Carnegie
Unit admission process. The study examined 660 application decisions made by
ten universities. The applications were divided equally between Carnegie Unit and
CBA materials.

The pilot study was conducted over a two-year period in 1996 and 1997. The
study was funded by a grant from the US. Department of Education (Fund for the
Improvement of Postsecondary Education — F IPSE). The FIPSE grant, which
covered the period from September 1994 through June 1997, provided the financial

resources necessary for the development of the University of Wisconsin CBA-

50

Subject Competencies, and the implementation of the two-year pilot study.

The pilot study involved a selected group of seven high schools from
Wisconsin and one from Minnesota (CBA: The Wisconsin Model, 1994). These high
schools were selected based on the fact that they were involved in a number of
curricular changes that could result in their students facing challenges meeting the
Carnegie Unit admission criteria (CBA: The Wisconsin Model, 1994). These high
schools were primarily located in rural communities, had similar gee—demographic
characteristics, and had very little racial and ethnic diversity in their student body
(CBA: The Wisconsin Model, 1994). As a result, the request for volunteers to
participate in this study yielded students from similar racial backgrounds.

At each high school, teachers and administrators were required to attend
workshops and seminars that focused on how to use the CBA-Competencies and
the SRP form to evaluate college readiness skills. In the case where a student,
during the course of their high school years had been taught by more than one
teacher in a specific subject area, the CBA process allowed these teachers to
collaborate in making a final competency evaluation. As a result, the pilot study
resulted in a number of high schools setting aside release time for teachers to meet
to discuss each student involved in the pilot study. Once teachers completed the
competency evaluation, high school counselors submitted to the appropriate
university a CBA application and a Carnegie Unit application for each student.

Each university was required to set up an independent review process that

ensured that these two application processes remained separate. Admission

51

officers were assigned to render decisions on either Carnegie Unit or CBA
applications. The process also required these admission officers to make
application decisions without being able to view the student’s second application
(i.e., either Camegle Unit or CBA application). The separate and independent
review process ensured that student applicants were held harmless by the
admission decision. This provision allowed students to be admitted even though
they may have been denied admission by one of the two admission programs.
Alternatively, a student was only denied admission to a university when they were
denied admission on both their Camegle Unit and CBA application.

In addition, all public universities were required to document the final
admission decision (Admit or Deny), and maintain a detailed log on the amount of
time needed to make each decision. These data were compiled and centralized by
the University of Wisconsin System for review and evaluation. The data on college
grades were collected after students matriculated to a University of Wisconsin
institution during the 1996/1997 academic year.

The researcher was able to secure these data from the University of

Wisconsin System to test several hypotheses.

The CBA Pilot Design
As part of the CBA pilot design, the University of Wisconsin System required

public universities to participate in the study. These universities were provided with

52

instructions for handling students submitting CBA evaluation profiles (Supplemental

Reporting Profile — SRP Form). So as to have a basis for evaluating the effects of

CBA, students submitted two sets of admission materials to each university. These

two sets of materials were:

1.

The CBA-Supplemental Reporting Profile (SRP Form): This form contained
a summary of teacher evaluations by subject. Each student applicant
received a competency evaluation in each academic subject area (e.g.,
English, math, science, social science, and foreign language). Teachers
evaluated the student’s subject-based competencies using the following
scale: 5 = Excellent performance, 4 = Very good performance, 3 =
Satisfactory performance, 2 = Limited performance, 1 = Poor performance,
NBE = No basis for evaluation.

The traditional application (Carnegie Unit application) material: This material
detailed all grades by class and subject area for each semester and each
academic year (academic transcript). In addition, the student’s class rank

and standardized test scores were included with each application.

The applications examined in this study were submitted to ten University of

Wisconsin schools. The data collected during the pilot phase included information

on final Carnegie Unit and CBA application decisions and the time needed to make

these decisions. In addition, after admitted students matriculated to college, data

were collected on grades during each of the first three semesters.

53

Mum-Attribute Utility Model (MAUT)

MAUT models have been used to help inform the decision making process
(Edwards, 1977). They are useful in helping policy makers finalize decisions that
involve program alternatives in a number of important areas. “Examples that
demonstrate the diversity of their use include the budgeting decisions of public
health officials, the job-choice decisions of job applicants, the student-admission
decisions of universities, the plant-location decisions of corporate executives, the
funding decisions of federal program administrators, the land-use decisions of
regional planning groups, and the personnel-assignment decisions of various
military services” (Huber, 1980, page 47).

The Multi-Attribute Utility (MAUT) model is an effective method for evaluating
programs with multiple and seemingly unrelated variables. The MAUT model can
be used to provide a policy maker with an analysis of outcomes associated with two
or more programs by examining specific variables in each program (Edwards,
Guttentag & Snapper, 1975). In this study, the primary comparison of Carnegie Unit
Admission and Competency Based Admission involves an analysis of variables that
looks at a comparison of final admission decisions. The focus of this examination is
to compare admit rates for these two admission programs. In doing so, the MAUT
process generates a utility ranking of each program. Here the MAUT evaluation
process will identify the admission program that meets the key priorities established
by program decision makers. As part of the early development of the CBA program,
it was decided that the basis for developing this program was to continue to provide
access to college for students completing non-traditional educational programs

(CBA: The Wisconsin Model, 1994). As a result of the CBA development process,

54

college access based on admit decisions is the number one reason for conducting a
MAUT college access utility analysis.

The MAUT model can be and has been used to make program evaluation
decisions among two or more programs (Edwards, 1977; Farmer, 1987). The MAUT
process allows programs to be evaluated using a comparison matrix consisting of
factors that have a consistent set of measurement outcomes. The MAUT process is
designed so that “if one alternative has a higher (or more preferable) attribute value
than any of the other alternatives, that alternative is chosen and the decision
process ends” (Yoon and Hwang, 1995, page 23). In addition, the MAUT model
used in this study is designed to provide policy makers the data needed to evaluate
the effectiveness of both admission programs. More specifically, the MAUT model
will provide a final utility ranking to compare the effectiveness of each admission
program in making college access decisions.

The MAUT model has been used successfully in applied settings ranging
from evaluating the effectiveness of specific government programs to examining
land use regulations (Edwards, 1977). In the case of the CBA program and the
Carnegie Unit program, the MAUT model will provide University ofWisconsin policy
makers with data on student access. The program with the highest score would
represent the admission model with the highest utility. This result is only one
measurement outcome that policy makers could use in making decisions on these
programs. Since the Carnegie Unit model is an established and fully operational
program, the results of the MAUT process would not prohibit University ofWisconsin
policy makers from deciding to implement both programs, rather than a substitution

strategy. Indeed, the goals outlined for the CBA pilot involved examining CBA to

55

determine if this new alternative could be used to meet the needs of some students
who would have challenges gaining access to college using the Camegle Unit
program (CBA: The Wisconsin Model, 1994).

The strategy behind the MAUT model is focused on determining the value of
attributes associated with each alternative. All attributes are assigned or have an
established numerical value that is maximized through the use of a mathematical
procedure. As a part of the mathematical process, each attribute will be assigned a
probability weight. While the assigned probability for each attribute will vary, the
sum of the assigned attribute values will always be equal to one. This sum of
attribute values is achieved through a normalization process that allows each
attribute to be scaled based on its value in relationship to the summed value of all
attributes.

The product of the attribute value and the attribute probability will result in a
final utility value for each attribute. Once the final utility for each attribute is
determined, the final utility for each alternative is calculated by taking the aggregate
value of the alternatives.

In using the MAUT model to evaluate the two admission programs, Carnegie
Unit Admission and Competency Based Admission are examined as competing
admission programs. The total applications processed are normalized for each
university. This process provides a value for the attribute related to the number of
admission applications received by each university. Also, the admit rates observed
in each admission program are used as the percentages associated with the
probability or the likelihood of an admit decision occurring. The MAUT process

involves a ten-step process for assisting policy makers in making programmatic

56

decisions on program alternatives (Edwards, Guttentag and Snapper 1977). The
following is the ten-step process used to determine the impact on college access

observed in examining each admission program (alternative):

Step 1
The organization’s utilities that are to be maximized are public universities in

Wisconsin. The focus of this process is centered on the admission offices in

these universities.

Step 2
The utilities to be maximized are college admission rates. A direct focus on

the admit rates in these universities is established.

Step 3
The examination of a group of applications submitted by students using the

Camegle Unit program and the Competency Based Admission program are

the basis for this evaluation.

Step 4
The number of university admission offices in Wisconsin was established at

ten based on the collection of data.

Step 5
An aggregate admit rate is established by evaluating all application

decisions. In addition, final admit rates for each university is developed by

examining the application decisions made in each admission office.

Step 6
The raw weights for each university is based on the number of Carnegie Unit

and CBA applications received and processed.

$92].
The number of applications received by each university (raw weight) is

57

normalized by dividing each raw weight by the sum of the ten weights and

then multiplying by 100. Detailed in table 5 is a listing of results derived from

this normalizing process.

Step 8

The evaluation of prior admit rates based on historical data, is evaluated and

compared against the posterior (observed) admit rates from the evaluation

period. The following are the methods used for determining prior and

posterior admit rates:

a.

Step 9

Prior admit probabilities are derived by taking the average Carnegie
Unit admit rate for each university during the five year period prior to
the development of the pilot program. These rates are listed in table
6. A projected number of admits for each university can be calculated
by multiplying the prior admit rate by the number of observed
admission applications for each program. The projected admits for
each university, using the prior admit rates, is listed in table 7.

The posterior probabilities are derived for Carnegie Unit and CBA
admit decisions by examining the results of all decisions during the
pilot evaluation period. The probability of an admit decision occurring
on any admission application is the observed probability (Percentage
of students admitted) based on decision made by each university.
These posterior admit rates for Carnegie Unit and CBA applications

are listed in tables 8 and 9, respectively.

The utilities are calculated for each university by multiplying the normalized

weights by the admit rate (probability). A set of utilities for each university is

58

calculated using prior admit probabilities, while a set of utilities are calculated
using the posterior (observed) admit probabilities. This process provides a
comparative ranking for Carnegie Unit and CBA admit decisions for each
university. The summation of the ten universities provides a final, overall
ranking for the two alternative admission programs. These results are

summarized in Chapter V.

Step 10
This final step provides an examination of the final utility rankings for the

purpose of deciding between the two admission alternatives. The utility

rankings and results associated with this method are detailed in Chapter V.

In mathematical terms, the ten step process can be illustrated be maximizing

the following MAUT Utility model used in this study:

Expected/Projected MAUT Utility Model (Prior Admit Probabilities)

Ui = Z (Wj 0 Pij)

Where:

Ui : Represents the total MAUT utility associated with the ith admission

model. In this study, it would represent the total expected MAUT
utility associated with the Camegle Unit admission model or the CBA
admission model.

2: The sum of the total for all University of Wisconsin institutions.
i

W]: The normalized application weight associated with the jth University of
Wisconsin institution.

59

Pij: The prior probability that a student applying for admission using the ith

admission model (Carnegie Unit or CBA) will be accepted to the jth
University of Wisconsin institution.

Calculated MAUT Utility Model (Posterior Admit Probabilities)
The calculated MAUT utility model is based on using the posterior admit
probabilities for each university (Pij) established during the application evaluation

period. The calculated MAUT utility model is:
Ui = Z (Wj O Pij)
1

Where:

Pij: The posterior probability that a student applying for admission using

the ith admission model (Carnegie Unit or CBA) will be accepted to
the jth University of Wisconsin institution.

Table 5: MAUT process, step 7.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Raw Applications Total Raw Normalized
(University) Applications Application
Camegle Unit CBA Weight
Institution 1 73 73 146 22
Institution 2 24 24 48 7
Institution 3 42 42 84 13
Institution 4 60 60 120 18
Institution 5 20 20 4O 6
Institution 6 11 11 22 3
Institution 7 12 12 24 4
Institution 8 25 25 50 8
Institution 9 13 13 26 4
Institution 10 50 50 100 1 5
Total 330 330 660 100

 

 

 

 

 

 

60

Table 6: Prior Admit Probabilities (Based on a five-year

average for each university).

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Prior Admit Rate
(University)

Institution 1 .77
Institution 2 .82
Institution 3 .70
Institution 4 .73
Institution 5 .78
Institution 6 .76
Institution 7 .80
Institution 8 .65
Institution 9 .72
Institution 10 .84
Total .76

 

 

 

Table 7: Estimated/Projected Carnegie Unit and CBA admits (Using Prior Admit

Probabilities and observed admission applications).

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Prior Admit Projected Projected CBA

(University) Rates Carnegie Unit Admits
Admits (Applications times
(Appflcations times Prior Admlt Rate)
Prior Admit Rate)

Institution 1 .77 56 56

Institution 2 .82 19 19

Institution 3 .70 29 29

Institution 4 .73 44 44

Institution 5 .78 16 16

Institution 6 .76 8 8

Institution 7 .80 10 10

Institution 8 .65 16 16

Institution 9 .72 9 9

Institution 10 .84 42 42

Total .755 249 249

 

 

 

 

61

 

Table 8: MAUT process, step 8 (Carnegie Unit Posterior Applications, Admits and

Admit Probabilities).

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Applications Admits Admit Rate
(University)

Institution 1 73 61 .83
Institution 2 24 23 .96
Institution 3 42 33 .79
Institution 4 60 41 .68
Institution 5 20 13 .65
Institution 6 11 6 .55
Institution 7 12 8 .67
Institution 8 25 18 .72
Institution 9 13 11 .85
Institution 10 50 41 .82
Total 330 255 .77

 

 

 

 

Table 9: MAUT process, step 8 (CBA Posterior Applications, Admits and Admit

Probabilities).

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Applications Admits Admit Rate
(University)

Institution 1 73 54 .74
Institution 2 24 18 .75
Institution 3 42 29 .69
Institution 4 60 36 .60
Institution 5 20 15 .75
Institution 6 11 9 .82
Institution 7 12 1 1 .92
Institution 8 25 17 .68
Institution 9 13 10 .77
Institution 10 50 42 .84
Total 330 242 .73

 

 

 

 

62

 

 

Admit Rates and the College Access Hypothesis

Previous CBA research revealed that admission officers had prior experience
making Carnegie Unit admission decisions (CBA: The Wisconsin Model, 1994). By
contrast, these same admission officers possessed a very steep Ieaming curve
related to the CBA program (CBA: The Wisconsin Model, 1994). Since the CBA
program was developed as a pilot initiative, these admission officers possessed less
knowledge and no prior history related to the implications associated with CBA
admit decisions. As a result, one would hypothesize that these admission officers
would be prone to be more selective in making CBA admit decisions. On the other
hand, the Carnegie Unit admission model represents a familiar program with a
detailed history related to the affects associated with admit decisions. In the case of
Carnegie Unit admission, we would expect admission officers to be less selective
resulting in higher admit rates, and a higher MAUT utility ranking associated with
these admit decisions.

