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The impact of diversity courses on students' critical thinking skills

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The impact of diversity courses on students' critical thinking skills

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Content THE IMPACT OF DIVERSITY COURSES ON STUDENTS’
CRITICAL THINKING SKILLS

by

Mark Adrian Pearson

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2012

Copyright 2012 Mark Adrian Pearson
ii
DEDICATION
This work is dedicated to the Pearson Family. To my grandparents, Mina and
William Pearson, who were educators that helped shape the future of education in the
Caribbean. To my mother and father, Alma and Erle Pearson, who were my first teachers
and sacrificed to provide their children with world class education. To my brother and
sister, Andrew Pearson and Arlene Patti, who lead the way in educational attainment,
professional success and family achievement. Finally, to my own family, my wife and
first born son, Sarah and Mason Pearson, who provide support and motivation. I love all
of you beyond words. This is dedicated to you.

iii
ACKNOWLEDGEMENTS
I thank God for being a constant positive guiding force in my life and leading me
to and through this process. God has carried me through trying times and joyous
occasions alike. God has blessed me with ambition and ability that continues to drive me
forward… thank you God.
To my mother and father, you are two of the best people, in life and certainly the
best parents. I cannot think of a bad decision that you have made for me or any of your
children. Your focus as parents is flawless. I aspire to have children as wonderful as
Andrew and Arlene and a family that is loving as ours. I understand the personal
sacrifices that you have lovingly and selflessly provided for me and all of your children,
especially in the area of education. Your support can always be relied upon. I am truly the
luckiest son to have you as parents.
To my wife Sarah. From when I first met you, there was something special about
you; I still think so today. You continue to evolve in wonderful ways. As a wife, you are
supportive and helpful. As a mother, you are kind and loving. As a friend, you are quick
witted and fun. I love spending time with you. We have a bright future ahead of us. I
thank you for starting a family with me and I look forward to growing old with you.
To my first son, Mason Andres Pearson, thank you for being the wonderful little
boy, well, maybe not so little boy that you are. You make me the happiest father with
every breathe you breathe. You are motivation in this process and in life. I know that you
are going to be a wonderful big brother to your siblings, who are not even here yet. You
light up a room with your smile and personality and I know you are going to grow up to
be one of the greatest men ever.
iv
To my main man, Kevin Bolen, what can I say? You have truly gone over and
beyond as a friend, a colleague, a classmate, a dissertation partner, etc. I literally would
not be completing this dissertation without you. From the nights hammering out syntax
on SPSS to delirium and megagigabytes son, you have been there to help out. I seriously
owe you one, thank you!
To my good friend and colleague, KC Mmeje, you’ve always been a consummate
professional and a good friend. Yard House, LA Live, Fall 2011, we vowed to keep each
other accountable. Although I really didn’t do much on that front, I have to thank you for
keeping up your part of our commitment. Your advice, recommendations and motivation
helped me knock this dissertation out.
To my life coach, Melissa Gaeke, you came along late in my dissertation process,
but early in my professional life. Thank you for playing a major role in helping me
remain focused and accountable to my goal of completing this dissertation and I look
forward to working with you in achieving some lofty goals, over the coming decades.
To Sumi, Sonja, Karen, Keri, Emily, Stephen, Matt, Kate, Anne, Anna Lisa and
Veronica, I know some of us are done and some of us will be done very soon. It has been
a pleasure working with you; studying alongside you; presenting with you and having a
cold one in between. Thank you for the camaraderie and friendship, I will always be here
for support and some more good times.
To Denzil, Frank and Shalamon, my BIG brothers, thank you for providing
friendship, advice, and a blue print for success. We’ve all come a long way from the first
time out on the links, at Arroyo. I’m proud of the professional advancement we have all
v
made, over the past years. I look forward to us getting together, as Doctors, consistently
and often.
Last, and most importantly, with regards to this process, to my Committee, Dr.
Tobey, Dr. Sundt and Dr. Cole, I thank each of you for your patience in my dissertation
process. Dr. Tobey- From working with you in the Assessment Committee to serving on
my dissertation committee, you have been a valuable resource for methodological advice
and motivation to complete my chapters – thank you! Dr. Sundt – Your recommendations
on my research proposal were integral to my research design and eventual success in
determining findings in my study – Thank you! Dr. Cole – You have been central to my
entire doctoral program. You offered me an opportunity to serve you as a research
assistant. You awarded me with a fellowship. You served me as a professor in the
program. You gave me a focus for my initial studies in higher education. You are my
mentor, my friend and my brother; that’s Phi Nu Pi-Thank you!
vi
TABLE OF CONTENTS
DEDICATION ................................................................................................................. ii

ACKNOWLEDGEMENTS ............................................................................................ iii

LIST OF TABLES ......................................................................................................... xii

LIST OF FIGURES ........................................................................................................xv

ABSTRACT .................................................................................................................. xvi

CHAPTER 1 Introduction.................................................................................................1
Introduction ...................................................................................................................1
Background ...................................................................................................................1
Statement of the Problem ..............................................................................................4
Purpose ..........................................................................................................................5
Delimitations and Limitations.......................................................................................5
Research Questions .......................................................................................................6
Conceptual Postulate .....................................................................................................6
Local Importance and Universal Relevance .................................................................7
Definitions of Terms .....................................................................................................8
Organization of the Study .............................................................................................9

CHAPTER 2 Review of Literature .................................................................................12
Introduction .................................................................................................................12
Student Development Theory .....................................................................................13
Cognitive Development Theory ..................................................................................15
Critical Thinking in Higher Education ...................................................................16
As an aspect of cognition, critical thinking is a complex notion with various
dimensions. .................................................................................................................16
Diversity in Higher Education ....................................................................................18
Diversity Courses in Higher Education ......................................................................20
Theoretical Framework ...............................................................................................21

vii
CHAPTER 3 Methodology .............................................................................................26
Overview .....................................................................................................................26
Research Methodology ...............................................................................................26
Research Questions .....................................................................................................27
Selection of Sample and Population .......................................................................28
Instrumentation and Selection of Surveys ..................................................................29
Conceptual Framework ...............................................................................................30
Data Collection ...........................................................................................................37
Data Analysis ..............................................................................................................37
Recoding and Computing New Variables ...................................................................38
Composite Variables ...................................................................................................39
Diversity Course Variables and Descriptive Statistics ...............................................39
Factor Analysis ...........................................................................................................40
Reliability Tests ..........................................................................................................40
Reliability and Validity ...............................................................................................40
Regression Analysis ....................................................................................................41
Summary .....................................................................................................................41

viii
CHAPTER 4 Analysis of the Data ..................................................................................42
Introduction .................................................................................................................42
Data Set Externalities ..................................................................................................43
The Data Set Composition ......................................................................................43
Participant Characteristics – Race ..........................................................................43
Participant Characteristics – Gender & Race ..........................................................43
Participant Characteristics – Majors .......................................................................44
Parental Education – White vs. Non-White ............................................................44
Data Set Characteristics – Summary ...........................................................................44
Environmental Categories & Variables ......................................................................45
Diversity Courses ........................................................................................................47
Diversity Experiences .................................................................................................51
Factor Analyses and Reliabilities for Variables ..........................................................53
Factor Analysis – Input Variable Analyticity (CIRP) .............................................54
Reliability – Input Variable Analyticity (CIRP) .....................................................55
Factor Analysis – Output Variable Analyticity (WUSS) ........................................56
Reliability – Output Variable Analyticity (WUSS) ................................................57
Factor Analysis – Input Variable Truth Seeking (CIRP) ........................................58
Reliability – Input Variable Truth Seeking (CIRP) ................................................59
Factor Analysis – Output Variable Truth Seeking (WUSS) ...................................60
Reliability – Output Variable Truth Seeking (WUSS) ...........................................61
Factor Analysis – Input Variable Judgment (CIRP) ...............................................62
Reliability – Input Variable Judgment (CIRP) .......................................................63
Factor Analysis – Output Variable Judgment (WUSS) ..........................................64
Reliability – Output Variable Judgment (WUSS) ..................................................65
Factor Analysis– Input Variable Inquisitiveness (CIRP) ........................................66
Reliability – Input Variable Inquisitiveness (CIRP) ...............................................67
Factor Analysis & Reliability– Output Variable Inquisitiveness (WUSS) .............68
Factor Analysis– Input Variable Open-mindedness (CIRP) ...................................69
Reliability – Input Variable Open-mindedness (CIRP) ..........................................69
Factor Analysis & Reliability– Output Variable Open-mindedness (WUSS) ........70
Factor Analysis– Input Variable Self-Confidence (CIRP) .....................................70
Reliability – Input Variable Self-Confidence (CIRP) .............................................71
Factor Analysis & Reliability– Output Variable Self-Confidence (WUSS) ..........72
Factor Analysis– Input Variable Systematicity (CIRP) ..........................................73
Reliability – Input Variable Systematicity (CIRP) .................................................73
Factor Analysis & Reliability– Output Variable Systematicity (WUSS) ...............74
Input & Output Variable – Metta Critical Thinking Variable ....................................75
Linear Regression Analysis ........................................................................................75
Regression A – Analyticity and Number of Diversity Courses Taken .......................76
Participant Characteristics ......................................................................................78
Majors .....................................................................................................................78
Diversity Experiences .............................................................................................78
Number of Diversity Courses Taken ......................................................................79
Analyticity Proxy – Influence Social Values ..........................................................79
Regression B – Analyticity and Diversity Course Typology......................................79
ix
Participant Characteristics ......................................................................................81
Majors .....................................................................................................................81
Diversity Experiences .............................................................................................81
Diversity Course Typology Level ...........................................................................82
Analyticity Proxy – Influence Social Values ..........................................................82
Analyticity, Diversity Courses Taken and Diversity Course Typology Level .......82
Regression A – Inquisitiveness and Number of Diversity Courses Taken .................83
Participant Characteristics ......................................................................................85
Majors .....................................................................................................................85
Diversity Experiences .............................................................................................85
Number of Diversity Courses Taken ......................................................................86
Inquisitiveness Proxy – Talking With Teachers Outside of Class ..........................86
Regression B – Inquisitiveness and Diversity Course Typology................................86
Participant Characteristics ......................................................................................88
Majors .....................................................................................................................88
Diversity Experiences .............................................................................................88
Diversity Course Typology Level ...........................................................................89
Inquisitiveness Proxy –Talking With Teachers Outside of Class ...........................89
Inquisitiveness, Diversity Courses Taken and Diversity Course Typology Level .89
Regression A – Judgment and Number of Diversity Courses Taken .........................90
Participant Characteristics ......................................................................................92
Majors .....................................................................................................................92
Diversity Experiences .............................................................................................92
Number of Diversity Courses Taken ......................................................................92
Judgment Proxy – Overwhelmed with the Amount of Things to Do .....................93
Regression B – Judgment and Diversity Course Typology ........................................93
Participant Characteristics ......................................................................................95
Majors .....................................................................................................................95
Diversity Experiences .............................................................................................95
Diversity Course Typology Level ...........................................................................95
Judgment Proxy – Overwhelmed with the Amount of Things to Do .....................96
Judgment, Diversity Courses Taken and Diversity Course Typology Level ..............96
Regression A – Open-mindedness and Number of Diversity Courses Taken ............97
Participant Characteristics ......................................................................................99
Majors .....................................................................................................................99
Diversity Experiences .............................................................................................99
Number of Diversity Courses Taken ....................................................................100
Open-mindedness Proxy – Socialize with Different Ethnic Groups ....................100
Regression B – Open-mindedness and Diversity Course Typology .........................100
Participant Characteristics ....................................................................................102
Majors ...................................................................................................................102
Diversity Experiences ...........................................................................................102
Diversity Course Typology Level .........................................................................103
Open-mindedness Proxy –Socialize with Different Ethnic Groups .....................103
Open-mindedness, Diversity Courses Taken and Diversity Course Typology Level
...............................................................................................................................103
x
Regression A – Self-confidence and Number of Diversity Courses Taken ..............104
Participant Characteristics ....................................................................................105
Majors ...................................................................................................................106
Diversity Experiences ...........................................................................................106
Number of Diversity Courses Taken ....................................................................106
Self-confidence Proxy – Intellectual Self-confidence ..........................................106
Regression B – Self-confidence and Diversity Course Typology ............................107
Participant Characteristics ....................................................................................108
Majors ...................................................................................................................109
Diversity Experiences ...........................................................................................109
Diversity Course Typology Level .........................................................................110
Self-confidence Proxy – Intellectual Self-confidence ..........................................110
Self-confidence, Diversity Courses Taken and Diversity Course Typology Level110
Regression A – Systematicity and Number of Diversity Courses Taken .................111
Participant Characteristics ....................................................................................113
Majors ...................................................................................................................113
Diversity Experiences ...........................................................................................113
Number of Diversity Courses Taken ....................................................................113
Systematicity Proxy – Mathematical Ability ........................................................114
Regression B – Systematicity and Diversity Course Typology ................................114
Participant Characteristics ....................................................................................116
Majors ...................................................................................................................116
Diversity Experiences ...........................................................................................116
Diversity Course Typology Level .........................................................................117
Systematicity Proxy – Mathematical Ability ........................................................117
Systematicity, Diversity Courses Taken and Diversity Course Typology Level .117
Regression A – Truth- seeking and Number of Diversity Courses Taken ...............118
Participant Characteristics ....................................................................................120
Majors ...................................................................................................................120
Diversity Experiences ...........................................................................................120
Number of Diversity Courses Taken ....................................................................121
Truth-seeking Proxy – Promote Racial Understanding ........................................121
Regression B – Truth-seeking and Diversity Course Typology ...............................121
Participant Characteristics ....................................................................................123
Majors ...................................................................................................................123
Diversity Experiences ...........................................................................................123
Diversity Course Typology Level .........................................................................124
Truth-seeking Proxy – Promote Racial Understanding ........................................124
Truth-seeking, Diversity Courses Taken and Diversity Course Typology Level .124

xi
CHAPTER 5 Findings, Implications, Recommendations, Limitations & Conclusion .126
Introduction ...............................................................................................................126
Critical Thinking Variables & Explanatory Variables ..........................................127
Analyticity and Number of Diversity Courses Taken ...........................................128
Analyticity and Diversity Course Typology .........................................................129
Inquisitiveness and Number of Diversity Courses Taken .....................................129
Inquisitiveness and Diversity Course Typology ...................................................130
Judgment and Number of Diversity Courses Taken .............................................130
Judgment and Diversity Course Typology ...........................................................131
Open-mindedness and Number of Diversity Courses Taken ................................132
Open-mindedness and Diversity Course Typology ..............................................132
Self-confidence and Number of Diversity Courses Taken ...................................133
Self-confidence and Number of Diversity Course Typology ...............................133
Systematicity and Number of Diversity Courses Taken .......................................134
Systematicity and Diversity Course Typology .....................................................135
Truth-seeking and Number of Diversity Courses Taken ......................................135
Truth-seeking and Diversity Course Typology.....................................................136
Major Findings ..........................................................................................................137
Implications...............................................................................................................137
Policy & Curriculum .............................................................................................137
Budget ...................................................................................................................138
Recommendations .....................................................................................................139
Student Cognitive Development Study .................................................................139
Other Areas for Institutional Improvement ...............................................................140
Limitations ................................................................................................................140
Future Research ........................................................................................................143
Conclusion ................................................................................................................145

REFERENCES .............................................................................................................146

APPENDICES ..............................................................................................................153
Appendix A: Diversity Course Requirement Guidelines
(Revised 04/22/09) .................................................................................................151
Appendix B: Diversity Committee Course Review Sheet ........................................154
Appendix C: Committee on Diversity Requirement Courses (DRC) .......................155
Appendix D: Typology of Diversity Courses (Cole & Sundt, 2008) .......................156
Appendix E: Western University’s Freshman Profile and Admission
Information (2004-2005) ..........................................................................................157
Appendix F: Role and Mission of Western University .............................................158
Appendix G: 2004 Cooperative Institutional Research Program (CIRP)
Instrument .................................................................................................................159
Appendix H: 2008 Western University Senior Survey (WUSS) Instrument ............163
Appendix I:: Diversity Courses offered at Western University (2004-2008) ...........182
Appendix J: Diversity Course Syllabus Rating Rubric .............................................188
Appenix K: Notes Regarding Diversity Course Syllabi ...........................................189

xii
LIST OF TABLES
Table 3.1 CIRP Characteristic Independent Variables 34

Table 3.3 Transcript Data Independent Variables 36

Table 4.1 Descriptive Data - Student Participants 46

Table 4.2 Frequency - Number of Diversity Courses Taken by Students 48

Table 4.3 Frequency - Enrollment Year the First Diversity Course Was Taken 49

Table 4.4 Number - Diversity Courses Taken Per Year and Diversity Courses
Typology 50

Table 4.5 Frequency - Typology Level of First Diversity Course Taken 51

Table 4.6 Frequency - Diversity Experiences Racial and Cultural Awareness
Workshops 52

Table 4.7 Frequency - Diversity Experiences Community Service 53

Table 4.8 Factor Analysis – Input Variable Analyticity (CIRP) 55

Table 4.9 Reliability – Input Variable Analyticity (CIRP) 56

Table 4.10 Factor Analysis – Input Variable Analyticity (WUSS) 57

Table 4.11 Reliability – Input Variable Analyticity (WUSS) 58

Table 4.12 Factor Analysis – Input Variable Truth Seeking (CIRP) 59

Table 4.13 Reliability – Input Variable Truth Seeking (CIRP) 60

Table 4.14 Factor Analysis – Input Variable Truth Seeking (WUSS) 61

Table 4.15 Reliability – Input Variable Truth Seeking (WUSS) 62

Table 4.16 Factor Analysis – Input Variable Judgment (CIRP) 63

Table 4.17 Reliability – Input Variable Judgment (CIRP) 64

Table 4.18 Factor Analysis – Input Variable Judgment (WUSS) 65

Table 4.19 Reliability – Input Variable Judgment (WUSS) 66

xiii
Table 4.20 Factor Analysis – Input Variable Inquisitiveness (CIRP) 67

Table 4.21 Reliability – Input Variable Analyticity (CIRP) 68

Table 4.22 Factor Analysis – Input Variable Open-mindedness (CIRP) 69

Table 4.23 Reliability – Input Variable Open-mindedness (CIRP) 70

Table 4.24 Factor Analysis – Input Variable Self-Confidence (CIRP) 71

Table 4.25 Reliability – Input Variable Self-Confidence (CIRP) 72

Table 4.26 Factor Analysis – Input Variable Systematicity (CIRP) 73

Table 4.27 Reliability – Input Variable Systematicity (CIRP) 74

Table 4.28 Regression Coefficients for Analyticity and Number of Diversity Courses
Taken 77

Table 4.29 Regression Coefficients for Analyticity and Diversity Course
Typology Level 80

Table 4.30 Regression Coefficients for Inquisitiveness and Number of Diversity
Courses Taken 84

Table 4.31 Regression Coefficients for Inquisitiveness and Diversity Course
Typology Level 87

Table 4.32 Regression Coefficients for Judgment and Number of Diversity Courses
Taken 91

Table 4.33 Regression Coefficients for Judgment and Diversity Course Typology
Level 94

Table 4.34 Regression Coefficients for Open-mindedness and Number of Diversity
Courses Taken 98

Table 4.35 Regression Coefficients for Open-mindedness and Diversity Course
Typology Level 101

Table 4.36 Regression Coefficients for Self-confidence and Number of Diversity
Courses Taken 105

Table 4.37 Regression Coefficients for Self-confidence and Diversity Course T
ypology Level 108
xiv
Table 4.38 Regression Coefficients for Systematicity and Number of Diversity
Courses Taken 112

Table 4.39 Regression Coefficients for Systematicity and Diversity Course
Typology Level 115

Table 4.40 Regression Coefficients for Truth-seeking and Number of Diversity
Courses Taken 119

Table 4.41 Regression Coefficients for Truth-seeking and Diversity Course
Typology Level 122

Table 5.1 Research Questions & Significant Findings Matrix 127

xv
LIST OF FIGURES
Figure 3.1 (Input – Environment – Output) Model for Critical Thinking & Number of
Diversity Courses Taken 32

Table 3.2 WUSS Independent Variables 35

xvi
ABSTRACT
This study examines the impact of diversity courses on 553 students’ critical
thinking skills. The study was conducted at a large, highly selective, private, tier one
research institution and analyzes a pre-college survey, post-college survey through
quantitative methodology, such as factor analyses, reliabilities and multiple regressions.
The findings suggest that the number of diversity courses taken statistically and
positively affect students’ critical thinking skills: (1) Analyticity (β = .242, p < .001); (2)
Inquisitiveness (β = .225, p < .001); (3) Open-mindedness (β = .100, p < .05); (4) Truth-
seeking (β = .255, p < .001). Participation in racial awareness workshops also statistically
and positively affect students’ critical thinking skills (1) Analyticity (β = .087, p < .05);
(2) Inquisitiveness (β = .119, p < .01); (3) Self-confidence (β = .090, p < .05); (4) Truth-
seeking (β = .168, p < .001). These findings strengthen the literature that suggests
diversity courses as well as other diversity experiences statistically and positively affect
students’ cognitive development.
1
CHAPTER 1
Introduction
Introduction
As indicated by Chang (2002), diversity courses are an understudied area within
higher education literature, and the degree by which diversity courses have an impact on
students’ critical thinking skills is a gap yet to be addressed. This study contributes to the
body of literature examining diversity courses in higher education and explores the
relationship between diversity courses and students’ critical thinking skills.
This chapter provides an introduction to diversity courses and students’ critical
thinking skills. To this end, this section provides a background of the problem as well as
educational trends and the societal context that relate to the problem. Additionally, this
chapter provides areas that outline scope; the statement of the problem, a goal oriented
purpose as well as delimitations and limitations of the study. Furthermore, this chapter
offers the leading questions of the study and the overarching assumptions that serve as
the underpinnings of the study. The chapter also presents the precursor of the
methodology in the statement of the hypotheses as well as explains the relevance of the
study on both a local and national level. This chapter will also assign definitions to
keywords to establish a common understanding of the terminology in the study. Lastly,
this chapter will outline the entire study to include descriptions of the subsequent
chapters: Literature Review (Chapter 2) and the Methodology (Chapter 3).
Background
In response to the race relations issues associated with the 1992 civil unrest in Los
Angeles and many other metropolitan cities within the United States, American higher
2
education institutions took on the social responsibility of engaging and framing an
understanding of the issues that caused the riots. Lawrence Levine (1996) asserted the
need for an evolution of a more divergent, liberal, culturally diverse curriculum relevant
to the times. This type of open-mindedness toward curriculum was a change from the
previous pedagogical strategies that prevailed in higher education. Typical general
education curriculums differed very little from campus to campus. These curriculums
were intended to indoctrinate students into an institution and provide a common liberal
study foundation for students to launch from both academically and socially. While the
academic rigor and foundational outcomes were not challenged, the learning outcomes
associated with student’s social worldviews was. To this end, higher education
institutions began to expand their general education curriculum requirements to include a
multicultural and or diversity requirement (La Belle & Ward, 1996). These requirements
include the knowledge base related to the concepts of human diversity and the
complexities multiculturalism within general education (Musil et al, 1999).
In an effort to better understand this process of curriculum reform, researchers
such as Christine Bennett (1999) constructed and proposed models of engaging change in
curriculum to include diversity. Bennett’s framework is a design for multicultural
education reform not limited to higher education but includes the education continuum
from pre-school through higher education. Bennett’s model is a six stage model to engage
diversity in curriculum reform: (1) Understanding Multiple Historical Perspectives; (2)
Developing Cultural Consciousness; (3) Developing Intercultural Competence; (4)
Combating Racism, Sexism, Prejudice and Discrimination; (5) Raising Awareness of the
State of the Planet and Global Dynamics; and (6) Developing Social Action Skills (1999)
3
to each of these stages (or cluster, depending on year of model). Bennett provides action
plans on how to achieve the overarching theme that guides each phase.
Frameworks like Bennett’s (1999) provide a useful lens to frame diversity
changes and how they apply to curriculum reform. In this regard, higher education
institutions began to think explicitly about how to operationalize a diversity requirement
as part of their institution’s general education requirements. To this end, institutions
devised specific missions for diversity courses or intended student learning outcomes.
Generally, the intended purpose of diversity courses, either implicit or explicit, is to
develop students (Chang, 2002). This type of development, as proposed through intended
student learning outcomes generally includes analytical reasoning as well as and
reflective and critical thinking (Sleeter & Grant, 1994). Additionally, these courses are
intend to challenge students to think about their assumptions concerning divergent issues
to that of their own as well as question social constructs (Sleeter & Grant, 1994).
Most institutions had varied ways of implementing their diversity course
requirements (Sleeter & Grant, 1994). This implementation is typically seen in the form
of a categorical mandate; students need to take a diversity course as well as other courses
such as science or math to fulfill their categorical mandate. Although diversity course
requirements vary institutionally, most requirements address myriad diversity topics in
American society including race, ethnicity, class, gender, sexual orientation, and physical
disabilities (Sleeter & Grant, 1994). These courses typically focus on the diversity that
composes humankind. The aforementioned curricular strategy assumes that, by
developing students to think more critically about one’s significant differences in society,
they will start thinking about other differences (Chang 2002). This philosophy predicates
4
itself on the notion that, by enhancing student’s ability to think critically about
differences, he or she will be able to appreciate cultural, racial and ethnic pluralism, to
question social constructs; to analyze inequalities manifested through race, ethnicity,
class, gender, sexual orientation, or physical disabilities (Chang, 2002). To what extent a
diversity course requirement achieves this is in question and has not received much
empirical attention (Chang, 2002).
Statement of the Problem
Chang’s quandary (2002) is the central issue addressed in this study. The problem
is diversity courses are an understudied area of student development in higher education.
The current higher education environment emphasizes assessment; diversity courses as a
part of general education requirements need to be evaluated in order to determine the
impact on student learning, specifically critical thinking skills.
As compared to other areas of student learning, the impacts of diversity courses
have been studied minimally. However, the need to study the impact of diversity courses
is great. In the current environment, of contracting budgets, it would behoove higher
education institutions to evaluate the impact of diversity courses, if solely for the purpose
of budgetary alignment with institutional diversity outcomes. To this end, diversity plays
a fundamental role.
Moreover, critical thinking is a skill set that is to be developed in general
education courses and by the higher education environment, as a whole. The degree by
which diversity courses influence students’ critical thinking skills is integral in
understanding the impact diversity in students’ cognitive development. Additionally, the
5
study analyzes diversity courses and co-curricular diversity opportunities to better
understand how diversity influence student learning.
Purpose
The purpose of this study was to examine the impact of diversity courses on
students’ critical thinking skills. Subordinately, the study investigates how specific
diversity courses relate to students critical thinking outcomes. Hurtado (1999) and Chang
(2002) are central to the literature on diversity courses and the majority of their respective
work has been on democratic values, prejudice reduction and higher order thinking skills.
This study contributes the necessary foundation for a better understanding of how
students’ critical thinking skills are influenced by diversity courses. As Hurtado (1999)
demonstrated the value of diversity on student’s democratic values and Chang established
the significance of diversity courses on race and prejudice reeducation (2002), this notion
is central to the goals of this study. Alongside the primary goal, the study establishes the
importance critical thinking as an impact of diversity courses. Additionally, this study
creates the groundwork for additional studies on critical thinking and diversity courses.
Last, the study provides generalizable findings that can be applied to other institutions.
Delimitations and Limitations
The aspects that are beyond the control of this study include the student
population of and the general education diversity course requirement at Western
University. Moreover, there are a number of features at Western University germane to
the university that cannot be replicated or compared to that of other institutions, such as
the diversity course requirement. The number of students who participated in both the
first year CIRP survey and the institutional, Senior Survey is not as large as anticipated.
6
The size of the population for this study is 550 students (n=550). Accordingly, this limits
the amount of variables that can be appropriately evaluated in the study. Additionally, the
questions posed in both surveys are not in the loci of control of the researcher. The scope
of the study is the impact of diversity courses on the 550 students at Western University
using data from 2004 CIRP as a pre-test and 2008 Senior Survey data as a post-test.
There are a tremendous amount of experiences, engagements and interactions that lead to
students’ critical thinking outcomes, and one of the challenges is determining to what
degree a diversity course affects critical thinking skills.
Research Questions
To ensure that the purposes of this study are addressed, the research questions
include:
Do diversity courses impact students’ critical thinking skills?
Do student characteristic input variables impact students’ critical thinking
dimensions?
To what extent does the number of diversity courses taken impact students’
critical thinking dimensions?
To what extent does the typology of diversity courses impact students’ critical
thinking dimensions?
To what extent do diversity experiences impact students’ critical thinking
dimensions?
Conceptual Postulate
There are major assumptions that are essential tenants of this study. From an
overarching perspective, it must be understood that diversity courses are a worthy area of
7
academic inquiry. This assumption has been addressed by authors such as Hurtado,
Chang and Cole (1999, 2002, Forthcoming) in their respective works; this is also be
outlined in further detail in the forthcoming literature review. Another assumption is
there is a significant relationship between diversity courses and critical thinking. Also,
the type of information collected demonstrates that there is a relationship between
diversity courses and critical thinking. The application of the theoretical framework
demonstrates a relationship between diversity courses and critical thinking. Moreover, all
of the variables and instruments used to collect data are reliable and produces statistically
significant and theoretically noteworthy information. Last, the findings of the study are
relevant to the local area studied, but are also generally applied.
Local Importance and Universal Relevance
The logic for assessing diversity courses begins with placing empirical scrutiny
toward diversity courses and evaluating the impact of diversity courses on undergraduate
students at Western University.
Locally, The College, the School of Letters, Arts and Sciences, at Western
University, provide the general education curriculum mandate for undergraduate
students. Undergraduates have to satisfy many general education requirements; one of
these requirements is a diversity course requirement. The University’s Catalogue (2007)
states that through fulfilling the diversity course requirement, “students will gain
exposure to analytical frameworks within which these issues are to be understood and
addressed, including social, political, cultural ethical and public policy analyses. It is the
University’s goal to prepare students through the study of human differences for
responsible citizenship in an increasingly pluralistic and diverse society.” This statement,
8
like many institutional statements about diversity courses, details that student will be
equipped to address complex issues that arise from the human condition through gaining
knowledge from a multitude of analytical perspectives, in order to prepare students for
responsible citizenship.
To meet the end of responsible citizenship, Western University emphasizes the
importance of student learning through diversity courses, by stating that the diversity
requirement is intended to provide undergraduate students with knowledge and analytical
skills to enable them to understand and respect distinctions between groups of people and
to comprehend the potential resources and/or conflicts arising from human differences on
the contemporary American and international scene. (University Catalogue, 2007) While
it may be useful to learn how diversity courses reduce various prejudices, the core of this
study is to research the underpinnings of diversity courses and relate them to students’
outcomes, to determine the impact on students’ critical thinking skills. In turn, the
findings from this study will help Western University determine to what extent diversity
courses achieve the student learning outcomes associated with critical thinking.
As Mitchell Chang (2002) stated, diversity course requirements have not received
much empirical attention; it is the purpose of this study to address this gap in research
and contribute to the deficits in diversity course literature.
Definitions of Terms
Critical Thinking: Akin to analytical reasoning, critical thinking is a type of higher order
thinking skill that requires applied thought. The type of thought where
and individual juxtaposes a myriad of issues and concepts toward
understanding a particular issue or set of. There are seven different
9
dimensions to critical thinking: (1) analyticity; (2) truth-seeking; (3)
inquisitiveness; (4) judgment; (5) open-mindedness; (6) self
confidence and (7) systematicity.
Diversity Courses: Courses with an emphasis on historical issues of oppressed groups or
contemporary issues analyze inequalities manifested through race,
ethnicity, class, gender, sexual orientation, or physical disabilities.
Diversity Typology: Categorization of diversity and social issues courses into a four
level rubric of the degree by which specific courses meets the
university’s diversity requirements.
Epistemological Belief:An individual’s learned and/or embedded values that comes from
one’s nature of knowledge and understanding
Ethnicity: Identity established from separate from racial, national or
cultural groups with linkages to community traditions, language or
beliefs.
Race: Social construct based on the identity on a pseudo anthropological classification of
identity. U.S. based classifications of White, American Indian or
Alaska Native, Asian, Black or African American, Hispanic or Latino,
Native Hawaiian or Other Pacific Islander (Office of Management and
Budget, 2009)
Organization of the Study
The remainder of the study is divided into four additional chapters. The next
chapter discusses the literature review. That chapter focuses on the body of knowledge
that gives rise to this study. To this end, chapter two commences with the historical
10
background of diversity courses as well as critical thinking in higher education. Next, the
chapter details the existing studies that create the body of knowledge of diversity courses
and students’ critical thinking skills. The literature review also analyzes the
methodologies of the studies and details the links between key research variables in
previous studies and outline what is researched in this study. Chapter two also details the
historical background of analytical framework that serves as the structure of the study’s
methodological procedures.
Chapter three is the basis of the study and it describes the methodology of the
study. This chapter begins with a description of the research protocol and the list the
leading questions of the study. This chapter also highlights the seminal studies that have
influenced the focus of this study. The chapter offers a comprehensive description of the
theoretical framework. Chapter three also describes the selection of surveys and the
development of instruments. Chapter three also explains the data collection and analysis
procedures. Last, this chapter presents the limitations of the study.
Chapter four focuses on the input variable descriptors of the data set, Western
University, participant characteristics, parental education, juxtaposition of participants
and declared majors. The second section, of this chapter, details the frequency of the
environmental variables, the number of diversity courses taken, the year the first diversity
course was taken, the level of intensity, represented in a typology, of the students’ first
diversity course, and institutional diversity experiences (workshops and community
service). The third section, of this chapter, provides factor analysis data for the
construction of eight composite critical thinking variable types in both the CIRP and the
WUSS; the variable types are analyticity, truth-seeking, inquisitiveness, judgment, open-
11
mindedness, self confidence, systematicity and a composite variable including all the
aforementioned critical thinking variable types. The final section, of this chapter,
provides regression analyses results based on proxy variables for the critical thinking
variable types.
Chapter five is the final chapter of this study and commences by answering the
primary research question, how do diversity courses impact students’ critical thinking
skills. This chapter also addresses the four subordinate research questions: (1) do student
characteristic input variables impact students’ critical thinking dimensions (2) to what
extent does the number of diversity courses taken impact students’ critical thinking
dimensions? (3) to what extent does the typology of diversity courses impact students’
critical thinking dimensions? (4) to what extent do diversity experiences impact students’
critical thinking dimensions? The results from these questions offer environmental
findings, implication and limitations to this study. Finally, this chapter culminates with a
comprehensive conclusion that outlines areas for future research.

12
CHAPTER 2
Review of Literature
Introduction
This study examines the impact of diversity courses on students’ critical thinking
skills at a large, highly selective, private, tier one research university. The prior chapter
provided a basic introduction and historical overview of diversity courses and students’
critical thinking skills. The chapter delineated the central problem of the study, which is
diversity courses are an understudied area of student development. This problem was linked
to educational trends and the societal context that relate to the problem. Additionally, the
chapter outlined the scope of the study and offered a leading question as well as the
overarching assumptions of the study. The chapter also explained the relevance of the study
on both a local and national level. Last, the chapter assigned definitions to keywords to
establish a common understanding of the terminology in this study.
Again, the previously-mentioned assertion by Mitchell Chang (2002) that diversity
courses and diversity course requirements are an understudied area within higher education
serves as a propelling force for this study. As it is understood that diversity courses are
essential aspects of most general education requirements, it is significant that there is little
research in the area of diversity and student development, specifically, student cognitive
development. To this end, the current chapter delves into highlighted studies that comprise
the existing body of student development literature, critical thinking literature, diversity
course literature and impact theory literature.
The remainder of this chapter commences with a review of student development theory.
Next, the chapter provides competing theories in cognitive development. Then, this chapter
13
reviews various studies in critical thinking that have influenced the methodological
framework of this study. Following, the chapter discusses various aspects of diversity,
diversity courses and diversity course experiences, which are all integral components of this
study’s methodology. Impact theory is the primary theoretical or methodological framework
employed by many of the studies highlighted in this chapter. Impact theory, specifically
Astin’s Impact model, is utilized as the theoretical framework for the methodological
approach of this study.
Student Development Theory
A foundation to basic developmental theory is expressed in an equation developed
by Kurt Lewin in 1936 (Evans et al., 1998). Lewin expresses his equation, B = f (P x E)
as an explanation of how a person develops as he or she interacts with his or her
environment. Lewin substitutes the letter (B) for Behavior as an (f) function of a (P)
Persons, (x) interaction with their (E) environment. This expression explains that a
person’s behavior is a product of that person interacting with their environment.
Erik Erikson (1946) provides the concept of identity into development theory.
Erikson details that an individual develops unique identity in late adolescences and early
adulthood. Erikson also delineates the optimal condition for identity development to take
hold: (1) maintain a constant semblance within oneself and a constant sharing with others
and (2) providing a psycho-social moratorium for young people (Erikson, 1946). The
college environment provides young people with the opportunity to do both.
In 1966, similar to Lewin’s equation, Nevit Sanford (as cited in Evans et al., 1998)
postulated student development is based on a student’s interaction with the environment.
Sanford’s theory outlines three developmental conditions: (1) readiness-explains that
14
individuals exhibit behaviors when they are ready for use; (2) challenge – explains
behaviors should be challenged with an appropriate amount of dissonance and (3)
support-is explained as the counterpart to challenge and should be applied
proportionately to challenge.
Feldman and Newcomb (1969) incorporate the concept of challenge. They espouse
the notion that students who are challenged or experience the most discontinuity during
their college years gain the greatest changes. They also theorize that students with
incongruent ethnic backgrounds, as compared to the majority of students at a particular
institution will have greatest gains.
As challenge and support are necessary components of student development,
involvement plays another fundamental role (Astin 1984). Astin (1984) describes
involvement as the necessary energy required for a student to be dedicated to academic
experiences. Astin (1984) denotes five postulates to student involvement: (1)
involvement is the investment of physical and psychological energy in various objects;
(2) involvement takes place on a continuum and students will manifest different degrees
on involvement into similar activities; (3) involvement maintains quantitative and
qualitative aspects; (4) student learning and development is directly proportional to the
quality and quantity of student involvement and (5) the efficacy policy and initiatives is
based the capacity of that policy and initiative to increase student involvement.
Similar to Astin’s postulate of involvement on a continuum, Ruble (1994)
provides a development model that engages transitions as the noteworthy moments in a
person or student’s development where an individual is presented with an uncharted and
will feel uncertainty. The most applicable phase of Ruble’s model to the college
15
environment is the construction transition phase. This phase speaks to the formative
moments of a new experience when an individual seeks knowledge to help make sense of
the new experience. This phase of Ruble’s model is extremely applicable to the college
environment because of the abundance of new experiences students will encounter; it is
also very similar to the fourth phase of Piaget’s cognitive development theory and
Vygotsky’s theory on Zones of Proximal Development (Ormond, J., 2008).
Cognitive Development Theory
There are two prevailing theories of cognitive development. The first is Piaget’s
Stages of Cognitive Development. Jean Piaget developed a four stage theory for
cognitive development (Ormond, J., 2008). The first stage is the Sensormotor which
commences at birth until year two; an infant finds ways to make sense of the world
(Ormond, J., 2008). The second stage is Preoperational which commences at the age of
two until seven years; in this stage children understand patterns but cannot yet reason
(Ormond, J., 2008). The third stage is Concrete Operations which commences at the age
of seven until year twelve; in this stage children maintain adult-like logic, but cannot
think abstractly (Ormond, J., 2008). The fourth stage, similar to Ruble’s construction
phase, is Formal Operations which commences at the age of twelve through adulthood; in
this stage children and adults are able to reason concretely and abstractly (Ormond, J.,
2008). Piaget’s cognitive developmental theory begins to explain notions of maturation
over time (King & Kitchner, 2002). This longitudinal development concept is important
because its helps inform this study’s longitudinal research design, which is explained
further in chapter three.
16
The other prevailing cognitive development theory is that of Lev Vygotsky.
Contrary to Piaget, Vygotsky asserted that learning and problem solving abilities emerge
as children are challenged to perform tasks that they would not be unable to perform
without assistance (Ormond, J., 2008). This theory is known as Zones of Proximal
Development. Vygotsky’s theory suggests a student who is left to learn without
assistance, that student will only perform tasks they have mastered.
Although both Piaget and Vygotsky’s theories lack the trappings of contemporary
social science, their theories help frame various educational issues that relate to critical
thinking. Moreover, the way humans cognitively develop, whether it is through a
sequence of theoretical milestones or by assistance and support, one’s ability to think
critically relies on an individual’s development over time. During this maturation
process, a student may have various experiences before, during and after taking a
diversity course. As a result, this ostensive cognitive development may affect critical
thinking skills and also helps inform this study’s research design.
Critical Thinking in Higher Education
As an aspect of cognition, critical thinking is a complex notion with various
dimensions. Facione et al. (1995) outline a seminal set of characterological attributes
associated with critical thinking. The researchers provided a longitudinal study of 587
new students and, mid-year, followed up with them (Facione et al, 1995). The authors
leveraged the work of Kufiss, 1988 Norriss & Ennis 1989, Jones 1993 and the American
Philosophical Association’s 1990 Delphi project which produced a comprehensive
conceptualization of the components that comprise critical thinking skills (Facione et al,
1995). These six components of critical thinking are (1) analysis; (2) inference; (3)
17
interpretation; (4) evaluation; (5) explanation and (6) self-regulation (Facione et al,
1995). Facione et al. (1995) used these six components as a base to develop a scale, the
California Critical Thinking Disposition Inventory. Facione and Facione (1992)
developed an instrument to measure an individual’s aptitude toward critical thinking, the
California Critical Thinking Index. This instrument engages the complexities of critical
thinking by breaking critical thinks into seven distinct dimensions: (1) Analyticity; (2)
Judgment (3) Inquisitiveness; (4) Open-mindedness (5) Self-confidence (6) Systematicity
and (7) Truth-seeking. These dimensions assist researchers decode an individual’s critical
thinking ability. This study employs the seven dimensions of critical thinking as
explanatory variables in the research design. This inventory is the instrument the
researchers employed in studying the 587 student population. Facione et al (1995) found
that entering freshmen showed strengths in open-mindedness and inquisitiveness and
weakness in systematicity and truth-seeking. The authors further detail that there is a
complex interrelationship between a students’ self-disposition toward critical thinking
and their critical thinking abilities (Facione et al, 1995). These findings are also essential
to this study because they elucidate potential variables that will be utilized in the research
design and methodologies of this study.
Similar to the dimensional conception of critical thinking mentioned above
Spiezio, Baker and Boland (2006) offer a complimentary definition of critical thinking,
which is an assortment of skills that enable students to access, analyze and effectively
apply information. The researchers found when students are engaged in community
service activities, critical thinking skills increased.
18
Giancarlo and Facione (2001) found gender and parental education levels and
race are accurate predictors of disposition towards critical thinking. Similarly, Terenzini,
Springer, Pascarella and Nora (1995) found that a parents’ education level had a
significant and positive impact on first year students’ critical thinking skills. Facione and
Giancarlo (2001) found that females scored significantly higher in their overall
disposition towards critical thinking as compared to males. With regards to race,
Pascarella, Palmer, Moye and Pierson (2001) found race and diversity experiences to be a
significant variable with students’ critical thinking skills. Giancarlo and Facione (2001)
also found that students’ declared majors affect critical thinking skills. The researchers
reported business and communications majors were positively disposed towards critical
thinking dimensions. They also found that humanities and language majors were
predisposed to critical thinking dimensions and, business, communications, math and
engineering majors were neutral with the development of critical thinking skills.
Nelson-Laird (2005) and Pascarella (2001) found students involved with diversity
experiences are more likely to measure higher in critical thinking dimensions as
compared to students not involved and these students are also more inclined to show
growth with their critical thinking skills. This type of finding is also seen in student
faculty interactions. Students who engage in student faculty interactions show positive
growth with their critical thinking skills Light, 2001; Lundberg & Schreiner, (2004) and
Terenzini, Springer, Pascarella and Nora (1995).
Diversity in Higher Education
Diversity can be understood in a multitude of ways; Gurin et al (2002) defined
diversity in higher education with three components: (1) structural diversity, which
19
explains the racial and ethnic make-up of the institution; (2) classroom diversity, which
refers to the curriculum based study of diversity and (3) informal interactional diversity,
which refers to the frequency and quality of diverse interactions that are diametric to
one’s own personal race or ethnicity. These three conceptions of diversity inform this
study and its research design.
Prior to Gurin et al’s study (2002), Alexander Astin (1993) conducted a study that
engaged student’s socialization with students of another race. Astin found students who
interacted with students of another race or were involved in an interracial relationship had
positive increases in academic development, racial understanding, cultural awareness,
and college satisfaction. Hurtado, (2007) postulates that cognitive dissonance that occurs
when students interact with students of another race provokes an active thinking process,
which in turn encourages students to consider the diversity of perspective from their
peers. Similar to Sanford’s theory of development (as cited in Evans et al., 1998), the
second stage of his model challenge, with the appropriate amount of dissonance disrupts
one’s cognitive equilibrium and makes an individual uncomfortable enough to step out of
comfort zones and this then stimulates intellectual growth (Chickering & Reisser, 1991;
Piaget, 1975), (Gurin et al., 2002; Hurtado et al., 2003; Hurtado, 2007).
In linking the gains that students receive from an educational environment that
challenges them through an appropriate amount of cognitive dissonance, Gurin, Dey,
Hurtado and Gurin (2002) found that, through informal interactional diversity, larger
gains in students’ development and learning takes place in institutions with a vast amount
of structural diversity. Chang (2001) also notes structural diversity has a significant
impact on student experiences. Campus diversity positively correlates to the increase in
20
students socializing with diverse peers, which is also positively linked to student
retention.
In turn, Hurtado (2007) found positive interactions with diverse peers lead to
higher complex thinking test scores as compared to students who reported negative
interactions with diverse peers; they scored lower. Hurtado (2007) attributes this finding
to students’ inability to deal with intergroup conflict. Accordingly, the researcher reasons
students who have negative interactions with diverse peers are likely to retreat to comfort
zones and should be supported, when their epistemological beliefs are challenged,
Sanford (as cited in Evans et al., 1998).
Diversity Courses in Higher Education
Over 63% of American universities maintain a diversity course general education
requirement. As a common initiative in the majority of universities, diversity courses play
integral role classroom diversity. Hurtado’s 2007 study also found that students who
enrolled in diversity courses had higher scores on 24 measured outcomes. Additionally,
students scored even higher on the same 24 measured outcomes when they were involved
with co-curricular diversity experiences.
The question was then posed, if the enrollment in a diversity course and co-
curricular diversity programs reflect higher scores for students, does the intensity of a
diversity course matter? Cole and Sundt (2008) developed a typology for diversity
courses that engages that inquiry. Their typology places courses into one of four
categories: (1) introductory; (2) basic; (3) intermediate and (4) advanced. This study
utilizes the Cole and Sundt (2008) typology in the research design.
21
Diversity courses are often attributed with changing people’s attitudes, values and
beliefs Chickering & Reisser, 1991; Piaget, 1975; Gurin et al., 2002; Hurtado et al., 2003;
Hurtado, 2007). Hogan and Mallett (2005) viewed diversity courses as a tool of
prejudice reduction. The researchers found intergroup tolerance improved when students
were enrolled in a diversity course. Yet, the researchers also determined the effects from
diversity courses were only temporary. Gurin et al. (2002), examine how classroom
diversity and informal interactional impact democratic values. The researchers found
students who interact with diverse peers have positive development outcomes (Gurin et
al., 2002). Gurin et al., (2002) provide prescriptive advice for higher education
institutions; they detail institutions must dedicate resources to develop structural and
classroom diversity to ensure students are able to realize positive gains from interactions
with diverse peers.
Theoretical Framework
Establishing a theoretical foundation is vital to understand variables that are being
studied by researchers, and theoretical framework is crucial for this study in its research
design. This section provides various theoretical models, primarily student impact
models, highlight some of the aforementioned researchers utilization of a particular
impact model and determine the most appropriate model, for use in this study.
College impact theory is an essential concept in comprehending how the collegiate
environment affects students. Many of the college impact models focus on the process of
change while students are immersed in a collegiate environment (Pascarella & Terenzini,
2005). These models concentrate on the composition of both the student and the
22
institution in order to analyze the change in the student as a result of the college
environment.
There are many impact models that help shape the understanding of student
development. Ernest Pascarella (1985) provides a model for understanding the change in
the student as it relates to the direct and indirect effects of an institution’s environmental
and structural characteristics, General Model for Assessing Change. In this model, there
are five aspects that serve as the underpinnings of the model: (1) the student’s
background; (2) structural characteristics: (3) the institution’s environment; (4)
interactions with agents of socialization and (5) quality of student effort (Pascarella,
1985). These five variables serve as the basic structure of the model and have been used
in studies that analyze student retention and matriculation (Pascarella & Terenzini, 2005).
There are other impact models that have been used to study the phenomena of
student retention such as Vincent Tinto (1975, 1993). Although there are many skeptics
to Tinto’s work, he offers an impact theory, the Theory of Student Departure, which
attempts to explain the student withdrawal process (1993). Similar to Pascarella’s work
(1985), there are also five aspects to Tinto’s theory: (1) student’s pre-enrollment
characteristics; (2) student’s goals and commitments; (3) student’s institutional
experiences; (4) student’s ability to integrate and (5) student’s outcomes. These five
variables are applied to better understand how student’s negative and positive interactions
in college affect student retention and persistence.
Dissimilar to Pascarella & Terenzini (2005) and Tinto’s (1975, 1993) works,
Alexander Astin (1985) developed a universal model for analyzing college/student
impact, I-E-O model. Astin’s (1985) model uses three elements: (1) Inputs; (2)
23
Environment and (3) Outcomes. Astin (1985) describes inputs as student’s characteristics
such as pre-college experience and general background. He explains environment as the
many interactions experienced in college. Then, he details outcomes as the
characteristics, awareness and viewpoints after college. This model is often
complimented by Astin’s (1985) theory of involvement but for the purposes of this study
the focus will remain on Astin’s I-E-O model.
Although there are many different types of college impact theories, the
aforementioned theories offer an array of different ways to understand the longitudinal
changes in students as they matriculate through college. Specifically, Astin’s model will
be employed throughout this chapter and the study as a framework to longitudinally
understand how student’s pre-college enrollment characteristics (input) are impacted by
diversity courses as well as other diversity experiences (an environmental factors) and
relate to various student attributes upon exiting college (outcomes).
Many higher education researchers (Chang, 1999, 2001, 2002; Cole, 2007; Cole
& Sundt, 2009; Dey et al, 2005; Gurin et al, 2002; Hogan & Mallott, 2005; Hurtado,
1996, 2001, 2006, 2007; Hurtado et al, 2003) have implicitly and explicitly used Astin’s
I-E-O model do analyze how diversity courses impact various types of student outcomes.
Astin’s I-E-O model was employed by Gurin, Dey, Hurtado, and Gurin (2002) in a study
where the researchers evaluated the different ways students engage diversity. The authors
developed three different categories of diversity: (1) structural diversity; (2) informal
interactional diversity and (3) classroom diversity (Gurin Dey, Hurtado, and Gurin 2002).
Structural diversity is described as the composition of diversity of students, faculty and
staff on campus. Informal interactional diversity is explained how peer interact on
24
various non-curricular environments throughout campus such as dormitories, student
unions and campus events. Classroom diversity is outlined as the interactions between
peers and faculty in the classroom as well as the pedagogy and curriculum of a course
(Gurin, Dey, Hurtado, and Gurin, 2002).
Gurin et al’s (2002) study applies Astin’s I-E-O model and analyzes two different
aspects of classroom diversity. The researchers engage students (Input) in diversity
courses (environment) and view two specific outcomes: (1) democratic outcomes as well
as (2) learning outcomes. The authors outline democratic outcomes as understanding of
race and culture, engaged citizenship and perspective-taking. Learning outcomes is
described by the authors as academic and intellectual engagement as well as active
thinking. The authors believed that a curriculum based on culture and race would
encourage and environment that has positive intellectual engagement and active thinking
impacts. To this end, Gurin et al (2002) found that there is a positive statistical
significance for some students with regard to classroom diversity/diversity initiatives and
democratic and learning outcomes.
A current study in diversity is related to student ability to engage in democratic
activities. Sylvia Hurtado (2008) has developed a project that is focused on Preparing
Students for a Diverse Democracy. Hurtado enacted an active study of 29,796 students to
evaluate their pluralistic orientation. The study includes surveys a various different
intervals from entering student, end of first year, senior surveys and a 10 year follow up
surveySome of the variables that the researcher is investigating are tolerance of others,
ability to work cooperatively, open-mindedness, ability to engage in controversial issues,
ability to view diametric perspectives (Hurtado, 2008). Some of Hurtado’s major findings
25
are there are many ways to measure students’ ability to participate in a diverse
democracy; these measures range from moral reasoning to cultural awareness.
In Hurtado’s (2008) Predisposition Diversity Content and Pedagogy Effects, not
only does one view the recurring theoretical framework of Astin’s (1985) I-E-O model,
one also sees the emergence of the impacts of diversity courses and critical thinking.
Primarily, Hurtado asserts that students’ critical thinking disposition is an outcome from
the environment. This is extremely relevant to the overall focus of this study: the impact
of diversity courses on student’s critical thinking skills. Hurtado’s (2008) research
positions students’ critical thinking disposition as one of many different ways to measure
students’ cognition. Hurtado’s current work serves as a vital link for this study and the
relationship between diversity courses and students’ critical thinking skills. The link that
Hurtado established between diversity courses and cognition is expressly important to
this study because she is the first researcher in higher education to make the connection
between diversity courses and students’ critical thinking skills.
Again, the impetus of this study is Chang’s quandary (2002); there is very little
research about diversity courses, but the need to study diversity courses and their
outcomes is great. To this end, this study evaluates the impact of diversity courses on
students’ critical thinking skills and utilize Astin’s I-E-O model as its theoretical
framework. The next chapter outlines the methodological framework to address the
underlying question of this study, how do diversity courses impact students’ critical
thinking skills?
26
CHAPTER 3
Methodology
Overview
This study examines the impact of diversity courses on students’ critical thinking skills
at a large, highly selective, private, tier one research university. The prior chapter outlined
the existing body of student development literature, critical thinking literature, diversity
course literature, impact theory literature and the empirical studies therein. Additionally, the
previous chapter offers a theoretical framework present in many of studies, Input-
Environment-Output model (Astin, 1993). This framework serves as the core of the
methodological structure of this study.
This chapter explains the approach and the procedures required to appropriately
examine the leading question of this study - Do diversity courses impact students’ critical
thinking skills? Accordingly, this chapter details the study’s research methodology,
theoretical models, survey selection, instruments, data collection, data analysis,
methodological assumptions and limitations. These core elements will drive the
methodological and procedural approaches for this study.
Research Methodology
This study is a non-experimental investigation of diversity courses and their impact on
student’s critical thinking skills. The study is a longitudinal single institution study. The
longitudinal nature of the study crosses the span of four years from 2004 through 2008. The
single institution is a valuable component of the study’s design through establishing effects
of environmental variables such as: student satisfaction; student learning; student
engagement, student analytical abilities and student critical thinking skills. All of these
27
components of the investigation are valuable, for they will help establish a core
understanding of the effects of the diversity courses on students at Western University. To
compliment these two components of the investigation, the study will also incorporate a
typology (Cole & Sundt 2008) of diversity courses that will facilitate a better understanding
of their purpose and degree by which they achieve criteria requirements for diversity courses
at Western University. Alongside, the typology, the study will incorporate an Input-
Environment-Output model (Astin, 1993) to frame how different variables relate.
Research Questions
The leading questions for this study are:
Do diversity courses impact students’ critical thinking skills?
Do student characteristic input variables impact students’ critical thinking
dimensions?
To what extent does the number of diversity courses taken impact students’
critical thinking dimensions?
To what extent does the typology of diversity courses impact students’
critical thinking dimensions?
To what extent do diversity experiences impact students’ critical thinking
dimensions?
A quantitative research design is employed to investigate the impact of diversity
courses on students’ critical thinking skills. A quantitative approach is the most appropriate
means by which to study the underlying question for two major reasons. First, the majority of
diversity course studies that precede this study have employed either a quantitative or mixed
methods study (Chang, 1999, 2001, 2002; Cole, 2007, Cole & Sundt, 2009; Dey et al, 2005;
28
Gurin et al, 2002; Hogan & Mallott, 2005; Hurtado, 1996, 2001, 2006, 2007; Hurtado et al,
2003). This approach is in alignment with contemporary researchers’ methodological
approaches in engaging diversity courses and their respective outcomes. Second, the data
gathered for this study is widely used and helps address inquiries that are quantitatively
based. Because the data is accessible and widely used other researchers are able to readily
reproduce the study. Replication of this study is an important characteristic; it will afford
other researchers the opportunity to test findings and build off this work.
Selection of Sample and Population
The site selected to conduct the study is Western University, a large, private,
highly selective, tier one research institution. Western University is the largest private
university in the United States and is set in one of the country’s most populated cities. As
a result, Western University is uniquely juxtaposed within a bustling metropolitan area,
but steeped with abounding traditions that lend toward excellent dynamic structural
diversity (Gurin el al, 2002 & Hurtado, 2006). Accordingly, Western University’s unique
characteristics afford it an extraordinary position to be representative of various
institution types both public and private large and small. This is a compelling attribute for
reasons of generalizability and applicability. Additionally, Western University is the
current site of a larger study of diversity courses and various outcomes (Cole & Sundt,
2008). This study is positioned to become a seminal study in diversity courses outcomes.
There is significant institutional buy-in that has already been created and will assist in the
implementation and execution of this study. Most importantly, Western University
maintains a mandatory diversity requirement for all of its undergraduate students. The
University has developed guidelines for courses to qualify as a diversity requirement. As
29
another significant indicator to Western University commitment to diversity, the
University’s role and mission detail its commitment to educate and prepare human being
for a pluralistic society and its coursework will reflect this notion.
Alongside these major structural diversity attributes (Gurin el al, 2002 & Hurtado,
2006), the student body is a relatively diverse cadre. The estimated student population is
32,836 students approximately 16,897 are undergraduate students. The student population
is 50.1% female and 49.9% male. Over one third of the student body is international
students. The ethnic composition of undergraduate student population 47% White, 21%
Asian / Pacific Islander, 13% Latino, 6% Black 3% Unknown and 1% Native
American/Alaskan (Western University Enrollment Statistics). From an ethno-cultural
perspective, Western University has a fairly diverse campus and it is from this student
body that the study draws its participants.
The population of this study comprises all undergraduate students who entered
Western University in fall of 2004 and were seniors in spring of 2008. The actual sample
of this population is N=553 students who completed both the 2004 Cooperative
Institutional Research Program (CIRP) and the 2008 Western University Senior Survey
(WUSS).
Instrumentation and Selection of Surveys
This study is a non-experimental research design that uses secondary sources as
the primary analysis for a longitudinal study. The 2004 CIRP data serves as pre-test or
the input (Astin, 1985). The 2008 Senior Survey serves as the post-test or the output
(Astin, 1985). The third instrument is the diversity typology (Cole & Sundt, 2008) which
analyzes the rigor of a diversity courses. The final instrument is student transcript data,
30
which provides important environmental characteristics. These surveys and instruments
were selected because they help inform unique characteristics of the Input-Environment-
Output model (Astin, 1993). All of these instruments will be described in greater detail,
later in this chapter.
Conceptual Framework
As described in the second chapter, the Input-Environment-Output model (Astin,
1993) serves as the conceptual framework for this study. This study adapts the Input-
Environment-Output model (Astin, 1970, 1993), in order to explain the relationship
between different variables. Additionally, the major strength in this study’s Input-
Environment-Output model (Astin, 1970, 1993) is the longitudinal design. By testing and
retesting the same student, over time, one is able to measure the student’s maturation
(Feldman and Newcomb 1969).
The inherent goal of this study is to measure a student’s maturity or growth by
identify significant factors. The conceptual framework provides the methodological
structure to identify these factors or variables. These variables are found in the three data
sets that this study utilizes: (1) the CIRP; (2) the WUSS and (3) transcript data. The
CIRP survey captures the characteristics and disposition of students pre-college; this
provides the input or independent variables for this study. The WUSS presents the
disposition of students post-college; the output or dependent variables are outlined in this
survey. The environmental or explanatory variables are found in both Diversity Typology
and Transcript Data. The last key aspect to the conceptual framework is the application of
Facione et al’s (1995) categorization of critical thinking dimensions as adapted from the
California Critical Thinking Index. The researchers outline critical thinking to be a
31
compilation of seven different dimensions: (1) Analyticity; (2) Judgment (3)
Inquisitiveness; (4) Open-mindedness (5) Self-confidence (6) Systematicity and (7)
Truth-seeking. This study took each of these seven dimensions of critical thinking and
placed any CIRP and WUSS survey questions that embodied one of these dimensions
into that unique category. In turn, all questions that fit within a unique critical thinking
dimension were aligned from CIRP/Input to WUSS/Output. The next chapter highlights
individual Input-Environment-Output models (Astin, 1970, 1993) for each of the seven
critical thinking dimensions. The two figures below diagrams the Input – Environment –
Output (I-E-O) Model for Critical Thinking (Astin, 1970, 1993) and the two different
explanatory variables the number of diversity courses taken and the diversity course
typology. The two models below will be the theoretical and organizational model for all
data analysis functions for this study.