Admit rates and the time needed to make decisions on each type of
application (Camegle Unit and CBA) is an important part of determining the
efficiency associated with each admission program. In evaluating admit rates for
each admission model, an analysis of all decisions is compared to all admit
(acceptance) decisions. This analysis will provide a gauge of “how selective” the
CBA program is when compared to the Camegle Unit program.

As a result, analyses exploring the variance that may exist in admit rates
between each admission program is conducted. Since the Carnegie Unit admission
program is the standard for evaluating any new program, the degree to which

significant differences exist in admit rates will determine the overall usefulness of the

63

CBA program. The MAUT model is used to estimate and evaluate this hypothesis.
Np" Hypothesis 1: There is no significant difference in the Multi-Attribute
Utility rankings derived from admit rates between the Carnegie Unit
admission program and the CBA admission program.
Alternative Hypothesis 1: There is a significant difference in the Multi-

Attribute Utility rankings derived from admit rates between the Camegle Unit
admission program and the CBA admission program.

College Grades Hypothesis

The CBA process serves as a decision-making model for determining access
and enrollment in University of Wisconsin four-year, public institutions. Given this
issue, it is important to evaluate how well CBA results compare with those obtained
using the Carnegie Unit admission process. In thinking about this analysis, the
comparison must maintain a focus on the primary reason students are admitted to
college. In essence, admission is provided to students who have the potential and
ability to be successful and ultimately matriculate to graduation. Examining the
grades received in college is a common method used for measuring student
success. The Carnegie Unit Grade Point Average (GPA) model has been validated
as a measurement tool for predicting levels of success in college (Willingham,
Lewis, Morgan 8. Ramist, 1990; Beecher & Fischer, 1999). The GPA model
associated with Carnegie Unit admission is designed to take the high school GPA,
test scores (ACT/SAT) and class rank to estimate how well an applicant will perform
in college courses. Alternatively, in order for CBA to be a valid process for
predicting success in college, the SRP scores should have a corresponding

relationship to college GPA. Using the CBA admission model and the rating scale

64

listed on the SRP form, the satisfactory score would seem to represent the minimum
requirement needed to ensure an adequate level of college success. Furthermore,
the scores received on the SRP form should correlate to the grades that students
received in their first semester in college. A comparison of the SRP scores by
subject area and the college grades received in each subject will provide a method
for determining how much of the first semester GPA can be explained by SRP
scores. If this analysis yields a meaningful correlation, it will provide a method for
estimating college success through a CBA predictive model.

At any rate, the fact that the Camegle Unit GPA model has been validated as
a successful method for predicting success in college could result in an expectation
that this process would explain more of the variation in grades than a similar method
associated with the CBA program.

Therefore, the second hypothesis concerns whether a significant difference
exist in the first semester grade/SRP correlations for CBA and the GPA correlations
for the Carnegie Unit admission process. This correlation would allow us to
determine what portion of the variance in first semester grades are explained using
each model. While this analysis is a measurement process for determining success
in college, it also serves as a way of determining if the CBA process will lead to
admission outcomes that are similar or vary from the Carnegie Unit process. A
grade variance and correlation analysis is used to evaluate this hypothesis. The
following null and alternative research hypotheses are evaluated:

MII Hypothesis 2; There is no significant difference in the explained grade
variance for CBA admitted students and Carnegie Unit admitted students.

65

Altematjve Hypothesis _2_:_ There is a significant difference in the explained
grade variance for CBA admitted students and Carnegie Unit admitted
students.

Admission Decision Times Hypothesis

During the CBA pilot study, University of Wisconsin institutions were asked to
gather and maintain data on the processing time needed to make CBA and
Carnegie Unit admission decisions. An analysis was conducted to determine (a) the
level of resources (time) necessary to render a CBA admission decision on student
applicants and (b) the level of resources (time) required to process Camegle Unit
admission application materials.

To address the issue of time and resource efficiency, several analyses that
look at both the aggregate times and the times associated with each university are
required. Again, an expectation exists that due to a lack of familiarity and
knowledge of the CBA process, admission officers will not be able to make time
efficient decisions that compare favorably to Carnegie Unit decisions. This
expectation of application decision times is focused on (1) aggregate decisions for
all universities and (2) decision outcomes associated with each university.

A two-way Analysis of Variance (ANOVA) is used to determine whether
significant differences existed in application processing time between the Carnegie
Unit application process and the CBA application process. This analysis is
performed to test whether differences in the means for each program exists.

Hypothesis 3 concerns whether a significant difference existed in the

66

processing time needed to make admission decisions on the aggregate number of

Camegle Unit and CBA admission applications.

Null Hypothesis 3: There is no significant difference between the amount of
time expended processing Carnegie Unit admission applications and the
amount of time expended processing CBA admission applications.

Alternative Hypothesis 3: There is a significant difference between the
amount of time expended processing Carnegie Unit admission applications
and the amount of time expended processing CBA admission applications.

Summary of Research Hypotheses
As a result of the previous discussion in this chapter, the following

hypotheses are derived:

H1: Admit rates and the corresponding MAUT utility will be higher for
Carnegie Unit admission when compared to CBA admission.

H2: The Carnegie Unit model explains a higher amount of the variation in
first semester grades.

H3: The time needed to make decisions on CBA applications will be
higher than the time needed to make decisions on Carnegie Unit

applications.

67

A summary of the expected outcomes stated in each hypothesis is listed in

an Expectation Matrix (see Table 10).

Table 10: Expectation Matrix.

 

 

 

Score/Ranking
Variable Highest Lowest
Admit Rates (Selectivity) Carnegie Unit CBA
1. Explained Grade Carnegie Unit CBA
Variation

2. Grade Correlation

 

 

by Subject Area

a. Math 3. Camegle Unit a. CBA

b. English b. Carnegie Unit b. CBA

c. Science 0. Carnegie Unit c. CBA

d. Social Science d. Carnegie Unit (I. CBA

e. Foreign Language e. Camegle Unit e. CBA
Admission Decision Time CBA Carnegie Unit

 

 

 

 

68

CHAPTER IV: RESULTS AND ANALYSIS OF DATA

Introduction

Detailed in Chapter IV are the research results. Listed in this chapter are
tables and charts that serve to allow for an analysis of each hypothesis. In some
cases, the results do not allow for the null hypothesis to be rejected. In other cases,
the results are significant and accordingly allow for the rejection of the null

hypothesis.

Research Results

Hypothesis 1

Npll Hypothesis 1: There is no significant difference in the Multi-Attribute

Utility rankings derived from admit rates between the Carnegie Unit

admission program and the CBA admission program.

The expected/projected MAUT utilities associated with each university are
listed in Table 11. These utilities are the results that would be expected based on
the use of prior admit probabilities (five year average admit rates for each university)
and the normalized application weights for each university. The expected results
are compared to the results generated from calculating the utility model using
posterior admit probabilities for the Carnegie Unit admission program and the CBA

admission program.

69

Table 11: Expected MAUT college access utilities (Based on Prior Admit

 

 

 

 

 

 

 

 

 

 

 

 

 

Probabilities.

Institution Normalized Prior Admit Expected MAUT

(University) Weights Rate Utilities (Prior
Admit Rate x
Normalized
Weight)

Institution 1 22 .77 16.94

Institution 2 7 .82 5.74

Institution 3 13 .70 9.1

Institution 4 18 .73 13.14

Institution 5 6 .78 4.68

Institution 6 3 .76 2.28

Institution 7 4 .80 3.2

Institution 8 8 .65 5.2

Institution 9 4 ' .72 2.88

Institution 10 15 .84 12.60

Total 100 .76 75.76

 

 

 

 

 

The Carnegie Unit admission program has a higher aggregate utility (77.18)
when compared to the CBA program (73.06). This result indicates that the Carnegie
Units admission program does a better job of providing broad access to college
based on aggregate admission decisions. The results of this analysis are detailed in
Table 12. These results show variations in MAUT rankings among several
universities. In fact, there are four universities that had CBA utility rankings that
were higher than Carnegie Unit utility rankings (Universities Number 5, 6,7 and 10).
The most significant difference in utility rankings among these four institutions was
observed in University 7. The CBA utility ranking for University 7 was 3.68

compared to 2.68 for the Carnegie Unit utility ranking.

70

Table 12: MAUT college access results (Based on Posterior Admit Probabilities).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Normalized Carnegie Carnegie Unit CBA CBA Utility
(University) Weights Unit Admit Utility Ranking Admit Ranking
Rate (Carnegie Unit Rate (CBA Admit
Admit Rate x Rate x
Normalized Normalized
Weight) Weight)
Institution 1 22 .83 18.26 .74 16.28
Institution 2 7 .96 6.72 .75 5.25
Institution 3 13 .79 10.27 .69 8.97
Institution 4 18 .68 12.24 .60 10.80
Institution 5 6 .65 3.90 .75 4.50
Institution 6 3 .55 1.65 .82 2.46
Institution 7 4 .67 2.68 .92 3.68
Institution 8 8 .72 5.76 .68 5.44
Institution 9 4 .85 3.40 .77 3.08
Institution 10 15 .82 12.30 .84 12.60
Aggregate Utility 77.18 (Carnegie Unit) 73.06 (CBA)
Final Rank 1 (Carnegie Unit) 2 (CBA)

 

 

 

 

A comparison of the expected and observed MAUT utility results for Camegle
Unit admission and CBA admission are listed in Tables 13 and 14, respectively.
The comparison of the expected and observed utilities show variation associated
with each university. In some cases, the expected utility model under-predicted the
observed results, while in other cases, the expected utility model over-predicted the
results derived from the calculated model. However, in examining University 10, the

expected utility achieved 100% success in predicting the actual CBA MAUT utility.

71

At the same time, the expected utility model under-predicted the Camegle Unit

MAUT utility by .30 for University 10.

Table 13: Differences in Expected and Calculated MAUT utilities for the Carnegie
Unit admission program.

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Expected MAUT Calculated Differences
(University) Utilities (Prior Carnegie Unit (Calculated minus
Probabilities) MAUT Utilities Expected)
(Posterior
Probabilities)
Institution 1 16.94 18.26 1.32
Institution 2 5.74 6.72 .98
Institution 3 9.1 10.27 1.17
Institution 4 13.14 12.24 (.9)
Institution 5 4.68 3.90 (.78)
Institution 6 2.28 1.65 (.63)
Institution 7 3.2 2.68 (.52)
Institution 8 5.2 5.76 .56
Institution 9 2.88 3.40 .52
Institution 10 12.60 12.30 (.30)
Total 75.76 77.18 1.42

 

 

 

 

Table 14: Differences in Expected and Calculated MAUT

admission program.

utilities for the CBA

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Expected MAUT Calculated CBA Differences
(University) Utilities (Prior MAUT Utilities (Calculated minus

Probabilities) (Posterior Expected)

. Probabilities)

Institution 1 16.94 16.28 (.66)
Institution 2 5.74 5.25 (.49)
Institution 3 9.1 8.97 (.13)
Institution 4 13.14 10.80 (2.34)
Institution 5 4.68 4.50 (.18)
Institution 6 2.28 2.46 .18
Institution 7 3.2 3.68 .48
Institution 8 5.2 5.44 .24
Institution 9 2.88 3.08 .20
Institution 10 12.60 12.60 ---
Total 75.76 73.06 (2.7)

 

 

 

 

72

 

 

The aggregate MAUT utilities derived for the expected utility models for both
Carnegie Unit and CBA were 75.76. These compare to a calculated aggregate
Carnegie Unit utility of 77.18 and a calculated aggregate CBA MAUT utility of 73.06.
In the case of Carnegie Unit admission, the expected MAUT utility model under-
predicted the actual MAUT results by 1.42. This represents a difference of 1.9%.
The expected MAUT utility model over-predicted the actual CBA MAUT utility results
by 2.7. This represents a difference of 3.6%. These results show that the CBA
program provided less admission access than would normally be expected, while
the Camegle Unit program provided more admission access than would normally be
expected.

As a result of the aggregate utility ranking for all universities, there exist
sufficient evidence that allow for the rejection of the null hypothesis. These admit
utility rankings show that the Carnegie Unit program provided a broader level of

college access than the utility results derived from the CBA program.

Hypothesis 2

Null Hypothesis 2: There is no significant difference in the explained grade

variance for CBA admitted students and Carnegie Unit admitted students.

The results highlighted in Table 15 show that the CBA model resulted in first
semester grade correlations that were comparable to the grade correlations
observed from the Carnegie Unit model. The correlations in Table 15 represent the
percentage of variation in grades explained by both models.

The combination of all subject areas and CBA Standardized Reporting Profile

73

(SRP) scores explained a similar amount of the variation in overall grade point
average when compared to the Carnegie Unit model that included high school GPA,
ACT composite score and class rank (See Table 15). The CBA model explained
47% of the variation in first semester grade point average, and the Carnegie Unit
model explained 48% of the variation in first semester GPA. Based on the
explained variation in grades of each admission model, the evidence is not

compelling enough to allow for the rejection of the null hypothesis.

Table 15: First semester correlation GPA weights by subject area.

 

 

 

 

 

 

 

 

Subject Area Correlation Carnegie Unit Model CBA Model

Math .37 .31

English .49 .40

Science .49 .45

Social Science .26 .33

Foreign Language .32 .37

Aggregate Correlation for all .48 .47
Subjects

 

 

 

 

In examining the results listed in Table 15, the CBA model explained a larger
portion of the variation in first semester grades in social science and foreign
language subjects. At the same time, the Carnegie Unit model explained a larger
portion of the variation in English, science and math grades. The higher Carnegie
Unit grade values in English, math and science could indicate that the use of
standardized test scores provide an added level of predictive power in estimating

first semester grades. The notion that these standardized exams add to the

74

predictive power of the Camegle Unit model is consistent with the composition of
these tests. Both the ACT and the SAT test student knowledge in English, math and
science. These two tests have a limited amount of material that focuses on areas of
the social sciences, and there is no testing of foreign language skills. The lack of
attention provided to the social sciences and foreign language could explain why the
CBA model had a higher predictive value when compared to the Camegle Unit

model.

Table 16: Comparison of SRP satisfactory ratings and first year college GPA.