32
Figure 3.1
(Input – Environment – Output) Model for Critical Thinking & Number of Diversity
Courses Taken
(Adapted from Astin, 1993)

STUDENT INPUT
(CIRP):
Seven Student Critical
Thinking Dimension
Variables

Student Characteristics
Gender
Race
Parental Education

Chosen Major

Student-Teacher
Interactions

ENVIRONMENT
(WUSS/Transcripts):
Other Diversity
Experiences
Diversity Courses
Total # of DC’s taken

Diversity Experiences
Racial Awareness Workshop
Studied Abroad
Community Service
STUDENT OUTPUT
(WUSS):

Seven Student
Critical Thinking
Dimension Variables
33
Figure 3.2
Input – Environment – Output Model for Critical Thinking & Typology
(Adapted from Astin, 1993)

Data Sets

Three data sets comprise this study: the 2004 CIRP survey, the 2008 WUSS, and
transcript data from students who participated in both the CIRP and WUSS surveys. First,
the CIRP is a national longitudinal study that assesses student experiences in higher
education. The survey is currently administered from the University of California Los
Angeles and was instituted in 1966 through the American Council on Education. To date,
CIRP has been administered at nearly 2000 institutions, to over 300,000 faculty members
and over 15,000,000 students. The survey is administered on an annual basis at over 700
participating institutions to over 400,000 freshman students. This makes the CIRP the
oldest and one of the most comprehensive student/faculty surveys.
For the purposes of this study, the 2004 CIRP was administered by Western
University’s Office of Student Outcomes Research. A total of 2,429 students participated
in the 2004 CIRP. These students represent the total universe of Western University
STUDENT OUTPUT
(WUSS):

Seven Student
Critical Thinking
Dimension Variables
STUDENT INPUT
(CIRP):
Seven Student Critical
Thinking Dimension
Variables

Student Characteristics
Gender
Race
Parental Education

Chosen Major

Student-Teacher
Interactions

ENVIRONMENT
(WUSS/Transcripts):
Other Diversity
Experiences
Diversity Courses
Typology of 1
st
DC taken

Diversity Experiences
Racial Awareness Workshop
Studied Abroad
Community Service
34
CIRP participants in 2004; each of the respondents was a first year student or freshman
when s/he took the survey and responses were collected before s/he started their
academic course. In short, the CIRP data serves as the “Input” variables for the Input –
Environment – Output (I-E-O) Model for Critical Thinking (Astin, 1970, 1993). The
table below indicates the characteristic input variables this study utilizes form the 2004
CIRP. The additional input variables that are employed in this study are explained in
greater detail in the final two chapters
Table 3.1
CIRP Characteristic Independent Variables
VARIABLE(S) TYPE ITEM RECODED I, E or O
Gender
Independent
Variable
SEX No Input
Race
Independent
Variable
RACE1-9
Yes
(RACE_R)
Input
Parents’ Levels
of Education
Independent
Variable
FATHEDUC &
MOTHEDUC
Yes
(ParentED_R)
Input
Major
Declared
Independent
Variable

MAJOR04
Yes
Into Individual
Majors

Input
Student-Faculty
Interactions
Independent
Variable
ACT0414 No Input

The second survey utilized is the 2008 WUSS. Again, the Western University
Office of Student Outcomes research administers this survey, which is an institutional
survey modeled after the CIRP. Its design highlights questions and self-reported
35
satisfaction and experiences that mirrors the CIRP. Unlike the CIRP, the WUSS is
administered every third year. With regards to this study, that limits the amount of
students who will have taken the CIRP and the corresponding WUSS. To establish the
longitudinal design of this study, the 2008 WUSS, which is the most recent Western
University student survey, is the driver of the year that can be used for the CIRP-2004.
Select WUSS data is used as “environmental” or explanatory variables as well as output
or “outcome” variables. The table below displays the WUSS independent variables used
in this study. The dependent WUSS variables are described in the remaining chapters.
Table 3.2
WUSS Independent Variables
VARIABLE(S) TYPE ITEM RECODED
I, E
or O
Racial
Awareness
Workshop
Independent
Variable

ever_5

Yes
(ever_5R)

E
Studied
Abroad
Independent
Variable

ever_8
Yes
(ever_8R)

E
Community
Service
Participation
Independent
Variable

first_5
freq_11
Yes
(CommunityServiceR)
Composite Variable

E
Transcript data is the third data set that is employed in this study. This
information was secured from the Western University Registrar’s Office. The transcript
36
data complements the WUSS data to provide the complete environmental variables for
this model. The table below indicates the transcript data independent variables.
Table 3.3
Transcript Data Independent Variables
VARIABLE(S) TYPE ITEM RECODED
I, E
or O
First time a
diversity course
was taken
Independent
Variable
COURSE01
thru
COURSE40
Yes
(FirstDCYear_R)

E
Total number of
diversity courses
taken
Independent
Variable
COURSE01
thru
COURSE40
Yes
(DiversityTaken_R)

E
Typology level
of first diversity
course taken
Independent
Variable
COURSE01
thru
COURSE40
Yes
(DCTypology1st_R)

E

Although the Diversity Course Typology is not a data set, it provides this study a
useful analytical lens utilized in the methodological structure as an environmental or
explanatory variable. The Typology was created by Cole and Sundt (2008, 2009) to
address the wide variety of diversity courses offered at Western University. Although
each diversity course is held to guidelines, every course varies in course structure and
complexity. Accordingly, the Typology is designed to measure the variation in diversity
courses. Each diversity course is assessed by a trained course rater. These course raters
perform a content analysis on the syllabi for each diversity course. The syllabi are
37
evaluated based on the diversity course guidelines and scored on a four point Likert scale.
The diversity course scores are then placed on a bell curve, where a mean score and
standard deviation are determined. Finally, the Typology classifies the diversity courses
into four groups: (1) Introductory – meets diversity requirements; (2) Basic – marginally
exceeds diversity requirements; (3) Intermediate – exceeds diversity requirements; and
(4) Advanced – far exceeds diversity requirements. With regards to this study, 118 of the
138 syllabi were collected and scored. This study will use the typology tool as a measure
of the intensity of a diversity course based on the aforementioned criteria.
Data Collection
The information collected in this study commenced in 2004, when freshman
Western University students were administered a hard-copy version of the CIRP survey,
the summer prior to their first academic year. Then, in 2008, the same students were
administered an on-line version of the WUSS. Of the 2,429 students who initially
responded to the 2004 CIRP, N=553 students responded to the WUSS, in 2008.
Data Analysis
The next chapter focuses solely on the data analysis of this study. This section
will outline the rationale for the use of specific statistical measures used in the
forthcoming chapter. The primary statistical tool used in this study is the software
package, Statistical Packages for Social Science (SPSS) 17.0. The three data sets
described in this chapter, 2004 CIRP, 2008 WUSS and transcript data were uploaded into
SPSS to create a master data file. Then, the following statistical analyses were performed:
(1) Descriptive Statistics; (2) Factor Analysis; (3) Reliabilities; and (4) Regression
38
Analysis. The following sections address the protocol and descriptions of how the data
used in this study was prepared.
Recoding and Computing New Variables
This study utilizes variables from three different data sets, 2004 CIRP, 2008
WUSS and transcript data. Even though the 2008 WUSS was modeled after the 2004
CIRP, variables needed to be recoded for various reasons. This recoding process is
performed to ensure the data provided is in its most useful form. For example values in
the 2008 WUSS such as “freq_11” are labeled: frequently=1; occasionally=2; not at
all=3. To make this data and data like it more useful, the data is recoded as: frequently=3;
occasionally=2; not at all=1. This is done to ensure as the degree of frequency increases
the numerical representation does the same.
Additionally, other data was recoded to ensure that responses were in alignment.
At times, WUSS survey questions and CIRP survey questions pose the same question,
but the responses may be labeled differently. For example CIRP data may be labeled as:
frequently=3; occasionally=2; not at all=1 and WUSS data may be labeled as every
day=4; three times a week=2; once times a week=2; never=1. In this type of case, the
WUSS data would be recoded to align with the CIRP; every day and three times would
be merged to equal a value of 3, once a week and never would remain as a value of 2 and
1 respectively.
Also, recoded variables were created to create binary variables. For example, the
CIRP offers nine different options for race. For the purposes of this study, the statistical
importance of White and Non-white is more important; this comparison aligns with past
research Hogan & Mallot 2005; Cole 2007). To this end, the variable “RACE1” was
39
created; a binary logic was used if a student is not “White” they indicate one of the eight
options that is not “White.” If a student responded affirmatively to this question a student
is classified “White.”
Composite Variables
As mentioned earlier, seven critical thinking dimensions are utilized (Facione et
al, 1995) to best understand the complexities of critical thinking. Each dimension
maintains its “own” Input – Environment – Output (I-E-O) Model (Astin, 1970, 1993). In
an effort to capture the various questions that embody specific critical thinking
dimensions, composite variables were attempted. The purpose of creating a metta
variable is to strengthen the statistical significance of a grouping of variables based on a
factor loading. Sixteen different composite variables were attempted and are described in
the next chapter.
Diversity Course Variables and Descriptive Statistics
Creating diversity course variables, FirstDCYear_R, DiversityTaken_R, and
DCTypology1st_R, was an arduous process. Transcript data outlined up to 73 courses
taken by students before their senior year. These courses were then identified as diversity
courses or non-diversity courses. When course was coded as a diversity course, the
corresponding year of when the first diversity course was taken was created into the
“FirstDCYear_R” variable. Next, a determination was made of how many diversity
courses were taken for each student; this variable is labeled as, “DiversityTaken_R.”
Last, the Typology variable was created based on the Typology score of a student’s first
diversity course taken; this variable is labeled as, “DCTypology1st_R.”
40
Descriptive statistics are used as the primary and simplest form of analysis in this
study. Basic characteristics about the data set, such as sample size the number of
responses to specific questions are collected and organized to ensure the correct
descriptors are being evaluated. This step helps summarize and make determinations of
the data set on aggregate.
Factor Analysis
Factor analyses are utilized in this study to determine the intercorrelations
between variables. In other words, if variables statistically “hang” together, there is a
strong likelihood that those variables can be merged into a composite variable. As
mentioned in this chapter, the attempt to create composite variables is important to
incorporating the most statistically significant critical thinking dimensions variables that
“hang” together.
Reliability Tests
After a factor analysis is conducted, reliability tests are performed to determine
the factor loading of each variable. This is the step is what is described in the previous
section as determining variables that “hang” together. What is actually being evaluated is
the factor loading. If the Cronbach’s Alpha is greater than .700 when combined with
other variables, these variables statistically “hang” together
Reliability and Validity
Reliability is one of the most important concepts in this study’s integrity.
Reliability tests for internal consistency help determine that, if conditions remain uniform
that results will also be uniform. Cronbach’s Alpha/if Cronbach’s Alpha is Deleted is
used to measure internal consistency. Furthermore, testing for internal consistency will
41
indicate the degree by which the measurement tool will produce the same result
consistently.
In hand with reliability, validity is also an important concept in this study’s
integrity. Validity is the analysis by which the findings of this study are well founded and
nothing else can be attributed to the finding. In short, reliability is a measurement of the
accuracy of the conclusion. Similar to most longitudinal studies, maturation is the biggest
threat to the validity of this study. This study attempts to control the threat by
highlighting various explanatory variables in multiple Input – Environment – Output (I-
E-O) Model (Astin, 1970, 1993).
Regression Analysis
Regression analyses are used in this study to evaluate the impact of the
relationship between variables. Simply put, the regression analysis allows one to
determine the influence that one variable has over another. To this end, this study
examines the impact that specific environmental or explanatory variables have on
controlled inputs. Therefore, statistically significant changes in each regression model
will be measured by impact of the environmental or explanatory variables.
Summary
This chapter outlined the overarching methodological approaches in this study.
Moreover, this chapter details research methodology, theoretical models, survey
selection, instruments, data collection, data analysis, methodological assumptions and
limitations. Additionally, this chapter has provided the background for the analysis of
data and findings that will follow in the subsequent chapters.

42
CHAPTER 4
Analysis of the Data
Introduction
This study examines the impact of diversity courses on students’ critical thinking
skills at a large, highly selective, private, tier one research university. The previous
chapter outlined the methodological approaches for this study. The purpose of this
chapter is to provide a description of the data set used in the study, outline the
frequencies of variables and analyze the specific variables that are used to address the
research question - how do diversity courses impact student’s critical thinking skills?
The first section of this chapter focuses on the input variable descriptors of the
data set, Western University, participant characteristics, parental education, juxtaposition
of participants and declared majors. The second section details the frequency of the
environmental variables, the number of diversity courses taken, the year the first diversity
course was taken, the level of intensity, represented in a typology, of the students’ first
diversity course, and institutional diversity experiences (workshops and community
service). The third section provides factor analysis data for the construction of eight
composite critical thinking variable types in both the CIRP and the WUSS; the variable
types are analyticity, truth-seeking, inquisitiveness, judgment, open-mindedness, self-
confidence, systematicity and a composite variable including all the aforementioned
critical thinking variable types. The final section provides regression analyses results
based on proxy variables for the critical thinking variable types.
Survey data from the CIRP, the WUSS as well as academic transcripts were
secured to create the data set. Then, Statistical Packages for the Social Sciences (SPSS)
43
software was utilized to analyze relationships between the study’s input, environment and
output variables.
Data Set Externalities
It must be noted that Western University is located in a large urban environment.
Accordingly, many student experiences outside the classroom and the institution will
provide supplemental diversity experiences. The data herein is based on classroom and
institutional experiences.
The Data Set Composition
The data set used in this study resulted from two student surveys, the CIRP and
WUSS. As part of the longitudinal deign of this study, data was collected from, 2004
CIRP and the 2008 WUSS. This study’s data set is comprised of the 553 student
respondents who participated in both the 2004 CIRP and 2008 WUSS. Additionally, the
data set was disaggregated by gender and racial characteristics to elucidate any
differences based on race and gender.
Participant Characteristics – Race
The data set indicates an uneven spectrum of participants with regards to race and
gender. Based on self-identified racial backgrounds, 69.3% of participants responded
their racial identity to be White, while 30.7% of the survey participants responded to be
Non-White.
Participant Characteristics – Gender & Race
The data set also indicates the largest gender represented in the data set is White
women with 41.4%; this is contrasted by Non-White men representing 9.2% of
respondents in the data set. Within the data set, White women represent 59.8% of the
44
respondents while White males comprise 40.2% of the respondents. The Non-White
category consists of 70% women and 30% men respondents.
Participant Characteristics – Majors
Business students make up almost 20% of the respondents within this data set. In
both White and Non-White groupings, this is the most popular major. Engineering majors
comprise 11.1% of respondents; this is the second most popular major for participants.
This remains true for White students with 7.8% of study’s respondents and 11.8% within
the White group, but, for Non-White students, the second most popular major is the
Biological Sciences which represents 3.6% of the study and 11.8% within the Non-White
group. The least popular major for all participants is Education with a combined .4% of
participants .2% from White and .2% of Non-White Students. It is also noted for Non-
White Students that .2% of the participants are English majors.
Parental Education – White vs. Non-White
About 96.6% of White students reported that one or both parents had attended
college or graduate school. This is contrasted by 84.1% of Non-White students reporting
that one or both of their parents had attended college or graduate school. Accordingly,
within the overall all study, 4.7% of the parents who had a high school education or less
are Non –White students while 1.8% of White students parents had a high school
education or less.
Data Set Characteristics – Summary
In juxtaposing Non-White students and White students, there are some striking
similarities and differences. In both Non-White and White students, women are the
largest number of participants. Business, as a major, followed by engineering, is the most
45
popular for both groups. A notable difference between White and Non-White students is
parental education; about 12% more White student’s parents have had some kind of
higher education as compared to Non-White student parents. This may or may not be a
significant factor, depending on institutional and national data on parental education,
which is a consideration this study does not expand on outside of noting basic
characteristics of the students in the data set. The most striking difference is White
students dominate responses at a rate of almost one Non-White response to every three
White responses. This is significant because White Students between 2004 and 2008
made up less than half of the entire student population at Western University. Therefore,
it must be noted that White students are disproportionately represented in this data set as
compared to the overall student population.
Table 4.1 helps demonstrate input variables listed above from student
background, gender, level of parental education and compares Non-White and White
Students.
Environmental Categories & Variables
The environmental design to this study outlines two environmental
categories, Diversity Courses and Diversity Experiences; within each category there are
two types of environmental variables. The number of and when diversity courses were
taken as well as the level of intensity of diversity course, as described by a typology are
the two main environmental variables that make up the Diversity Courses category.
Participation in racial or cultural awareness workshops and participation in and frequency
of participation in Community Service work, as part of a course are the two
environmental variables that comprise the Diversity Experience category.
46
Table 4.1
Descriptive Data - Student Participants
Student Background & College
Entry Variables
a

Non-White
(n=170)
30.7%
Non-White
(Within Non-
White Group)
White
(n=383)
69.3%
White
(Within White
Group)
Gender of Student

Men 9.2% 30.0% 27.9% 40.2%
Women 21.5% 70.0% 41.4% 59.8%

Level of Parental Education

High School or Less 4.7% 15.3% 1.8% 2.6%
Some College or Degree 12.5% 40.6% 27.3% 39.4%
Grad Degree or Less 13.4% 43.5% 39.6% 57.2%

Major

Agriculture 0.0% 0.0% 0.0% 0.0%
Biological Sciences 3.6% 11.8% 6.0% 8.6%
Business 6.7% 21.8% 12.7% 18.3%
Education 0.2% 0.6% 0.2% 0.3%
Engineering 3.3% 10.6% 7.8% 11.2%
English 0.2% 0.6% 1.3% 1.8%
Health Profession 3.4% 11.1% 2.9% 4.2%
History/Political Science 2.0% 6.5% 4.5% 6.5%
Humanities 1.6% 5.3% 4.7% 6.8%
Fine Arts 0.5% 1.8% 6.2% 8.9%
Math/Statistics 0.5% 1.8% 0.2% 0.3%
Physical Science 0.4% 1.2% 1.8% 2.6%
Social Science 1.8% 5.9% 1.8% 2.6%
Other - Technical 0.4% 1.2% 1.1% 1.6%
Other 2.9% 9.4% 9.0% 13.1%
Undecided 2.4% 7.7% 7.8% 11.2%
a
2004 CIRP Data.

47
The aforementioned environmental categories and variables are reflected in a
series of tables that demonstrate how students are involved with diversity courses and
diversity experiences.
Diversity Courses
Table 4.2 provides the number of diversity courses taken at Western University.
The table exhibits the number of diversity courses taken and compares Non-White
students’, White students’ and all students’ diversity course history. The majority of
students, 52.3%, took one diversity course and 28.6% of students took no diversity
courses. Of the students who took one diversity courses, Non-White students took about
11% less diversity courses as compared to their White counterparts. For the remaining
students who took two or more diversity courses, Non-White and White students’
diversity course taking data are very similar. In turn, Non-White students who did not
take a diversity course are about 11% higher than their White counterparts.

48
Table 4.2
Frequency - Number of Diversity Courses Taken by Students
__________________________________________________________________

Non-
White
Students
Non-
White
Students
White
Students
White
Students
All
Students
All
Students
Year Taken
% of
Population
# of
Students
% of
Population
# of
Students
% of
Population
# of
Students
1 DC 45.3% 77 55.4% 212 52.3% 289
2 DC's 11.8% 20 14.4% 55 13.6% 75
3 DC's 2.9% 5 3.1% 12 3.1% 17
4 DC's 3.5% 6 1.6% 6 2.2% 12
5 DC's 0.6% 1 0.3% 1 0.4% 2
0 DC's 35.9% 61 25.3% 97 28.6% 158

Table 4.3 displays the ordinal year of their enrollment at Western University and
when students took their first diversity course; this table also compares Non-White
students’, White students’ and all students’ course taking habits. The most popular year
to take a diversity course is the first year; 32.7% of student’s took their first diversity
course in the first year of their enrollment. Corresponding to the previous table, the
second most popular diversity course activity is to not take a diversity course; 28.6% of
all students did not take a diversity course within their first five years. Additionally, Non-
White and White students’ course taking habits did not vary considerably.
49
Table 4.3
Frequency - Enrollment Year the First Diversity Course Was Taken
__________________________________________________________________

Non-
White
Students
Non-
White
Students
White
Students
White
Students
All
Students
All
Students
Year Taken
% of
Population
# of
Students
% of
Population
# of
Students
% of
Population
# of
Students
Year 1 30.6% 52 33.7% 129 32.7% 181
Year 2 15.3% 26 17.5% 67 16.8% 93
Year 3 10.0% 17 11.2% 43 10.8% 60
Year 4 5.3% 9 7.0% 27 6.5% 36
Year 5 2.9% 5 5.2% 20 4.5% 25
Not at all 35.9% 61 25.3% 97 28.6% 158

Table 4.4 presents a high level overview of the number of diversity courses, the
year taken, the typology level and the number of courses taken in each typology level. In
all, a total of 556 diversity courses were taken over the five years captured in this study.
The most popular year to take a diversity course is the first year of a student’s enrollment.
This number continues to decrease through the fifth year. The majority of the courses
taken were in typologies two and three, although typology two had four more courses
taken.

50
Table 4.4
Number - Diversity Courses Taken Per Year and Diversity Courses Typology
Year Taken # of Students

Typology Level # of Students
Year 1 201

Typology 1 100
Year 2 120

Typology 2 182
Year 3 97

Typology 3 178
Year 4 88

Typology 4 96
Year 5 50

Table 4.5 expands on the typology level of the first diversity course taken and
compares Non-White students’, White students’ and all students’ course taking behavior.
The majority of students, 24.6% of students took a typology level three course, while
24.1% of students took a typology level two course, 11.4% of students respectively took
a typology one or a typology four course and 28.6% of students did not take a diversity
course.

51
Table 4.5
Frequency - Typology Level of First Diversity Course Taken
______________________________________________________________________________

Non-
White
Students
Non-
White
Students
White
Students
White
Students
All
Students
All
Students
Typology
Level
% of
Population
# of
Students
% of
Population
# of
Students
% of
Population
# of
Students
Typology 1 8.2% 14 12.8% 49 11.4% 63
Typology 2 20.6% 35 25.6% 98 24.1% 133
Typology 3 28.8% 49 22.7% 87 24.6% 136
Typology 4 6.5% 11 13.6% 52 11.4% 63
0 Taken 35.9% 61 25.3% 97 28.6% 158

Diversity Experiences
Table 4.6 exhibits students’ participation in Racial and Cultural Awareness
Workshops. About 73% of all students did not take a racial or awareness workshop. The
comparison to between Non-White and White students reflects a slight difference in
students never taking a workshop with White students taking workshops 11% more than
their Non-White counterparts.

52
Table 4.6
Frequency - Diversity Experiences Racial and Cultural Awareness Workshops

Non-White
Students White Students All Students
Diversity
Experiences Participation
% of
Students
# of
Students
% of
Students
# of
Students
% of
Students
# of
Students

Racial &
Cultural
Awareness
Workshops Yes 34.7% 59 23.8% 91 27.1% 150

No 65.3% 111 76.2% 292 72.9% 403

Table 4.7 also exhibits students’ participation in Diversity Experiences,
specifically the Community Service projects linked to course curriculum. The majority of
students, 54.4%, never participated in a community service project. Similar to the
comparison of Non-White and White students, White students participate in community
service projects about 10% more than their Non-White counterparts.

53
Table 4.7
Frequency - Diversity Experiences Community Service

Non-White Students White Students All Students
Diversity
Experiences Participation
% of
Students
# of
Students
% of
Students
# of
Students
% of
Students
# of
Students
Community
Service Yes 52.9% 90 41.5% 159 45.0% 249

No 47.1% 80 57.7% 221 54.4% 301

Factor Analyses and Reliabilities for Variables
In evaluating how environment variables affect input variables over a period of
time, it is compulsory that input and output variables are exact or measure similar
attributes. In lieu of having perfect matches for each of the critical thinking variables,
analyticity, truth-seeking, inquisitiveness, judgment, open-mindedness, self-confidence,
systematicity, proxy variables from the CIRP and WUSS were employed as described in
chapter three of this study. In order to decrease the amount of and functionally manage
statistically related variables, into a refined grouping of variables, in a fashion that will
include the majority of variability and expose correlations, linear arrangements of
variables were merged into overarching variables for each of the abovementioned critical
thinking variables (Kim and Mueller, 1978 and Pallant, 2005).
Noting all variables with a factor loading above .600, a principle component
analysis with a Varimax rotation method with a Kaiser Normalization was utilized, to
determine the variables with the most statistical commonalities. A factor analysis was
performed on the variables that “hang together,” with a factor loading above .600. These
54
variables were formed into one composite variable, for each of the seven critical thinking
variables; an additional “mega” composite variable that included all of the critical
thinking variables was also formed; this portion of the analytic process ensured the
reliability of the variables included in composite variables. Then, a reliability test also
ensured that variables with a Cronbach’s alpha (α), above .700 were included in the
composite variables.
Factor Analysis – Input Variable Analyticity (CIRP)
There are myriad variables that could have been employed from the CIRP. As
mentioned above, a factor analysis was performed juxtaposing input variables in the
CIRP, the three variables that statistically hang together within the analyticity composite
were: (1) Influence Political Structure; (2) Influence Social Values and (3) Develop
Meaningful Philosophy of Life. These three variables were constructed into a composite
variable for analyticity-CIRP. In Table 4.8 the three variables mentioned above appear to
correlate, meeting the .600 factor loading requirement.

55
Table 4.8
Factor Analysis – Input Variable Analyticity (CIRP)
Variables
a
Component
Analyticity (CIRP)
Influence Political Structure .848
Influence Social Values .883
Develop Meaningful Philosophy to Life .593
Percent of Variance 61.64
Total Percent 61.64
a
2004 CIRP Data.

Reliability – Input Variable Analyticity (CIRP)
Table 4.9 presents the results of the reliability of the three CIRP variables for
analyticity. If Cronbach’s Alpha is deleted from the scale, the “Influence Political
Structure” and “Influence Social Values” variables would decrease below the
unacceptable internal consistency level. Therefore, these questions should not be
removed. However, there was a significant increase in the “Develop Meaningful
Philosophy to Life” variable. This may lead one to believe that this item should be
removed from the composite. Notwithstanding, the variables appear to be on the low end
of acceptability; Cronbach’s Alpha for this composite is .676.

56
Table 4.9
Reliability – Input Variable Analyticity (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Analyticity (CIRP)
Influence Political Structure .499
Influence Social Values .395
Develop Meaningful Philosophy to Life .788
Reliability Coefficients (3 Items) .671
Standardized (std) item alpha .676
a
2004 CIRP Data.

Factor Analysis – Output Variable Analyticity (WUSS)
In an effort to align the CIRP and the WUSS composite variables, two exact
variables and one similarly related variable were utilized from the WUSS. As mentioned
above, a factor analysis was performed juxtaposing WUSS input variables, the three
variables within the analyticity composite were: (1) Identify Moral and Ethical Issues; (2)
Influence Social Values and (3) Develop Meaningful Philosophy of Life. These three
variables were constructed into a composite variable for analyticity-WUSS.
In Table 4.10, the three variables mentioned above appear to correlate analytically
and statistically; they all meet the .600 factor loading requirement.

57
Table 4.10
Factor Analysis – Input Variable Analyticity (WUSS)
Variables
a

Component
Analyticity (WUSS)

Identify Moral & Ethical Issues
.660
Influence Social Values
.730
Develop Meaningful Philosophy to Life
.749

Percent of Variance
50.99
Total Percent
50.99
a
2008 WUSS Data.

Reliability – Output Variable Analyticity (WUSS)
Table 4.11 presents the results of the reliability of the three WUSS variables from
the factor analysis immediately above. However, Cronbach’s Alpha for these variables is
.518. This reliability rating is poor to unacceptable. As a result, these three WUSS
variables do not hang together and cannot be used as an output composite variable for
analyticity. Accordingly, there would be no alignment with the input composite variable.
Therefore, one variable will be used as a proxy for analyticity. The “Influence Social
Values” variable had the highest component rating on the CIRP (.883) and the WUSS
(.730); it is used as an input and output proxy variable for “Analyticity,” when
regressions are performed.

58
Table 4.11
Reliability – Input Variable Analyticity (WUSS)
Variables
a

Cronbach’s
Alpha if
Deleted
Analyticity (WUSS)

Identify Moral & Ethical Issues
.443
Influence Social Values
.141
Develop Meaningful Philosophy to Life
.989

Reliability Coefficients (3 Items) .514
Standardized (std) item alpha
.518
a
2008 WUSS Data.

Factor Analysis – Input Variable Truth Seeking (CIRP)
The CIRP offered seven variables that qualified: (1) Too Much Rights for
Criminals; (2) Prohibit Homosexual Relations; (3) Racial Discrimination Is Not a
Problem, (4) Abolish Affirmative Action; (5) Activities of a Married Women Are best at
Home (6) Increase Federal Military Spending; and (7) Colleges have rights to ban
speakers. Most of the seven variables mentioned appear to loosely correlate.

59
Table 4.12
Factor Analysis – Input Variable Truth Seeking (CIRP)
Variables
a

Component
Truth Seeking (CIRP)

Criminal Rights
.574
Prohibit Homosexual Relations
.642
Racial Discrimination
.549
Abolish Affirmative Actions
.485
Activities of Married Women Should be at Home
.494
Increase Federal Military Spending
.699
Colleges Have Right to Ban Speakers
.514

Percent of Variance
27.25
Total Percent
27.25
a
2004 CIRP Data.

Reliability – Input Variable Truth Seeking (CIRP)
Table 4.13 exhibits the reliability test outcomes for the “Truth Seeking” variables.
If Cronbach’s Alpha is deleted from the scale, the coefficient would increase nearly all of
the variables. However, none of the variables meet an acceptable threshold. Albeit, the
reliability of the items on the scale appears to be on the low end of poor; Cronbach’s
Alpha for this composite is .645.

60
Table 4.13
Reliability – Input Variable Truth Seeking (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Truth Seeking (CIRP)
Criminal Rights .606
Prohibit Homosexual Relations .589
Racial Discrimination .609
Abolish Affirmative Actions .632
Activities of Married Women Should be at Home .626
Increase Federal Military Spending .572
Colleges Have Right to Ban Speakers .623

Reliability Coefficients (7 Items) .645
Standardized (std) item alpha .648
a
2004 CIRP Data.

Factor Analysis – Output Variable Truth Seeking (WUSS)
The WUSS provided two variables that were similarly related to the variables on
the CIRP. This attempt to form a composite variable from two was a stretch in alignment
to the CIRP composite for truth seeking. Regardless, a factor analysis was performed on
two similar variables from the WUSS: (1) Helping Promote Racial Understanding and (2)
Sought Counseling in the Past Year. These three variables were constructed into a
composite variable for analyticity-WUSS.
In Table 4.14 the two variables mentioned above appear to correlate analytically
and statistically; they all both exceed the .600 factor loading requirement.
61
Table 4.14
Factor Analysis – Input Variable Truth Seeking (WUSS)
Variables
a
Component
Truth Seeking (WUSS)
Helping Promote Racial Understanding .725
Sought Counseling in the Past Year .725
Percent of Variance 52.51
Total Percent 52.51
a
2008 WUSS Data.

Reliability – Output Variable Truth Seeking (WUSS)
Table 4.15 presents the results of the reliability of the two WUSS variables from
the factor analysis immediately above. Cronbach’s Alpha for these variables is .095. This
reliability rating is unacceptable. Additionally, if the coefficient was removed, the rating
would be almost zero for both variables; they do not hang together and cannot be used as
an output composite variable. Again, it was stretch in alignment at the onset of
performing these tests. Therefore, two similar variables are used as proxy variables when
regression are performed for truth seeking “Helping Promote Racial Understanding”
(WUSS) aligned with “Racial Discrimination” (CIRP).

62
Table 4.15
Reliability – Input Variable Truth Seeking (WUSS)
Variables
a

Cronbach’s
Alpha if
Deleted
Truth Seeking (WUSS)
Helping Promote Racial Understanding .003
Sought Counseling in the Past Year .003

Reliability Coefficients (2 Items) .095
Standardized (std) Item Alpha .096
a
2008 WUSS Data.

Factor Analysis – Input Variable Judgment (CIRP)
Table 4.16 presents ten variables that satisfactorily hang together in this
composite: (1) Make at Least a “B” Average; (2) Communicate Regularly with
Professors; (3) Socialize with Different Ethnic Group; (4) Strengthen Religious Beliefs;
(5) Academic Ability; (6) Understanding of Others; (7) Creativity; (8) Drive to Achieve;
(9) Public Speaking Ability; and (10) Writing Ability.

63
Table 4.16
Factor Analysis – Input Variable Judgment (CIRP)
Variables
a
Component
Judgment (CIRP)
Make at Least a “B” Average .061
Communicate Regularly with Professors .167
Socialize with Different Ethnic Group .033
Strengthen Religious Beliefs .-.046
Academic Ability .243
Understanding of Others .472
Creativity .667
Drive to Achieve .365
Public Speaking Ability .667
Writing Ability .668

Percent of Variance 27.25
Total Percent 27.25
a
2004 CIRP Data.

Reliability – Input Variable Judgment (CIRP)
Table 4.17 exhibits the results of the test for internal consistency. When
Cronbach’s alpha is removed all of variables increase to the low end of questionability.
Cronbach’s Alpha for this composite is .642.

64
Table 4.17
Reliability – Input Variable Judgment (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Judgment (CIRP)
Judgment (CIRP)
Make at Least a “B” Average .617
Communicate Regularly with Professors .613
Socialize with Different Ethnic Group .627
Strengthen Religious Beliefs .664
Academic Ability .611
Understanding of Others .621
Creativity .603
Drive to Achieve .627
Public Speaking Ability .601
Writing Ability .581
Reliability Coefficients (10 Items) .642
Standardized (std) item alpha .672
a
2004 CIRP Data.

Factor Analysis – Output Variable Judgment (WUSS)
The WUSS presented eight variables that did not align with the variables from the
CIRP, but did align with attributes of judgment. These eight variables are: (1) Place
Current Problems in Historical Perspective; (2) Formulate Original Ideas; (3) Evaluate
and Choose Between Different Courses of Action; (4) Understand the Process of Science
and Experimentation; (5) Evaluate the Role of Science and Technology in Society; (6)
65
Acquire New Skills on Own; (7) Function Independently Without Supervision; (8) Plan
and Execute Projects.
Table 4.18
Factor Analysis – Input Variable Judgment (WUSS)
Variables
a
Component
Judgment (WUSS)
Place Current Problems in Historical Perspective .605
Formulate Original Ideas .786
Evaluate and Choose Between Different Courses of
Action .762
Understand the Process of Science and Experimentation .536
Evaluate the Role of Science and Technology in Society .603
Acquire New Skills on Own .747
Function Independently Without Supervision .585
Plan and Execute Projects .713

Percent of Variance 38.76
Total Percent 38.76

Reliability – Output Variable Judgment (WUSS)
Table 4.19 presents the reliability ratings for the “Judgment” composite. The
Cronbach’s Alpha is .815. Although the ratings improved and range from good to
questionable, this composite was not used as an output variable because there were too
few similarities between the input and output variables “ Ove r wh el me d” is used as a
proxy for the input and output variable when regressions are performed.
66
Table 4.19
Reliability – Input Variable Judgment (WUSS)
Variables
a

Cronbach’s
Alpha if
Deleted
Judgment (WUSS)
Place Current Problems in Historical Perspective .806
Formulate Original Ideas .786
Evaluate and Choose Between Different Courses of
Action .762
Understand the Process of Science and Experimentation .536
Evaluate the Role of Science and Technology in Society .603
Acquire New Skills on Own .747
Function Independently Without Supervision .585
Plan and Execute Projects .713
Reliability Coefficients (8 Items) .815
Standardized (std) item alpha .823
a
2008 WUSS Data.

Factor Analysis– Input Variable Inquisitiveness (CIRP)
There are number of survey questions on the CIRP that engage aspects of critical
thinking. However, there were three that fit into the category of inquisitiveness: (1) Talk
to Teacher Outside of Classroom; (2) Reading for Pleasure and; (3) Understanding Other
Countries or Culture. A factor analysis was performed on these variables with subpar
outcomes. There are no common group factors; these variables cannot form a statistically
significant composite variable.
67
In Table 4.12 the three variables mentioned above do not correlate. Talk to
teacher outside of the classroom is the only variable that meets the .600 factor loading
threshold.
Table 4.20
Factor Analysis – Input Variable Inquisitiveness (CIRP)
Variables
a
Component
Inquisitiveness (CIRP)
Talk to Faculty Outside of Class .980
Reading for Pleasure .082
Understanding of Other Countries or Cultures -.196
Percent of Variance 39.39
Total Percent ?
a
2004 CIRP Data.

Reliability – Input Variable Inquisitiveness (CIRP)
Table 4.21 exhibits the results of the reliability of the three CIRP variables for
“Inquisitiveness.” If Cronbach’s Alpha is deleted from the scale, all three of the variables
would decrease to unacceptable internal consistency levels. Therefore, these variables
that appeared to measure the “Inquisitiveness” construct do not produce similar scores.
Cronbach’s Alpha for this composite is .194.

68
Table 4.21
Reliability – Input Variable Analyticity (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Inquisitiveness (CIRP)
Talk to Faculty Outside of Class .276
Reading for Pleasure -.022
Understanding of Other Countries or Cultures .064
Reliability Coefficients (3 Items) .178
Standardized (std) item alpha .194
a
2004 CIRP Data.

Factor Analysis & Reliability– Output Variable Inquisitiveness (WUSS)
No factor analysis or reliability tests were performed on the WUSS output
variables that aligned with the CIRP input variables for “Inquisitiveness.” The three
proposed composite input variables for “Inquisitiveness” met unacceptable levels for
internal consistency. As a result, an output composite variable would not have an optimal
input/output alignment. Fortunately, the WUSS maintains the “Talk to Faculty Outside of
Class” variable and it had the highest component rating from the CIRP (.980); it will be
used as input and output proxy variable for “Inquisitiveness,” when regressions are
performed.

69
Table 4.22
Factor Analysis – Input Variable Open-mindedness (CIRP)
Variables
a
Component
Open-mindedness (CIRP)
Participate in a Study Abroad Program .730
Socialized With a Different Ethnic Group -.716
Volunteer Work .004
Percent of Variance 33.39
Total Percent 33.39
a
2004 CIRP Data.

Factor Analysis– Input Variable Open-mindedness (CIRP)
The CIRP provides three variables that fit within the profile of open-mindedness:
(1) Participate in a Study Abroad Program; (2) Socialized With a Different Ethnic Group
and; (3) Volunteer Work. A factor analysis was performed on these variables with mixed
results. It appears that the variables are not statistically related. In Table 4.22, the three
variables mentioned above do not appear to relate. “Participate in a Study Abroad
Program” variable is the only variable that meets the .600 factor loading threshold.
Reliability – Input Variable Open-mindedness (CIRP)
Table 4.23 exhibits the results of the reliability of the three CIRP variables for
“Open-mindedness.” If Cronbach’s Alpha is deleted from the scale, all three of the
variables would decrease to or maintain unacceptable internal consistency levels.
Therefore, these variables that appeared to measure the “Open-mindedness” construct do
not produce similar scores. Cronbach’s Alpha for this composite is -.057.
70
Table 4.23
Reliability – Input Variable Open-mindedness (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Open-mindedness (CIRP)
Participate in a Study Abroad Program -.020
Socialized With a Different Ethnic Group -.005
Volunteer Work -.092
Reliability Coefficients (3 Items) -.057
Standardized (std) item alpha -.061
a
2004 CIRP Data.

Factor Analysis & Reliability– Output Variable Open-mindedness (WUSS)
No factor analysis or reliability tests were performed on the WUSS output
variables that aligned with the CIRP input variables for “Open-mindedness.” The three
proposed composite input variables for “Open-mindedness” met unacceptable levels for
internal consistency. As a result, an output composite variable would not have an optimal
input/output alignment. Fortunately, the CIRP and the WUSS maintains the “Socialized
With a Different Ethnic Group” variable. This variable is used as input and output proxy
variable for “Open-mindedness,” when regressions are performed.
Factor Analysis– Input Variable Self-Confidence (CIRP)
The CIRP offers three variables that fit within the Self-confidence critical
thinking construct. The three variables for Self-Confidence: are: (1) Intellectual Self-
confidence; (2) Social Self-confidence and; (3) Self-Understanding. A factor analysis was
71
performed on these variables with acceptable outcomes. There appears to be common
group factors; these variables should form a statistically significant composite variable. In
Table 4.24, the three variables mentioned above do relate to each other. All of these
variables have a facto loading over .700.
Table 4.24
Factor Analysis – Input Variable Self-Confidence (CIRP)
Variables
a
Component
Self-Confidence (CIRP)
Intellectual Self-confidence .776
Social Self-confidence .771
Self-Understanding .774
Percent of Variance 59.90
Total Percent 59.90
a
2004 CIRP Data.

Reliability – Input Variable Self-Confidence (CIRP)
In the table below, the three variables that fit within the category of “Self-
Confidence” are listed in a reliability chart. If Cronbach’s Alpha is deleted from the scale,
all three of the variables’ ratings would decrease. Therefore, these variables that appeared
to measure the “Self-Confidence” construct and produce similar scores reveal poor
internal consistency levels. Cronbach’s Alpha for this composite is .660.

72
Table 4.25
Reliability – Input Variable Self-Confidence (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Self-Confidence (CIRP)
Intellectual Self-confidence .560
Social Self-confidence .574
Self-Understanding .559
Reliability Coefficients (3 Items) .660
Standardized (std) item alpha .665
a
2004 CIRP Data.

Factor Analysis & Reliability– Output Variable Self-Confidence (WUSS)
No factor analysis or reliability tests were performed on the WUSS output
variables that aligned with the CIRP input variables for “Self-confidence.” The three
proposed composite input variables for Self-confidence” met poor levels for internal
consistency. As a result, an output composite variable would not have an optimal
input/output alignment. Fortunately, the WUSS maintains the “Think Critically” variable,
which is an excellent proxy variable for the critical thinking self-confidence construct.
Although there is not a perfect alignment with input and out variables, this variable will
align comfortably with the “Intellectual or Social Self-Confidence” variable from the
CIRP; each of these variables are respectively used as input and output proxy variable for
“Self-confidence,” when regressions are performed.
73
Factor Analysis– Input Variable Systematicity (CIRP)
The CIRP presents four variables that fit within the “Systematicity” variable.
These four variables are: (1) Mathematical Ability; (2) Time Management; (3) Computer
Skills; and (4) Leadership Ability. A factor analysis was performed on these variables
with mixed outcomes. There appeared to be common group factors and could form a
statistically significant composite variable. In Table 4.26 the four variables mentioned
from above, loosely meet the .600 factor loading threshold.
Table 4.26
Factor Analysis – Input Variable Systematicity (CIRP)
Variables
a
Component
Systematicity (CIRP)
Mathematical Ability .698
Time Management .556
Computer Skills .639
Leadership Ability .539

Percent of Variance 37.40
Total Percent 37.40
a
2004 CIRP Data.

Reliability – Input Variable Systematicity (CIRP)
Table 4.27 displays the results of the reliability of the four CIRP variables for
“Systematicity.” If Cronbach’s Alpha is deleted from the scale, all four of the variables
would decrease to unacceptable internal consistency levels. Therefore, these variables
74
that appeared to measure the “Systematicity” construct do not produce similar scores.
Cronbach’s Alpha for this composite is .437.
Factor Analysis & Reliability– Output Variable Systematicity (WUSS)
No factor analysis or reliability tests were performed on the WUSS output
variables that aligned with the CIRP input variables for “Systematicity.” The four
proposed composite input variables for “Systematicity” met unacceptable levels for
internal consistency. As a result, an output composite variable would not have an optimal
input/output alignment. Fortunately, the CIRP and the WUSS maintain the
“Mathematical Ability” variable used as input and output proxy variable for
“Systematicity,” when regressions are performed.
Table 4.27
Reliability – Input Variable Systematicity (CIRP)
Variables
a

Cronbach’s
Alpha if
Deleted
Systematicity (CIRP)
Mathematical Ability .315
Time Management .394
Computer Skills .367
Leadership Skills .393
Reliability Coefficients (3 Items) .437
Standardized (std) item alpha .438
a
2004 CIRP Data.

75
Input & Output Variable – Metta Critical Thinking Variable
In response to all of the aforementioned input and output critical thinking
component variables neither aligning nor maintaining acceptable levels for internal
consistency, a metta composite input and output variable was created from the respective
variables from the WUSS and CIRP. The attempt to create a metta composite variable
failed for the same reasons that were outlined for each of the seven component variables
of critical thinking, poor input and output alignment and unacceptable reliability ratings.
Therefore, the analytic design of this study shifted slightly. Instead of utilizing composite
variables to measure environmental impact, an individual proxy variable for each of the
seven critical thinking variables was utilized in performing regressions.
Linear Regression Analysis
A goal of social science disciplines is to best understand the relationship between
variables; education is no different. There are many statistical measures that can explain
the relationships between variables, variances and other attributes of probability theory.
This study will utilize linear regressions to best understand the relationship between the
critical thinking input and output variables alongside environmental variables.
Additionally, multiple regressions are performed in order to explain the impact of
explanatory/dependent variables, the seven input and output critical thinking variables, as
well as the four environmental variables: (1) number of diversity courses taken, (2)
diversity typology; (3) racial awareness workshops and (4) community service.
This portion of the chapter will report the beta from each regression performed
on: (1) each of the seven input and output proxy variables for critical thinking with the
environmental variable of number of diversity courses taken and (2) each of the seven
76
input and output proxy variables for critical thinking with the environmental variables of
diversity typology, racial awareness workshop and community service.
Regression A – Analyticity and Number of Diversity Courses Taken
The table below and the subsequent narratives within this section examine the
impact of participant characteristics, majors, diversity experiences and the number of
diversity courses taken have on students’ analyticity.