 

 

 

 

 

 

 

 

Number of Competencies Number of Students First Year GPA (Mean)
Rated Satisfactory or Higher
0 25 2.47
1 26 2.57
2 36 2.90
3 25 2.87
4 35 3.19
Total 147 2.85

 

 

 

 

In addition, the statistics listed in Table 16 provide an analysis of the mean
GPA at the end of the first year for students who received a rating of satisfactory or
higher in subject areas listed on the CBA-SRP form. This table shows a direct
relationship between the number of SRP areas with a rating of satisfactory or higher
and first year grade point average. The direct correlations, summarized in Table 16,
between GPA and the number of satisfactory SRP scores are an important first step
in helping to validate the use of the CBA program as a viable alternative in

predicting student success in college. Furthermore, Table 17 shows a strong

75

correlation at the end of three semesters between the number of SRP areas rated
satisfactory or higher and both grade point average and credits attempted. This
initial result does indicate that for the pilot study the SRP teacher evaluations of
students were a good and fairly accurate representation of their level of preparation
for college. Since the SRP form is to the CBA process what the high school
transcript is to the Carnegie process, this is an important finding. Ultimately, the
validation of the CBA program rests on how well it is able to predict each student’s
level of preparation for college. As a result, additional research that compares the
SRP satisfactory scores and college grades of future CBA applicants would be
necessary to validate the CBA program. However, the results of the pilot study do
show a positive relationship between the SRP satisfactory ratings and the level of
student preparation for college. Table 17 also highlights a strong relationship
between the number of SRP areas rated satisfactory or higher and the percentage

of students with end of third semester grade point averages of 2.0 or higher.

Table 17: Comparison of SRP satisfactory ratings, GPA and completed course

 

 

 

 

 

 

 

credits.
Number of Number of Third Semester Percentage with Mean Credits
Competencies Students GPA GPA of 2.0 or Attempted
Rated Higher
Satisfactory or
Higher
0 25 2.45 74% 37.4
1 26 2.58 84% 40.9
2 36 2.85 89% 42.1
3 25 2.83 95% 44.1
4 35 3.15 100% 44.5
Total 147 2.82 90% 42.2

 

 

 

 

 

 

 

76

The statistics show that students receiving scores of satisfactory or higher on
the SRP form have a higher level of success in college based on grade point
averages. These data also show that when members of the pilot group received a
satisfactory or higher rating in four of the five competency areas, these students
performed at a much higher level than their cohorts who received no satisfactory
rating (First year: 3.19 mean GPA versus 2.47 mean GPA). In addition, all students
in the group with a minimum satisfactory rating in four of the five competency areas
had grade point averages higher than 2.0 (Table 17), compared with 74% of

students with no satisfactory rating.

Hypothesis 3
Mill Hypothesis 3: There is no significant difference between the amount of

time expended processing Carnegie Unit admission applications and the
amount of time expended processing CBA admission applications.

The use of a two-way Analysis of Variance (ANOVA) allowed for the
evaluation of the main effects highlighted in this hypothesis (Shavelson, 1988; Bryk
& Raudenbush). This statistical method provided a thorough examination of the
mean processing times associated with each university and each admission model.
In addition, the use of the ANOVA provided an analysis of the interaction between
universities and admission models in this study.

The ANOVA performed to measure the effect of university and application
type on the time required to make admission decisions yielded important time-

efficiency results. Displayed in Table 18 are the descriptive statistics (means,

77

standard deviations, and cell sizes) for Carnegie Unit admission decisions. Listed in

Table 19 are the comparative descriptive statistics for CBA decisions.

Table 18: Time needed to make decisions on Carnegie Unit admission

 

 

 

 

 

 

 

 

 

 

 

 

applications.

Institution Mean SD p
Institution 1 4.68 4.02 73
Institution 2 7.71 4.63 24
Institution 3 5.07 3.37 42
Institution 4 4.93 .52 60
Institution 5 7.60 3.14 20
Institution 6 8.64 2.58 11
Institution 7 3.42 1.16 12
Institution 8 3.76 1.56 25
Institution 9 5.69 3.28 13
Institution 10 10.34 5.03 50

Total 6.09 4.05 330

 

 

 

 

 

 

The means in the tables are given in minutes as the sole time measurement.
For all but one university, the mean time expended to make Carnegie Unit
admission decisions was less than the time needed to make CBA decisions. The
one university (Institution 10) with a mean CBA time that was less than the mean
Carnegie Unit time differed significantly from the other universities in the sample.
The mean CBA time for that university was 2.84 minutes with a standard deviation
of .87 minutes, whereas the mean Carnegie Unit time was 10.34 minutes with a
standard deviation of 5.03 minutes. These results show a high level of efficiency

78

that existed in processing CBA applications. If admission officers at University 10
developed a high degree of comfort in examining the SRP forms, this familiarity may
have translated into efficient processing of CBA applications. At the same time, the
10.34 minutes needed to process Carnegie Unit applications is almost 2 minutes
greater (1.70 minutes) than the next highest university in the study. It appears that
something in the decision making process for University 10 resulted in the high
Carnegie Unit processing time and low CBA processing time. Further on-site
research at University 10 might provide important insight concerning both the CBA
and Carnegie Unit results.

Two other universities showed important time differences in processing each
kind of admission application. University 4 had a mean time of 4.93 minutes with a
standard deviation of .52 for processing Carnegie Unit applications, and a mean
time of 15.47 minutes with a standard deviation of 10.26 for processing CBA
applications. In addition, University 8 had a mean time of 3.76 minutes with a
standard deviation of 1.56 for processing Carnegie Unit applications, and a mean
time of 9.20 minutes with a standard deviation of 6.89 for processing CBA
applications. Listed in Table 20 are data on all applications (Carnegie Unit and
CBA) processed by each university. This table includes the mean times, standard

errors, and confidence intervals for all admission decisions.

79

Table 19: Time needed to make decisions on CBA admission applications.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Institution Mean S]; p
Institution 1 6.27 5.16 73
Institution 2 8.46 6.62 24
Institution 3 8.69 3.26 42
Institution 4 15.47 10.26 60
Institution 5 10.00 8.58 20
Institution 6 10.00 4.47 1 1
Institution 7 5.17 1.75 12
Institution 8 9.20 6.89 25
Institution 9 8.46 2.40 13
Institution 10 2.84 .87 50

Total 8.51 7.30 330

 

 

Table 20: Aggregate admission application decision time (Carnegie Unit and CBA).

 

 

 

 

 

 

 

 

 

 

 

 

 

95% Confidence Interval
Institution Mean Std. Error Lower Bound Upper Bound
Institution 1 5.479 .470 4.557 6.402
Institution 2 8.083 .820 6.474 9.693
Institution 3 6.881 .620 5.664 8.098
Institution 4 10.200 .518 9.182 11.218
Institution 5 8.800 .898 7.037 10.563
Institution 6 9.318 1.211 6.941 11.695
Institution 7 4.292 1.159 2.016 6.568
Institution 8 6.480 .803 4.903 8.057
Institution 9 7.077 1.114 4.890 9.264
Institution 10 6.590 .568 5.475 7.705

 

 

 

 

 

 

Data from the ANOVA assisted in evaluating Null Hypothesis 3, related to the
time required to process CBA and Carnegie Unit applications. In testing the null
hypothesis, the ANOVA showed a strong E—test for the time required to make
admission decisions across application types (CBA and Carnegie Units
applications). A painlvise comparison of the E-test computed at the .05 alpha level
yielded an E-value equal to 9.26 and an eta-squared value of .125 (Table 21). The
value of the _E-test at this alpha level was statistically significant, indicating that a
significant difference existed in the mean time required to make CBA and Carnegie
Unit admission decisions. As a result, this analysis provided the evidence
necessary to reject the null hypothesis of no significant difference between the time
expended processing CBA applications and the time expended processing Carnegie
Unit applications. An _E-value of 29.99 for the main effect of the ANOVA was

calculated for admission time and application type (see Table 21).

Table 21: Results of ANOVA test of between-subject effects.

 

 

 

 

 

 

 

 

Type of

Sum 0f Mean Eta Noncent. Observed
Source Squares _d_f Square E Sig.a Squared Parameter Power
Corrected 2986.711 10 298.671 9.262 .000 .125 92.623 1.000
model
Intercept 23449.596 1 23449.596 727.215 .000 .528 727.215 1.000
APPTYPE 967.274 1 967.274 29.997 .000 .044 29.997 1.000
UWSCHOOL 2019.437 9 224.382 6.958 .000 .088 62.626 1.000
Error 20927.488 649 32.246
Total 59071 .000 660
Corrected 23914.198 659
total

 

 

 

 

 

 

 

 

 

 

 

Notes: Dependent variable: admission decision time.
_R_ squared = .125 (adjusted R squared = .111).

81

Further, an examination of the interaction effect between university and
application type for admission-decision time resulted in an E-value of 15.80. In
addition, a post hoc Tukey analysis of mean differences was used to highlight
between-university differences in the time required to make admission decisions
(see Table 22). Differences in mean admission decision-making time were
observed between a number of universities in this study (e.g., Institutions 4 and 10
exhibited differences that cut across multiple universities). This pairwise analysis
indicated that the means for University 4 varied significantly (at the .05 alpha level)
from the means of all nine other universities analyzed in this study. Similariy, the

means for University 10 varied significantly from the means of six other universities.

Table 22: Results of Tukey’s multiple comparison of mean differences.

 

 

 

 

 

 

 

 

 

 

 

 

(rI‘JsrtgrLgigirt'y) Institution (University)
1 2 3 4 5 6 7 8 9 10
Institution 1 - - - - - - -g_1g - - - - .. - - - - - - -
Institution 2 - - - - - - -7.01 - - - - - - - - - - 5.62
Institution 3 - - - - - - -6.67 - - - - - - - - - - 5.85
Institution 4 9.19 7.01 6.78 - - 5.47 5.47 10.3 6.27 7.01 12.63
0

Institution 5 - - - - - - -5,47 - - - - - - - - - - 7.16
Institution 6 - - - - - - -5,47 - - - - - - - - - - 7.16
Institution 7 .. - - - - - -1030 - - - - - - - - - - - -
Institution 8 - - - - - - -6.27 - - - - - - - - - - 6.36
Institution 9 - - - - - - -7,o1 - - - - - - - - - - - -
Institution 10 - - -5.62 -5.85 -12.63 -7.16 -7.16 - - 636 - - - -

 

 

 

 

 

 

 

 

 

 

 

 

 

82

Table 23: Results of ANOVA test for CBA admission

application decision time for each institution.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

95%

Confidence

Interval for
Institution Std. Mean
(University) N Mean SQ Error Lower Upper Min Max

Bound Bound
Institution 1 73 6.27 5.16 .60 5.07 7.48 1 29
Institution 2 24 8.46 6.62 1.35 5.66 11.25 1 30
Institution 3 42 8.69 3.26 .50 7.67 9.71 2 15
Institution 4 60 15.47 10.26 1.32 12.82 18.12 2 50
Institution 5 20 10.00 8.58 1.92 5.98 14.02 5 45
Institution 6 11 10.00 4.47 1.35 7.00 13.00 5 15
Institution 7 12 5.17 1.75 .51 4.06 6.28 2 10
Institution 8 25 9.20 6.89 1.38 6.36 12.04 2 25
Institution 9 13 8.46 2.40 .67 7.01 9.91 5 10
Institution 10 50 2.84 .87 .12 2.59 3.09 2 5
Total 330 8.51 7.30 .40 7.72 9.30 1 50

 

 

A summary of the results of all three hypotheses is found in Table 24. This
table highlights the results of the highest and lowest ranking admission program for
each variable. These results are detailed using the Expectation Matrix table found
in Chapter III. The results for the highest and lowest ranked admission program in
explaining variations in first semester grades was indeterminable. Both Carnegie
Unit and CBA explained a similar percentage of grade variation. In examining the
grade correlations by subject area, differences between the expectation matrix and

the actual results are found in social studies and foreign language. The Carnegie

83

Table 24: Results of Expectation Matrix.

 

 

 

 

 

Score/Ranking
Variable Highest Lowest
Admit Rates Carnegie Unit CBA
1. Explained Grade Indeterrninable lndeterrninable
Variation
2. Grade Correlation by
Subject Area
a. Math a. Carnegie Unit a. CBA
b. English b. Carnegie Unit b. CBA
0. Science c. Carnegie Unit c. CBA
d. Social Science d. CBA d. Carnegie Unit
e. Foreign Language e. CBA e. Carnegie Unit
Admission Decision Time CBA Carnegie Unit

 

 

 

Unit program had a higher expected grade correlation for these two subject areas.
These results proved to be opposite of what was expected from the model. Listed
in Table 25 is a decision-making matrix that a policy maker could use in making final
decisions concerning each admission program. The MAUT utility ranking and utility
scores for each program are listed along with explained grade variation; the time

needed to make final admit decisions; and the time needed to make decisions on all

applications (admit and deny decisions).

84

 

Table 25: Alternative admission program policy decision-making matrix.

 

 

 

 

Admission MAUT Utility Explained Mean Admit Mean
Model Ranking Variation in Decision Decision
(Admit Utility) GPA Time Time
(Percentage) (Aggregate)
Carnegie Unit 1 (77.18) 48% 6.08 Minutes 6.09 Minutes
Admission
Competency 2 (73.06) 47% 7.41 Minutes 8.51 Minutes
Based
Admission

 

 

 

 

 

85

 

CHAPTER V: SUMMARY, CONCLUSIONS, IMPLICATIONS AND

RECOMMENDATIONS FOR FUTURE RESEARCH

Introduction
The discussion of the results is detailed in several sections of this chapter.
The chapter starts with a summary of the research hypotheses. A summary and
discussion of the findings and conclusions of the results of each hypothesis is
reviewed. This is followed by a discussion of the implications of this study. Finally,
the direction for future research is discussed and a listing of future research

summary points is outlined.

Hypotheses

The hypotheses that were tested are the following:

o Admit rates and the corresponding MAUT utility will be higher for Carnegie
Unit admission when compared to CBA admission.

. The Carnegie Unit model explains a higher amount of the variation in first
semester grades.

0 The time needed to make decisions on CBA applications will be higher than

the time needed to make decisions on Carnegie Unit applications.

86

Findings and Conclusions

Hypothesis 1 states: Admit rates and the corresponding MAUT utility
will be higher for Carnegie Unit admission when compared to CBA admission.
The results of the MAUT utility ranking showed that the Camegle Unit admission
program had a higher aggregate utility value than the CBA admission program.
Therefore, the hypothesis is accepted. The results were expected based on the
hypothesis related to admission access. Furthermore, these results shed light on
differences in the two programs in evaluating admit decisions. The CBA program
yielded a lower admit utility ranking for six of the ten universities. However, these
disaggregated results do indicate that there is a level of high access maintained in
four universities by the CBA program that is not present in the Carnegie Unit
program. In dissecting these results, it could be appropriately argued that a student
with a lower Carnegie Unit profile (i.e., grades and test scores) would have a better
chance of gaining admission to one of these four universities if s/he possesses an
average or better than average CBA profile (i.e., SRP evaluation scores). On the
other hand, students with a higher Carnegie Unit profile would be better served
applying for admission to one of the six universities where the Carnegie Unit
program had a higher MAUT utility ranking.