77
Table 4.28
Regression Coefficients for Analyticity and Number of Diversity Courses Taken
Independent Variables
Analyticity
β

Student's Gender .049
Race -.092*
Parental Education .045
Major-Business .224
Major-Biological Sciences .221
Major-Education .009
Major-Engineering .098
Major-English .057
Major-Health Prof .143
Major-History / Political Science .205
Major-Humanities .201
Major-Fine Arts .118
Major-Math / Statistics .032
Major-Physical Science .012
Major-Social Science .133
Major-Other Technology .055
Major-Other .195
Major-Undeclared .185
R
2
.078
Influence Social Values .242***
Diversity Courses Taken .113**
Racial Awareness Workshop .087*
Community Service .033

Adjusted R
2
.110
R
2
.148
F 3.872***
Highest Condition Index 52.21
* p < .05, ** p < .01, *** p < .001

78
Participant Characteristics
Divergent from Giancarlo and Facione’s (2001) findings that females scored
significantly higher in all critical thinking categories, the above table illustrates a .049
beta that aligns with the sig test score of .246. In this model, gender is not a significant
impact. Standing alongside Hu & Kuh’s findings (2003), this model outlines race (β = -
.092, p < .05), as the only independent variable that has a significant impact on a
student’s analytical abilities. Unlike Terenzini, Springer, Pascarella and Nora’s (1995)
findings, there is a significant and positive impact on critical thinking; parental education
was not significant in this model.
Majors
As mentioned above, the only independent variable that is significant is race.
Accordingly, a student’s declared major is not significant in this model. Again, unlike
Giancarlo and Facione’s (2001) findings, the thought necessary as well as the educational
curriculum that is outlined by diametric majors was not found to be significant in this
model.
Diversity Experiences
This model finds that some diversity experiences have a significant positive
impact. Although community service was not found to be significant in this model, racial
awareness workshops (β =.087, p < .05), was found to be significant. This aligns with the
findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings,
which indicate diversity experiences positively, impact critical thinking skills.

79
Number of Diversity Courses Taken
Similar to Nelson-Laird, Engberg and Hurtado’s (2005) findings, students who
enrolled in more diversity courses are likely to have higher critical thinking ratings. This
model finds the number of diversity courses taken (β = .113, p < .01), is significant.
Analyticity Proxy – Influence Social Values
As an aspect of critical thinking, as a construct, analyticity, is the most significant
variable in the model (β = .242, p < .001). Although a proxy variable was used to
illustrate this finding, it aligns with Giancarlo and Facione’s (2001) Nelson-Laird,
Engberg and Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Analyticity and Diversity Course Typology
The table below and the following accounts within this section examine the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ analyticity.

80
Table 4.29
Regression Coefficients for Analyticity and Diversity Course Typology Level
Independent Variables
Analyticity
β

Student's Gender .060
Race -.090*
Parental Education .040
Major-Business .233
Major-Biological Sciences .223
Major-Education .016
Major-Engineering .101
Major-English .062
Major-Health Prof .151
Major-History / Political Science .210
Major-Humanities .197
Major-Fine Arts .118
Major-Math / Statistics .031
Major-Physical Science .011
Major-Social Science .144
Major-Other Technology .053
Major-Other .210
Major-Undeclared .205
R
2
.078
Influence Social Values .241***
Diversity Course Typology Level .068
Racial Awareness Workshop .090*
Community Service .039

Adjusted R
2
.110
R
2
.148
F 3.872***
Highest Condition Index 52.55
* p < .05, ** p < .01, *** p < .001

81
Participant Characteristics
Similar to the findings from analyticity and the number of diversity courses, this
model diverges from Giancarlo and Facione’s (2001) finding that females scored
significantly higher in all critical thinking categories,. The above table illustrates a .060
beta that aligns with the sig test score of .183. This model also reports that gender is not a
significant impact. Also similar to the findings from analyticity and the number of
diversity courses, this model outlines race (β = -.090, p < .05), as the only independent
variable that has a significant impact on a student’s analytical abilities; this also
corresponds with Hu & Kuh’s findings (2003). Again, similar to the findings from
analyticity and the number of diversity courses, parental education was not significant in
this model, which is dissimilar to Terenzini, Springer, Pascarella and Nora’s (1995)
findings.
Majors
Mimicking the findings of analyticity and the number of diversity courses, the
only independent variable that is significant in this model is race. Therefore, a student’s
declared major is not significant in this model, which contrasts Giancarlo and Facione’s
(2001) findings that declared majors seem to be significant.
Diversity Experiences
Continuing to parallel the findings of analyticity and the number of diversity
courses, community service was not significant, but racial awareness workshops (β
=.090, p < .05) was found to be significant. Again, this aligns with the findings of
Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings, which
indicate diversity experiences positively affect critical thinking skills.
82
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Analyticity Proxy – Influence Social Values
Analogous to analyticity and the number of diversity courses, this model’s most
significant variable is “Influence Social Values” (β = .241, p < .001). The impact of this
explanatory variable aligns with Giancarlo and Facione’s (2001) Nelson-Laird, Engberg
and Hurtado (2005) and Pascarella’s (2001) findings; critical thinking (analyticity) is
improved over time when environmental variables such as other diversity experiences are
a component of environmental variables.
Analyticity, Diversity Courses Taken and Diversity Course Typology Level
Analyticity as a component of critical thinking is essential to evaluate a student’s
ability to analyze, interpret and apply knowledge. The proxy variable measuring social
values is essential in understanding the analyticity component of critical thinking.
The percent of variance (R
2
) in the two models measures analyticity. The model
measuring the environmental variable “Number of Diversity Courses Taken” explains
14.8% of the model and the model examining “Typology” explains 14.1% of its model.
There is a 2% change in the number of diversity courses taken model and a 1.4% change
in the typology model.
There are twenty-three variables, or dimensions, in both of the models that
measure analyticity. It must be noted that the relatively high condition index (see table
4.28 & 4.29), for both models, is attributed to the collinearity in the explanatory
83
variables. These variables cannot be removed and the high index is an accepted flaw of
this model. This issue will be discussed further in the following chapter, in the
“Limitations” section.
Even though the models only explain about 14%, the preliminary results, they
reflect a slight positive change in both models. The input/output variable “Influence
Social Values” is statistically significant; the environmental variables of “Racial
Awareness Workshops” and “Number of Diversity Courses Taken” also contribute to the
slight positive change. Once all seven components of critical thinking are discussed, a
final analysis and summary that addresses each of this study’s research questions will
conclude this chapter.
Regression A – Inquisitiveness and Number of Diversity Courses Taken
The table below and the succeeding account within this section analyze the impact
of participant characteristics, majors, diversity experiences and the number of diversity
courses taken have on students’ inquisitiveness.

84
Table 4.30
Regression Coefficients for Inquisitiveness and Number of Diversity Courses Taken
Independent Variables
Analyticity
β

Student's Gender -.020
Race -.054
Parental Education .062
Major-Business -.148
Major-Biological Sciences -.024
Major-Education -.028
Major-Engineering -.033
Major-English -.030
Major-Health Prof -.083
Major-History / Political Science -.067
Major-Humanities .007
Major-Fine Arts .076
Major-Math / Statistics -.037
Major-Physical Science .020
Major-Social Science -.130*
Major-Other Technology .020
Major-Other -.063
Major-Undeclared -.037
R
2
.078
Talking with Faculty Outside of
Class .225***
Diversity Courses Taken -.017
Racial Awareness Workshop .119**
Community Service .035

Adjusted R
2
.076
R
2
.113
F 3.004***
Highest Condition Index 28.848
* p < .05, ** p < .01, *** p < .001

85
Participant Characteristics
Deviating from Giancarlo and Facione’s (2001) findings, who reported females
scored notably higher in all critical thinking categories, the above table exhibits a -.020
beta that aligns with the sig test score of .658. In this model, gender is not a significant
impact. Also, deviating from previous studies, Hu & Kuh (2003), race is also not
significant, the above table exhibits a -.054 beta that aligns with the sig test score of .226.
Also, deviating from previous studies, Terenzini, Springer, Pascarella and Nora’s (1995),
parental education was not significant in this model; the above table exhibits a .062 beta
that aligns with the sig test score of .153
Majors
The only independent variable that is significant is the Social Science declared
major. Similar to Giancarlo and Facione’s (2001) findings, the thought necessary as well
as the educational curriculum that is outlined by diametric majors was found to be
significant in Social Science majors (β = -.130, p < .05).
Diversity Experiences
This model finds that some diversity experiences have a significant positive
impact. Even though community service was not found to be significant, in this model,
racial awareness workshops (β =.119, p < .01), was found to be significant. This supports
the findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001)
findings, which indicate diversity experiences positively, impact critical thinking skills.

86
Number of Diversity Courses Taken
Dissimilar to Nelson-Laird, Engberg and Hurtado’s (2005) findings, students who
enrolled in more diversity courses are likely to have higher critical thinking ratings. This
model did not find the number of diversity courses taken to be significant.
Inquisitiveness Proxy – Talking With Teachers Outside of Class
As another aspect of critical thinking, inquisitiveness, is the most significant
variable in the model (β = .225, p < .001). Again, a proxy variable was used to explain
this finding, it supports Giancarlo and Facione’s (2001) Nelson-Laird, Engberg and
Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Inquisitiveness and Diversity Course Typology
The table below and the following accounts within this section examine the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ inquisitiveness.

87
Table 4.31
Regression Coefficients for Inquisitiveness and Diversity Course Typology Level
Independent Variables
Inquisitiveness
β

Student's Gender -.021
Race -.052
Parental Education .062
Major-Business -.150
Major-Biological Sciences -.024
Major-Education -.028
Major-Engineering -.034
Major-English -.030
Major-Health Prof -.083
Major-History / Political Science -.068
Major-Humanities .008
Major-Fine Arts .075
Major-Math / Statistics .037
Major-Physical Science .019
Major-Social Science -.131*
Major-Other Technology .021
Major-Other -.065
Major-Undeclared -.038
R
2
.078
Talking with Faculty Outside of
Class .225***
Diversity Course Typology Level -.026
Racial Awareness Workshop .119**
Community Service .034

Adjusted R
2
.076
R
2
.114
F 3.015***
Highest Condition Index 29.010
* p < .05, ** p < .01, *** p < .001

88
Participant Characteristics
Similar to the findings from inquisitiveness and the number of diversity courses,
this model deviates from Giancarlo and Facione’s (2001) findings that females score
significantly higher in all critical thinking categories, the above table exhibits a -.021 beta
that aligns with the sig test score of .636. This model also reports that gender is not a
significant impact. Also similar to the findings from inquisitiveness and the number of
diversity courses taken, this model finds race insignificant; the above table exhibits a -
.052 beta that aligns with the sig test score of .238. Again, similar to the findings from
inquisitiveness and the number of diversity courses taken, parental education was not
significant in this model, and this is also unlike Terenzini, Springer, Pascarella and
Nora’s (1995) findings.
Majors
Mirroring the findings of inquisitiveness and the number of diversity courses
taken, the only independent variable that is significant, in this model, is the declared
Social Science major (β = -.131, p < .05). Again, similar to, Giancarlo and Facione’s
(2001) findings that declared majors are significant.
Diversity Experiences
Continuing to correspond with the findings of inquisitiveness and the number of
diversity courses taken, community service was not significant and racial awareness
workshops (β =.119, p < .01), was found to be significant. Again, this aligns with the
findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings,
which indicate diversity experiences positively, impact critical thinking skills.

89
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Inquisitiveness Proxy –Talking With Teachers Outside of Class
Analogous to analyticity and the number of diversity courses, this model’s most
significant variable is “Talk with Teachers Outside Class” (β = .225, p < .001). The
impact of this explanatory variable aligns with Giancarlo and Facione’s (2001) Nelson-
Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings; critical thinking
(inquisitiveness) is improved over time when environmental variables such as other
diversity experiences are a component of environmental variables.
Inquisitiveness, Diversity Courses Taken and Diversity Course Typology Level
Inquisitiveness is another as a component of critical thinking. This component is
integral in assessing a student’s curiosity and questioning their own knowledge. The
proxy variable measuring communicating with teachers outside of class is essential in
understanding the inquisitiveness component of critical thinking.
The percent of variance (R
2
), in the two models measuring inquisitiveness, the
model measuring the environmental variable “Number of Diversity Courses Taken”
explains 11.3% of the model and the model examining “Typology” explains 11.4% of its
model. There is a 1.5% change in the number of diversity courses taken model and a
1.5% change in the typology model.
90
There are twenty-three variables or dimensions in both of the models that measure
inquisitiveness. The high condition index of 29 for both models is attributed to the low
collinearity levels in this model.
Even though the models only explain about 11%, the preliminary results from
these models illustrate a slight positive change in both models. The input/output variable
“Talk with Teachers Outside Class” is statistically significant; the explanatory variables
of “Racial Awareness Workshops” and “Number of Diversity Courses Taken” also add to
the slight positive change. Once all seven components of critical thinking are discussed, a
final analysis and summary that addresses each of this study’s research questions will
conclude this chapter.
Regression A – Judgment and Number of Diversity Courses Taken
The table below and the following explanation within this section analyze the
impact of participant characteristics, majors, diversity experiences and the number of
diversity courses taken have on students’ judgment.

91
Table 4.32
Regression Coefficients for Judgment and Number of Diversity Courses Taken
Independent Variables
Judgment
β

Student's Gender .082
Race -.134**
Parental Education -.112*
Major-Business -.155
Major-Biological Sciences -.066
Major-Education -.003
Major-Engineering -.085
Major-English -.036
Major-Health Prof -.018
Major-History / Political Science -.179
Major-Humanities -.100
Major-Fine Arts -.084
Major-Math / Statistics -.043
Major-Physical Science -.032
Major-Social Science -.120
Major-Other Technology -.035
Major-Other -.181
Major-Undeclared -.035
R
2
.078
Overwhelmed .040
Diversity Courses Taken .026
Racial Awareness Workshop -.074
Community Service -.009

Adjusted R
2
.047
R
2
.085
F 2.212***
Highest Condition Index 29.641
* p < .05, ** p < .01, *** p < .001

92
Participant Characteristics
Again, differing from Giancarlo and Facione’s (2001) findings, who reported
females scoring higher on critical thinking scales, the above table exhibits a .082 beta that
aligns with the sig test score of .079. In this model, gender is not a significant impact.
However, similar to Hu & Kuh (2003), race is significant (β = -.134, p < .01). Also,
similar to previous studies, Terenzini, Springer, Pascarella and Nora’s (1995), parental
education is significant in this model (β = -.112, p < .01).
Majors
The third independent variable that is significant is the Political Science declared
major. Similar to Giancarlo and Facione’s (2001) findings, the thought necessary in
determining a major as well as the educational curriculum outlined a particular major was
found to be significant in Political Science majors (β = -.179, p < .05).
Diversity Experiences
This model finds that no diversity experiences have a significant positive impact.
This runs in conflict with the findings of Nelson-Laird, Engberg and Hurtado (2005) and
Pascarella’s (2001), which indicate diversity experiences positively, impact critical
thinking skills.
Number of Diversity Courses Taken
Unlike to Nelson-Laird, Engberg and Hurtado’s (2005) findings, students who
enrolled in more diversity courses are likely to have higher critical thinking ratings. This
model did not find the number of diversity courses taken to be significant.

93
Judgment Proxy – Overwhelmed with the Amount of Things to Do
Yet, another aspect of critical thinking is judgment. Overwhelmed with the
Amount of Things to do is the proxy variable utilized in this model, but it was not found
to be significant; this is dissimilar to findings of Giancarlo and Facione’s (2001) Nelson-
Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Judgment and Diversity Course Typology
The table below and the subsequent description within this section examines the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ judgment.

94
Table 4.33
Regression Coefficients for Judgment and Diversity Course Typology Level
Independent Variables
Judgment
β

Student's Gender .083
Race -.134**
Parental Education -.113**
Major-Business -.152
Major-Biological Sciences -.066
Major-Education -.022
Major-Engineering -.084
Major-English -.035
Major-Health Prof -.015
Major-History / Political Science -.178*
Major-Humanities -.101
Major-Fine Arts -.083
Major-Math / Statistics -.043
Major-Physical Science -.032
Major-Social Science -.117
Major-Other Technology -.035
Major-Other -.177
Major-Undeclared -.031
R
2
.078
Overwhelmed .041
Diversity Course Typology Level .018
Racial Awareness Workshop -.073
Community Service -.007

Adjusted R
2
.046
R
2
.085
F 2.204***
Highest Condition Index 29.858
* p < .05, ** p < .01, *** p < .001

95
Participant Characteristics
Similar to the findings from judgment and the number of diversity courses, this
model differs from Giancarlo and Facione’s (2001) findings, who found females score
significantly higher in all critical thinking categories, the above table exhibits a .083 beta
that aligns with the sig test score of .072. This model also finds that gender is not a
significant impact. However, similar to Hu & Kuh (2003), race is significant (β = -.134, p
< .01). Also, similar to previous studies, Terenzini, Springer, Pascarella and Nora’s
(1995), parental education is significant in this model (β = -.113, p < .01).
Majors
Paralleling the findings of judgment and the number of diversity courses taken,
the third independent variable that is significant, in this model, is the declared Political
major (β = -.178, p < .05). Again, similar to, Giancarlo and Facione’s (2001) findings that
declared majors are significant.
Diversity Experiences
Continuing to correspond with the findings of judgment and the number of
diversity courses taken, no diversity experiences have a significant positive impact. This
runs in conflict with the findings of Nelson-Laird, Engberg and Hurtado (2005) and
Pascarella’s (2001), which indicate diversity experiences positively, impact critical
thinking skills.
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
96
Judgment Proxy – Overwhelmed with the Amount of Things to Do
Analogous to judgment and the number of diversity courses taken, this model did
not find its critical thinking proxy variable “ Overwhelmed with the Amount of Things to
Do” to be significant; this is dissimilar to findings of Giancarlo and Facione’s (2001)
Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings.
Judgment, Diversity Courses Taken and Diversity Course Typology Level
Judgment is yet another component of critical thinking. This component is vital in
assessing a student’s decision making and self-efficacy. The proxy variable measuring
intellectual self-confidence is necessary in understanding the judgment component of
critical thinking.
The percent of variance (R
2
), in the two models measuring judgment, the model
measuring the environmental variable “Number of Diversity Courses Taken” and
Typology explain 8.5% of the model. There is about a .5% change in the number of
diversity courses taken and typology model.
There are twenty-three variables or dimensions in both of the models that measure
judgment. The high condition index of 29 for both models is attributed to the relatively
low collinearity levels in this model.
Even though the models only explain about 8.5%, the preliminary results from
these models exemplify no change in any of the explanatory variables. Once all seven
components of critical thinking are discussed, a final analysis and summary that
addresses each of this study’s research questions will conclude this chapter.
97
Regression A – Open-mindedness and Number of Diversity Courses Taken
The table below and the later description within this section analyze the impact of
participant characteristics, majors, diversity experiences and the number of diversity
courses taken have on students’ open-mindedness.

98
Table 4.34
Regression Coefficients for Open-mindedness and Number of Diversity Courses Taken
Independent Variables
Open-
mindedness
β

Student's Gender -.052
Race .003
Parental Education .043
Major-Business .122
Major-Biological Sciences .045
Major-Education -.015
Major-Engineering .186
Major-English .064
Major-Health Prof .048
Major-History / Political Science .169*
Major-Humanities .162*
Major-Fine Arts .042
Major-Math / Statistics .019
Major-Physical Science .060
Major-Social Science .077
Major-Other Technology .058
Major-Other .138
Major-Undeclared .227*
R
2
.078
Socialized with a Different Ethnic
Group .100*
Diversity Courses Taken -.058
Racial Awareness Workshop .022
Community Service .071

Adjusted R
2
.028
R
2
.067
F 1.704*
Highest Condition Index 36.736
* p < .05, ** p < .01, *** p < .001

99
Participant Characteristics
Again, conflicting with Giancarlo and Facione’s (2001) findings, who reported
females scored notably higher in all critical thinking categories, the above table exhibits a
-.052 beta that aligns with the sig test score of .257. In this model, gender is not a
significant impact. Also, deviating from previous studies, Hu & Kuh (2003), race is also
not significant, the above table exhibits a .003 beta that aligns with the sig test score of
.947. Also, deviating from previous studies, Terenzini, Springer, Pascarella and Nora’s
(1995), parental education was not significant in this model; the above table exhibits a
.043 beta that aligns with the sig test score of .333
Majors
The only independent variables that are significant are three different declared
majors, Political Science (β = .169, p < .05), Humanities (β = .162, p < .05) and
Undeclared (β = .227, p < .05). Similar to Giancarlo and Facione’s (2001) findings, the
thought necessary to choose a major as well as the educational curriculum within that
major was found to be significant.
Diversity Experiences
This model finds that no diversity experience have a significant positive impact.
This does not support the findings of Nelson-Laird, Engberg and Hurtado (2005) and
Pascarella’s (2001) findings, which indicate diversity experiences positively, impact
critical thinking skills.

100
Number of Diversity Courses Taken
Divergent from Nelson-Laird, Engberg and Hurtado’s (2005) findings, students
who enrolled in more diversity courses are likely to have higher critical thinking ratings.
This model did not find the number of diversity courses taken to be significant.
Open-mindedness Proxy – Socialize with Different Ethnic Groups
Another aspect of critical thinking, open-mindedness, is the most significant
variable in the model (β = .100, p < .05). Again, a proxy variable was used to explain this
finding; this finding supports Giancarlo and Facione’s (2001) Nelson-Laird, Engberg and
Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Open-mindedness and Diversity Course Typology
The table below and the subsequent report within this section examines the impact
of participant characteristics, majors, diversity experiences and the diversity course
typology level have on students’ open-mindedness.

101
Table 4.35
Regression Coefficients for Open-mindedness and Diversity Course Typology Level

Independent Variables
Open-
mindedness
β

Student's Gender -.056
Race .004
Parental Education .045
Major-Business .117
Major-Biological Sciences .044
Major-Education -.017
Major-Engineering .184
Major-English .062
Major-Health Prof .043
Major-History / Political Science .167*
Major-Humanities .164*
Major-Fine Arts .041
Major-Math / Statistics .020
Major-Physical Science .059
Major-Social Science .073
Major-Other Technology .060
Major-Other .130
Major-Undeclared .218*
R
2
.078
Socialize with a Different Ethnic
Group .101*
Diversity Course Typology Level -.053
Racial Awareness Workshop .021
Community Service .067

Adjusted R
2
.027
R
2
.067
F 1.696*
Highest Condition Index 36.937
* p < .05, ** p < .01, *** p < .001

102
Participant Characteristics
Similar to the findings from open-mindedness and the number of diversity courses
taken, this model deviates from Giancarlo and Facione’s (2001) findings, who found
females score significantly higher in all critical thinking categories, the above table
exhibits a -.056 beta that aligns with the sig test score of .216. This model also reports
that gender is not a significant impact. Also, similar to the findings from open-
mindedness and the number of diversity courses taken, this model also finds race
insignificant; the above table exhibits a -.052 beta that aligns with the sig test score of
.238. Again, similar to the findings from open-mindedness and the number of diversity
courses taken, parental education was not significant in this model, and this is also unlike
Terenzini, Springer, Pascarella and Nora’s (1995) findings.
Majors
Similar to the findings of open-mindedness and the number of diversity courses
taken, there are three significant independent variables, Political Science (β = .167, p <
.05), Humanities (β = .164, p < .05) and Undeclared (β = .218, p < .05). Similar to
Giancarlo and Facione’s (2001) findings, the thought necessary to choose a major as well
as the educational curriculum within that major was found to be significant.
Diversity Experiences
Continuing to correspond with the findings of open-mindedness and the number
of diversity courses taken, this model finds that no diversity experience have a significant
positive impact. This does not support the findings of Nelson-Laird, Engberg and
Hurtado (2005) and Pascarella’s (2001) findings, which indicate diversity experiences
positively, impact critical thinking skills.
103
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Open-mindedness Proxy –Socialize with Different Ethnic Groups
Analogous to open-mindedness and the number of diversity courses, this model’s,
most significant variable is “Socialize with Different Ethnic Groups” (β = .101, p <
.05). The impact of this explanatory variable aligns with Giancarlo and Facione’s (2001)
Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings; critical
thinking (open-mindedness) is improved over time when environmental variables such as
other diversity experiences are a component of environmental variables.
Open-mindedness, Diversity Courses Taken and Diversity Course Typology Level
Open-mindedness is another component of critical thinking. This component is
fundamental in assessing a student’s tolerance and acceptance of others. The proxy
variable measuring socialization with different ethnic groups is indispensable in
understanding the open-mindedness component of critical thinking.
The percent of variance (R
2
), in the two models measuring open-mindedness, in
the model measuring the environmental variable “Number of Diversity Courses Taken”
and “Typology” explains 6.7% of the model. There is a .7% change in the number of
diversity courses taken model and a .8% change in the typology model.
There are twenty-three variables or dimensions in both of the models that measure
open-mindedness. The relatively high condition index (see table 4.34 & 4.35), for both
models, is attributed to the collinearity in the explanatory variables. These variables
104
cannot be removed and the high index is an excepted flaw of this model. This issue will
be discussed further in the following chapter, in the “Limitations” section.
Even though the models only explain about 6.7%, the preliminary results from
these models demonstrate a slight positive change in both models. The input/output
variable “Socialize with Different Ethnic Groups” is statistically significant; this is the
only explanatory variable that shows a slight positive change. Once all seven components
of critical thinking are discussed, a final analysis and summary that addresses each of this
study’s research questions will conclude this chapter.
Regression A – Self-confidence and Number of Diversity Courses Taken
The table below and the following narratives within this section analyze the
impact of participant characteristics, majors, diversity experiences and the number of
diversity courses taken have on students’ self-confidence.

105
Table 4.36
Regression Coefficients for Self-confidence and Number of Diversity Courses Taken
Independent Variables
Self-confidence
β

Student's Gender .077
Race .019
Parental Education -.022
Major-Business -.037
Major-Biological Sciences -.076
Major-Education -.005
Major-Engineering -.153
Major-English -.008
Major-Health Prof -.152
Major-History / Political Science -.049
Major-Humanities -.014
Major-Fine Arts -.101
Major-Math / Statistics .000
Major-Physical Science -.053
Major-Social Science -.086
Major-Other Technology -.009
Major-Other -.083
Major-Undeclared -.090
R
2
.078
Intellectual Self-Confidence .001
Diversity Courses Taken .039
Racial Awareness Workshop .090*
Community Service .026

Adjusted R
2
.007
R
2
.048
F 1.177
Highest Condition Index 32.455
* p < .05, ** p < .01, *** p < .001

Participant Characteristics
106
Again, conflicting with Giancarlo and Facione’s (2001) findings, who reported
females scored notably higher in all critical thinking categories, the above table exhibits a
-.077 beta that aligns with the sig test score of .098. In this model, gender is not a
significant impact. Also, differing from previous studies, Hu & Kuh (2003), race is also
not significant, the above table exhibits a .019 beta that aligns with the sig test score of
.674. Also, differing from previous studies, Terenzini, Springer, Pascarella and Nora’s
(1995), parental education was not significant in this model; the above table exhibits a -
.022 beta that aligns with the sig test score of .621
Majors
There are no independent variables that are significant. Unlike Giancarlo and
Facione’s (2001) findings, the thought necessary to choose a major as well as the
educational curriculum within that major was found to be insignificant.
Diversity Experiences
This model finds that one diversity experience has a significant positive impact,
Racial Awareness Workshops (β = .090, p < .05). This supports the findings of Nelson-
Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings, which indicate
diversity experiences positively, impact critical thinking skills.
Number of Diversity Courses Taken
Divergent from Nelson-Laird, Engberg and Hurtado’s (2005) findings, students
who enrolled in more diversity courses are likely to have higher critical thinking ratings.
This model did not find the number of diversity courses taken to be significant.
Self-confidence Proxy – Intellectual Self-confidence
107
Another aspect of critical thinking is self confidence. The proxy variable
“Intellectual Self-confidence” was utilized. However, it was not found to be statistically
significant. This does not support the findings of Giancarlo and Facione’s (2001)
Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001).
Regression B – Self-confidence and Diversity Course Typology
The table below and the following narrative within this section examines the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ self-confidence.

108
Table 4.37
Regression Coefficients for Self-confidence and Diversity Course Typology Level
Independent Variables
Self-confidence
β

Student's Gender .078
Race .020
Parental Education -.024
Major-Business -.038
Major-Biological Sciences -.075
Major-Education -.009
Major-Engineering -.154
Major-English -.007
Major-Health Prof -.155
Major-History / Political Science -.054
Major-Humanities -.016
Major-Fine Arts -.101
Major-Math / Statistics .000
Major-Physical Science -.053
Major-Social Science -.066
Major-Other Technology -.005
Major-Other -.043
Major-Undeclared -.091
R
2
.078
Intellectual Self-Confidence .002
Diversity Course Typology .041
Racial Awareness Workshop .091*
Community Service .022

Adjusted R
2
.006
R
2
.048
F 1.107
Highest Condition Index 32.756
* p < .05, ** p < .01, *** p < .001

Participant Characteristics
109
Similar to the findings from self-confidence and the number of diversity courses
taken, this model deviates from Giancarlo and Facione’s (2001) findings, who found
females score significantly higher in all critical thinking categories, the above table
exhibits a -.078 beta that aligns with the sig test score of .100. This model also reports
that gender is not a significant impact. Also, similar to the findings from self-confidence
and the number of diversity courses taken, this model also finds race insignificant; the
above table exhibits a .020 beta that aligns with the sig test score of .702. Again, similar
to the findings from self-confidence and the number of diversity courses taken, parental
education was not significant in this model, and this is also unlike Terenzini, Springer,
Pascarella and Nora’s (1995) findings.
Majors
Similar to the findings of self-confidence and the number of diversity courses
taken, there are no significant independent variables, Dissimilar to Giancarlo and
Facione’s (2001) findings, the thought necessary to choose a major as well as the
educational curriculum within that major was found to be significant.
Diversity Experiences
Continuing to correspond with the findings of self-confidence and the number of
diversity courses taken, this model finds that one diversity experience has a significant
positive impact, Racial Awareness Workshops (β = .091, p < .05). This supports the
findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings,
which indicate diversity experiences positively, impact critical thinking skills.

110
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Self-confidence Proxy – Intellectual Self-confidence
Analogous to self-confidence and the number of diversity courses taken, this
model was not found to be statistically significant. This does not support the findings of
Giancarlo and Facione’s (2001) Nelson-Laird, Engberg and Hurtado (2005) and
Pascarella’s (2001).
Self-confidence, Diversity Courses Taken and Diversity Course Typology Level
Self-confidence is another component of critical thinking. This component is
essential in understanding a student’s poise and independence. The proxy variable
measuring intellectual self-confidence is indispensable in understanding the self-
confidence component of critical thinking.
The percent of variance (R
2
), in the two models measuring open-mindedness, in
the model measuring the environmental variable “Number of Diversity Courses Taken”
and “Typology” explains 4.8% of the model. There is a 1. % change in the number of
diversity courses taken model and a 1.1% change in the typology model.
There are twenty-three variables or dimensions in both of the models that measure
open-mindedness. The relatively high condition index (see table 4.36 & 4.37), for both
models, is attributed to the collinearity in the explanatory variables. These variables
cannot be removed and the high index is an accepted flaw of this model. This issue will
be discussed further in the following chapter, in the “Limitations” section.
111
Even though the models only explain about 4.8%, the preliminary results from
these models demonstrate a slight positive change in both models. The input/output
variable “Intellectual Self-confidence” is statistically significant; this is the only
explanatory variable that shows a slight positive change. Once all seven components of
critical thinking are discussed, a final analysis and summary that addresses each of this
study’s research questions will conclude this chapter.
Regression A – Systematicity and Number of Diversity Courses Taken
The table below and the following explanations within this section examine the
impact of participant characteristics, majors, diversity experiences and the number of
diversity courses taken have on students’ systematicity.

112
Table 4.38
Regression Coefficients for Systematicity and Number of Diversity Courses Taken
Independent Variables
Systematicity
β

Student's Gender -.001
Race -.016
Parental Education -.026
Major-Business .094
Major-Biological Sciences .024
Major-Education -.017
Major-Engineering -.015
Major-English .034
Major-Health Prof .066
Major-History / Political Science .086
Major-Humanities .140*
Major-Fine Arts .151*
Major-Math / Statistics -.032
Major-Physical Science -.009
Major-Social Science .029
Major-Other Technology .015
Major-Other .190*
Major-Undeclared .038
R
2
.078
Mathematical Ability -.589***
Diversity Courses Taken .065*
Racial Awareness Workshop -.008
Community Service -.047

Adjusted R
2
.464
R
2
.486
F 22.371***
Highest Condition Index 31.497
* p < .05, ** p < .01, *** p < .001

113
Participant Characteristics
Divergent from Giancarlo and Facione’s (2001) findings, who reported females
scored significantly higher in all critical thinking categories, the above table illustrates a -
.001 beta that aligns with the sig test score of .965. In this model, gender is not a
significant impact. Also, divergent from previous studies, Hu & Kuh (2003), race is also
not significant, the above table exhibits a -0.16 beta that aligns with the sig test score of
.640. Also, deviating from previous studies, Terenzini, Springer, Pascarella and Nora’s
(1995), parental education was not significant in this model; the above table exhibits a .-
.026 beta that aligns with the sig test score of .427.
Majors
There are three different independent variables that are statistically significant,
Humanities (β = .140, p < .05), Fine Arts (β = .151, p < .05) and Other (β = .190, p < .05).
Similar to Giancarlo and Facione’s (2001) findings, the thought necessary to choose a
major as well as the educational curriculum within that major was found to be significant.
Diversity Experiences
This model finds that no diversity experiences have a significant positive impact.
This does not support the findings of Nelson-Laird, Engberg and Hurtado (2005) and
Pascarella’s (2001) findings, which indicate diversity experiences positively, impact
critical thinking skills.
Number of Diversity Courses Taken
Similar to Nelson-Laird, Engberg and Hurtado’s (2005) findings, students who
enrolled in more diversity courses have a significant statistical impact. This model finds
the number of diversity courses taken (β = .065, p < .05), to be significant.
114
Systematicity Proxy – Mathematical Ability
As an aspect of critical thinking, systematicity, is the most significant variable in
the model (β = -.589, p < .001). Although a proxy variable was used to illustrate this
finding, it aligns with Giancarlo and Facione’s (2001) Nelson-Laird, Engberg and
Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Systematicity and Diversity Course Typology
The table below and the following accounts within this section examine the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ systematicity.

115
Table 4.39
Regression Coefficients for Systematicity and Diversity Course Typology Level
Independent Variables
Systematicity
β

Student's Gender .003
Race -.014
Parental Education -.029
Major-Business .101
Major-Biological Sciences .026
Major-Education -.012
Major-Engineering -.012
Major-English .037
Major-Health Prof .074
Major-History / Political Science .089
Major-Humanities .139*
Major-Fine Arts .151*
Major-Math / Statistics -.032
Major-Physical Science -.008
Major-Social Science .036
Major-Other Technology .015
Major-Other .200**
Major-Undeclared .052
R
2
.078
Mathematical Ability -.594***
Diversity Course Typology Level .029
Racial Awareness Workshop -.006
Community Service -.044

Adjusted R
2
.461
R
2
.483
F 22.119***
Highest Condition Index 31.653
* p < .05, ** p < .01, *** p < .001

116
Participant Characteristics
Similar to the findings from Systematicity and the number of diversity courses,
this model diverges from Giancarlo and Facione’s (2001) findings, who reported females
scored significantly higher in all critical thinking categories, the above table illustrates a
.003 beta that aligns with the sig test score of .934. This model also reports that gender is
not a significant impact. Also, similar to the findings from systematicity and the number
of diversity courses taken, this model is divergent from previous studies, Hu & Kuh
(2003), race is also not significant; the above table exhibits a -0.14 beta that aligns with
the sig test score of .669. Also, deviating from previous studies, Terenzini, Springer,
Pascarella and Nora’s (1995), parental education was not significant in this model; the
above table exhibits a .-.029 beta that aligns with the sig test score of .369.
Majors
Similar to the findings of systematicity There are three different independent
variables that are statistically significant, Humanities (β = .139, p < .05), Fine Arts (β =
.151, p < .05) and Other (β = .200, p < .05). Similar to Giancarlo and Facione’s (2001)
findings, the thought necessary to choose a major as well as the educational curriculum
within that major was found to be significant.
Diversity Experiences
Continuing to parallel the findings of systematicity, this model finds that no
diversity experiences have a significant positive impact. This does not support the
findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings,
which indicate diversity experiences positively, impact critical thinking skills.

117
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Systematicity Proxy – Mathematical Ability
Analogous to systematicity and the number of diversity courses taken, this
model’s, most significant variable is “Mathematical Ability” (β = -.594, p < .001). The
impact of this explanatory variable aligns with Giancarlo and Facione’s (2001) Nelson-
Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings; critical thinking
(systematicity) is improved over time when environmental variables such as other
diversity experiences are a component of environmental variables.
Systematicity, Diversity Courses Taken and Diversity Course Typology Level
Systematicity, as a component of critical thinking, is essential to evaluate a
student’s ability to think methodically or to apply a methodology. The proxy variable
measuring mathematical ability is essential in understanding the systematicity component
of critical thinking.
The percent of variance (R
2
), in the two models measuring systematicity, the
model measuring the environmental variable “Number of Diversity Courses Taken”
explains 48.6% of the model and the model examining “Typology” explains 48.3% of its
model. There is a .6% change in the number of diversity courses taken model and a .3%
change in the typology model.
There are twenty-three variables or dimensions in both of the models that measure
systematicity. It must be noted that the relatively high condition index (see table 4.38 &
118
4.39), for both models, is attributed to the collinearity in the explanatory variables. These
variables cannot be removed and the high index is an excepted flaw of this model. This
issue will be discussed further in the following chapter, in the “Limitations” section.
This model explains a great deal, nearly half of the model; the preliminary results
from these models reflect a slight positive change in both models. The input/output
variable “Mathematical Ability” is statistically significant; the environmental variable of
“Number of Diversity Courses Taken” also contribute to the slight positive change. Once
all seven components of critical thinking are discussed, a final analysis and summary that
addresses each of this study’s research questions will conclude this chapter.
Regression A – Truth- seeking and Number of Diversity Courses Taken
The table below and the following explanations within this section examine the
impact of participant characteristics, majors, diversity experiences and the number of
diversity courses taken have on students’ truth-seeking.

119
Table 4.40
Regression Coefficients for Truth-seeking and Number of Diversity Courses Taken
Independent Variables
Truth-seeking
β

Student's Gender .065
Race -.189***
Parental Education .018
Major-Business -.028
Major-Biological Sciences .037
Major-Education .027
Major-Engineering -.088
Major-English -.014
Major-Health Prof -.005
Major-History / Political Science .020
Major-Humanities .080
Major-Fine Arts .025
Major-Math / Statistics .042
Major-Physical Science -.028
Major-Social Science -.026
Major-Other Technology .044
Major-Other .008
Major-Undeclared -.051
R
2
.078
Promote Racial Understanding .255***
Diversity Courses Taken .132**
Racial Awareness Workshop .168***
Community Service -.074

Adjusted R
2
.190
R
2
.225
F 6.429***
Highest Condition Index 52.096
* p < .05, ** p < .01, *** p < .001

120
Participant Characteristics
Divergent from Giancarlo and Facione’s (2001) findings, who reported females
scored significantly higher in all critical thinking categories, the above table illustrates a
.065 beta that aligns with the sig test score of .129. In this model, gender is not a
significant impact. However, similar to Hu & Kuh (2003), race is significant (β = -.189, p
< .001). Also, unlike previous studies, Terenzini, Springer, Pascarella and Nora’s (1995),
parental education is not significant in this model; the above table exhibits a .018 beta
that aligns with the sig test score of .658.
Majors
As mentioned above, the only independent variable that is significant is race.
Accordingly, a student’s declared major is not significant in this model. Again, unlike
Giancarlo and Facione’s (2001) findings, the thought necessary to select a major as well
as the educational curriculum that is outlined by diametric majors was not found to be
significant in this model.
Diversity Experiences
This model finds that some diversity experiences have a significant positive
impact. Although community service was not found to be significant in this model, racial
awareness workshops (β =.168, p < .001), was found to be significant. This aligns with
the findings of Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001)
findings, which indicate diversity experiences positively, impact critical thinking skills.

121
Number of Diversity Courses Taken
Similar to Nelson-Laird, Engberg and Hurtado’s (2005) findings, students who
enrolled in more diversity courses have a significant statistical impact. This model finds
the number of diversity courses taken (β = .132, p < .01), to be significant.
Truth-seeking Proxy – Promote Racial Understanding
As an aspect of critical thinking, truth-seeking, is the most significant variable in
the model (β = .255, p < .001). Although a proxy variable was used to illustrate this
finding, it aligns with Giancarlo and Facione’s (2001) Nelson-Laird, Engberg and
Hurtado (2005) and Pascarella’s (2001) findings.
Regression B – Truth-seeking and Diversity Course Typology
The table below and the following accounts within this section examine the
impact of participant characteristics, majors, diversity experiences and the diversity
course typology level have on students’ truth-seeking.

122
Table 4.41
Regression Coefficients for Truth-seeking and Diversity Course Typology Level

Independent Variables
Truth-
seeking
β

Student's Gender .078
Race -.183
Parental Education .010
Major-Business -.024
Major-Biological Sciences .035
Major-Edu
ation .037
Major-Engineering -.090
Major-English -.009
Major-Health Prof .003
Major-History / Political Science .022
Major-Humanities .073
Major-Fine Arts .019
Major-Math / Statistics .039
Major-Physical Science -.032
Major-Social Science -.016
Major-Other Technology .042
Major-Other .022
Major-Undeclared -.028
R
2
.078
Promote Racial Understanding .257***
Diversity Course Typology Level .047
Racial Awareness Workshop .172***
Community Service -.068

Adjusted R
2
.177
R
2
.212
F 5.952***
Highest Condition Index 52.421
* p < .05, ** p < .01, *** p < .001

123
Participant Characteristics
Similar to the findings from Truth-seeking and the number of diversity courses
taken, this model diverges from Giancarlo and Facione’s (2001) findings, who reported
females scored significantly higher in all critical thinking categories, the above table
illustrates a .078 beta that aligns with the sig test score of .071. This model also reports
that gender is not a significant impact. Also, similar to Hu & Kuh (2003), race is
significant (β = -.183, p < .001). Also, unlike previous studies, Terenzini, Springer,
Pascarella and Nora’s (1995), parental education is not significant in this model; the
above table exhibits a .010 beta that aligns with the sig test score of .809.
Majors
Similar to the findings of truth-seeking, the only independent variable that is
significant is race. Accordingly, a student’s declared major is not significant in this
model. Again, unlike Giancarlo and Facione’s (2001) findings, the thought necessary to
select a major as well as the educational curriculum that is outlined by diametric majors
was not found to be significant in this model.
Diversity Experiences
Continuing to parallel the findings of truth-seeking, this model finds that some
diversity experiences have a significant positive impact. Although community service
was not found to be significant in this model, racial awareness workshops (β =.172, p <
.001), was found to be significant. This aligns with the findings of Nelson-Laird, Engberg
and Hurtado (2005) and Pascarella’s (2001) findings, which indicate diversity
experiences positively, impact critical thinking skills.

124
Diversity Course Typology Level
The diversity course typology level did not have a significant impact within this
model. Unlike the previous environmental variable, the diversity course typology level
does not represent a significant explanatory variable within this model.
Truth-seeking Proxy – Promote Racial Understanding
Analogous to truth-seeking and the number of diversity courses taken, this
model’s, most significant variable is “Promote Racial Understanding” (β = .257, p <
.001). The impact of this explanatory variable aligns with Giancarlo and Facione’s (2001)
Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) findings; critical
thinking (systematicity) is improved over time when environmental variables such as
other diversity experiences are a component of environmental variables.
Truth-seeking, Diversity Courses Taken and Diversity Course Typology Level
Truth-seeking, as a component of critical thinking, is essential to evaluate a
student’s ability to think philosophically and universally. The proxy variable measuring
promotion of racial understanding is essential in understanding the truth-seeking
component of critical thinking.
The percent of variance (R
2
), in the two models measuring truth-seeking, the
model measuring the environmental variable “Number of Diversity Courses Taken”
explains 22.5% of the model and the model examining “Typology” explains 21.2% of its
model. There is a 4.8% change in the number of diversity courses taken model and a
3.5% change in the typology model.
There are twenty-three variables or dimensions in both of the models that measure
truth-seeking. It must be noted that the relatively high condition index (see table 4.40 &
125
4.41), for both models, is attributed to the collinearity in the explanatory variables. These
variables cannot be removed and the high index is an excepted flaw of this model. This
issue will be discussed further in the following chapter, in the “Limitations” section.
This model explains a great deal, nearly a quarter of the model; the preliminary
results from these models reflect a slight positive change in both models. The
input/output variable “Promote Racial Understanding” is statistically significant; the
environmental variable of “Number of Diversity Courses Taken” and “Racial Awareness
Workshops” also contribute to the slight positive change

126
CHAPTER 5
Findings, Implications, Recommendations, Limitations & Conclusion
Introduction
The preceding chapter offers a discussion of the study’s data set, defines
descriptors and frequencies of input, environmental and output variables, presents factor
analysis data for the construction of eight possible composite critical thinking variables.
It also provides regression analyses results based on proxy variables for seven critical
thinking variable types. The results of the seven dimensions of critical thinking variables
address the leading research question - how do diversity courses impact student’s critical
thinking skills?
This chapter will commence by answering the aforementioned leading question
and engaging the study’s results through the four subordinate research questions: (1) do
student characteristic input variables impact students’ critical thinking dimensions (2) to
what extent does the number of diversity courses taken impact students’ critical thinking
dimensions? (3) to what extent does the typology of diversity courses impact students’
critical thinking dimensions? (4) to what extent do diversity experiences impact students’
critical thinking dimensions? The results from these questions offer environmental
findings that are discussed in a section of this chapter that focuses on policy and
curricular implications. Pursuant to the implication section, this chapter imparts
institutional and global recommendations that also address policy and curriculum. Next,
the chapter presents overarching limitations to this study. Finally, this chapter culminates
with a comprehensive conclusion that outlines areas for future research.

127
The matrix below displays the study’s major research question and the two
subordinate research questions that were answered in this study. The betas reported in the
table below are from the I-E-O model for critical thinking and number of diversity
courses taken; this is the same information outlined in the abstract.
Table 5.1
Research Questions & Significant Findings Matrix
Research
Questions
Number of
Diversity Courses Taken
N=553
Racial Awareness
Workshops
N=553
β β
Do diversity
courses impact
students’ critical
thinking skills?
Analyticity (β = .242, p < .001)
Inquisitiveness (β = .225, p < .001)
Open-mindedness (β = .100, p < .05)
Truth-seeking (β = .255, p < .001)
Analyticity (β = .087, p < .05)
Inquisitiveness (β = .119, p < .01)
Self-confidence (β = .090, p < .05)
Truth-seeking (β = .168, p < .001)
To what extent
does the number
of diversity
courses taken
impact students’
critical thinking
dimensions?
Analyticity (β = .242, p < .001)
Inquisitiveness (β = .225, p < .001)
Open-mindedness (β = .100, p < .05)
Truth-seeking (β = .255, p < .001)

To what extent do
diversity
experiences
impact students’
critical thinking
dimensions?

Analyticity (β = .087, p < .05)
Inquisitiveness (β = .119, p < .01)
Self-confidence (β = .090, p < .05)
Truth-seeking (β = .168, p < .001)