The admit rates for all universities are detailed in Table 26. The data show a
close admit ratio between the two admission programs for University 10. The
Carnegie Unit admit rate for this university was 82% and the CBA admit rate was
84%. These results compare favorably to the MAUT utility rankings calculated for

University 10. The Carnegie Unit MAUT utility was 12.30 and the CBA MAUT utility

87

was calculated at 12.60. In addition, the results indicate that not only does the CBA
model lead to similar access outcomes when compared to the Carnegie Unit model,
it also would result in a small increase in admission access for University 10. The
differences in the admit rates (variation), for this institution, would indicate that over
time 2 more students out of 100 would be granted admission using the CBA model

versus the use of the Carnegie Unit model.

Table 26: Admit rates and variations in admit rates for the
Carnegie Unit model and the CBA model.

 

 

 

 

 

 

 

 

 

 

 

University Camegle Unit CBA Admit Admit Rate Variation
(Institution) Admit Rate Rate (Camegle Unit - CBA)
Institution 1 .83 .73 .09
Institution 2 .96 .75 .21
Institution 3 .79 .69 .10
Institution 4 .68 .60 .08
Institution 5 .65 .75 (.10)
Institution 6 .55 .82 (.27)
Institution 7 .67 .92 (.25)
Institution 8 .72 .68 .04
Institution 9 .85 .77 .08

Institution 10 .82 .84 (.02)

 

 

 

 

 

 

The universities with the highest variations in admit rates were Universities 2,
3, 5, 6 and 7. Each of these universities had a difference in admit rates greater than
10%. In fact, Universities 2, 6 and 7 had admit rate variations greater than 20%.

For University 2, the Carnegie Unit admit rate was 96% while the CBA admit rate

88

was 75%. Overtime, this variation would result in 21 more students out of 100 being
admitted through the Carnegie Unit program or 21 fewer students being admitted
using the CBA program. Likewise, the trend is reversed for Universities 6 and 7.
The Carnegie Unit and CBA admit rates for University 6 were 55% and 82%,
respectively. Overtime, these rates would result in 27 more students out of 100
being admitted to University 6 using the CBA program or 27 fewer students gaining
admission access using the Carnegie Unit program. The corresponding Carnegie
Unit and CBA admit rates for University 7 were 67% and 92%, respectively. In
keeping with the analysis provided for University 6, 25 more students out of 100
would be granted admission to University 7 using the CBA program.

The MAUT and admit rate differences across the ten universities studied has
important implications for students planning to attend a University of Wisconsin
institution. For students who have strong grades and test scores, submitting this
material for Carnegie Unit admission would result in these students having a 96%
chance of being successfully admitted to University 2. Alternatively, students with
strong Supplemental Reporting Profiles (SRP) would have a 92% chance of gaining
a positive CBA admission decision when applying to University 7. By comparison,
students would only have a 55% chance of gaining a positive Carnegie Unit
admission decision when applying to University 6. These same students would also
have a 60% chance of receiving an affirmative CBA admission decision when
applying for admission to University 4.

The results of this study show that for two of the ten universities studied the

89

CBA model achieves similar access outcomes in comparison to the Camegle Unit
model. This statement is best represented with University 8 and University 10. With
University 8, there is a 4% admit rate variation in favor of the Camegle Unit model,
and with University 10, there is a 2% admit rate variation in the direction of the CBA
model.

Based on both the individual university results and the aggregate admission
rates, the CBA program does prove itself to be a worthy, alternative program for
making college admission decisions.

The MAUT process used in this study provides University ofWisconsin policy
makers with important information on the Carnegie Unit and CBA programs. In
trying to make a final decision on which program maintains the highest level of
access, the policy decision could be balanced by looking at both the aggregate
utilities and the utilities derived for each university. In some cases, the final decision
on programs that have a societal impact, as is the case in this comparison, will
come down to whether there are important redeemable outcomes (e.g., providing
access to college to groups of students who would othenlvise be denied admission)
associated with each program. If this were the basis of final decision-making
between Carnegie Unit and CBA, then the decision on access would result in both
programs being available for use by students applying for admission to a University
of Wisconsin institution. If the program review decision requires a final decision
based solely on access rates, then the final program choice would be to continue to

use the Carnegie Unit program as the sole admission strategy for all public

90

universities in Wisconsin.

The universities examined in this study consisted of institutions that vary in
size from 5,000 to 40,000 enrolled students. In comparing the level of access and
the size of the university, there appears to be no discemable trends. Some
universities provided a higher level of access using the Carnegie Unit program while
others had higher access rates with the CBA program. In comparing access and

university enrollment, the following four results were observed:

1. The smallest university (Based on enrollment) had the highest
Carnegie Unit access rate.

2. The third smallest university had the lowest Carnegie Unit access
rate.

3. The second smallest university had the highest CBA access rate.

4. The largest university had the lowest CBA access rate.

These results are important when considering the institutional mission
associated with these universities. For example, the smaller universities are
characterized as regional universities; are less selective in their admission practices;
and devote fewer financial resources to research in comparison to larger universities
in this study. The observations noted in numbers 3 and 4 point towards a
conclusion that lower CBA access rates may exist more often in among large,
research-intensive universities, while higher CBA access rates may be more
commonly associated with smaller, regional universities.

These universities also consist of regional, national and institutions that have

a global enrollment appeal. The geo-demographic characteristics of these

91

universities are diverse. The net affect of all of these characteristics is a group of
institutions that are representative of most public universities. The CBA program
results appear to be outcomes that could be generalized across many public

universities in America.

Hypothesis 2 states: The Carnegie Unit model explains a higher amount
of the variation in first semester grades. Based on an evaluation of the collected
data, the evidence does not support this hypothesis. The amount of variation in
grades explained by the Carnegie Unit model was 48%, while the CBA model
explained 47%. The difference in the explained grade variation between these two
admission models is relatively small (1%). However, differences in each subject
area highlights greater levels of explained grade variations between the two
admission models. For example, the Carnegie Unit model explained 37% of the
variation in grades in the subject of math, and 49% of the variation in grades for
English and science. These results compare favorably to a CBA math rate of 31%,
an English rate of 41%, and a science rate of 45%. Alternatively, the CBA model
accounted for a higher amount of the explained grade variation in social science and
foreign language. In fact, the explained grade variation for CBA in social science
was 33% and a rate of 37% for foreign language. These results are higher than the
Camegle Unit rates of 26% for social science and 32% for foreign language.

The math, English and science results could point towards the impact that

92

test scores and test methodologies have in improving grade prediction in the
Carnegie Unit model. Since the ACT and SAT evaluate levels of student knowledge
in these subjects, we might expect an admission model that utilizes these tests (i.e.,
Carnegie Unit model) would explain higher levels of grade variation when compared
to a model that excludes these exams (i.e., CBA model). The ACT and SAT do not
evaluate proficiency levels in foreign language and general knowledge in the area of
social science. As a result, the addition of test scores does not enhance the
Camegle Unit model’s ability to explain levels of grade variation in foreign language
and social science. This point could explain why the CBA model yielded higher
grade variation results for these two subjects when compared to the Carnegie Unit
model.

Another possible explanation for these results, and specifically the amount of
explained grade variation observed in the CBA model for foreign language may
relate to the pedagogical methods used in both high school and college curricula.
The instructional methods used to evaluate a student’s proficiency in high school
and college foreign language courses are similar. These courses are graded using
a combination of written tests and oral examinations. The ability to verbally
communicate in an expressive and understandable manner is often evaluated at a
much higher level when compared to written expression. Consequently, the CBA-
SRP evaluation process provides teachers the opportunity to express in a detailed
manner the student’s level of mastery of foreign language material. The Carnegie

Unit model has to rely on high school grades as the primary means for predicting

93

success in college foreign language courses. The foreign language results
represent a clear example of how an written explanation of a student’s skills
provides an enhanced college grade prediction method when compared to a

strategy that predicts results by examining high school grades.

Hypothesis 3 states: The time needed to make decisions on CBA
applications will be higher than the time needed to make decisions on
Carnegie Unit applications. The data indicate that time differences did exist
between the two processes. The average time needed to make aggregate Carnegie
Unit admission decisions was 6.09 minutes and the average time needed to make
aggregate CBA admission decisions was 8.51 minutes. Therefore, the hypothesis is
accepted. These time differences identified in the study could have resulted from
different levels of familiarity among admission officers with the two types of
applications. Typically, such familiarity will result in very little time needed to pause
or be indecisive in rendering final application decisions. As a result, most admission
offices in this study were able to make time-efficient admission decisions on
Carnegie Unit applications.

Conversely, because the CBA process was a new pilot program, much of the
time admission officers needed to make decisions could be explained by a lack of
familiarity with this program (CBA: The Wisconsin Model, 1994). With any new
initiative, there may exist a steep learning curve prior. The CBA program required

admission officers to spend significant time understanding the parameters

94

surrounding the decision-making process (CBA: The Wisconsin Model, 1994).
Once this knowledge base is better established, processing and decision-making
efficiency should begin to improve. Over time we would expect processing time
differences between the two admission programs to be less significant.

In nine of the ten universities studied, the CBA program had higher rates for
the amount of time needed to make application decisions than the Carnegie Unit
program. The aggregate time needed to make Carnegie Unit decisions was 2.42
minutes less than the time needed to make CBA decisions. The average time
needed to make Carnegie Unit decisions for University 2 was 45 seconds less than
the time expended on CBA decisions. At the same time, Universities 6 and 1
experienced Camegle Unit decision times that were less than CBA decision times
by 82 seconds and 95 seconds, respectively. These results show that CBA does
represent a viable time efficient instrument for some universities.

The two most startling results in comparing each admission program came
from Universities 4 and 10. University 4 was the school with the highest average
time needed to make CBA decisions, while University 10 was the school that had
the lowest average CBA decision time. In addition, these two schools had the
largest time differences when comparing the average Carnegie Unit time to the
average CBA time. The average time needed to make Carnegie Unit decisions for
University 4 was 4.93 minutes compared to an average time of 15.47 minutes
needed to make CBA decisions. The time difference between the two admission
programs was 10.54 minutes. These results show the huge gap in efficiency that

could be the result of a lack of familiarity with the CBA-SRP form. If such a lack of

95

knowledge concerning the SRP form exists, through the continuous use of the CBA
program, the time efficiency gap with the Camegle Unit program should start to
close. Another possible explanation for this time difference may relate to the way
admission officers viewed each program. For example, the Carnegie Unit program
is primarily an evaluation of quantitative data (e.g., the examination of letter grades
from the high school transcript and the evaluation of standardized test scores).
Alternatively, the CBA application could be viewed by some admission officers as
mostly a qualitative evaluation process. Under certain conditions, a qualitative
admissions review could result in a greater amount of time needed to make
decisions when compared to a process that is primarily a quantitative review. Time
differences between the two programs could also occur if some universities used
committees (i.e., two or more admission officers) to make admission decisions. In
some cases, the committee process of trying to arrive at a group consensus can be
more time consuming than a process of having one officer make the same
admission decisions.

At the opposite end of the efficiency spectrum is University 10. The results
observed for this institution represent more of an “outlier" effect when compared to
the other nine universities in the study. University 10 was the only school that
experienced results that found the CBA program to be more efficient than the
Carnegie Unit program. The analyses of these results show a huge average time
gap between the two admission programs. The average time expended on CBA
application decisions was 2.84 minutes compared to an average time for Carnegie

Unit applications of 10.34 minutes. These totals represent the second largest time

96

gap (7.50 minutes) among institutions in the study. While these results for
University 10 are important, they are also surprising and counterintuitive to what
would normally be expected. The normal expectation for time differences between
each admission program would be in a direction similar to the other nine
universities. A logical hypothesis would be targeted and directed toward the
average Carnegie Unit decision time for each university being less or lower than the
average CBA decision time for each school. The fact that the results for University
10 are in the opposite direction of this hypothesis raises at least one important

question:

. What happened in the admission office for University 10 that generated these

results?

While this is a difficult question to answer without conducting on-site research
. at this university, there are some possible explanations. One explanation could be
that an experienced admission officer was assigned to make all CBA decisions,
while a less experienced admission officer was assigned to make all Camegle Unit
decisions. Another possible explanation could be that the CBA admission officer
may have quickly grasped the logic behind the SRP form and made time efficient
decisions once his/her Ieaming curve reached its peak. An additional explanation
focuses on the complexity of the admission decision-making process for Camegle
Unit applications. Some American universities employ a complex admission
decision logarithm that assigns points to applicants based on a large number of
characteristics which include factors such as letters of recommendation and an

applicant’s personal statement (Fetter, 1995).

97

If University 10 uses a Carnegie Unit application decision-making system that
utilizes a complex point system, similar to the aforementioned process, this would
explain the large time differences between Carnegie Unit and CBA. At any rate, a
follow-up study on university 10 would go far in determining the basis for these time
differences.

This is one of the first studies to examine admission decisions using a time-
focused evaluation process. The data analysis could serve a useful purpose that
may enable colleges and universities to develop strategies and establish time-

efficient benchmarks for making decisions on college admission applications.

Implications of the Study

This study provides some useful contributions to the literature by establishing
a better understanding of the evaluation of alternative methods for determining
access to college. The study also contributes to the body of literature that deals with
process oriented efficiency by examining research data that quantifies and provides
a benchmark for the average amount of time needed to make final college
admission decisions.

From the study, the development of a new admission model, the Competency
Based Admission program, is proven to be an effective decision making tool in
determining access to college. These evaluations of CBA admit rates show that this
new program, when compared to the standard program (Carnegie Unit Admission),

is successful in maintaining a sufficiently high level of college access. The first

98

semester and first year grades received by students admitted using the CBA
program compare favorably to the Carnegie Unit program. These results assist in
helping to validate the CBA program as an effective model in determining future
success in college. The strong admit rates and the success in college achieved by
students admitted using the CBA program points toward an admission model that
could have use that extends far beyond the borders of Wisconsin.

The other important contribution of this study is in the area of time based
admission decision-making literature. Since Carnegie Unit admission is a widely
used process, this study could assist admission offices by helping them establish a
benchmark related to the amount of time an admission officer should spend making
application decisions. To date, a thorough review of the body of literature yields no
studies that provide this type of benchmark and efficiency analysis. The Camegle
Unit admission results generated by this study could become the standard used to
establish a benchmark of decision-making efficiency for college admission officers.
In addition, the study of the time required to make CBA decisions is important in
helping to establish a benchmark of efficiency for the evaluation of newly developed,
alternative admission programs.

The admit rates and college grade success derived from the CBA program is
an important finding in arguing against the prominent use of standardized test
scores in college admission decisions. The CBA results show that an effective
admission model, which minimizes the reliance on test scores, can be successfully
developed and implemented.

The study results have their most important contribution nested in the minds

99

of policy makers who may have felt helpless in examining meritorious college
access using only one evaluation process. This merit based access issue has also
become a highly charged issue impacting access to college for minority students in
key states like California and Texas (San Miguel & Valencia, 1998). In California,
Proposition 209 was passed into law in 1996, which requires the evaluation of
college admission materials to center on Carnegie Unit criteria and away from any
Affirmative Action based consideration (Jones, 1998). In the years following the
strict enforcement of Proposition 209, the data show admission rates for minority
students have been dramatically lower when compared to the rates observed in the
years before this law (Douglass, 1999; Jones, 1998; Karabel, 1999). In the two
years following the Proposition 209 law, enrollment of Black and Hispanic freshman
in California’s public universities declined 54% and 30%, respectively (Douglass,
1999). During that same period, White freshman student enrollment increased by
10% in these public universities (Douglass, 1999).

A CBA type of program could serve an important role in moving the
admission debate in states like California to a level that focuses on qualifications
based on demonstrated success in high school with good indicators of knowledge
and competencies. The data analyzed in this study did not focus on the direct use
of CBA in states other than Wisconsin, however, the results do hold much promise
for this program being able to successfully maintain broad college access while

minimizing the dependence on test scores.

100

Direction for Future Research

The imposition of any new system on an organization could place an
additional burden on already constrained resources. This may be particularly true in
the case of the CBA program and its affects on universities. During the pilot study,
no financial resources were provided to Wisconsin universities to process and
compile data on the CBA program. As a result, a study that investigates the impact
of CBA on existing financial resources for each university is needed.

A challenge to anyone conducting research on the CBA program is the
examination of data that are generated during the pilot phase of the program. In
fact, much of the data for this study were gathered at the conclusion of the CBA pilot
phase. Processes used in operating a program in its full implementation period
might and often do differ significantly from those practices established during a pilot
phase. In addition, during the full-implementation phase of a program like CBA,
some of the college access and resource-expenditure (time) issues might be
eliminated. Thus, providing data and evidence that may allow admission personnel
to devise strategies to refine and continue to improve the ability of colleges and
universities to make better and more informed decisions and to utilize more
efficiently admission staff members time is an important reason to carry out a
thorough longitudinal study of the CBA program.

Another critical area for future research should focus on examining the use of
teacher evaluations as utilized in preparing the CBA-Supplemental Reporting Form
(SRP). These teacher SRP assessments of student skills and subject competencies

are the primary basis for making CBA admission decisions. The rationale for a

101

future study in this area is driven by the need to validate the SRP instrument in
college admission decisions. Before a program like CBA can experience broad and
wide spread acceptance in higher education, its core tool for predicting student
success should have a consistent degree of predictive validity. The availability of a
predicted validity standard would provide admission counselors with the confidence
needed to make admit and deny decisions based on a reliable SRP scoring
benchmark. The results in this study show a strong and direct relationship between
satisfactory SRP scores and college grades. Future research that continues to
examine this relationship is one way of attempting to validate the use of the SRP
form in making college admission decisions.

This study was inconclusive in evaluating the impact of CBA on college
access for women and minority students. The attack on the use of Affirmative
Action practices in college admission was an important catalyst behind the need to
study the CBA program. A future study that explores the impact of the CBA
program on women and minority students could help in shaping the discussion
concerning college access for these groups.

In addition, future research studies should explore the affects of CBA on
college admission offices and the impact of CBA on K-12 education. Specifically,
these studies should examine the following aspects of each area:

0 College Admission Offices: This research should explore time
comparisons between admit decisions and deny decisions.
0 K-12 Education: An examination and study of the impact of CBA on K-

12 education in Wisconsin is important and should focus on evaluating

102

the explained college grade variation observed in this study in the
subjects of social science and foreign language. A study that
evaluates and compares the high school and college curriculum for
these two subjects may provide valuable insight and knowledge. In
addition, a study should be undertaken to determine the time
demands placed on teachers in completing the CBA-SRP evaluation

form.

Future research that explores these areas will provide a better understanding

of the overall affects associated with the CBA program.

Summary of Areas for Future Research

. A study that examines the financial impact of CBA on university
admission offices.

. A longitudinal study of CBA to evaluate admission decision-making
time over an extended period.

. A continuous study that attempts to identify a direct relationship
between CBA-SRP ratings/scores and first semester college
grades.

0 A study that examines the impact of CBA on the enrollment of

women and minority students.

103

. A study that examines and compares CBA admit and deny
decisions.

0 A further examination that seeks to explore why CBA explained a
high level of grade variation in the subjects of social science and
foreign language.

. A study that examines the time demands placed on high school

teachers in completing the CBA-SRP evaluation process.

The results derived from this study on admit decisions for the Camegle Unit
program and the CBA program does provide concrete ways in which broad levels of
admission access can be preserved as new admission strategies are developed.
The level of access maintained by CBA in this study does appropriately address this
point. The results also provide a better understanding of the time efficiencies
associated with Carnegie Unit and CBA admission decisions. In addition, this study
and its findings provide a starting point for future research on the impact on access
of a newly implemented admission program. While it is important to the general
knowledge, that future studies on CBA and other alternative admission programs be
undertaken, this study does provide an important and promising start in expanding

on this body of literature.

104

Post-Pilot Summary Status

After the conclusion of the pilot study, the University of Wisconsin System
used the collected data to argue for the widespread use of the CBA program.
During the fall of 1997, the findings from the CBA pilot study were provided to the
University of Wisconsin Board of Regents. These Board members were asked to
consider a recommendation from the System’s administration that called for the full
implementation of the CBA program. At their November 1997 meeting, the Regents
approved the recommendation to allow the CBA program to be used as an
alternative admission procedure (CBA: Spring 1998 Final Report, 1998).

Today, the CBA program is available for students to use for admission
consideration to a University of Wisconsin institution. However, since the full
implementation of CBA, the program has received limited use. Only a small number
of CBA applications have been submitted for admission review. There are a number
of possible explanations for the limited use of the CBA program during this post pilot
period. These include the following possibilities:

. There are a limited number of high schools trained to evaluate student
competency levels in accordance with the CBA criteria. The University
of Wisconsin System requires all high schools that are considering
using the CBA program to attend a formal orientation and training
session. This orientation is designed to provide training to high school
personnel on key aspects of CBA. If high schools are not able to find

the time for training, then they are restricted from using the CBA

105

program. Currently, the only high schools trained to use CBA are the
ten schools involved in the early pilot study.

There may exist among high school personnel a belief that the CBA
application process places a higher level of demand on staff time
when compared to Carnegie Unit application process. The time
commitments associated with the completion of the five subject
evaluations by teachers and the submission of these materials by high
school counselors to each university involves numerous school
personnel. By comparison, the Carnegie Unit program requires high
school counselors to compile and submit the high school transcript
and standardized test scores to universities. The Carnegie Unit
program usually requires the time of one staff member to complete the
process of submitting these application materials. As a result, the
time needed by teachers to complete the SRP evaluations may be
dampening the enthusiasm of high school officials for the CBA
program.

In 1998, the governor of Wisconsin issued an executive order
mandating the development of various assessment methods to
evaluate student Ieaming (Executive Order 326, 1998). This
legislation requires mandatory testing of students at the elementary,
middle and high school level, and culminates in a high school
graduation examination that must be successfully passed as a

condition for receiving the high school diploma. The high school

106

graduation test is being developed for implementation during the 2003
school year. This test is being developed as part of the strategy in
Wisconsin’s K-12 education plan for the evaluation of each student’s
competency in the core academic disciplines of math, science,
English and social science. The University of Wisconsin’s President’s
Office has decided to establish a number of committees to evaluate
the relationship between the CBA competencies and the core
competencies needed for graduation from a Wisconsin high school.
These committees are organized by disciplinary area and include high
school officials, university faculty and administrators. The University
of Wisconsin System refers to this process as the Curriculum
Articulation Project. The goal of this initiative is to ensure that there is
consistency in the knowledge and skills universities expect student to
have for admission and the actual Ieaming that is occurring in the k-12
system. As a result, the University of Wisconsin System has focused
much of its attention on the Curriculum Articulation Project, and less
attention on promoting the CBA program among high schools in

Wisconsin.

These aforementioned items will need to be reconciled before the University

of Wisconsin System can have a reasonable expectation that the CBA program will

become a commonly used tool among high schools.

107

APPENDICES

108

APPENDIX A

109

APPENDIX A

COMPETENCY-BASED ADMISSION: THE WISCONSIN MODEL

FINAL REPORT

INTRODUCTION

In response to educational reform efforts occurring in K-12 schools in
Wisconsin and throughout the country, the University of Wisconsin (UW) System
is developing a supplemental admissions process for students graduating from
high schools using performance-based curricula. This process is called
Competency-Based Admission (CBA). CBA will be used to determine whether
students graduating from high schools with restructured curricula are prepared
for college level coursework.

As part of the implementation process, the UW System will conduct a CBA
pilot project with eight Wisconsin high schools during the 1995-96 school year. In
preparation, subcommittees comprised of UW faculty, in consultation with
representatives from the Department of Public Instruction (DPI), the Wisconsin
Technical College System (WTCS), and the K-12 schools, have developed
competencies in English, foreign language, mathematics, science, and social
studies. UW institutions will use levels of competency attainment as one factor to
determine whether students graduating from the eight pilot high schools will be
admitted.

The CBA approach was devised to be an alternative to the Carnegie Unit
approach to admission. It was not devised to change the standards of admission
to UW System institutions. During the pilot project, no student will be denied
admission based solely on the descriptions of competency level attainment
contained in the Standardized Reporting Profile (SRP). Any student who is not
deemed ”admissible" based on the SRP will be reevaluated based on the
traditional transcript.

This report explains the background and the process used to develop the
CBA approach and the competencies. The report also summarizes the
procedures and timeline that will be used to implement the Competency-Based
Admission pilot project.

110

BACKGROUND

In its July 1992 report to the Board of Regents recommending revision of
the freshman admission policy, the Working Group on Math and Science
Admission Requirements also recommended that a task force be appointed to
examine the feasibility of developing a competency-based process for admission
to UW institutions. This recommendation was based on the growing restructuring
and reform efforts taking place in K-12 schools in Wisconsin. The working group
reasoned that as school districts changed their curricula to become, in many
cases, more performance-based, it would be difficult for UW institutions to use
the traditional Carnegie Unit approach to admission for all students.

The Working Group suggested that the UW System encourage and
support K-12 educational reform because such reform may result in better
prepared students entering the university. One way to demonstrate support
would be through an admission process that would allow UW institutions to use
non-traditional information in making admission decisions. The Working Group
recommended that the UW System consider an admission process that focused
on attainment of knowledge and skills rather than Carnegie Units.

A Task Force was appointed in October 1992 by the UW System Senior
Vice President for Academic Affairs. Task Force members included LTW faculty
and administration and representatives from the Department of Public Instruction
(DPI), the Wisconsin Technical College System (WTCS), and the K-12 schools.
'After careful deliberation of the issues surrounding competency-based admission
and the possible implications that may result from the adoption of such an
approach, the Task Force recommended that the UW System adopt a
competency-based admission process as a supplement to the current admission
policy based on Carnegie Units.

Subsequently, a Steering Committee and six subcommittees were
appointed to develop competencies in English, foreign language, mathematics,
science, and social studies and to design a standardized reporting profile that
would be used by the pilot high schools to report levels of student competency
attainment to UW admission offices. Seventy-five faculty, along with consultants
from DPI, WTCS, and the K-12 schools served on the subcommittees.

In November 1993, the subcommittee members attended a seminar to
begin this major initiative. The Senior Vice President for Academic Affairs and the
chair of the Task Force charged each discipline subcommittee to develop
competencies that students should attain for admission to UW institutions. The
profile subcommittee was asked to design a standardized reporting profile that
would allow for competitive admission decisions. Finally, the members were
given training and practice in generating and writing the competencies. The
subcommittees completed their work in May 1994.

111

COMPETENCIES

Competency-Based Admission is formulated on the premise that if
students attain and demonstrate a certain level of knowledge and skill in the
major disciplinary areas, they will be adequately prepared for a successful
college career. in this report competency is defined as the state of being properly
prepared or well qualified for college level success. It does not exclude higher
achievement, but rather exists on a continuum from minimum to maximum levels
of competency attainment.

Competencies define the knowledge and skills that students should
possess and the appropriate levels of mastery that students should demonstrate.
Competency attainment is a key predictor of student success in college, but it is
only one of many predictors.

Competency-Based Admission is not intended to make admission to the
university more difficult. This process is comparable to the Carnegie Unit
process, but designed to facilitate admission for students graduating from high
schools using restructured, non-Camegle based curricula.

The competencies will form the basis for the Standardized Reporting
Profile that will be used by the schools to report levels of student competency to
university admission offices. These competencies will be included in the CBA
Training Manual that will be provided to each Wisconsin high school prior to
implementation of this initiative.

COMPETENCY ASSESSMENT

The Task Force recommended that the responsibility for presentation of
the students' case for college readiness should remain with the secondary
schools. UW institutions will be responsible for setting admission standards and
for determining the general requirements for admission. Through the use of valid
and reliable techniques such as traditional assessment, performance based
measures, and portfolio reviews, secondary school personnel will determine what
level of competency the student has attained and will report this information to
admission offices on the Standardized Reporting Profile.

A good assessment strategy should be comprehensive and
multidimensional. It should include written tests, problem solving simulations,
peer review and a range of performance-based measures. Leaving the
responsibility for determining levels of competency attainment with the secondary
schools will provide a greater likelihood that students will be comprehensively
evaluated on several dimensions. Secondary school teachers have the

112

knowledge, skills, and opportunities to provide this kind of effective evaluation.
The UW System, due to time and resource constraints, would most likely only be
able to administer a single standardized measure to determine competency
attainment. This kind of one-dimensional assessment would not accurately test
student knowledge, and, in all likelihood, might tend to drive the high school
curriculum.

Students in Wisconsin already participate in several comprehensive
assessment programs. DPI is developing a Student Assessment System that will
include evaluation of every student in fourth, eighth and tenth grades using
traditional, performance based and locally developed portfolio assessment.
Students in tenth grade take the UW Early Math Placement exam to help
determine their level of mathematics ability. This information helps them decide
how to proceed with mathematics in high school and gives them an idea of how
they will likely perform at UW institutions. In addition, UW institutions require
students to take math, foreign language, and English placement exams to help
determine their levels and placement upon admission. Finally, each student
applying for admission must take an ACT exam. This information helps students
decide at which institutions they are likely to be successful and to determine their
academic strengths and weaknesses.

The combination of the information from the evaluation systems already in
place and the Standardized Reporting Profile received from the secondary
schools should give the UW admission offices and faculty the information
necessary to make accurate and informed decisions for admission and course
placement.

STANDARDIZED REPORTING PROFILE

Currently, students are admitted to UW institutions according to the
number of high school credits, or Camegle Units, they acquire. Under this
approach, students take discrete classes and receive credits and grades based
on their performance. These credits and grades are recorded and transmitted to
the university on a traditional student transcript. If students have the required
number of credits in the required academic areas and meet class rank and ACT
score requirements, they are eligible for admission.

While this system works well for a curricular structure based on Carnegie
Units and standard grades (i.e., A-F), it does not work as well for an integrated
and applied performance-based curriculum. As K-12 schools restructure their
curricula, they will need a different way to report the knowledge and skills their
students have learned. In turn, UW institutions will need a new method to
evaluate these students for admission.

113

In response to these concerns, a subgroup was formed to develop a
common profile that high schools with restructured curricula could use to report
levels of student achievement to university admission offices. lle Standardized
Reporting Profile (SRP) will provide a scale that the high schools can use to rate
the students' levels of competency attainment. The SRP also will solicit additional
information about a student (e.g. attendance, effort, extra-curricular activities,
honors, etc.) that may be used by institutions in determining eligibility for
admission. In certain cases, the SRP may be used in conjunction with a
traditional transcript to provide a more complete record.

It is anticipated that the SRP would be completed by teachers at the end
of the junior year and again after graduation. The competency levels reported on
the SRP would be based on the results of the assessment process used by the
high school. Each UW institution would determine the competency level that
would be required for admission and how other factors would be considered. The
purpose of the CBA approach is not to change admission standards, but to
provide an alternative to the Carnegie Unit approach.

PILOT PROJECT

Since Competency-Based Admission is a significant departure from the
present admission process, and because it is unclear at this time how extensive
K-12 school reform will be, the UW System decided to implement CBA on a pilot
basis. Up to eight Wisconsin high schools in various stages of curricular reform
will be invited to participate in a pilot project that will be conducted during the
1995-96 academic year. Teachers and other representatives from these schools
will participate in a training program and will use the CBA process for students
seeking admission to a UW institution for Fall 1996. The pilot project will provide
important information about the training component, the Standardized Reporting
Profile and the overall CBA. admission process. The results of the pilot win be
used to enhance the process and help determine the feasibility of implementing
this approach on a wider basis.

TRAINING AND DISSEMINATION

The LTW System will use a Trainer-of-Trainers approach to facilitate the
implementation of CBA. A Core Training group consisting of two UW faculty, a
LTW ,admission director, and a K-12 representative will plan and conduct a
training seminar that will be held in January 1995. A group of Site Trainers,

114

consisting of a representative from each K-12 pilot school, an admission officer,
and faculty member from each UW institution, will attend the seminar and will
subsequently be responsible for training colleagues at their respective schools
and institutions.

Specifically, the K-12 Site Trainers will train high school faculty,
administrators, and other staff at their high schools to use the Standardized
Reporting Profile for reporting student levels of competency. The UW admission
office Site Trainers will train the other admission personnel at their institutions to
evaluate the Standardized Reporting submitted by the K-12 pilot schools for
competitive student admission. The UW faculty Site Trainers will meet with other
faculty members to explain the CEA process and its purpose. This information
may be used to help the faculty establish institutional admission standards for
students applying through this process.

The Core Training Group will write a Training Manual during the 1994-95
academic year. This Training Manual will be used as a resource for the Site
Trainers, admission personnel, and secondary school and university faculty as
they implement the CBA pilot project. In addition, the Training Manual will be
disseminated in written and electronic form to other colleges and universities
throughout the nation for use as a model in developing their own alternative
admission programs. The Training Manual will detail the process the UW System
used to develop the CBA process and the procedures that were put in place to
implement the pilot project. It will include a listing of the competencies and
definitions of the competency levels, examples of activities or evidence that may
be used to assess student knowledge and skills, instructions for using the
Standardized Reporting Profile to report student competency, and how it will be
used in making competitive admission decisions.

NEXT STEPS

This report will be sent to the Vice Chancellors and to other governance
groups during the 1994 fall semester. Preparation and training for CBA will occur
during the 1995 spring semester and the pilot study will begin in the 1995 fall
semester. After the pilot is completed, the competencies and the SRP will be
reviewed and modified as needed. The results of the pilot study will be used to
enhance the CBA process and help determine how it might be used on an
expanded statewide and national basis.

115

CONCLUSION

The Task Force on Competency-Based Admission that first examined this
issue concluded that a competency-based admission process in the LTW System
had the potential to support K-12 restructuring, to allow for diversity among
school districts and individual students, to provide cost-saving measures in
remedial programs, and to promote collaboration between UW institutions and
the K-12 schools. At a time when most institutions of higher education are
moving slowly in changing their admission policies, CEA puts the UW System in
a leading position in educational reform. The development and implementation of
the CBA process has been a collaborative effort between the educational
agencies that will support educational reform. It is difficult to predict its impact
before it is implemented and evaluated, but its potential benefits are far reaching.

\NJK\COM\COMPRPRT
1 0-27-94

116

APPENDIX B

117

APPENDIX B

UNIVERSITY OF WISCONSIN SYSTEM
COMPETENCY-BASED ADMISSION

ADMISSION COMPETENCIES

Competencies, Standardized Reporting Profile
and Rating Scale for
Competency-Based Admission Pilot Project

January 1995 Competency-Based Admission Pilot Project is an initiative of
University of Wisconsin System. Additional support for the training and
evaluation components is provided by the Fund for the Improvement of
Post Secondary Education; United States Department of Education.

118

RATING SCALE

Completing the Competency-Based Admission Standardized Reporting Profile
for a student requires a numerical rating for each of the major categories under
the subject headings English, mathematics, science, social studies and foreign
language. A student’s level of proficiency is described using a five point scale.

5 - Excellent Performance

4 - Very Good Performance

3 - Satisfactory Performance
2 - Limited Performance

I - Poor Performance

NBE - No Basis for Evaluation

In the case of the rating for foreign language, the assumption is that the student
has completed a minimum of 2 years in a high school foreign language program.

Excellent Performance

This rating is used to describe a student who performs the competency-related
tasks with outstanding quality, initiative and adaptability and who can lead others.
There may be evidence of insight, originality, or other attributes that characterize
deep understanding of the concept or process. The few students who achieve
this level of performance may well be capable of going into advanced
coursework upon entering the university.

Very Good Performance

The student who receives this rating performs the competency-related tasks with
more than acceptable quality and can apply past knowledge in solving new
problem situations. Work tends to show evidence of originality, rather than
simple rote execution.

Satisfactory Performance

The student performs the competency-related tasks satisfactorily without
additional supervision or assistance from the teacher. When encountering a new
concept, he or she builds on previous knowledge but may have some difficulty
using new concepts to solve a related problem. Work tends to be relatively free
from errors and on time but not necessarily original or imaginative in its scope.

Limited Performance

This student may work very hard, but lacks the understanding to carry out the
competency-related tasks independently and with originality. Work may be on
time but probably has errors. This rating also describes the student who may be
capable but who is sporadic in providing evidence of proficiency.

119

Poor Performance
Work is unacceptable by usual performance standards. The student
may also have difficulty understanding new concepts.

No Basis for Evaluation

Due to the degree of difficulty or selection of coursework, the
student may not have encountered specific concepts or tasks.

120

ENGLISH

The following points should be understood by anyone using these competencies:

They apply not only to English composition and literature; but to reading and
writing across the disciplines.

The order in which the competencies appear does not correspond to their
Importance.

”Text" means any written discourse in any discipline; “literature” means chiefly
imaginative writing In English, or works translated Into English.

A. Writing: Process

WAn effective writer

1.

Formulates and explores ideas using strategies such as brainstorming,
listing, mapping, journal writing, questioning, clustering, and outlining;

. Considers purpose and audience in selecting and limiting topics;

Gathers and evaluates materials and Information pertinent to the topic;

Uses primary and secondary research to shape ideas, when appropriate.

Drafting: An effective writer

5.
6.

9.

Develops and elaborates ideas, distinguishing between topics and theses;
Distinguishes major features from minor points;

Develops support that is both sufficient and relevant, including source
materials where appropriate;

Uses appropriate resources for research, e.g., interviews, bibliographies and
data bases;

Reports and acknowledges the ideas of others;

10. Writes multiple drafts when necessary.

121

Revising: An effective writer

11.

12.

13.

14.

15.

16.

17.

Reads own drafts critically to refine the development of ideas;
Anticipates the needs and responses of readers;

Incorporates feedback from readers and provides constructive feedback to
other writers;

Assesses and, as necessary, improves the focus and clarity of the controlling
ldea(s);

Reviews supporting material for relevance and adequacy;

Revises for Ideas, coherence, and organization, reshaping the text as
necessary by adding, deleting, substituting, and rearranging;

Demonstrates control of Edited American English,

B. Writing: Product

Effective writipg

1.

2.

Displays a clear purpose and addresses an appropriate audience;
Focuses on a subject, employs unifying Ideas, and uses appropriate
organizational patterns (e.g., comparison/contrast, cause/effect,
description/narration);

Has a logical organization, appropriate transitions, and Internal coherence
and cohesion;

Uses a variety of sentence types and lengths appropriate for the reader and
genre;

Supports generalizations with appropriate details;
Expresses ideas with individuality and insight;

Employs conventional formats of documentation, e.g., MLA, APA, Chicago.

122

C. Reading

An effective reader

1.

2.

10.

11.

Reads, analyzes, and interprets texts orally and in writing;
Understands denotative, connotative, and figurative meanings;
Comprehends literal and inferential meanings;

Distinguishes main ideas from subordinate details;
Summarizes and paraphrases texts orally and in writing;

Formulates questions about the implications of a text;

Recognizes and evaluates the validity of differing interpretations of a text;

. Transfers critical reading skills from one discipline, or setting to another,

Recognizes the influences of historical, social, biographical, cultural, ethnic,
and other contexts on, a text;

Recognizes, understands, and discusses, orally and in writing, conventional
literary forms and terms;

Discusses, orally and in writing, characterization, setting, point of view, and
plot development in imaginative literature;

Understands the role of imaginative literature in the development of cultures.

D. Oral Communication

An effective -speaker

1.

2.

Presents Information that is well organized;
Communicates in ways appropriate to a variety of audiences and contexts;

Supports a position with evidence and effective reasoning;

Presents Information which reflects effective language skills, e.g., use or.
transitions and clear and appropriate word choices;

123

5. Delivers messages using effective vocal articulation, pronunciation, volume,
pitch, vocal quality and body movement;

6. Distinguishes among the five functions or purposes of communication:
informative, affective, imaginative, ritualistic and persuasive;

8. Employs and responds to nonverbal communication.

An effective listener
8. Distinguishes between hearing and listening;

9. Identifies barriers to effective listening and applies techniques to overcome
the barriers;

10. Identifies the different types and levels of listening.

124

FOREIGN LANGUAGE

Foreign Language is not a general admission requirement of UW System
institutions, but institutions that do require foreign language, require two years at
the high school level. These competencies are, therefore, based on expected
competency levels for third semester foreign language Instruction at UW System
institutions.

A. Culture: A student who demonstrates competency in culture can

1.

E.

Demonstrate basic familiarity with the role of important social institutions
within the target culture or cultures.

Identify and evaluate superficial stereotypes of the target culture or cultures,

. Writing: A student who demonstrates competency in writing

. Can communicate information on familiar topics in the target language.

Can make correct and appropriate use of present, past and future time.

. Speaking: A student who demonstrates competency in speaking can
. Respond appropriately to an inquiry.

. Participate in discussion about familiar topics.

Use the target language to accomplish everyday tasks.

Address everyday problems by asking pertinent, logical questions and making
suggesfions.

. Listening: A student who demonstrates competency in listening can

. Understand and respond to native or near-native speech in familiar situations

and on familiar topics.

Reading: A student who demonstrates competency in reading can

125

1. Comprehend authentic written materials on familiar topics.

2. Extract particular information from a variety of authentic documents and
make reasonable comments about style, tone, purpose, and audience.

F. Transferable Skills (Provisional): Foreign language competency includes
the ability to

1. Contrast and compare the structure and usage of the target language with
English.

2. Summarize, Isolate main and subordinate ideas, infer meaning, and draw
conclusions from context.

126

MATHEMATICAL KNOWLEDGE AND REASONING

GENERAL EXPECTATIONS: Knowing the mathematics listed in the sections
which follow includes knowing how to put that mathematics to use in common
varieties of problem situations. Thus, knowing about use of variables in linear
situations includes knowing how to set up and analyze such common situations
as those Involving mixtures or constant rates. Rational situations include
variation and proportion. Transcendental situations include exponential growth
and decay problems. In all cases, the use includes interpreting, in terms of the
problem, results obtained from mathematical analysis.

Knowing the mathematics in the detailed listings also means being able to

translate or interpret between different representations: between functions,

equations, tables and graphs; between pictures and the trigonometric functions

sine, cosine and tangent; between pictures of plane regions and equations or

Inequalities.

A. Use of Constants

1. Perform arithmetic operations in proper order, represent real numbers in a
variety of forms and simplify arithmetic expressions involving radicals. Use
arithmetic operations to model problem situations. Use mental arithmetic and
estimation.

2. Construct and read charts, tables and graphs that summarize data from real
world situations.

B. Use of Variables In:

Linear Situations

1. Solve linear algebraic equations and inequalities in one variable, including
those with literal coefficients.

2. Solve linear systems of equations in two or more variables and interpret
solutions both symbolically and graphically

3. Use linear functions and their graphs.

4. Use matrices to represent and analyze linear situations.

127

flgebraic Sitpations

5.

Add, subtract, multiply, divide and exponentiate polynomial, rational, complex
fractional and radical expressions and simplify the results.

Solve algebraic equations and inequalities in one variable, including those

which can be factored into linear and quadratic expressions, or which contain
fractional expressions, absolute values, radicals or fractional exponents.

. Use the language, notation and properties of algebraic functions and their

graphs, with particular attention to quadratic functions.

Transcendental Situations

8.

Manipulate and simplify expressions involving exponentials or logarithm.
Solve equations and inequalities involving exponential and logarithmic
expressions.

Use the language, notation and properties of exponential, logarithmic and
trigonometric (sin, cos, tan) functions and their graphs.

C. Geometry

1.

Solve geometric problems (with or without coordinates) by analyzing figures
in terms of points, lines, circles, and polygons, including finding perimeters
and areas.

. Visualize and sketch points lines planes and simple solids in three

dimensional space and find volumes of boxes and cylinders.

Use knowledge of parallelism, perpendicularity and associated angle
properties to analyze and construct figures and represent problem situations
(with or without coordinates).

Apply knowledge of the angle sum and relationship between sides and angles
in a triangle (including isosceles and equilateral triangles).

Use knowledge of similarity and congruence to make a reasoned analysis of
relations, angles, lengths and areas in a figure or problem situation.

Demonstrate knowledge of the relationship between triangle properties, the
Pythagorean theorem and distance (with or without coordinates).

128

7. Use right triangle relationships and the trigonometric ratios sine, cosine and
tangent to analyze relationships and formulate and solve problems.

129

SOCIAL STUDIES

Social Studies is an academic area defined for school programs and
encompasses a number of fields in the humanities and social sciences.

A. Knowledge: Students should be able to

1.

recognize the principal significance and chronological sequence of major

events, movements and personalities In the mlitical and diploma__tic history of
the British North American colonies to 1776 and the United States thereafter;

distinguish among the powers assigned to the executive, legislative, and
judicial branches of the government in the US. Constitption and between the
areas of responsibility assigned to the state and federal governments; identify
significant changes that have altered the foregoing through Judicial
interpretation and other developments;

describe the processes for choosing political and governmental leaders in the
United States, including formal constitutional and other conventional
procedures, and the role of such major elements in American political culture
as political parties, interest groups, traditional images and values, and the
media;

discuss the sources and history of civil rights in the political system of the
United States, recognizing distinctions between ideas of natural and civil
rights, and identifying issues and competing interests in debates over human
and civil rights;

discuss the concepts of class. race, ethnicityLand gender In the analysis of
society, and: -

. characterize the major ethnic and racial groups that compose the population

of the United States, identifying their linguistic, religious, and other cultural
differences, the chronology of their arrival in North America, and their main
regional and national influences within the United States;

describe how the following have affected the status of women in various
cultures of the wor1d, including the United States: 1) increasing numbers of
women in the economy, 2) the rebirth of an organized women's movements;
3) traditional definitions of women's roles;

130

10.

11.

recognize the principal eras in the history of western civilization from Greek
and Roman times to the present, identifying elements used in conventional
periodization; show a knowledge of the basic chronologies of work} histonr;

demonstrate an ability to compare and contrast the various political theories
including socialism, communism, fascism, totalitarianism, and democracy;

discuss patterns of .qovemmental amority in countries other than the United
States in relation to their differing historical, geographical, cultural and social
circumstances;

recognize in chronological order the major wars ofthe twentieth centugy and
alliances of nations that preceded and emerged from the wars, and the
principal international organizations that have been founded to resolve
disputes and promote concord and cooperation among nations;

demonstrate knowledge of major world religious systems and philosophical
schools and

explain how the scarcity of productive resources requires the development
of economic systems to make decisions about how goods and services are
produced and distributed.

B. Skills and Methods: Students should be able to

1.

distinguish between Primary and secondary soprces use them appropriately
as evidence to support an argument in formal writing, giving Full and accurate
citations;

demonstrate ability to use geographic tools and_ resources (e.g., maps,
atlases, data bases, and spatial data);

demonstrate ability to analyze and correlate data through the use of
conventional historical, comparative, and quantitative research techniqwfi
(using, e.g., tables, graphs, and basic statistics); and

. show awareness of the variety of sources used as evidence by social

scientists and humanists, including print material, statistics, paintings,
sculpture, architecture, film, photographs, and other artifacts.

Integrative Applications: Students should be able to demonstrate their
knowledge and skills through critical analyses in which, for example, they

131

. compare and contrast the impact or race, class. ethnicity. and_gender on the
histories or US. and other cultures;

. compare and contrast the definition, role and significance or citizenship in the
history of the US. and other countries;

. discuss the significance or geography in the development of cultures with
specific reference both to the US. and other areas of the worid;

. apply economic reasoning, to help explain historical and current
developments and Issues, distinguishing between and showing the interaction
of the US. domestic economy and the global economy;

. explain how major world religious systems and philosophical schools affect
the way people react to crises and dilemmas;

.describe the interconnections among cultural, political, social and
technological, and environmental change accounting for and resulting from the

emergence 9f modem Industrial economies in the United States and the
world; and

. use social science methods in such disciplines as anthropology, sociology,
and psychology to analyze historical and contemporary issues.

132

SCIENCE

A. Science Process: given a specific scientific concept, the student should be

able to complete this process:

1. State a hypothesis

2. Design an experiment to test the hypothesis

3. Collect and organize appropriate data and

4. Interpret these data to communicate conclusions related to that concept.

Science Knowledge Base: the student will be able to demonstrate an
understanding of fundamental concepts from at least two of the science
disciplinary areas that are typically covered In high school curricula: earth
science, environmental science, chemistry, biology and physics. Examples of
such concepts are given below. Note: these lists of concepts are not Intended
to be all-inclusive, but rather to serve as a minimum model for secondary
school science curriculum content.

Laws of conservation of engqy and matter as they apply to living and non-Iivipg
system:

1.

2.

3.

Apply the, concepts or force as they relate to motion.
Exhibit an understanding of the basic principles of wave motion.

Analyze the movement of charge in an electrical circuit.

Understand the nature of chemical reactions, including rates of reactions and
energy changes.

. Apply the concepts of stoichiometry (i.e., mole concept) to chemical reactions

and in the preparation of solutions.

Understand the relationship between respiration and photosynthesis, and the
central role of ATP (adenosine triphosphate) in the energy transfer process.

Recognize that the total amount of matter and energy in the universe is
constant.

133

The atomic natpre of matter.

8.

Express measurements from subatomic to astronomical using the appropriate
scale and units.

Describe the structure and changes of matter from subatomic to
macromolecular levels.

10. Use the kinetic molecular theory to describe phases, solutions and changes

in states of matter.

11. Identify the relationships among the structure, shape, function and properties

of molecules.

The natpr_e of organisms-frpm cellular to macroscopic:

12.

13.

14.

15.

Describe cell structure and function, and their relationships to chemical and
physical principles.

Conceptualize the classification of living things according to structure and/or
function.

Integrate structure, function and control mechanisms of a variety of living
organisms.

Understand the nature of genetic information, and the role of heredity in
controlling cell processes and the transmission of genetic Information.

Relationships within and between systems, e.g., atmosphere, hydrpsphere and
geosphere

16.

17.

18.

19.

Describe the evolution through time of the earth’s systems through repeated
interactions and transitions.

Describe the level and consequences of the relationship between living
organisms and their environment.

Recognize the central role of the sun in the production of energy.

Trace the cyclical flow of matter and energy through living and non-living
systems.

134

. Science Communication: the student will be able to read and discuss
scientific information from print and electronic sources, and to

. Correctly use appropriate scientific terminology.

. Locate and use appropriate sources to obtain scientific information (e.g.,
electronic, print, etc.)

. Cogently communicate, orally and in writing, this knowledge.

. Science, Technology and Society. the contextual study of science should

magnify the scientific ideals of curiosity, diligence and skepticism for probing
and seeking understanding of relationships among science, technology and
social issues. The student will be able to demonstrate the following
competencies:

. Recognize the relationships among science, technology and social issues.

. Identify situations and problems that include a science component, and be
able to identify relevant concepts.

. Distinguish opinion from data and fact in discussions and considerations of
personal, social and global issues.

. Analysis/Problem Solving: the student will be able to

. Gather, organize and use information to provide qualitative and/or quantitative
solutions to problems.

. Use data to construct graphs to represent the relationships shown in an
appropriate mathematical form.

. Identify the correct units required to describe a given quantity and to use
dimensional analysis to solve problems.

. Make informed decisions by examining options and anticipating the
consequences of actions.

. Convert the magnitude of data to/from decimal, scientific and engineering

notation, and to perform basic mathematical computations using any of these
forms.

135

F. Laboratory Skills: the student will be able to

1. Follow written and/or oral direction to use laboratory equipment to collect
experimental data.

2. Assimilate and correlate laboratory data with theory to render a clear,
comprehensive, and concise presentation in written or oral reports supported,
where appropriate, with various models of data presentation (e.g., tables,
diagrams, graphs, models, etc.).

3. Achieve a desired result by interpreting and executing instructions, plans,
models and diagrams, using appropriate equipment and technology.

4. Use graphical extrapolation and interpolation to predict the magnitude of
variables not directly measured.

136

APPENDIX C

137

APPENDIX C

50.9.1.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

33...... 2.6
5.8335 8.. v.83 oz n mmz
m sea bani...
.I‘lll 99.5582 Loom u _
3.30m Eu.»8.—.a:a.na<
coca—Eton v2.8..— u N
923m d has—3:93. .92—9.9m
= 238. 8:58.»... bSanam u m
. L5 5 =2.5.§E§b aux—Rum
3.82.5 2.... ocean—Stun 30m bo> n v
3.... 83.35. 853
85:5...2. 29:90am n m
3...... 88.8
mov- act-3:”.—
.§ no... 5:82.800. Palm—Um
35.3... 3.5 35...... 3R.
":13 faves
9.22.: 22.3.... 3.3.32.3... 5 332.3 .o 8:
mac—355 36:2...» 2592?. 5 335:3, no 3.).
3......» 22.8.5 as... c. 825.5 .5 x:
22.5 «so 3.. F852
.99.. .8. 9:32.36. .5505... 25:5... .3... 8... toxemia _ 8.35:3:
8.9.9:. 2.5 3535 28
5.26.5550 35
5.5.39. 9:332... 8353.358...
52.3: Ba 23.». .83... 2.2.3
$3305. 382; 95...?
a»: ”3350733
.23 a... 55.2.5.5 _ 3:58 .308 .96.. 3... guisei 52.55
a» an... 5...; .83
38¢.
5.5.35... 2.5 8.... .85... .3: .25.. 2...: .835
£35 .86.. .o 882 .85.» an... .o 25.2

mar—OK.— DZF—b—Omm—d GHN_Q¢<GZ<hw
207.9204. Gaga >UzmhmmECU

138

8:... 33295 .8 0:82

m—IWM<AOIUm “_O mtm’be—Ohfim O... Dmh<4m¢ mPZmZEOU .720an

 

 

 

 

9:: .3 3.2.58

Ohm .mUfimEH" .mbfi. mZE 7: HZmZm>m~=U< QZ< ZO~H<A=UFM<m

 

 

 

 

 

2.; .3 32.58

mmUZmEmme HZmZIU—Mzm U~ZmQ<U< ~5th QZ< v—mOBmmMDOU ka<xm4muu<

 

 

139

BIBLIOGRAPHY

140

BIBLIOGRAPHY

Allmendinger, David F. (1971). New England Students and the Revolution in
Higher Education, 1800-1900. Histgrv of Education Quarterly, 11,
381-389.

Allmendinger, David F. (1975). Paugers and Scholars: The Tra_nsfonnat£)n of
fldent Life in 19th Centgry New England, New York: St. Martins Press.

Angelo, Richard (1983). The Social Transformation of American Higher
Education. in Jarausch, K.H. (ed.), The Transformation of Higher
Learning, 1860-1930, Chicago: University of Chicago Press.

Astin, Alexander W. (1991) Assessment For Education: The Philosophy and
Practice of Assessment and Evaluation in Higher Education. American
Council on Education, New York: MacMillan Publishing Company.

Axtell, James (1971). The Death of the Liberal Arts College. Histom of Education
Quarterly, 11, 339-352.

Beecher, Mark and Fischer, Lane (1999). High School Courses and Scores as
Predictors of College Success. The Journal of College Admissigfl,
Spring/Summer 1999.

Bell, Richard and Hay, John (1987). Differences and Biases in English Language
Examination Formats. British Joqunal of Educational Psychology, 57, 212-
220.

Blackburn, Robert T., and Conrad, Clifton F. (1986). The New Revisionists and
the History of US. Higher Education. Higher Education, 15, 211-230.

Bok, Derek (2000), Assessing the Results of Race-Sensitive College Admissions,
flmal of Blacks in Hifler Education, 24, 106-111.

Bolger, Niall and Kellaghan, Thomas (1990). Method of Measurement and
Gender Differences in Scholastic Achievement. Journal of Educational
Measurement, 27, 165-174.

Bracey, Gerald (1990). Do Admissions Officers Fail the SAT? College and
University, 66, No. 2, 16-19.

141

Breland, Hunter, Maxey, James, McLure, Gail T., Valiga, Michael J., Boatwright,
Michael A., Ganley, Veronica L. and Jenkins, Laura M. (1995). Challenges
in College Admissions. American Association of Collegiate Registrars and
Admissions Officers (AACRAO). Washington, DC.

Broome, Edwin (1903). A Historical and Critical Look at College Admission
Rquirements, New York: MacMillan.

Bryant, Anne (1996). Affirmative Action: Are We There Yet? The Jogmal of
College Admission. Summer/Fall 1996, 48-51.

Bryk, Anthony and Raudenbush, Stephen (1992). Hierarchical Linear Models:

Applications and Data Analysis Methods, Newbury Park, CA: Sage
Publications.

Burke, Colin (1982). American Collegiate Population: A T_e_§t of the Traditional
View, New York: New York University Press.

Chapa, Jorge and Lazaro, Vincent (1998). Hopwood in Texas: The Untimely End
of Affirmative Action. In Chilling Admissions: The Affirmatiye Act_ion Crisis
fl the Search for Alternatiygs, edited by Orfield, Gary and Miller,
Edward, Cambridge, MA: Harvard Education Publishing Group.

Codina, Edward (1991). Factors and Trends in SAT Performance of Texas
Hispanic Stupents. Claremont, CA: The Tomas Rivera Center.

Cole, Beverly (1987). College Admissions & Coaching. The Npgro Educational
Review, 38, No. 2-3, 125-135.

Competency-Based AdLmission (C_BA): Agmission Competencies; (1994).
Madison: the University of Wisconsin System.

Corppetencv-Based Admission (C_BA): Sprigg 1998 Fina_l Repgrt (1998),
Madison: the University of Wisconsin System.

Competency-Caseg Admission (CBA): The S_upplement_a_l Reporting Profile
(1994), Madison: the University of Wisconsin System.

Competency-Based Admission (C_BA): The Wisconsin Model (1994), Madison:
the University of Wisconsin System.

Cortada, Rafael (1984). Change Without Growth: The Access Dilemma of the

Community College in the 1980’s, in Educational StandardsI Testing and
Access, Princeton: Educational Testing Service (ETS).

142

Cross, Theodore and Slater, Robert Bruce (1999). Only the Onset of Affirmative
Action Explains the Explosive Growth in Black Enrollment in Higher
Education. The Journal of Black_s_in Higher Education, 23, 110-115.

Crouse, James and Trusheim, Dale (1991). How College Can Correctly
Determine Selection Benefits from the SAT. Harvard Educational Review,
61, No. 2, 125-147.

Crouse, James and Trusheim, Dale (1988). The Case Against the SAT, Chicago:
The University of Chicago Press.

Douglass, John Aubrey (1999). The Evolution of a Social Contract: the University
of California before and in the aftermath of Affirmative Action. European
Journal of Education, 34, No. 4, 393-412.

Duffy, Elizabeth and Goldberg, ldana (1998), Crafting A Class: College
Admissions and Financial Aid, 1955-1994, Princeton: Princeton University
Press.

Edwards, Ward, Guttentag, Marcia, and Snapper, Kurt (1975). A Decision-
Theoretic Approach to Evaluation Research. In Han®ook of Evaluation
Research, edited by Guttentag, Marcia, Beverly Hills, CA: Sage
Publications.

Edwards, Ward (1977). Use of Multiattribute Utility Measurement for Social
Decision Making. In Conflicting Obiectives in Decisions, edited by Bell,
David, Keeney, Ralph, and Raiffa, Howard, New York: John Wiley and
Sons.

Eineder, Dale V. and Bishop, Harold L. (1997). Block Scheduling the High
School: The Effects on Achievement, Behavior and Student-Teacher
Relationships, NASSP—Bulletin, 81, No. 589, 45-54.

Emanuel, William H.(1953). College-Entrance Requirements Ten Years After The
Eight Year Study. The School Review, 61, 521-526.

Farmer, Timothy (1987). Testing the Robustness of Multiattributed Utility Theory
in an Applied Setting. Journal for the American Institute for Decision
Sciences, 18, No. 2, 178-193.

Farrand, Elizabeth M. (1885). History of the University of Michigan, Ann Arbor:
Register Publishing House.

Fetter, Jean H. (1995). Questions and Admissions: Reflectjons on 100,000
Admissions Decisions 1 Stanford, Stanford: Stanford University Press.

143

Fine, B. (1946). Admissions to Agnerican Colleges: A Study of Current Palicy
and Practice, New York: Harper and Brothers.

Fitzpatrick, James E. and Mowers, Mary (1997). Success and the Four Block
Schedule: Stakeholders Buy In! NASSP Bulletin. 81, No. 588, 51-56.

Fleming, Jacqueline and Garcia (1998), Nancy, Are Standardized Tests Fair to
African American Students?: Predictive Validity of the SAT in Black and
White Institutions, appmal of Higher E_ducation, 69, No. 5, 471-495.

Gardner, Clinton (1996), Research interviews conducted with University of
Wisconsin Admission Directors, April 17-19,1996.

Gordon, William M., Russo, Charles J., and Miles, Albert S. (1994) TheJLaw of
Home Schooling, Topeka, KS: National Organization On Legal Problems of
Education.

Goren, Arnold L. (1962). The Background of College Admissions, The Journal of
Educational Sociology, 35, No. 7.

Grossman,. D. A. (1935). Trends in Admissions to Higher Institutions, Bulletin of
t_he American Association of Collegiate Registrars and Admissions
Dfficers (AACRAQ). Washington , DC. 10, 251-261.

Guskey, Thomas R. (1994). Making the Grade: What Benefits Students?,
Educational Leadership, 52, No. 2, 14-20.

Hagedom, Linda and Nora, Amaury (1996). Rethinking Admissions Criteria in
Graduate and Professional Programs. In New Directions For Institutional
Research. Assessing Graduate and Professional Edgatjon: @rrent
Realitiea. Fpture Prospecta, edited by Haworth, Jennifer, Pages, 31-44,
San Francisco: Jossey-Bass.

Heamden, Arthur (1973). Eaihs to Dnivgsitv: Preparaflon. Aasessment.
Selection, London: MacMillan.

Helms, Janet (1992). Why is there no study of Cultural Equivalence in
Standardized Cognitive Ability Testing? finericaLn Psychologjat, 47, 1083-
1101.

Herbst, Jurgen (1974). The First Three American Colleges: Schools of the
Reformation. Perspectives in A_merican History, 8, 7-52.

Herbst, Jurgen (1975) The Eighteenth Century Origins of the Split Between

Private and Public Higher Education in the United States, Histogy of
Education Quarterly, 15, 273-280.

144

Huber, George (1980). Managerial Decision Maki_n_g. Dallas: Scott, Foresman
and Co.

Hu-DeHart, Evelyn (1997-1998). To Treat People Equally, We Must Treat Them
Differently. The College BoardLReview, Number 183, 24-31.

Jacobs, Walter (1991). The Traditional Role of the SAT in the 19903. The Journal
of College Admission. 131, 21-26.

Johnson, Andrew and Gentry, Marcia (2000). Admissions Portfolio for a
Graduate Program: Matching Practice and Paradigm. Roeper Review.
Volume 23, Number 2.

Jones, Terry (1998). Life After Proposition 209. Academe, 84, No. 4, 22-28.

Karabel, Jerome (1999). The Rise and Fall of Affirmative Action at the University
of California. The ngal of Blacks in Higher Education, 25, 109-112.

Kenney, Evelyn and Perry, Suzanne (1994). Talking with Parents About
Performance-Based Report Cards. Educational Leadership, 52, No. 2,
24-27.

Klicka, Christopher (1995). The Right to Home School. Durham, NC: Carolina
Academic Press.

Lyman, Howard (1998). Test Scores an_d What Thav Mead, Boston: Allyn and
Bacon.

Michigan State College, Catalogue Number for 1940-41. East Lansing: Michigan
State College, Volume 35, No. 2, March 1941.

Maeroff, Gene (1983). Sphool andfillege: Partgership in Education, Princeton:
Carnegie Foundation for the Advancement of Teaching.

Mazzeo, J., Schmitt, AP, and Bleistein, CA. (1993). Sex-Related Differences on
Constrgcted Resmnse and Multiple-Choice Sections of Advance
Placement Examinations, Report No. 92-7, New York: College Entrance
Examination Board.

Medina, Noe, and Neill, Monty (1990). Fallout Frgm Lhe Testing Explosion,
Cambridge: National Center for Fair and Open Testing.

Navarro, Susana (1984). The Quality Education Movement: New State
Standards and Minority Access to College. In Educational Standards
Testing and Access. Princeton: Educational Testing Service (ETS).

 

145

Needle, Stacy (1991). The cher Rodte into Colleg How Tp_Get into Collega
when You_Can’t [fipend on Yopr Grades or SATs. New York: Random
House.

Nettles, Arie and Nettles, Michael (1999). Measuring Up: Challenges Minoriti_e_s
Face in Educational Assessment, Boston: Kluwer Academic Publishers.

Newman, Frank (1984). Standards, Testing and Access in the Year 2001. In
Educational Standards, Testing and Access. Princeton: Educational
Testing Service (ETS).

Olson, Keith (1974), The GI. Bill.1he Veterans, and gm Collegaa, Lexington: the
University Press of Kentucky.

Orfield, Gary (1988). Campus Resegregation and Its Alternatives. In Chilling
Missions: The Affirmative AgionCnsis and the Search for Alternatives,
edited by Orfield, Gary and Miller, Edward, Cambridge, MA: Harvard
Education Publishing Group.

Pennock-Roman, Maria (1990). Test Validity and language Background. New
York: College Entrance Examination Board.

Potts, David B. (1971). American Colleges in the Nineteenth Century: From

Localism to Denominationalism. History of Education Quarterly, 11,
363-380.

Potts, David B. (1975). Students and the Social History of American Higher
Education. Histopg of Education Quarterly, 15, 317-327.

Potts, David B. (1977). College Enthusiasm: As Public Response, 1800-1860.
Harvard Educational Review. 47, 28-42.

Powell, Brian and Steelman, LaIa Carr (1996). Bewitched, Bothered and
Bewildering: The Use and Misuse of State SAT and ACT Scores. Harvard
Educational Review, 66, No.1, 27-59.

Proficiency-Based Admission Standards System: Pass Project (1996). Eugene:
Oregon State System of Higher Education, 1996.

Pusser, Brian (2001). The Contemporary of Access Policy: California after
Proposition 209. In The States anéd Public Higher Education Policy, edited
by Heller, Donald, Pages 121-152, Baltimore: The Johns Hopkins
University Press.

Reeves, Floyd W. and Russell, John D. (1933). Admission and Retention of
Dniversitv Stpdents, Chicago: University of Chicago Press.

146

Roderick, Gordon, and Stephens, Michael (1979). Higher Education For All?.
Sussex, England: The Falmer Press.

Ross, Earle D. (1942). A History of t_he Iowa State College, Ames: The Iowa
State College Press.

Rosser, Phyllis (1989a). Sex Bias in College Admissions Tests: Why Women
Lose Out, Cambridge: National Center for Fair and Open Testing.

Rosser, Phyllis (1989b). The SAT Gender GAP: Identfling the Causes,
Washington, DC: Center for Women Policy Studies.

Rudolph, Frederick (1990). The American College & University: A History.
Athens: University of Georgia Press.

Sandoval, Jonathan and Duran, Richard (1998). Language. In Education in Test
Interpretation and Diversity, edited by Sandoval, Jonathan, Frisby, Craig,
Geisinger, Kurt, Scheuneman, Janice Dowd and Grenier, Julia Ramos,
Pages 181 -21 1 , Washington, DC: American Psychological Association.

San Miguel, Guadalupe and Valencia, Richard (1998). From the Treaty of
Guadalupe Hidalgo to Hopwood: The Educational Plight and Struggle of
Mexican Americans in the Southwest. Harvard Educational Review, 68,
No. 3, 353-401.

Scheuneman, Janice Dowd (1987). An Experimental Exploratory Study of
Causes of Bias in Test Items. Journal of EducationaLMeaflrement. 24,
97-118.

Scheuneman, Janice Dowd and Oakland, Thomas (1998). High-Stakes Testing.
In Education in Education in Test Interpretation and Diversity, Edited by
Sandoval, Jonathan, Frisby, Craig, Geisinger, Kurt, Scheuneman, Janice
Dowd and Grenier, Julia Ramos, Pages 77-103, Washington, DC:
American Psychological Association.

 

Shavelson, Richard (1988). Statistical Reasoning for t_he Behavioral Sciences.
Boston: Allyn and Bacon.

Skrobarcek, Sharon A., Chang, Hsin Wen Maggie, Thompson, Christine,
Johnson, Julie, Atteberry, Robert, Westbrook, Robert, and Manus, Alice
(1997). Collaboration for Instructional Improvement: Analyzing the
Academic Impact of a Block Scheduling Plan, NASSP Bulletin, 81: No
589, 104-111.

147

Sperling, Doris (1994). Assessment and Reporting: A Natural Pair. Educational
Leadership, 52, No. 2,10-13.

Stadtmann, Verne (1970). The University of California 1868-1968. New York:
McGraw-Hill Book Co.

Stephens, Frank F. (1962). A Histprv of t_he t_Jnivarsitv of Missouri, Columbia:
University of Missouri Press.

Stewart, Donald (1993). Education, Race and Class: A New Calculus for the 21st
Century. Journal of Negro Education, 62, No. 2, 113-124.

 

Story, Ronald (1975a). Harvard and the Boston Brahmins: A Study in Institutional
and Class Development, 1800-1865. J_0L_Imal of Social History. 8, 94-121.

Story, Ronald (1975b). Harvard Students, the Boston Elite, and the New England

Preparatory System, 1800-1876. History of Education Quarterly, 15,
281-298.

Taylor, Orlando and Lee, Dorian (1987). Standardized Tests and African

Americans: Communication and Language Issues. Negro Educational
Review, 38, No. 2-3, 67-80.

Tewksbury, Donald G. (1965). The Founding of A_merican Colleges and
Universities, Columbia University, Doctoral Dissertation, 1932, Reprinted
New York: Archon Books.

Tompkins, Ellsworth and Gaumnitz, Walter H. (1954). The C_amegie ynits: Its
_O_rigin, Statpsy and Trends, Washington: US. Department of Health,
Education and Welfare, United States Government Printing Office, Bulletin
Number 7.

Trow, Martin (1981). Comparative Perspectives on Access. In Accass td Higher
Education. Oliver Fulton, Editor, England: The Society for Research in
Higher Education, 1981.

United States Department of Education, National Center for Education Statistics,
1999.

Weiger, Pamela (2000). As Latino Populations Grow: So Does Their Power,
Slack Issues in Higher Education, 17, No. 16, 20-23.

Wechsler, Harold S. (1977). The gpalified Stpdent: A History of Selectiya
College Achission In A_merica, New York: John Wiley and Sons.

148

Whitehead, John W. and Bird, Wendell R. (1987). Home Education and
Constitutional Libertfi, The Rutherford Institute Report: Volume 2,
Westchester, II.: Crossway Books.

Willie, Charles (1985). The Problem of Standardized Testing in a Free and
Pluralistic Society, Phi Delta Kappan, 66, No. 9, 626-628.

Wiggins, Grant (1994). Toward Better Report Cards. Educational Leadership, 52,
No. 2, 28-37.

Willingham, Warren, Lewis, Charles, Morgan, Rick and Ramist, Leonard (1990).
Predicting College Gra_des: An Analysis of Institutional Trends Over Two
Decades. Princeton: Educational Testing Service.

Yoon, K. Paul, and Hwang, Ching-Lai (1995). Multiple Attribute Decision Making,
Thousand Oaks, CA: Sage Publication.

Wisconsin Executive Order

Wisconsin Executive Order Number 326 (1998), Wisconsin Statutes 118.30
(1)(b), January 13, 1998.

CONGRESSIONAL ACTS
Land Grant Act of 1862 (1862 Morrill Act), U. S. Statutes At Large 7, 301-308.

Land Grant Act of 1890 (1890 Morrill Act), U. S. Statutes At Large 7, 323.

149

       
     
     

IIIIIIII

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

. 3 1293 02334