Critical Thinking Variables & Explanatory Variables
The “I-E-O” model (Astin, 1984) that used in this study employs two categories
of variables independent and dependent. There are two types of independent variables,
input and environmental variables; the input variables define student’s characteristics and
pre-college critical thinking skills; the environmental variables are used to explain the
128
change in student’s critical thinking skills. This is determined by the change in the
dependent variables, which are post-college critical thinking skills or output variables.
The study’s design offers a longitudinal methodology that tracks similar variables over a
four years period. In essence, the study assesses the impact of the environment on input
and output variables.
The forthcoming sections evaluate the statistical significance of each of the seven
critical thinking input and output variables: (1) Analyticity; (2) Judgment (3)
Inquisitiveness; (4) Open-mindedness (5) Self-confidence (6) Systematicity and (7)
Truth-seeking, to determine if the change in students’ critical thinking dimensions can be
attributed to explanatory variables, either Diversity Courses Taken or Diversity Course
Typology and Diversity Experiences. Three of the four subordinate research questions,
outlined in the introduction section of this chapter, are addressed by interpreting the
statistical results of the linear regressions described in chapter four.
Analyticity and Number of Diversity Courses Taken
In the Analyticity and Number of Diversity Courses Taken Model, the “Influence
Social Values” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = .242, p < .001). Race is the only statistically significant student
characteristic input variable; it makes a minor unique contribution explaining the
dependent variable, after controlling the variance for all variables (β = -.092, p < .05).
The number of diversity courses taken is statistically significant and makes a unique
contribution to explaining the dependent variable after controlling the variance for all
variables (β = .113, p < .01). Racial awareness workshops is statistically significant and
129
makes a minor unique contribution to explaining the dependent variable, after controlling
the variance for all variables (β = .087, p < .05).
Analyticity and Diversity Course Typology
In the Analyticity and Diversity Course Typology Model, the “Influence Social
Values” variable makes the strongest, statistically significant and unique contribution to
explaining the dependent variable, after controlling the variance for all variables (β =
.241, p < .001). Race is the only statistically significant student characteristic input
variable; it makes a minor unique contribution explaining the dependent variable, after
controlling the variance for all variables (β = -.090, p < .05). The course typology is not
statistically significant. Racial awareness workshops is statistically significant and makes
a minor unique contribution to explaining the dependent variable, after controlling the
variance for all variables (β = .90, p < .05).
In combining the results from both models for analyticity, it is noted that the
environment does make a strong positive significant impact. Analyticity, as a dependent
variable and one of seven dimensions of critical thinking, is significantly and positively
impacted by race, the number of diversity courses taken and racial awareness workshops.
Inquisitiveness and Number of Diversity Courses Taken
In the Inquisitiveness and Number of Diversity Courses Taken Model, the
“Talking with Faculty Outside of Class” variable makes the strongest, statistically
significant and unique contribution to explaining the dependent variable, after controlling
the variance for all variables (β = .225, p < .001). The Social Science Major is the only
statistically significant student characteristic input variable; it makes a minor unique
contribution explaining the dependent variable, after controlling the variance for all
130
variables (β = -.130, p < .05). The number of diversity courses taken is not statistically.
Racial awareness workshops are statistically significant and make a unique contribution
to explaining the dependent variable, after controlling the variance for all variables (β =
.119, p < .01).
Inquisitiveness and Diversity Course Typology
In the Inquisitiveness and Diversity Course Typology Model, the “Talking with
Faculty Outside of Class” variable makes the strongest, statistically significant and
unique contribution to explaining the dependent variable, after controlling the variance
for all variables (β = .225, p < .001). The Social Science Major is the only statistically
significant student characteristic input variable; it makes a minor unique contribution
explaining the dependent variable, after controlling the variance for all variables (β = -
.131, p < .05). The diversity course typology is not statistically significant. Racial
awareness workshops are statistically significant and make a unique contribution to
explaining the dependent variable, after controlling the variance for all variables (β =
.119, p < .05).
Inquisitiveness, as a dependent variable and one of seven dimensions of critical
thinking, is significantly and positively impacted by the Social Science major and racial
awareness workshops. The combination of the results from both models for
inquisitiveness, details the environment does make a significant and positive impact.
Judgment and Number of Diversity Courses Taken
In the Judgment and Number of Diversity Courses Taken Model, the “Other
Major” variable makes the strongest, significant and unique contribution to explaining the
dependent variable, after controlling the variance for all variables (β = -.181); it is not
131
statistically significant. There are two statistically significant student characteristic input
variables, Race and Parental education. Race makes a statistically significant unique
contribution explaining the dependent variable, after controlling the variance for all
variables (β = -.134, p < .01). Parental Education makes a statistically significant unique
contribution explaining the dependent variable, after controlling the variance for all
variables (β = -.112, p < .05).The number of diversity courses taken is not statistically
significant. Racial awareness workshops and community service are also not statistically
significant.
Judgment and Diversity Course Typology
In the Judgment and Diversity Course Typology Model, the “History/Political
Science Major” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = -.178, , p < .05). There are two additional statistically significant student
characteristic input variables, Race and Parental education. Race makes a statistically
significant unique contribution explaining the dependent variable, after controlling the
variance for all variables (β = -.134, p < .01). Parental Education makes a statistically
significant unique contribution explaining the dependent variable, after controlling the
variance for all variables (β = -.113, p < .05).The diversity course typology is not
statistically significant. Racial awareness workshops and community service are also not
statistically significant.
Judgment, as a dependent variable and one of seven dimensions of critical
thinking, is significantly and positively impacted by the History/Political Science major,
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alongside race and parental education. Conversely, the combination of the results from
both models for judgment, details the environment does not make a significant impact.
Open-mindedness and Number of Diversity Courses Taken
In the Open-mindedness and Number of Diversity Courses Taken Model, the
“Undeclared Major” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = .227, p < .05). Two other majors are also statistically significant,
History/Political Science and Humanities majors. History/Political Science major makes
a statistically significant unique contribution explaining the dependent variable, after
controlling the variance for all variables (β = .169, p < .05). The Humanities major makes
a statistically significant unique contribution explaining the dependent variable, after
controlling the variance for all variables (β = .162, p < .05). The “Socialized with
Different Ethnic Group” variable makes, statistically significant and unique contribution
to explaining the dependent variable, after controlling the variance for all variables (β =
.100, p < .05).The number of diversity courses taken is not statistically significant. Racial
awareness workshops and community service are also not statistically significant.
Open-mindedness and Diversity Course Typology
In the Open-mindedness and Number of Diversity Course Typology Model, the
“Undeclared Major” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = .218, p < .05). Two other majors are also statistically significant,
History/Political Science and Humanities majors. History/Political Science major makes
a statistically significant unique contribution explaining the dependent variable, after
133
controlling the variance for all variables (β = .167, p < .05). The Humanities major makes
a statistically significant unique contribution explaining the dependent variable, after
controlling the variance for all variables (β = .164, p < .05). The “Socialized with
Different Ethnic Group” variable makes, statistically significant and unique contribution
to explaining the dependent variable, after controlling the variance for all variables (β =
.101, p < .05).The diversity course typology is not statistically significant. Racial
awareness workshops and community service are also not statistically significant.
In combining the results from both models for open-mindedness, it is noted that
the environment does not make a significant impact. Open-mindedness, as a dependent
variable and one of seven dimensions of critical thinking is significantly and positively
impacted by Undeclared, History/Political Science and Humanities majors.
Self-confidence and Number of Diversity Courses Taken
In the Self-confidence and Number of Diversity Courses Taken Model, the
Engineering major variable makes the strongest, significant and unique contribution to
explaining the dependent variable, after controlling the variance for all variables (β = -
.153); it is not statistically significant. Racial awareness workshops are the only
statistically significant explanatory variable; it makes a unique contribution explaining
the dependent variable, after controlling the variance for all variables (β = .090, p < .05).
The number of diversity courses taken and community service are also not statistically
significant.
Self-confidence and Number of Diversity Course Typology
In the Self-confidence and Diversity Course Typology Model, the Health
Profession major variable makes the strongest, significant and unique contribution to
134
explaining the dependent variable, after controlling the variance for all variables (β = -
.155); it is not statistically significant. Racial awareness workshops are the only
statistically significant explanatory variable; it makes a unique contribution explaining
the dependent variable, after controlling the variance for all variables (β = .091, p < .05).
The diversity course typology and community service are also not statistically significant.
Self-confidence, as a dependent variable and one of seven dimensions of critical
thinking, is statistically positively impacted by racial awareness workshops. The
combination of the results from both models for self-confidence, details the environment
does make a significant and positive impact.
Systematicity and Number of Diversity Courses Taken
In the Systematicity and Number of Diversity Courses Taken Model, the
“Mathematical Ability” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = -.589, p < .001). Humanities, Fine Arts and “Other” majors are also
statistically significant input variables. The Humanities major makes a statistically
significant unique contribution explaining the dependent variable, after controlling the
variance for all variables (β = .140, p < .05). The Fine Arts major makes a statistically
significant unique contribution explaining the dependent variable after controlling the
variance for all variables (β = .151, p < .05). The “Other” major makes a statistically
significant unique contribution explaining the dependent variable, after controlling the
variance for all variables (β = .190, p < .05). The number of diversity courses taken is
statistically significant and makes a unique contribution to explaining the dependent
135
variable, after controlling the variance for all variables (β = .065, p < .05). Racial
awareness workshops and community service are not statistically significant.
Systematicity and Diversity Course Typology
In the Systematicity and Diversity Course Typology Model, the “Mathematical
Ability” variable makes the strongest, statistically significant and unique contribution to
explaining the dependent variable, after controlling the variance for all variables (β = -
.594, p < .001). Humanities, Fine Arts and “Other” majors are also statistically
significant input variables. The Humanities major makes a statistically significant unique
contribution explaining the dependent variable, after controlling the variance for all
variables (β = .139, p < .05). The Fine Arts major makes a statistically significant unique
contribution explaining the dependent variable, after controlling the variance for all
variables (β = .151, p < .05). The “Other” major makes a statistically significant unique
contribution explaining the dependent variable, after controlling the variance for all
variables (β = .200, p < .05). The diversity course typology, racial awareness workshops
and community service are not statistically significant.
Combining the results from both models for systematicity, it is noted that the
environment does make a strong significant negative and positive impact on specific
variables. Systematicity, as a dependent variable and one of seven dimensions of critical
thinking is significantly negatively impacted by the number of diversity courses taken
and Humanities, Fine Arts and “Other” majors were statistically and positively impacted.
Truth-seeking and Number of Diversity Courses Taken
In the Truth-seeking and Number of Diversity Courses Taken Model, the
“Promote Racial Understanding” variable makes the strongest, statistically significant
136
and unique contribution to explaining the dependent variable, after controlling the
variance for all variables (β = .255, p < .001). Race, is the only statistically significant
student characteristic input variable; it makes a minor unique contribution explaining the
dependent variable, after controlling the variance for all variables (β = -.189, p < .05).
The number of diversity courses taken is statistically significant and makes a unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = .132, p < .01). Racial awareness workshops is statistically significant and
makes a minor unique contribution to explaining the dependent variable, after controlling
the variance for all variables (β = .168, p < .001). Community Service is not statistically
significant.
Truth-seeking and Diversity Course Typology
In the Truth-seeking and Diversity Course Typology Model, the “Promote Racial
Understanding” variable makes the strongest, statistically significant and unique
contribution to explaining the dependent variable, after controlling the variance for all
variables (β = .257, p < .001). Race, is the only statistically significant student
characteristic input variable; it makes a minor unique contribution explaining the
dependent variable, after controlling the variance for all variables (β = -.183, p < .05).
The course typology and community service are not statistically significant. Racial
awareness workshops is statistically significant and makes a unique contribution to
explaining the dependent variable, after controlling the variance for all variables (β =
.172, p < .05).
In combining the results from both models for truth-seeking, it is noted that the
environment does make a strong significant and positive impact. Truth-seeking, as a
137
dependent variable and one of seven dimensions of critical thinking is significantly and
positively impacted by race, the number of diversity courses taken and racial awareness
workshops.
Major Findings
After analyzing data and juxtaposing the study’s subordinate research questions, it
can be empirically proven that certain environmental factors, the Number of Diversity
Courses Taken and Racial Awareness Workshops, positively impact student’s critical
thinking skills. Five out of seven of the dimensions of critical thinking: (1) Analyticity;
(2) Inquisitiveness; (3) Self-Confidence; (4) Systematicity; and (5) Truth-seeking are
impacted by environmental factors. Also, it may be noted that the number of diversity
courses taken by students positively impact the majority of critical thinking dimensions.
In turn, the number of diversity courses taken impact student’s critical thinking skills.
Additionally, racial awareness workshops impact the majority of critical thinking
dimensions. In turn, racial awareness impact student’s critical thinking skills.
Implications
The study’s major findings, the number of diversity courses taken and racial
awareness workshops impact student’s critical thinking skills, are significant in a few
different areas in higher education administration. Specifically, the findings have policy,
curricular and budgetary implications.
Policy & Curriculum
As mentioned in the first chapter, like most universities, Western University has a
policy that undergraduate students fulfill a general education requirement in order to
graduate and, in some cases, commence study in a particular major. Accordingly, the
138
diversity course requirement is part of university policy. It would be a reasonable
assumption that university agents continue to support diversity course requirements as
part of general education. In fact, the findings may encourage university agents to
increase the amount of units or racial awareness workshops necessary. This study can
provide the justification for policy and curriculum reform for diversity courses and serve
as the impetus for evaluation of the impact of higher education environments on student’s
cognitive development. This impact is a much larger concept and endeavor, but this
study, on a micro level, lends credence to the feasibility and applicability of such a
project. However, commencing a similar evaluation in size and scope to this study would
require resources. To engage an evaluation in size and scope to higher education
environments and cognitive development would require a vast amount of resources.
would be.
Budget
Budgets are the drivers for activities of most organizations, including universities.
When universities launch initiatives such as a diversity course requirement, budgets for
academic units are affected. Needless to say, most schools within Western University
offer courses that meet the diversity requirement to ensure tuition dollars are directed
toward the efforts of their specific school. In turn, if university officials maintain or
increase the diversity course requirement, schools will likely respond accordingly.
Notwithstanding, if university officials use this study’s findings to make policy or
curriculum changes, budgets will inevitability adjust to meet the need of the change.
139
Recommendations
In the prior section, policy and curriculum implications are outlined. This section
continues to discuss some of the ideas that emerged in the prior section. Specifically, this
section will discuss the establishment of expanded higher education environment and
student cognitive development evaluation efforts and some areas for institutional
improvement.
Student Cognitive Development Study
As described above, and throughout this chapter, the findings from this study
demonstrate the number of diversity courses taken and racial awareness workshops
impact students’ critical thinking skills. These findings create an opportunity to continue
and expand upon this study. To this end, it is recommended that Western University
provides institutional resources to establish a longitudinal data warehouse that collects
specific data, similar to the input, environment and output variables of this study. In
conjunction with the development of the longitudinal data warehouse, an analytic
dashboard should be created to extract and manipulate data for various purposes. The
analytics established in the dashboard should allow for administrators and researchers
alike to leverage the data to create programs and interventions or conduct research.
In short, this effort can continue to assess diversity course information, but
eventually could assess all university courses. The continual process of data collection
would create an institutional universe of student data to include pre-college, Western
University environmental and post-college data. This initiative would advance the study
of the impact of higher education on student learning. Furthermore, moving beyond
Western University this effort could be portable and applied at other universities of
140
organizations that want to track the environmental factors that contribute to cognitive
development.
Other Areas for Institutional Improvement
The final recommendation that this study will offer is in response to the finding
that community service is not statistically significant variable in any of the critical
thinking dimensions. Racial awareness workshops were found to be statistically
significant in many of the critical thinking dimensions. This study did not formally
address this issue, but in the development phase of the Diversity Course Typology, it was
noted that racial awareness workshops were also followed by faculty lead discussions and
writing assignments. Conversely, community service participation was typically co-
curricular activities and not supported by discussions or assignments. In turn, this could
be an indication of community service statistical insignificance in impacting student’s
critical thinking skills. Notwithstanding, this study recommends courses that offer a
community service component be considered for the diversity requirement or some
courses that are already designated as diversity courses include a community service
component that is supported by lecture, discussion and/or writing assignments.
Additionally, this recommendation is based on a postulate that was not directly covered
in this study and in the conclusion section of this chapter; it is discussed as an area for
future research.
Limitations
The purpose of this study is to provide an evaluation of the impact of the
educational environment on student’s cognitive development, specifically students’
critical thinking skills. The longitudinal design and quantitative approach of this study
141
provide a solid framework to engage the study. Nevertheless there are limitations to both
of those aspects of the study’s design.
The primary limitation in any longitudinal study is aging. The chief critics of
socio-cultural theory (Vygotsky) note that environmental impacts may not be due to the
zones of proximal development; it may be caused by physical development and natural
maturity of the students (Miller). This study is not impervious to those types of criticism.
Without having the ability to create a true experiment, with control and test groups, it is
nearly impossible to rule out other/external factors. Therefore, the phenomena found in
this study are limited to the variables being tested in the model that frames this study.
This leads to other criticisms of generalizability. This study focuses on one institution and
that limits the ability to apply the findings to other institutions.
Another major limitation is the use of one variable as a proxy for each of the
seven critical thinking variables. Albeit an attempt to synthesize the seven critical
thinking dimensions into this study, it must be noted that use of one proxy question from
the CIRP and WUSS as a proxy for each of the seven critical thinking variable is a loose
synthesis. Accordingly, all the variation that could be noted in each of the critical
thinking dimensions may not be accounted. This would be more problematic if this study
was using G-theory to make broader and more specific generalizations about the impact
of diversity courses on critical thinking skills. Notwithstanding, the one proxy variable
for each of the seven critical thinking variables is a technical limitation to this study.
Even still, there are also other technical issues with the study, the reach of the
model and collinearity. Many of the regressions report low R squared. This means that
the overall model only accounts for a small amount of the change in the dependent
142
variable. Additional technical concerns with collinearity are presented in the study. Some
of the regression models maintain high condition index, scores over 30.00. Accordingly,
there is collinearity issues that are best attributed to the number of Majors outlined as
input variables.
A potential design flaw in the longitudinal design of the study is the alignment of
pre and post variables. This study leverages two different surveys, CIRP and WUSS. In
view of that, each survey was not thought of the other in their design. Therefore, this
study in some cases use questions that ask similar and not exact questions as variables in
the study. Additionally, to synthesize the seven dimensions of critical thinking, unique
proxy variables are used to assess the change of each unique critical thinking dimension.
Similar to the CIRP and WUSS not being created in conjunction with each other, neither
the CIRP nor the WUSS were created as solely a critical thinking survey. As a result, the
proxy variables used to address the dimensions of critical thinking were not intended for
the singular use critical thinking assessment. Although the application of the critical
thinking dimensions is sound, the proxy variables may not capture the entirety and
uniqueness of each dimension.
Further, in preparing the data set, another design limitation must be noted. When
the data set was prepared it was determined that most undergraduate degrees require 128
units. This unit requirement is based on students completing 16units a semester, for 2
semesters, for 4 years. Therefore, when the data set was prepared an additional year was
considered and the data set included up to 160 units or 32 additional units, which equates
to 2 complete 16 unit semesters. Additionally, the data set also only includes diversity
courses taken up to 40 units of diversity courses or the first 10 diversity courses students
143
have taken. Consequently, if students took a diversity course after 160 units that data was
not captured in this study. Also, if a student took more than 11 or more diversity courses
that data was not captured in this study.
Intuitively, courses that deal with more complex issues should have more
statistical significance in change of critical thinking skills, or one would think. However,
there was no statistical significance found in the diversity course typology models. This is
more than likely attributed to the scoring and coding system of the typology. The scoring
system of the typology is based on course syllabi. The syllabi is a proxy for what actually
takes place in the courses and simply stated the syllabi may not be a perfect indication of
the quality and intensity of the course.
The last limitation in the study is the age of the data. Although data was collected
from 2004 through 2008 and was vetted and prepared in 2010, some may question why
more recent data is not used in the study. To address this specific issue, a
recommendation is offered earlier in this chapter that outlines continued research in
Student Cognitive Development. If additional institutional support is provided to
continue this research, there will be ongoing assessment and the most up-to-date data can
be accessed and reported.
Future Research
Throughout this final chapter, there are a number of indications about future
research; this section completes those references. The first recommendation for future
research is based on diversity courses. The issues cited earlier is this chapter, with regards
to the diversity course typology, should be taken in to consideration and research should
be conducted on the impact of the intensity of diversity courses on student’s cognitive
144
development. Akin to that research, the outcomes from each course should also be
studied; student performance is a factor in how engaged a student is with the material and
with the faculty (Cole, 2000). Accordingly, if students are more engaged, there may be
greater gains in cognitive development. Community service, as an activity, should have
yielded similar gains as compared to racial workshops. A longitudinal study based on
individual community service events, how do students think before the event and how do
student think after the event, should offer an evaluation that could help determine if
community service is an environmental factor that should be considered for longer
longitudinal studies. Additionally, community service projects that are supported by
lectures, faculty lead discussion and writing assignments should be separated from co-
curricular community service events. In turn, the curriculum based community service
projects should be assessed for its ability to impact student’s critical thinking skills.
Another significant factor in the higher education environment is peer-interactions
(Bolen, 2011). In turn, fraternal organizations, student organizations, themed housing and
athletic teams should be studied as environmental factors in student’s cognitive
development. In all, for any of this future research to be executed, institutional and
philanthropic support must be leant to researchers to provide the necessary resources to
engage quandaries of what environmental factors impact student’s cognitive
development. It is the fiduciary responsibility of all university agents to engage research
that speaks to how student’s develop their, if not gain a better understanding to continue
to improve research and instruction in higher education.
145
Conclusion
The final section of this chapter and this study focus on providing a
comprehensive summary of the study and defining areas for future research. The
summary section outlines the major findings and literary support. Lastly, the study will
conclude with specific areas for suture research.
This study answers the leading research question, how do diversity courses
impact student’s critical thinking skills, with the initial major finding, the number of
diversity courses taken impact students critical thinking skills. This notion is supported
by Nelson-Laird, Engberg and Hurtado (2005) and Pascarella’s (2001) research. The fact
that this major finding is longitudinal in nature is consistent with Giancarlo and Facione’s
(2001) as well as Vygotsky concepts on Zones for Proximal Development.
Moreover, the other major finding, racial awareness workshops impacts students
critical thinking skills is also supported by Vygotsky’s notions of Zones of Proximal
Development. Outside of actual diversity courses impacting student’s critical thinking
skills, other diversity experiences that contribute to the higher education environment
impact students critical thinking skills; this is also supported by findings of Nelson-Laird,
Engberg and Hurtado (2005) and Pascarella’s (2001), which indicate diversity
experiences positively, impact critical thinking skills.

146
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Journal of Higher Education, Vol.56, No. 6, November/December 1985.
Pascarella, E. T. & Terenzini, P. T. (1991). Twenty years of research on college students:
Lessons for future research. Research in Higher Education 32(1), 83-92.
Pascarella, E. T. & Terenzini, P. T. (1998). Studying college students in the 21
st
century:
Meeting new challenges. The Review of Higher Education 21(2), 151-165.
Pascarella, E. T. (2001, November/December). Cognitive growth in college: Surprising
and reassuring findings from the national study of student learning. Change, 33,
20-27.
Pascarella, E. T., Palmer, B., Moye, M., & Pierson, C. T. (2001). Do diversity
experiences influence the development of critical thinking? Journal of College
Student Development, 42, 257-271.
Pascarella, E.T. & Terenzini, P.T. (2005). How College Affects Students. Jossey-Bass:
San Francisco.
Sleeter, C. E., & Grant, C. A. (1994). Making choices for multicultural education:
Fiveapproaches to race, class, and gender. New York: Macmillan.
Piaget, J. (1975). The equilibrium of cognitive structures: The central problem of intellectual
development. Chicago: University of Chicago Press.
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Ruble, D. N. (1994). A phase model of transitions: Cognitive and motivational
consequences. Advances in Experimental Social Psychology, 26, 163-214.
Spiezio, K. E., Baker, K. Q. & Boland, K. (2006). General education and civic
engagement: An empirical analysis of pedagogical possibilities. The Journal of
General Education, 54(4), 273-292.
Terenzini, P. T., Springer, L., Pascarella, E. T., & Nora, A. (1995). Influences affecting
the development of students’ critical thinking skills. Research in Higher
Education, 36(1), 23-39.
Terenzini, P. T. & Wright, T. M. (1987). Influences on students’ academic growth during
four years of college. Research in Higher Education, 26(2), 161-179.
Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent
research. Review of Educational Research, 45, 89-125.
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition
(2
nd
ed.). Chicago: The University of Chicago Press.
Vygotsky, L. S. (1978). Internalization of higher cognitive functions. In M. Cole, V.
John-Steiner, & E. Souberman (Eds. & Trans.), Mind in society: The development
of higher psychological process (pp. 52-57). Cambridge: Harvard University
Press.
Western University Course Catalogue 2007
Western University Senior Survey http://www.usc.edu/student
affairs/student_surveys/surveys.html on January 21, 2010).
Western University Enrollment Statistics http://education-
portal.com/directory/school/University_of_Southern_California.html
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APPENDIX A
Diversity Course Requirement Guidelines (Revised 04/22/09)

Purpose and rationale
The Diversity Course Requirement is designed to meet an important educational need of
undergraduates. The current generation of undergraduates, and those for some years to
come, will increasingly be faced with issues arising from the diversity of the human
condition. These issues, for example, about equity and equality between men and women,
about racial and other biases and their social and cultural consequences, will have important
ramifications for students’ personal, professional, and intellectual lives. We must equip our
students with the background knowledge and analytical skills which will enable them to
understand and respect differences so that they may view unfamiliar customs and
perspectives not with suspicion born of ignorance, but with an understanding of the
opportunities this diversity makes possible for our private and public aspirations.

The Diversity Course Requirement represents institutional recognition of the
importance of issues arising from human diversity and of the University’s commitment
to educate students about these issues. Such education is particularly important in light of
an ASCUS strategic focus on having a global presence and our commitment to preparing
undergraduate students (both domestic and foreign born) to be global citizens.

Guidelines for courses
Human diversity has many dimensions. The dimensions addressed in courses
satisfying the Diversity Course Requirement may include but are not limited to: age,
disability, ethnicity, gender, language, race, nationality, religion, sexual orientation, and
social class. Courses satisfying the Diversity Course Requirement must examine two or
more dimensions of human diversity and must consider these dimensions in terms of
their social and/or cultural consequences. These consequences need to explore how
differences among social groups have led to conflicts, and may include possible solutions
to those conflicts or address how living in a diverse society can function as a form of
enrichment. As a rule, at least one third of the course should be addressed to these issues,
and this should be proportionately reflected in the assigned readings, lectures, and topics
for papers, quizzes, tests, or other graded formal course requirements. Although courses
must include at least two dimensions of human diversity, it is not the case that equal or
near equal attention must be given to each; in many cases the main focus will be on one
152
dimension of diversity, with the other dimension brought in to illuminate general issues.
Interdisciplinary approaches to these issues are especially encouraged.
The Diversity Course Requirement was adopted so that students will understand issues
and conflict arising from human differences in contemporary American and
international environments. Each course should give students the opportunity for personal
reflection on the formation of their own attitudes toward other groups and the effect of
those attitudes on the institutions (e.g., cultural, professional, political). Courses carefully
focused on issues of diversity in specific societies outside the Anglo-American
world may also be considered. Courses that examine diversity from an international or
historical perspective should include some discussion of (or connection to) an American
context.
All syllabi are expected to show how the topics addressed related to issues facing
students in a contemporary context. No particular ‘slant’ or conclusion regarding the
issues addressed in the course is mandated by the requirement; the Diversity Requirement
Committee affirms that academic freedom is a fundamental value, and that it will take no
action which threatens to infringe the legitimate academic freedom of any member of
the faculty.
Any course which satisfies the Diversity Requirement satisfies the University
requirement for any student who passes the course, regardless of his or her major or
other academic program. This does not mean that courses satisfying the requirement
cannot be restricted in enrollment to students in a particular academic program, or to
students who have satisfied certain prerequisites for admission to the course. Courses
satisfying the Diversity Requirement may also satisfy General Education and/or major
requirements.
Procedure for approving course proposals
The Diversity Requirement Committee reviews course proposals to determine whether
or not they satisfy the Diversity Requirement. Approved courses will be listed in the
University Catalogue, and Schedule of Classes, as satisfying the Diversity Requirement.
The committee will consider new and revised courses as they are proposed, and will
conduct periodic (every five years) reviews of the courses listed as satisfying the
requirement to insure that they continue to be effective in meeting the relevant
educational needs of the students.
To be considered for inclusion in the list of Diversity Requirement courses, a faculty
member or academic department must submit a proposal including the following
information:

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Names and qualifications of faculty members in the department who would
teach the course
All information on the UCC course approval form (even if the course in question
has previously been approved by UCC)
A syllabus including a week by week breakdown of readings and topics, and for
those weeks containing material addressing issues of diversity, a brief description of
how that material relates to these issues;
A complete bibliography of required and recommended readings;
A general statement in the syllabus briefly explaining how the course
meets the criteria for satisfying the Diversity Requirement (e.g., “This
course fulfills the Diversity Requirement by focusing on two different
forms of difference: race, and to a lesser extent, class. Students will learn
about race and racism in several ways, including housing segregation, the
racialized nature of the economy, and how institutional racism works,
and how learning about and living in a diverse society can function as a
form of enrichment
• An indication of the comparative and/or interdisciplinary elements, if any,
of the methodology of the course.

The submissions are to be sent the Curriculum Coordination Office, which will coordinate
the Diversity Requirement course selection process. Faculty whose proposals are not
at first accepted are encouraged to respond to committee comments and to revise their
courses before the Diversity Requirement Committee arrives at a final decision on that
proposal.

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APPENDIX B
Diversity Committee Course Review Sheet

155
APPENDIX C
Committee on Diversity Requirement Courses (DRC)
The Committee on Diversity Requirement Courses (DRC) reports to the office of the
president through the office of the provost and recommends to the provost courses to
meet the Diversity Requirement that all undergraduate students must fulfill. These
courses, which will be designated by the letter "m," may range from general education
courses to courses restricted to students in a certain major. Any of these courses must
satisfy the requirement for any major in the event that a student transfers from one major
to another. Approval of a course will be based upon the committee's review of its
syllabus or a set of typical syllabi, which will then be a model for instructors teaching the
course. The committee also reviews sets of required major courses that academic units
may present as alternatives to the single-course method of fulfilling this requirement and
comments upon their comparability to the single courses that are approved. Finally, the
committee may be asked to take up any larger issues that may arise concerning the
requirement, in the event, for instance, of an insufficient number of courses being
approved to meet students' needs.
The DRC makes its recommendations directly to the provost and reports its decisions as
information items on the Undergraduate Curriculum Committee (UCC) agenda.
6/98

156
APPENDIX D
Typology of Diversity Courses (Cole & Sundt, 2008)

157
APPENDIX E
Western University’s Freshman Profile and Admission Information (2004-2005)

158
APPENDIX F
Role and Mission of Western University
The central mission of the Western University is the development of human beings and society as
a whole through the cultivation and enrichment of the human mind and spirit. The principal
means by which our mission is accomplished are teaching, research, artistic creation, professional
practice and selected forms of public service.
Our first priority as faculty and staff is the education of our students, from freshmen to post-
doctorals, through a broad array of academic, professional, extracurricular and athletic programs
of the first rank. The integration of liberal and professional learning is one of WU's special
strengths. We strive constantly for excellence in teaching knowledge and skills to our students,
while at the same time helping them to acquire wisdom and insight, love of truth and beauty,
moral discernment, understanding of self, and respect and appreciation for others.
Research of the highest quality by our faculty and students is fundamental to our mission. WU is
one of a very small number of premier academic institutions in which research and teaching are
inextricably intertwined, and on which the nation depends for a steady stream of new knowledge,
art, and technology. Our faculty are not simply teachers of the works of others, but active
contributors to what is taught, thought and practiced throughout the world.
WU is pluralistic, welcoming outstanding men and women of every race, creed and background.
We are a global institution in a global center, attracting more international students over the years
than any other American university. And we are private, unfettered by political control, strongly
committed to academic freedom, and proud of our entrepreneurial heritage.
An extraordinary closeness and willingness to help one another are evident among WU students,
alumni, faculty, and staff; indeed, for those within its compass the Trojan Family is a genuinely
supportive community. Alumni, trustees, volunteers and friends of WU are essential to this family
tradition, providing generous financial support, participating in university governance, and
assisting students at every turn.
In our surrounding neighborhoods and around the globe, WU provides public leadership and
public service in such diverse fields as health care, economic development, social welfare,
scientific research, public policy and the arts. We also serve the public interest by being the
largest private employer in the city of Los Angeles, as well as the city's largest export industry in
the private sector.
WU has played a major role in the development of southern California for more than a century,
and plays an increasingly important role in the development of the nation and the world. We
expect to continue to play these roles for many centuries to come. Thus our planning,
commitments and fiscal policies are directed toward building quality and excellence in the long
term.
Adopted by the WU Board of Trustees, February, 1993

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APPENDIX G
2004 Cooperative Institutional Research Program (CIRP) Instrument

160

161

162

163
APPENDIX H
2008 Western University Senior Survey (WUSS) Instrument

Name Label (question text)
WUID
PID
time_degree How long has it taken you to earn your degree?
deg_1
How important were the following factors in increasing the
time it took to earn your degree: Changed major one or
more times
deg_2
How important were the following factors in increasing the
time it took to earn your degree: Added additional majors
and/or minors
deg_3
How important were the following factors in increasing the
time it took to earn your degree: Couldn't get courses when
I needed them
deg_4
How important were the following factors in increasing the
time it took to earn your degree: Poor advising
deg_5
How important were the following factors in increasing the
time it took to earn your degree: Took extra time to improve
my GPA
deg_6
How important were the following factors in increasing the
time it took to earn your degree: Internship
deg_7
How important were the following factors in increasing the
time it took to earn your degree: Travel or study abroad
deg_8
How important were the following factors in increasing the
time it took to earn your degree: Extracurricular activities
deg_9
How important were the following factors in increasing the
time it took to earn your degree: Work/employment
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deg_10
How important were the following factors in increasing the
time it took to earn your degree: Family commitments
deg_11
How important were the following factors in increasing the
time it took to earn your degree: Illness or accident
deg_12
How important were the following factors in increasing the
time it took to earn your degree: Other
prof_1
How often have professors at WU provided you with the
following: Encouragement to pursue graduate/professional
study
prof_2
How often have professors at WU provided you with the
following: An opportunity to work on a research project
prof_3
How often have professors at WU provided you with the
following: Advice and guidance about your educational
program
prof_4
How often have professors at WU provided you with the
following: Respect (treated you like a colleague/peer)
prof_5
How often have professors at WU provided you with the
following: An opportunity to publish a paper
prof_6
How often have professors at WU provided you with the
following: Emotional support and encouragement
prof_7
How often have professors at WU provided you with the
following: A letter of recommendation
prof_8
How often have professors at WU provided you with the
following: Assistance to improve your study skills
prof_9
How often have professors at WU provided you with the
following: Negative feedback about your academic work
prof_10
How often have professors at WU provided you with the
following: Intellectual challenge and stimulation
prof_11
How often have professors at WU provided you with the
following: An opportunity to discuss your coursework
165
outside of class
prof_12
How often have professors at WU provided you with the
following: Help in achieving your professional goals
first_1
In your first year at WU, did you: Participate in Learning
Communities offered by the College of LAS
first_2
In your first year at WU, did you: Take a Freshman Seminar
course
first_3
In your first year at WU, did you: Participate in programs
sponsored by the residential hall or college where you lived
(if applicable)
first_4
In your first year at WU, did you: Participate in other
programs designed for freshmen
first_5
In your first year at WU, did you: Perform community
service work as part of a course
first_6
In your first year at WU, did you: Perform community
service work that was not required by a course
ever_1
Since enrolling at WU, have you ever: Had a part-time job
on campus
ever_2
Since enrolling at WU, have you ever: Had a part-time job
off campus
ever_3
Since enrolling at WU, have you ever: Worked full-time
while attending school
ever_4
Since enrolling at WU, have you ever: Participated in
student government
ever_5
Since enrolling at WU, have you ever: Attended a
racial/cultural awareness workshop
ever_6
Since enrolling at WU, have you ever: Participated in an
internship program
ever_7
Since enrolling at WU, have you ever: Participated in
leadership training
166
ever_8 Since enrolling at WU, have you ever: Studied abroad
ever_9
Since enrolling at WU, have you ever: Participated in
undergraduate research or creative projects
ever_10
Since enrolling at WU, have you ever: Participated in a WU
Honors Program
freq_1
Since enrolling at WU, indicate how often you: Worked on
independent study projects
freq_2
Since enrolling at WU, indicate how often you: Discussed
course content with students outside of class
freq_3
Since enrolling at WU, indicate how often you: Worked on
group projects in class
freq_4
Since enrolling at WU, indicate how often you: Had been a
guest in a professor's home
freq_5
Since enrolling at WU, indicate how often you: Participated
in intramural sports
freq_6
Since enrolling at WU, indicate how often you: Failed to
complte homework on time
freq_7
Since enrolling at WU, indicate how often you: Felt bored
in class
freq_8
Since enrolling at WU, indicate how often you: Studied
with other students
freq_9
Since enrolling at WU, indicate how often you: Challenged
a professor's ideas in class
freq_10
Since enrolling at WU, indicate how often you: Voted in a
student election
freq_11
Since enrolling at WU, indicate how often you: Performed
community service work as part of a course
freq_12
Since enrolling at WU, indicate how often you: Missed
class due to employment
167
freq_13
Since enrolling at WU, indicate how often you: Tutored
another college student
freq_14
Since enrolling at WU, indicate how often you: Felt
supported by my family
freq_15
Since enrolling at WU, indicate how often you: Participated
in Student Affairs-sponsored activities
freq_16_myWU How often do you use the MyWU student portal?
freq_17
Please indicate how often you engaged in each of these
activities during the past year: Smoked cigarettes
freq_18
Please indicate how often you engaged in each of these
activities during the past year: Felt lonely or homesick
freq_19
Please indicate how often you engaged in each of these
activities during the past year: Socialized with someone
from another racial/ethnic group
freq_20
Please indicate how often you engaged in each of these
activities during the past year: Felt depressed
freq_21
Please indicate how often you engaged in each of these
activities during the past year: Felt overwhelmed by all I
had to do
freq_22
Please indicate how often you engaged in each of these
activities during the past year: Attended a religious service
freq_23
Please indicate how often you engaged in each of these
activities during the past year: Drank beer
freq_24
Please indicate how often you engaged in each of these
activities during the past year: Drank wine or liquor
freq_25
Please indicate how often you engaged in each of these
activities during the past year: Performed volunteer work
freq_26
Please indicate how often you engaged in each of these
activities during the past year: Participated in organized
demonstrations
168
freq_27
Please indicate how often you engaged in each of these
activities during the past year: Discussed politics
freq_28
Please indicate how often you engaged in each of these
activities during the past year: Overslept and missed class or
appointment
freq_29
Please indicate how often you engaged in each of these
activities during the past year: Sought personal counseling
freq_30
Please indicate how often you engaged in each of these
activities during the past year: Visited an art gallery or
museum
freq_31
Please indicate how often you engaged in each of these
activities during the past year: Discussed religion
org_1
In the past academic year, indicate the types of
organizations that you have been involved in and your level
of involvement: WU-based
org_2
In the past academic year, indicate the types of
organizations that you have been involved in and your level
of involvement: Off-campus
hours_1
During the past year, how much time did you spend during
a typical week doing the following activities:
Studying/homework
hours_2
During the past year, how much time did you spend during
a typical week doing the following activities: Socializing
with friends
hours_3
During the past year, how much time did you spend during
a typical week doing the following activities: Talking with
faculty outside of class
hours_4
During the past year, how much time did you spend during
a typical week doing the following activities:
Exercising/sports
hours_5
During the past year, how much time did you spend during
a typical week doing the following activities: Partying
169
hours_6
During the past year, how much time did you spend during
a typical week doing the following activities: Working (for
pay)
hours_7
During the past year, how much time did you spend during
a typical week doing the following activities: Volunteer
work
hours_8
During the past year, how much time did you spend during
a typical week doing the following activities: Student
clubs/groups
hours_9
During the past year, how much time did you spend during
a typical week doing the following activities: Watching TV
hours_10
During the past year, how much time did you spend during
a typical week doing the following activities:
Housework/child care
hours_11
During the past year, how much time did you spend during
a typical week doing the following activities: Reading for
pleasure
hours_12
During the past year, how much time did you spend during
a typical week doing the following activities: Using a
personal computer
hours_13
During the past year, how much time did you spend during
a typical week doing the following activities: Commuting
hours_14
During the past year, how much time did you spend during
a typical week doing the following activities: Playing video
games
hours_15
During the past year, how much time did you spend during
a typical week doing the following activities:
Prayer/meditation
hours_16
During the past year, how much time did you spend during
a typical week doing the following activities: Classes/labs
self_1
Rate yourself on each of the following traits as compared
with the average person your age: Academic ability
170
self_2
Rate yourself on each of the following traits as compared
with the average person your age: Artistic ability
self_3
Rate yourself on each of the following traits as compared
with the average person your age: Athletic ability
self_4
Rate yourself on each of the following traits as compared
with the average person your age: Competitiveness
self_5
Rate yourself on each of the following traits as compared
with the average person your age: Cooperativeness
self_6
Rate yourself on each of the following traits as compared
with the average person your age: Creativity
self_7
Rate yourself on each of the following traits as compared
with the average person your age: Drive to achieve
self_8
Rate yourself on each of the following traits as compared
with the average person your age: Emotional health
self_9
Rate yourself on each of the following traits as compared
with the average person your age: Leadership ability
self_10
Rate yourself on each of the following traits as compared
with the average person your age: Mathematical ability
self_11
Rate yourself on each of the following traits as compared
with the average person your age: Physical health
self_12
Rate yourself on each of the following traits as compared
with the average person your age: Popularity
self_13
Rate yourself on each of the following traits as compared
with the average person your age: Public speaking ability
self_14
Rate yourself on each of the following traits as compared
with the average person your age: Self-confidence
(intellectual)
self_15
Rate yourself on each of the following traits as compared
with the average person your age: Self-confidence (social)
self_16
Rate yourself on each of the following traits as compared
171
with the average person your age: Self-understanding
self_17
Rate yourself on each of the following traits as compared
with the average person your age: Spirituality
self_18
Rate yourself on each of the following traits as compared
with the average person your age: Understanding of others
self_19
Rate yourself on each of the following traits as compared
with the average person your age: Writing ability
self_20
Rate yourself on each of the following traits as compared
with the average person your age: Religiousness/religiosity
change_1
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Think critically
change_2
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Place current problems in
historical/cultural/philosophical perspective
change_3
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Formulate/create original ideas and
solutions
change_4
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Evaluate and choose between different
courses of action
change_5
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand the process of science and
experimentation
change_6
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Evaluate the role of science and technology
in society
172
change_7
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Acquire new skills and knowledge on my
own
change_8
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand myself: abilities, interests,
limitations, personality
change_9
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Develop self-esteem/self-confidence
change_10
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Develop a healthy lifestyle
change_11
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Appreciation of the cultural arts
change_12
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Function independently, without
supervision
change_13
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Plan and execute complex projects
change_14
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Work cooperatively
change_15
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Resolve interpersonal conflicts positively
change_16
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Identify moral and ethical issues
173
change_17
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Get along with people from different
races/cultures
change_18
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand different religions/belief
systems
change_19
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand issues related to gender
change_20
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand issues surrounding lesbian,
gay, bisexual, and transgender people
change_21
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand the problems facing the
community that surrounds WU
change_22
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand social problems facing our
nation
change_23
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Understand global issues
change_24
Compared with when you first enrolled at WU, please
indicate how your ability or skill level has changed in the
following areas: Become an informed citizen
success_1
Since enrolling at WU, how successful have you been in:
Understanding what your professors expect of you
academically
success_2
Since enrolling at WU, how successful have you been in:
174
Adjusting to the academic demands of college
success_3
Since enrolling at WU, how successful have you been in:
Managing your time effectively
success_4
Since enrolling at WU, how successful have you been in:
Getting to know faculty
success_5
Since enrolling at WU, how successful have you been in:
Developing close friendships with other students
success_6
Since enrolling at WU, how successful have you been in:
Utilizing campus services available to students
satis_1
Please rate your satisfaction with WU in each of the
following areas: General education courses
satis_2
Please rate your satisfaction with WU in each of the
following areas: Courses in your major field
satis_3
Please rate your satisfaction with WU in each of the
following areas: Overall quality of teaching by faculty
satis_4
Please rate your satisfaction with WU in each of the
following areas: Overall quality of teaching by TA’s
satis_5
Please rate your satisfaction with WU in each of the
following areas: The degree to which you can experience
intellectual growth
satis_6
Please rate your satisfaction with WU in each of the
following areas: Academic advising before declaring a
major
175
satis_7
Please rate your satisfaction with WU in each of the
following areas: Academic advising in your major
satis_8
Please rate your satisfaction with WU in each of the
following areas: Advising on other matters (careers, life
plans, etc.)
satis_9
Please rate your satisfaction with WU in each of the
following areas: WU's commitment to academic excellence
satis_10
Please rate your satisfaction with WU in each of the
following areas: Relationships with other students
satis_11
Please rate your satisfaction with WU in each of the
following areas: Relationships with faculty members
satis_12
Please rate your satisfaction with WU in each of the
following areas: Relationships with student affairs
administrative personnel
satis_13
Please rate your satisfaction with WU in each of the
following areas: Relationships with administrative
personnel in other offices
satis_14
Please rate your satisfaction with WU in each of the
following areas: Racial harmony on campus
satis_15
Please rate your satisfaction with WU in each of the
following areas: Services provided by the Division of
Student Affairs
satis_16
Please rate your satisfaction with WU in each of the
following areas: Services provided by other offices at WU
176
satis_17
Please rate your satisfaction with WU in each of the
following areas: The degree to which you have been able to
find out what's happening on campus
satis_18
Please rate your satisfaction with WU in each of the
following areas: The degree to which you can monitor your
academic progress and personal development
satis_19
Please rate your satisfaction with WU in each of the
following areas: The degree to which you can resolve
problems and express complaints
satis_20
Please rate your satisfaction with WU in each of the
following areas: WU's concern for you as an individual
satis_21
Please rate your satisfaction with WU in each of the
following areas: The degree to which you feel a sense of
belonging on campus
satis_22
Please rate your satisfaction with WU in each of the
following areas: The degree to which you feel safe and
secure on campus
satis_23
Please rate your satisfaction with WU in each of the
following areas: Overall college experience
choice_over
If you could make your college choice over, would you still
choose to enroll at WU?
continue
Do you plan to continue your studies beyond the bachelor's
degree?
degree_1
Which, if any, degrees do you plan to pursue: Law (L.L.B.
or J.D.) - Immediately upon graduation
177
degree_2
Which, if any, degrees do you plan to pursue: Law (L.L.B.
or J.D.) - Future plans
degree_3
Which, if any, degrees do you plan to pursue: Medicine
(M.D.) - Immediately upon graduation
degree_4
Which, if any, degrees do you plan to pursue: Medicine
(M.D.) - Future plans
degree_5
Which, if any, degrees do you plan to pursue: Other
Medical - Immediately upon graduation
degree_6
Which, if any, degrees do you plan to pursue: Other
Medical - Future plans
degree_7
Which, if any, degrees do you plan to pursue: Second
Bachelor's Degree - Immediately upon graduation
degree_8
Which, if any, degrees do you plan to pursue: Second
Bachelor's Degree - Future plans
degree_9
Which, if any, degrees do you plan to pursue: Master's
Degree - Immediately upon graduation
degree_10
Which, if any, degrees do you plan to pursue: Master's
Degree - Future plans
degree_11
Which, if any, degrees do you plan to pursue: Doctorate -
Immediately upon graduation
degree_12
Which, if any, degrees do you plan to pursue: Doctorate -
Future plans
grad_program
What graduate/professional degree program is of primary
178
interest to you?
V191

ug_influence
To what extent has your overall undergraduate experience
influenced your future plans for graduate or professional
studies?
accepted
Have you already been accepted to a graduate or
professional program?
school Which graduate or professional program will you attend?
grad_activity
What is most likely to be your principal activity upon
graduation?
other_activity If you answered "other" what is your principal activity?
employ_plan
If employment will most likely be your primary activity,
which of the following best describes your current state of
plans for employment immediately after graduation?
employ_type
If you have accepted a position, in what type of organization
or sector will you work?
other_employ If you answered "other" what is the type of organization?
occup_cat
Which occupation category best describes the position you
have accepted or are seeking?
related_ug
Is your prospective position related to your undergraduate
field(s) of study?
related_minor
Is your prospective position related to your undergraduate
minor?
prep_job
How well do you think WU has prepared you for the job
market?
job_offer
If you plan to work after graduation, do you have a job offer
yet?
impor_1
Indicate the importance to you personally of each of the
following items: Becoming accomplished in one of the
179
performing arts
impor_2
Indicate the importance to you personally of each of the
following items: Becoming an authority in my field
impor_3
Indicate the importance to you personally of each of the
following items: Obtaining recognition from my colleagues
for contributions to my special field
impor_4
Indicate the importance to you personally of each of the
following items: Influencing the political structure
impor_5
Indicate the importance to you personally of each of the
following items: Influencing social values
impor_6
Indicate the importance to you personally of each of the
following items: Raising a family
impor_7
Indicate the importance to you personally of each of the
following items: Having administrative responsibility for
the work of others
impor_8
Indicate the importance to you personally of each of the
following items: Being very well off financially
impor_9
Indicate the importance to you personally of each of the
following items: Helping others who are in difficulty
impor_10
Indicate the importance to you personally of each of the
following items: Making a theoretical contribution to
science
impor_11
Indicate the importance to you personally of each of the
following items: Writing original works (poems, novels,
short stories, etc.)
impor_12
Indicate the importance to you personally of each of the
following items: Creating artistic work (painting, sculpture,
decorating, etc.)
impor_13
Indicate the importance to you personally of each of the
following items: Becoming successful in a business of my
own
180
impor_14
Indicate the importance to you personally of each of the
following items: Becoming involved in programs to clean
up the environment
impor_15
Indicate the importance to you personally of each of the
following items: Developing a meaningful philosophy of
life
impor_16
Indicate the importance to you personally of each of the
following items: Participating in a community action
program
impor_17
Indicate the importance to you personally of each of the
following items: Helping to promote racial understanding
impor_18
Indicate the importance to you personally of each of the
following items: Keeping up to date with political affairs
impor_19
Indicate the importance to you personally of each of the
following items: Keeping up to date with issues related to
third world development and human rights
impor_20
Indicate the importance to you personally of each of the
following items: Becoming a community leader
impor_21
Indicate the importance to you personally of each of the
following items: Integrating spirituality into my life
impor_22
Indicate the importance to you personally of each of the
following items: Becoming a life-long learner
impor_23
Indicate the importance to you personally of each of the
following items: Identifying myself as a Trojan
impor_24
Indicate the importance to you personally of each of the
following items: Remaining active in the Trojan Network
social_class
Which of the following best describes your social class
when you were growing up?
register_vote Are you registered to vote?
current_zip What is your current local zip code
181
amt_borrowed
At the time you graduate, approximately what will be the
total amount borrowed to finance your undergraduate
education that you are personally responsible for repaying?
benefit_cost
Reflecting back, do you now think that the benefits you
have received from attending your undergraduate institution
were worth the financial costs to you and your family?
comments
Please provide any additional comments or questions you
have

182
APPENDIX I
Diversity Courses offered at Western University (2004-2008)
# COURSE
SUM
CRITERIO
N
TYPOLOG
Y
LEVEL
1 AHIS 250 5 1

Mean = 15.2
2 AHIS 304 5 1

SD = 4.573378344
3 AHIS 363 19 3

4 AHIS 364 19 3

Typology
Levels
5 AHIS 365 13 2

(1=5-10.5)
6 AHIS 365 02 13 2

(2=10.6-15.1)
7 AHIS/AMST 475 20 4

(3=15.2-19.8)
8
AHIS/AMST 475
03 20 4

(4=19.9-20)
9 AMST 101 18 3
10 AMST 135 12 2
11 AMST 200 13 2
12 AMST 200 07 13 2
13 AMST 202 14 2
14 AMST 206 20 4
15 AMST 220 15 2
16 AMST 250 20 4
17 AMST 252 20 4
18 AMST 274 16 3
19 AMST 285 18 3

183
20 AMST 330 17 3
21 AMST 342 20 4
22 AMST 357 18 3
23 AMST 374 15 2
24 AMST 374 06 15 2
25 AMST 377 17 3
26 AMST 378 15 2

27
AMST/ANTH
395 15 2
28 AMST 448 17 3

29
AMST/ENGL
449 16 3
30 AMST 466 16 3
31 AMST/AHIS 475 20 4

32
AMST/AHIS 475
03 20 4
33 ANTH 240 20 4
34 ANTH 316 15 2
35 ANTH 328 13 2
36 ANTH 371 19 3

37
ANTH/AMST
395 15 2
38 ARCH 440 5 1
39 ARCH 442 7 1
41 BUC0 333 20 4
42 CLAS 320 13 2

184
43 COLT 374 7 1
44 COLT 445 9 1
45 COMM 324 17 3
46 COMM 324 05 17 3
47 COMM 324 07 17 3
48 COMM 383 16 3
49 COMM 395 15 2
50 COMM 458 14 2
51 COMM 465 9 1
52 CTCS 192 20 4
53 EALC 335 5 1
54 EASC 160 12 2
55 EDCO 102 20 4
56 EDCO 324 20 4
57 ENGL 444 15 2

58
ENGL/AMST
449 16 3
59 ENGL 476 20 4
60 FBE 428 5 1
61 FREN 370 5 1
63 GEO 340 19 3
64 GEO 350 19 3
65 GEOG 100 19 3
66 GEOG 215 18 3

185
67 GS 324 20 4
68 HIST 101 5 1
69 HIST 200 9 1
70 HIST 245 14 2
71 HIST 378 14 2
72 HIST 387 14 2
73 HP 420 18 3
74 JOUR 466 18 3
75 JOUR 468 18 3
76 MDA 167 20 4
77 MOR 385 5 1
78 MOR 385 07 5 1
79 MUJZ 100 19 3
80 MUJZ 419 5 1
81 MUSC 400 20 4
82 MUSC 420 18 3
83 MUSC 430 16 3
84 MUSC 450 18 3
85 PHIL 137 8 1
86 POSC 333 16 3
87 POSC 424 16 3
88 POSC 441 20 4
89 POSC 442 20 4
90 PPD 250 13 2

186
91 PPD 372 18 3
92 PSYC 462 12 2
94 REL 145 6 1
95 REL 336 15 2
96 SOCI 142 17 3
97 SOCI 150 11 2

98 SOCI 169 15 2
99 SOCI 200 17 3
100 SOCI 250 11 2
101 SOCI 305 20 4
102 SOCI 342 18 3
103 SOCI 355 18 3
104 SOCI 360 19 3
105 SOCI 375 16 3
106 SOCI 376 16 3
107 SOCI 432 17 3
108 SOCI 435 8 1
109 SPAN 413 15 2
110 SW 200 19 3
111 SWMS 210 13 2
112 SWMS 301 14 2
113 SWMS 384 20 4
114 SWMS 385 17 3
115 THTR 393 19 3

187
116 THTR 395 15 2
117 THTR 476 18 3
118 THTR 488 20 4

188
APPENDIX J
Diversity Course Syllabus Rating Rubric

GUIDELINE #1

Diversity Course Requirement must examine two or more dimensions of human diversity
and must consider these dimensions in terms of their social and/or cultural consequences.

GUIDELINE #2

As a rule, at least one third of the course should be addressed to these issues, and this
should be proportionately reflected in the assigned readings, lectures, and topics for
papers, quizzes, tests, or other graded formal course requirements.

GUIDELINE #3

Each course should give students the opportunity for personal reflection on the formation
of their own attitudes toward other groups and the effect of those attitudes on the
institutions (e.g., cultural, professional, political).

GUIDELINE #4

All syllabi are expected to show how the topics addressed related to issues facing
students in a contemporary context.

GUIDELINE #5

Course encourages comparative and analytical thinking about issues of diversity.

Scoring the syllabi under each guideline:

1 = Meets Requirement
2 = Marginally Exceeds Requirement
3 = Exceeds Requirement
4 = Well Exceeds Requirement

189
APPENDIX K
Notes Regarding Diversity Course Syllabi

COURSE MISSING SYLLABI NOTES
ENGL 445 No cooperation from department
ENGL 447 No cooperation from department
ENGL 448 No cooperation from department
ENGL 474 No cooperation from department
ENGL 478 No cooperation from department
GERO 380 Department unable to locate syllabus
GERO 435 Department unable to locate syllabus
HP 400 No cooperation from department
MDA 166 Department claims there is no record of an MDA 166
PPD 100 Department unable to locate syllabus
PPD 260 Department unable to locate syllabus
PPD 300 Department unable to locate syllabus
PPD 302 Department unable to locate syllabus
PPD 352 Department unable to locate syllabus
PPD 485 Department unable to locate syllabus
SOCI 356 Department claims course has not been taught in over ten years
SOCI 366 Department claims course has not been taught in over ten years
SOCI 437 Department claims course has not been taught in over ten years
SWMS 364
Course was never developed, however a flier advertising the class was
created
SWMS 455 Department claims course has not been taught in over ten years
190

COURSE ADDITIONAL NOTES:
HIST 101 Course has not been taught since Spring 2003
MDA 167
Course has not been taught in a while (syllabus we have is for Fall
1999)
REL 145 Department claims the syllabus was developed but course wasn't taught
SWMS 384 Course used to be called "Overcoming Prejudice"

Abstract (if available)

Abstract This study examines the impact of diversity courses on 553 students’ critical thinking skills. The study was conducted at a large, highly selective, private, tier one research institution and analyzes a pre-college survey, post-college survey through quantitative methodology, such as factor analyses, reliabilities and multiple regressions. The findings suggest that the number of diversity courses taken statistically and positively affect students’ critical thinking skills: (1) Analyticity (β = .242, p < .001)

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Asset Metadata

Creator Pearson, Mark Adrian (author)

Core Title The impact of diversity courses on students' critical thinking skills

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/27/2012

Defense Date 06/20/2012

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag CCTDI,CIRP,cognitive development theory.,critical thinking,diversity courses,Education,general education requirements,Higher education,OAI-PMH Harvest,student impact theory,student learning,student outcomes survey,sudent development theory

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Cole, Darnell G. (committee chair), Sundt, Melora A. (committee member), Tobey, Patricia Elaine (committee member)

Creator Email drmarkpearson@me.com,mpearson@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-74965

Unique identifier UC11289339

Identifier usctheses-c3-74965 (legacy record id)

Legacy Identifier etd-PearsonMar-1024-0.pdf

Dmrecord 74965

Document Type Dissertation

Rights Pearson, Mark Adrian

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA