THE IMPACT OF RESIDENTIAL LEARNING COMMUNITIES AT FOUR-YEAR, PUBLIC, MIDWEST UNIVERSITIES ON STUDENTS’ SELF-REPORTED LEVELS OF CIVIC ENGAGEMENT
Suhua Dong
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
May 2005
Committee:
C. Carney Strange, Chair
Rachel Vannatta Graduate Faculty Representative
Michael Dannells
Carolyn Palmer
©2005
Suhua Dong
All Rights Reserved
iii
ABSTRACT
C. Carney Strange, Advisor
This dissertation focused on the impact of participation in residential learning communities (RLCs) at five four-year, public, Midwest institutions on first-year students’ self- reported levels of civic engagement. Such impact was assessed through examining the main and conditional effects of participation on five dimensions of civic engagement—volunteerism and service to the community, responsibility to the common good, civic empowerment, understanding of and appreciation for diversity, and moral values development. Furthermore, it investigated how RLC students’ input characteristics and a wide range of environmental conditions related to the direction and magnitude of such impact.
This dissertation completed secondary analyses of data collected through The 2004
Residence Environment Survey, employing a comparative-correlational research design, with a sample of 1,822 RLC students and 1,820 conventional students. Analyses of variance and hierarchical regression models were completed by using the Statistical Analysis System (SAS) for Windows 8.0.
Results indicated that RLC participation produced significant, positive main effects on students’ overall level of civic engagement, volunteerism and service to the community, responsibility to the common good, and civic empowerment. Gender, sexual orientation, race, religion, citizenship, father’s education, and high school grades also demonstrated significant conditional effects on one or more of the outcome measures used. However, magnitudes of all the main and conditional effects were extremely small. Pre-college motivations for involvement and growth, enjoyment of integrated learning, intellectual challenge, application of knowledge, iv
multiplicity of learning, and integration of academic learning and self-discovery, diverse peer
interactions, use of residence hall peer, faculty, and co-curricular resources, sense of belonging
to the campus community, and involvement in religious and ethnic activities contributed most to
the overall variance in levels of civic engagement for RLC students as a whole and for each
major demographic group examined.
The findings suggest that institutions would do well to continue to support RLCs through
attending to students’ pre-dispositions. To further enhance such impact, RLCs might consider greater emphases on the integration of curricular and out-of-class learning and providing students opportunities to interact with peers from diverse backgrounds and views. Recommendations for
future research were suggested.
v
ACKNOWLEDGEMENTS
I am deeply indebted to Dr. C. Carney Strange—my advisor, teacher, and mentor, who guided me through every phase of this journey. We met on a regular basis and each and every meeting was an enormous learning opportunity for me. His insightful feedback, sense of responsibility, dedication, and patience were integral to the successful completion of this project; his enthusiasm and good cheer made this task enjoyable. Carney, your scholarship on higher education, the depth and breadth of your understanding of inquiry, will continue to have an impact on my future professional career. And your class “Qualitative Problems and Methods in
Higher Education” remains my favorite.
I would also like to express my heart-felt appreciation for other members of my committee—Dr. Michael Dannells, Dr. Carolyn Palmer, and Dr. Rachel Vannatta, all of whom contributed valuable comments on my research and demonstrated continued support and understanding during the entire process.
Dr. Vannatta, thank you for sharing your expertise on the feasibility of conducting a path analysis. Your suggestion prompted me to reconsider one of the originally proposed research questions and eventually I chose to leave the path analysis for future research.
Dr. Dannells, I enjoy reading the “dog-eared” pages on which you marked your edits.
Thank you for challenging me to be a better writer since I took the first class with you in Fall
2001. As the director of the Higher Education Administration (HIED) Program then, you also deserve special thanks for assisting me with finding the assistantship that best fits my career goals. Indeed, it was through the assistantship position in the Office of Residence Life that I had the opportunity of being involved in coordinating the 2004 National Study of Living-Learning
Programs (NSLLP) which furnished data for this dissertation. vi
Dr. Palmer, your perspectives on the history of student housing have undoubtedly enriched my understanding of this topic. Thank you for bringing me into this renowned doctoral
program, which has made a tremendous difference in my life!
Special appreciation is due to Dr. Karen Inkelas at the University of Maryland, who, as
the principal investigator for the NSLLP, graciously shared her data and offered to merge the
complex datasets from multiple institutions for my use in this dissertation. Dr. Inkelas, I
appreciate your selfless assistance and admire the values you represent as a scholar.
Lastly, I want to thank my family and friends for their love support. My husband, Shanbo
Wang, took up the responsibility of taking care of our daughter, Lining, during the first two years
of my study in the U. S. Lining, thank you for being so gentle when your nocturnal mom
constantly “messed up” our apartment with piles of statistical outputs. Your periodic questions,
“When are you going to complete your big dissertation, Mom?”, or “How many chapters have
you finished?”, reminded me to stay disciplined and focused.
A special thank you to Cheryl, Janice, Mary Ann, Peggy, and other HIED cohort
members as well as my assistantship supervisor, Tim King. You have made my experience at
BGSU so memorable.
My friends—Ms. Jana Brasser, Dr. Philip Holtrop, and Mr. James Heller offered their
generous assistance when I applied to come to the U. S. To them, I am full of gratitude.
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TABLE OF CONTENTS
Page
CHAPTER I. STATEMENT OF THE PROBLEM ...... 1
The Colonial Period ...... 1
The Modern American University ...... 3
A Resurgence of Living and Learning...... 7
Statement of the Problem...... 10
Significance of the Study...... 11
CHAPTER II. REVIEW OF LITERATURE ...... 15
College Impact on Student Learning and Personal Development ...... 15
Impact of Living in Conventional Residence Halls...... 19
Major Features and Theoretical Foundations of the RLC Model...... 24
The Impact of RLCs on Student Learning and Development...... 27
The Construct of Civic Engagement...... 30
College Impact on Student Civic Engagement ...... 34
RLCs and Student Civic Engagement...... 39
A Summary of Literature...... 40
CHAPTER III. METHODS...... 42
Overall Research Design...... 42
Data Source, Participants, Sampling Methods, and Delimitations ...... 42
Instrument ……...... 44
Major Variables Used in This Study...... 56
Input Variables...... 61 viii
Environmental Variables...... 61
Outcome Variables...... 63
Validity and Reliability of Data and Findings ...... 63
Accuracy of Self-Report Data...... 64
Validity of the Research Data and Findings ...... 68
Reliability of the Data...... 72
Major Research Questions ...... 73
Methods of Data Analysis...... 74
CHAPTER IV. RESULTS...... 76
Pre-Analysis Data Screening ...... 76
Data Recoding...... 76
Data Screening...... 78
Testing Normality, Linearity, and Homogeneity...... 81
Data Reduction and Construct Validity ...... 83
Characteristics of the RLC Sample...... 100
Demographic Distributions ...... 100
Differences on Pre-College Perceptions between the RLC Sample
and the Comparison Group ...... 104
Differences on Pre-College Perceptions within the RLC Sample
by Demographics ...... 106
Summary of the Characteristics of the RLC Sample...... 123
Main Effects of RLC Participation on Civic Engagement...... 125
Main Effects on Volunteerism and Service to the Community ...... 128 ix
Main Effects on Responsibility to the Common Good...... 128
Main Effects on Civic Empowerment...... 129
Main Effects on Understanding of and Appreciation for Diversity... 129
Main Effects on Moral values Development ...... 129
Main Effects on the Overall Level of Civic Engagement...... 130
Summary of Main Effects...... 130
Conditional Effects of RLC Participation on Civic Engagement by
Demographic Characteristics...... 131
Significant Mean Differences by Gender ...... 131
Significant Mean Differences by Sexual Orientation ...... 135
Significant Mean Differences by Race ...... 138
Significant Mean Differences by Religion ...... 141
Significant mean Differences by Citizenship...... 145
Significant mean Differences by Father’s Education ...... 148
Significant mean Differences by Parents’ Income...... 151
Significant mean Differences by High School Grades ...... 154
Summary of Conditional Effects ...... 157
Predictors for RLC Students’ Levels of Civic Engagement ...... 159
Predictors for RLC Students’ Overall Level of Civic Engagement... 163
Predictors for Perceptions on Volunteerism and Service
to the Community...... 164
Predictors for Sense of Responsibility to the Common Good ...... 165
Predictors for Sense of Civic Empowerment...... 166 x
Predictors for Understanding of and Appreciation for Diversity...... 167
Predictors for Growth in Moral Values Development...... 167
Predictors for RLC Students’ Overall Level of Civic Engagement by
Demographic Characteristics...... 170
Predictors for RLC Female Students’ Overall Level of Civic
Engagement...... 170
Predictors for RLC Male Students’ Overall Level of Civic
Engagement...... 172
Predictors for RLC White Students’ Overall Level of Civic
Engagement...... 173
Predictors for the Overall Level of Civic Engagement Reported
by RLC Students of Color ...... 174
Predictors for RLC Christian Students’ Overall Level of Civic
Engagement...... 176
Predictors for the Overall Level of Civic Engagement of RLC
Students Reporting Having No Religion ...... 177
Predictors for the Overall Level of Civic Engagement of RLC
Students Who Were Natural-Born Citizens...... 177
Predictors for the Overall Level of Civic Engagement of RLC
Students Who Were Immigrant Citizens ...... 178
Summary of Hierarchical Regression Analyses ...... 181
Summary of Major Results ...... 182
xi
CHAPTER V. DISCUSSION, IMPLICATIONS, AND RECOMMENDATIONS 184
Discussion of Key Findings...... 184
RLC Participants...... 184
RLC Participation and Civic Engagement...... 185
Conditional RLC Participation ...... 188
Predictors for Civic Engagement...... 190
Implications for Policy and Practice...... 192
Recommendations for Future Research...... 197
Concluding Thoughts...... 202
REFERENCES ...... 204
APPENDIX A. INSTRUMENT ...... 223
APPENDIX B. REQUEST LETTER ...... 224
APPENDIX C. SUMMARY OF PRINCIPAL COMPONENT ANALYSES...... 233 xii
LIST OF TABLES
Table Page
1 Variables Used in this Study within the Framework of the I—E—O Model...... 57
2 Component Loadings of Items under Question 1 ...... 86
3 Component Loadings of Items under Question 2 ...... 87
4 Component Loadings of Items under Question 4 ...... 88
5 Component Loadings of Items under Question 7 ...... 89
6 Component Loadings of Items under Question 8 ...... 90
7 Component Loadings of Items under Question 9 ...... 91
8 Component Loadings of Items under Question 10 ...... 93
9 Component Loadings of Items under Question 12 ...... 94
10 Component Loadings of Items under Question 13 ...... 95
11 Component Loadings of Items under Question 14 ...... 96
12 Component Loadings of Items under Question 15 ...... 97
13 Component Loadings of Items under Question 16 ...... 98
14 Component Loadings of Items under Question 17 ...... 99
15 Frequency Distributions of Respondents by Selected Demographic Characteristics 101
16 Group Means on Pre-college Perceptions: RLC versus the Comparison Group...... 105
17 RLC Group Means on Pre-college Perceptions: Male versus Female Students...... 107
18 RLC Group Means on Pre-college Perceptions: GLB versus Heterosexual Students 108
19 RLC Group Means on Pre-college Perceptions by Race...... 110
20 ANOVA Summary Table: Effects of Race on RLC Students’ Pre-college
Perceptions ...... 111 xiii
21 RLC Group Means on Pre-college Perceptions by Citizenship...... 113
22 ANOVA Summary Table: Effects of Citizenship on RLC Students’ Pre-college
Perceptions ...... 114
23 RLC Group Means on Pre-college Perception by Religion...... 116
24 ANOVA Summary Table: Effects of Religion on RLC Students’ Pre-college
Perceptions ...... 117
25 RLC Group Means on Pre-college Perception by Father’s Education ...... 119
26 ANOVA Summary Table: Effects of Father’s Education on RLC Students’
Pre-college Perceptions...... 120
27 RLC Group Means on Pre-college Perception by High School Grades ...... 121
28 ANOVA Summary Table: Effects of High School Grades on RLC Students’
Pre-college Perceptions...... 122
29 Group Means on Levels of Civic Engagement: RLC versus the Comparison Group 126
30 ANOVA Summary Table: Main Effects of RLC Participation on Civic
Engagement ...... 127
31 Group Means for Male and Female RLC Students’ Levels of Civic Engagement.... 133
32 ANOVA Summary Table: Main Effects of Gender on RLC Students’
Levels of Civic Engagement...... 134
33 RLC Group Means on Levels of Civic Engagement by Sexual Orientation ...... 136
34 ANOVA Summary Table: Main Effects of Sexual Orientation on RLC Students’
Levels of Civic Engagement...... 137
35 RLC Group Means on Levels of Civic Engagement by Race ...... 139
36 ANOVA Summary Table: Main Effects of Race on RLC Students’ xiv
Levels of Civic Engagement...... 140
37 RLC Group Means on Levels of Civic Engagement by Religion ...... 143
38 ANOVA Summary Table: Main Effects of Religion on RLC Students’
Levels of Civic Engagement...... 144
39 RLC Group Means on Levels of Civic Engagement by Citizenship...... 146
40 ANOVA Summary Table: Main Effects of Citizenship on RLC Students’
Levels of Civic Engagement...... 147
41 RLC Group Means on Levels of Civic Engagement by Father’s Education...... 149
42 ANOVA Summary Table: Main Effects of Father’s Education on RLC Students’
Levels of Civic Engagement...... 150
43 RLC Group Means on Levels of Civic Engagement by Parents’ Income ...... 152
44 ANOVA Summary Table: Main Effects of Parents’ Income on RLC Students’
Levels of Civic Engagement...... 153
45 RLC Group Means on Levels of Civic Engagement by High School Grades...... 155
46 ANOVA Summary Table: Main Effects of High School Grades on RLC Students’
Levels of Civic Engagement...... 156
47 Summary of Hierarchical Regression Analyses for Variables Predicting
Civic Engagement ...... 169
48 Summary of Hierarchical Regression Analyses by Gender and Race ...... 175
49 Summary of Hierarchical Regression Analyses by Citizenship and Religion ...... 180
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LIST OF FIGURES
Figure Page
1 Blocks of Variables Entered into the Hierarchical Regression Analyses...... 161
1
CHAPTER I: STATEMENT OF THE PROBLEM
Living on campus is a time-honored tradition in American higher education and a major component in college life for a significant number of undergraduates. However, the role and importance of residential experiences have ascended and descended across time, depending on evolving institutional missions, the availability of financial resources, and varying faculty interests. Specifically, the fluctuations of campus residential programs and purposes can be understood in terms of three characteristic eras in the history of American higher education: (a) the Colonial period; (b) the era of the modern American university; and (c) the resurgence of living and learning programs in current times.
The Colonial Period
The undergraduate residential tradition traces back to the first Colonial colleges (e. g.,
Harvard College), which were substantially influenced by English universities, particularly
Oxford and Cambridge, referred to collectively as Oxbridge (Duke, 1996). At Oxbridge, residential colleges, as the principal organizational units of the institution, were intentionally designed to bring faculty and students together in a common intellectual and social life in and beyond the classroom (Brubacher & Rudy, 1968). Although early American higher education was also molded by other forces, such as the non-residential Scottish and Continental universities that were not concerned with students beyond the lecture hall, the English influences were dominant (Brubacher & Rudy, 1997). Not surprisingly, early Colonial colleges acknowledged the value of on-campus living by modeling themselves after the English residential system. As a result, dormitories, though “spare barracks-like” (Brubacher & Rudy, 1997, p. 40), were erected in all of these early institutions. Although such dormitories might have been inadequate to foster the well-knit social life characterizing the English residential college, they were expected to 2 become an integral part of the collegiate life, with the belief that a curriculum, a library, a faculty, and students are not enough (Brubacher & Rudy, 1968).
The value of residential life was often dictated and strengthened by the major purpose of the Colonial colleges—to educate the whole man who was expected to join a special elite for community leadership, most often and importantly through the ministry. Day-to-day fellowship between faculty and students nurtured by the common life in the classrooms, and in the living quarters and dining rooms, was apparently perceived to be essential for the forming of students’ sound moral character. In addition, religion exerted a powerful influence on most of these colleges, and a strict system of moralistic discipline prevailed, facilitated by the presence of resident fellows (Brubacher & Rudy, 1997).
Nevertheless, the unique circumstances in early American colleges made it difficult for dormitories to fulfill the same role as that exemplified at Oxbridge. First, colleges lacked financial resources to construct elaborate self-contained quadrangles; second, educators feared that students’ evil habits, e. g., disorderly conduct, might arise from on-campus community living; third, American professors were usually married men residing off-campus while English dons were required to remain unmarried and to live in the college itself; lastly, challenges of student discipline added to the difficulty of applying the English residential system in its entirety.
Unlike at Oxbridge, where officials, such as proctors, assumed the responsibility for student discipline, Colonial faculty had to perform a dual function of both teaching and proctoring. Even if single faculty gave instruction and resided in the college, it was more for the supervision and control of the young students than for developing a close intellectual and sometimes personal relationship (Blimling & Schuh, 1981; Brubacher & Rudy, 1997). 3
Although the English residential model was not imported intact to the U. S. system, the
tradition of residential living survived and endured, with Harvard becoming the prototype for all
the institutions that followed (Brubacher & Rudy, 1997). Despite the various challenges in
implementing the dormitory model, it remained entrenched in American colleges for two
hundred years (Brubacher & Rudy, 1997). However, the shifting purposes and expectations of a
new type of institution—the modern university—radically changed the role of on-campus living,
first in negative but ultimately in positive ways.
The Modern American University
In the latter half of the 19th century (especially following the Civil War), student housing
entered a new era (Brubacher & Rudy, 1997), one characterized by mixed forces. On the one
hand, advocates for on-campus living continued to argue for the educational value in the common life of a dormitory perceived to be irreplaceable by any other means. Largely because of strong voices of this kind, the dormitory system survived in many liberal arts colleges in the
East and Midwest. On the other hand, new imperatives of the modern American university diminished the discussion of the importance of residential living. However, its emergence created a new set of problems, such as a loss of connection between the curriculum and the extra- curriculum and a disconnection between faculty and students, prompting educators to rethink the role of dormitories and eventually reigniting a renewed interest in sponsoring such programs.
More specifically, with the growing influence of the German university model, vocal views against dormitory living were widely heard and residential education at many institutions suffered a decline in popularity. As large American universities started to embrace a new research orientation, some prominent educational leaders claimed that universities should emphasize advanced specialized training and invest more funds in building laboratories rather 4
than dormitories. Henry Philip Tappan, the University of Michigan’s first President, for example,
bore testimony to this sentiment when he remarked straightforwardly, “In our country we have
ever begun at the wrong end. We have erected vast dormitories for the night’s sleep, instead of
creating libraries and laboratories for the day’s work” (cited in Sagendorph, 1948, p. 80). He
denounced the dormitory system as “objectionable in itself” (Tappan, 1853, pp. 11-12).
The widespread perception that dormitories were no longer vital to the teaching and
research of the university, together with financial constraints, reduced dormitory construction to
a low priority for institutional resource allocations during this era. This problem was particularly
severe with the newly founded state universities in the West and those that grew out of the
Morrill Acts (1862 and 1890) that lacked both funds and drive to provide such facilities for their
constantly enlarging enrollments.
In the evolution from college to modern university, some educators also argued for a new
relationship between the institution and the student. They held that universities should treat students as responsible adults, thus weakening the paternalistic control by resident faculty that
once prevailed.
As a result of such financial and ideological reasons, a growing number of institutions
soon adopted a laissez faire policy in student housing, and the traditional pattern of collegiate
living thus faded. Consequently, many students had to secure their own off-campus residences.
In spite of this apparent trend, however, some colleges started to build their own luxurious
dormitories, which attracted the serious attention of Charles William Eliot, President of Harvard
from 1869 to 1909 (Brubacher & Rudy, 1997). Being concerned with the effect of such solutions
on accentuating social disparities among students, Eliot explicitly voiced, once again, the need to
build more dormitories with common rooms and dining halls where students from diverse 5
backgrounds could freely mix. His statements marked a point from which some leading educators started to develop an awareness of the relevance of on-campus living to the total educational experience.
Furthermore, even in those institutions that were able to provide dormitories, the social life in residence, especially the unfocused, unsupervised mayhem among students (Brubacher &
Rudy, 1997), was increasingly separated from the intellectual life in the classrooms and laboratories. Residential programs all but divorced themselves from academic learning. Such disconnection was a manifestation of the overall dissolution of unity between the curricular and extra-curricular worlds, a unity that had prevailed prior to 1865 (Brubacher & Rudy, 1997). This loss of cohesiveness of student life came on the heels of changing motivations among students, who more often attended colleges out of diverse motives, desiring more a degree to support an occupation than the rigorous intellectual life their predecessors valued. It was also a result of the emergence of the modern American university. The forming of highly specialized departments as teaching units, supported by an elective system, eroded the once strong social and intellectual bonds among students made possible by the class system. The grounds for a common social and intellectual life in the residences were shaken. Students living in the same dormitory might belong to different departments and therefore might share little common curricular experience.
The emphasis on specialized training that characterized the modern American university also undermined the intellectual intimacy and sense of community between students and faculty once present in the early colleges. With a changed reward system (Blimling & Schuh, 1981), faculty were increasingly devoted to producing original research and became concerned only with students’ intellectual development within their narrow areas of academic specialization.
Dormitories were no longer an out-of class locus for faculty-student interactions. 6
As the modern American university took shape, dormitories were still considered a
problem by some educators, though others started to recognize their educational potential in
alleviating a range of pressing issues. As early as the mid-1890s, inspired by Oxbridge, some educators at Harvard, Chicago, and Yale experimented with establishing undergraduate
residential colleges (Duke, 1996), with the purposes of re-creating a common intellectual and
social life among students and faculty, counteracting the depersonalizing effects of the
university, reintegrating the world of the curriculum and extra-curriculum, and ultimately
enhancing students’ holistic development. Like Oxbridge, they attempted to use such colleges as
the principal organizing units within a large-scale curricular restructuring.
Most of these enterprises, however, suffered ill fates. From the early 1900s, thanks to the
changing state laws on the financing of university dormitories and the involvement of the federal
government (Frederisksen, 1993), dormitory construction flourished. By 1915, dormitories were
being built at an unprecedented rate. Faced with a growing on-campus resident population,
discussion of the idea of the residential college continued well into the late 1920s when several institutions, including Harvard and Yale, again tried to develop such facilities, but failed.
To summarize, with the evolution of the modern American university came questions about the relevance of on-campus residential living in the academic enterprise. Although it was not long that educators were reminded of its role in addressing the problems created in turn by this new institutional form, the early attempts to reclaim the legacy of residential colleges were ambitious but largely fruitless.
7
A Resurgence of Living and Learning
The tremendous expansion of student enrollment following the passage of the G. I. Bill of
Rights (Duke, 1996) at the close of the Second World War intensified the continuing problems
that persisted with the emergence of the modern university. In particular, with the sudden influx
of large numbers of students, higher education was moving further away from the ideal of
educational community (Blimling & Schuh, 1981; Boyer, 1987). Equally troubling was its
continuing curricular fragmentation.
Residence halls, now called upon to generate solutions to some of the above problems,
became a major avenue through which a more effective means of delivering undergraduate
education was sought. Because of these continuing unsuccessful efforts, interest in the idea of
developing full-fledged residential colleges suffered a decline in the late 1940s and early 1950s
(Duke, 1996). This led student affairs professionals to explore more feasible ways to realize the
educational potential of dormitories (or residence halls, as they were later called) to remedy such
problems. The 1950s saw the emergence of professionally trained individuals charged with the implementation of residential programs (Blimling & Schuh, 1981), thus replacing the custodial care philosophy prevalent in dormitories staffed with “elderly housemothers, retired military people, discarded football coaches, and random others” (Blimling & Schuh, p. 41). During this period, too, the first professional housing organization—the Association of College and
University Housing Officers (ACUHO)—was founded, increasing the visibility and credibility of student housing as a distinct specialization within student affairs. However, such remarkable changes were but a prelude to the fundamental developments in the 1960s and beyond.
In the 1960s, the idea of residential colleges resurged on many campuses. As a result,
forty-four new facilities were established across the country (Duke, 1996), epitomized by the 8
University of California, Santa Cruz’s residential system in 1966, the largest undertaking of the
kind up to that point in the residential college movement (Duke).
Within the housing profession, starting from the 1960s, there was a shift from a service
model to a developmental model of housing; that is, from controlling students and serving their
social needs to assisting their academic learning and personal development. Pioneering
residential educators, such as Riker (1965), who explicitly pointed out that residential life can be
intentionally designed to enrich students’ academic learning and personal development. Housing
professionals thus articulated a new direction in their programmatic emphasis—going beyond chance happenings and peripheral activities to provide a learning component equal to the
classroom through building community and reconnecting the curriculum and extra-curriculum
(Blimling & Schuh, 1981). As a result, they started to develop a more intentional approach to
residential education, guided by principles of student intellectual, moral, and psycho-social development theories (e. g., Chickering, 1969; Kohlberg, 1969; Perry, 1970), emerging theories of campus ecosystem design (e. g., Barker, 1968; Holland, 1973; Moos, 1979; Schroeder, 1979;
Schroeder & Jackson, 1987; Schuh, 1979; Stern, 1970), and higher standards for residential staff selection and training. Well-conceptualized residential interventions began to flourish.
By the 1970s and 1980s, the status of the residence hall experience was elevated further
from merely supplemental to integral to the educational process (Blimling & Schuh, 1981).
During this period, many of the important premises now driving residential education were laid,
as expressed in an impressive body of literature (e. g., Blimling & Schuh, 1981; Chamberalin,
1979; Colwell & Lifka, 1983; DeCoster & Mable, 1974; Harding, 1974; Hennessy, 1981;
Hubbell & Sherwood, 1973; Lacy, 1978; Leean & Miller, 1981; Littlefield & Spencer, 1973;
Magnarellas, 1979; Pascarella & Terenzini, 1977, 1981; Riker, 1965). The publication of the 9
Journal of College and University Housing in 1971 represented a milestone in developing a unique focus on housing. Despite a meager amount of empirical research produced in the first decade, assessment of student development in residence halls proliferated in the 1980s.
Amidst the new models for residential programming, the idea of transforming conventional residence halls into living-learning centers captured the interest of institutional leaders (Brown, 1974; DeCoster & Mable, 1974; Riker, 1965; Rowe, 1981). This model was actually a revisiting of an earlier idea—the residential college—and a reaffirmation of the value of intellectual intimacy and sense of community among faculty and students. What distinguished it from the residential college, though, was that it did not involve a large-scale curricular restructuring nor was it used as a quasi-academic unit. After its reappearance in the late 1960s, the living-learning model led to various experiments across the nation and continued to evolve in the 1970s and 1980s (Conroe, 1986; Duncan & Stoner, 1976; Grass, 1974; Grimm, 1993; Kuh,
1979), developing a continuum ranging from the least to the most structured (Rowe, 1981).
By the 1990s, educators had developed a keener awareness that simply living in a residence hall does not guarantee positive impact and residential interventions must become more intrusive (Blimling, 1993). The new imperative for higher education to maximize student learning and the realization that residence halls were not fulfilling their educational potential spurred institutions to seek better ways to maximize the contribution of on-campus living to student learning and growth. New evidence generated by empirical research (Schroeder, Mable,
& Associates, 1994; Terenzini & Pascarella, 1994) highlighted the need to design environments where students can integrate classroom-based and out-of-class learning and can meaningfully interact with peers and faculty. Such studies supplied sound assumptions for a sustained focus on 10
residence halls, bringing residential living once again into the mainstream of the undergraduate
educational experience.
In these circumstances, living and learning programs came into full swing in the 1990s,
often under various labels, but referred to collectively here as residential learning communities
(RLCs). By linking residence halls and the formal curriculum, the RLC model has been
promoted as an effective approach in maximizing student learning by creating the most favorable
conditions for learning to occur. This recent renaissance of RLCs has received much attention
from researchers (e. g., Arminio, 1994; Blimling, 1993; Cornwell & Stoddard, 1997; Golde &
Pribbenow, 2000; Henry & Schein, 1998; Kanoy & Bruhn, 1996; Pike, Schroeder, & Berry,
1996; Ryan, 1992; Schein & Bower, 1992; Smith, 1994), and interest in this movement shows
little sign of abatement. Indeed, it has been, together with its parent concept—learning
community (that does not necessarily involve common living arrangements)—among the most
vigorously discussed concepts in higher education in the last decade.
Although the RLC model is unlikely to be a panacea to the ills of contemporary
undergraduate education, an increasing number of institutions are employing it as a strategy to
address a broad range of problems and outcomes; e. g., developing students to be engaged,
committed citizens and nurturing their appreciation for differences. The question remains,
however, as to what actual impact these units have on the espoused goals of learning they
endorse. It is within this broad context—the need and worth of RLCs and their claimed
outcomes—that this dissertation was conducted.
Statement of the Problem
Most research on RLCs has focused almost exclusively on their influences on student
satisfaction, academic performance, retention, and graduation rates. While these are undoubtedly 11 important concerns, other equally significant outcomes remain largely unexplored, such as the impact of RLCs on student civic engagement, about which few researchers (Cornwell &
Stoddard, 1997) have asked in-depth questions. In this dissertation, I examined the impact of participating in RLCs on first-year students’ self-reported levels of civic engagement at four- year, public, Midwest institutions. Furthermore, I explored how student pre-college characteristics and a wide range of environmental conditions, such as interactions with peers and faculty, influence the direction and magnitude of such impact.
Significance of the Study
This study addressed a problem of historical importance to American higher education, with the purpose of evaluating the effectiveness of a sample of current RLCs. The significance of this study lay in at least four key aspects. First, enhancing students’ civic engagement has been a legitimate, integral component of the mission of American higher education, which has a long and distinguished tradition of serving democracy and preparing graduates for democratic citizenship (Boyte & Kari, 2000; Guarasci & Cornwell, 1997). Early Colonial colleges were founded with a strong civic mission (Boyte & Kari), devoting equal attention to developing students’ intellect and character, largely defined in terms of moral and civic virtues (Ehrlich,
2000). Historically, the establishment of land-grant and state universities was driven by the purpose of public service to meet the needs of an industrial democracy. Nevertheless, since the mid-1980s, there seemed to be a decline of civic engagement, particularly political involvement, in American society at large, and in higher education in particular (Erhlich; Sax, 2000).
Education is the key to civic engagement that is fundamental for American society to realize the potential of its citizens and its communities (Boyte & Kari; Ehrlich). Faculty and administrators should play a significant role in addressing this issue, by acting as engaged citizens of their 12
communities and as educators of civic leaders (Ehrlich). Building on such a rationale, a recent
Carnegie Foundation Report (cited in Ehrlich) maintained that providing education for
citizenship is still the most important responsibility of the nation’s schools and colleges. Indeed,
among the challenges higher education faces today, none is more important than to meet the
mandate that Dewey posed for all of American education—education for democracy (Ehrlich).
Unfortunately, on most college campuses, nurturing students’ moral and civic responsibility is still more an aspiration than a reality (Erhlich), calling for continued attention to this educational outcome.
Second, the focus on residence halls in this study is justified by the sheer scale of the on-
campus undergraduate population and the level of resource investment in residential facilities.
According to the National Center for Educational Statistics, during the 2002-2003 academic
year, of approximately 653 four-year or above, public, degree-granting institutions, about 78.4% provided on-campus housing. At these 510 institutions, typical fees for on-campus room and board per student for an academic year represented 43% of an in-state student’s total annual college expenditures and 26% of an out-of-state student’s total college price (The Integrated
Postsecondary Education Data System Dataset Cutting Tool, 2004). Such financial investments warrant attention from educators who are committed to helping students get the most out of their residential experience. More importantly, in residence halls, opportunities to influence student learning and growth abound, since students, particularly first-year students, spend most of their out-of-class time there (Blimling & Schuh, 1981; Pascarella & Terenzini, 1991; Schroeder et al.,
1994).
Likewise, interest in evaluating the worth of the RLC model, a promising option for on- campus living, will increase over time as institutions continue to invest resources in such 13
facilities. As of 2003, nearly 200 RLCs had been created in public and private institutions (The
Residential Learning Communities International Registry, 2004), and the number continues to
grow. In terms of geographic locations, slightly over half of them exist at four-year, public,
Midwest institutions. Meanwhile, the financial resources available for campus program developments may diminish due to continued declines in state funding. Given the vast popularity of the RLC model, it seems fair to assess whether it deserves priority in resource allocation.
Third, the growing demand for public accountability calls for more empirical evidence of
the benefits of educational programs in a time of state budget shortfalls. In recent decades,
American undergraduate education has come under increased public scrutiny. As early as 1993,
Astin (1993) remarked that “There is a rapidly growing interest among federal and state policy
makers in improved outcomes assessment and accountability in postsecondary education” (p. 2).
Such statements still ring true today. To remain competitive, institutions need to focus their
shrinking resources on meeting the public demand for maximizing student learning. The RLC
model represents a way of creating a residential environment potentially most conducive to
student learning. Claims abound regarding their potential benefits. However, constituents, both
internal and external, are unlikely to buy into program costs unless such benefits can be
substantiated through convincing evidence. The assumption that, once RLCs are established,
their intended goals will automatically be accomplished and thus require no assessment may
result in misallocation of limited resources.
Institutions and the general public will gain substantially from assessments that can
provide valuable feedback for continuous program improvement. Evidence suggests that most
RLCs, some of which might have been established out of a flurry of enthusiasm, can be
redesigned to generate greater positive effects on student learning. To bring the full impact of 14
RLCs to bear on all the dimensions of student learning and development, institutions need to
determine the complex and interrelated influences on the effectiveness of RLCs so as to identify
factors contributing to program successes or failures, a goal sound assessments will help achieve.
Fourth, the relative paucity of empirical data on this problem adds to the importance of
this research. Recent years have witnessed an enhanced recognition of the imperative, or “a
strong and growing movement” (Colby, Ehrlich, Beaumont, Rosner, & Stephens, 2000, p.
xxxviii), to revitalize the civic mission of higher education—preparing students for responsible
citizenship (Guarasci & Cornwell, 1997). This is evidenced by the growing national efforts to
foster communications about civic engagement across campuses, as reflected by the Campus
Compact and the President’s Declaration of Responsibility for Enhancing Civic Engagement, to
name only two. New approaches to institutional accreditation are meanwhile suggesting the
inclusion of student civic virtue within college outcomes (Colby et al.). As a result, institutions
have implemented strategies to achieve this end, notably through service learning and RLCs.
Nevertheless, in higher education as a whole, “assessment of student outcomes is the least
developed component of the overall efforts to foster student moral and civic development”
(Guarasci & Cornwell, p. xxxvii). In particular, scant research has been conducted on the effectiveness of programs other than service learning in attaining this outcome. This dissertation partially remedied this perceived shortcoming in the literature by focusing on the impact of
RLCs on students’ civic engagement levels at four-year, public, Midwest institutions and by investigating various factors closely associated with such impact.
15
CHAPTER II: REVIEW OF LITERATURE
Addressing the impact of RLCs on student civic engagement entails a comprehensive
understanding of the three core components framing the problem statement: college impact, the
design of the RLCs, and the nature of civic engagement. The purposes of this chapter are to
review literature related to these three components and identify knowledge gaps so as to establish
a context for the specific research questions that comprise this dissertation.
The first section of this chapter provides a synopsis of literature on how college affects
students in terms of broad educational outcomes. Within this larger context of overall college
impact, the second section provides a more focused review of the influences of on-campus living
on students. The third section outlines the major features and theoretical foundations of the RLC model and the fourth section, the research findings on the impact of RLCs on student learning
and development. The fifth section addresses the dimensions of the outcome construct measured:
civic engagement, with the purpose of gleaning the indicators of civic engagement that were used in this dissertation. The sixth section synthesizes research on college impact on the dimension of student civic engagement; and the last section clarifies the link between RLCs and civic engagement. In terms of the overall organization, this chapter flows from the general college experience to the more specific RLC experience, from the impact in terms of broad educational outcomes to a specific one: civic engagement.
College Impact on Student Learning and Personal Development
Strange (2003) summarized major findings regarding college impact, covering the
earliest systematic analyses by Pace (1941, 1979), Trent and Medsker (1968), and Feldman and
Newcomb (1969), along with the subsequent landmark works by Bowen (1977), Astin (1977,
1993), and Pascarella and Terenzini (1991). Two generations of studies conclusively point to the 16
fact that college does make a difference as measured by a wide range of outcomes for individual
students. Bowen concluded that, in terms of cognitive outcomes, a college education “produces
large increases in verbal skills, intellectual tolerance, esthetic [sic] sensibility, and lifelong cognitive development; and small increases in mathematical skills, rationality, and creativity” (p.
432). In addition, a college education leads to affective outcomes, such as helping students find their personal identity and make lifelong choices congruent with their identity, moderately increasing students’ psychological well-being as well as their understanding, human sympathy, and tolerance of differences.
Using similar categories as Bowen (1977), and basing his analysis on empirical data obtained through national surveys over two decades, Astin (1977, 1992) reported that after they enter college, students develop “a more positive self-image … substantial increases in Social
Activism, Feminism, alcohol consumption, and support for legal abortion” (p. 396). In addition, students increase their “commitment to participate in programs to clean up the environment, to promote racial understanding, and to develop a meaningful philosophy of life” (p. 397). Lastly, students report “substantial growth in most areas of knowledge and skills, especially in
knowledge of a field or discipline” (p. 397).
In How College Affects Students, “the most comprehensive and systematic review to date on the question of college impact” (Strange, 2003, p. 335), Pascarella and Terenzini (1991) conducted a thorough meta-analysis of more than 2,600 empirical studies completed over a period of 20 years. This culminating work presented consistent and compelling evidence that college positively affects students with reference to ten outcomes: subject-matter competency, cognitive skills, academic and social self-concept and self-esteem, ability to relate to others, attitudes and values, use of principled reasoning to judge moral issues, career choice, educational 17
attainment, economic benefits, and quality of life. In particular, Pascarella and Terenzini
concluded that students’ relational system changes during the college years, including increases in their “freedom from the influences of others …, in non-authoritarian thinking, and tolerance for other people and their views, [and] in intellectual orientation to problem solving and their own world view in general” (p. 257). Departmental activities, living-learning centers, and interactions with peers and faculty positively influence the attainment of these outcomes.
Furthermore, some of these works established several conceptual frameworks for assessing college impact. For example, Astin (1977, 1993) put forward his Inputs (I)—
Environments (E)—Outputs (O) model, which specified three sources of data: with inputs referring to characteristics of students at the point of entry to college; environments referring to various programs, policies, faculty, peers, and educational experiences to which students are exposed; and outcomes referring to students’ characteristics after exposure to the environments.
Later, Pascarella and Terenzini (1991) considered college impact in terms of net effects
(i. e., student change or development that can be attributed to the college experience itself, rather than other potential influences), between-college effects (i. e., varying influences that different types of institutions have on students during college), within-college effects (i. e., effects that different experiences within the same institution have on students, such as academic major field, course work, study abroad, place of residence, Greek membership, peer interactions, and faculty interactions), and conditional effects of college (i. e., how different college experiences affect
different students in different ways).
In addition, these studies identified the environmental factors associated with such
outcomes. Astin (1977, 1993) and Pascarella and Terenzini (1991), in particular, 18
[e]Established the finding that positive individual effects of higher education are related
directly to a myriad of factors, such as peer group involvement, interaction with faculty,
and time devoted to learning, and indirectly related to a range of institutional
characteristics, such as size and mission, inasmuch as they encourage or mitigate such
dimensions of engagement. (Strange, 2003, p. 340)
More specifically, Pascarella and Terenzini (1991) suggested that the following factors demonstrate a positive impact on student learning and development: peer culture, interactions with faculty, and involvement or engagement in campus activities. Astin (1993), in particular, emphasized that “the student’s peer group is the single most potent source of influence on growth and development during the undergraduate years” (p. 398). In other words, “Students’ values, beliefs, and aspirations tend to change in the direction of the dominant values, beliefs, and aspirations of the peer group” (p. 398).
Interactions with faculty also play an important role in student learning (Pascarella &
Terenzini, 1991) and are indeed the most significant contributor to students’ development, second only to the peer group (Astin, 1993). Positive faculty-student interactions bring about a wide range of outcomes for students: learning and cognitive growth, occupational values, socio- political attitudes and values, academic and social self-concepts, intellectual orientation, moral development, maturity, educational aspirations, persistence, and degree attainment.
Moreover, the quality of student involvement in campus activities is consistently shown to be proportional to the amount of learning and personal development from any educational program. More learning occurs when students are actively engaged in the learning process. In other words, the more time and energy they invest in campus activities and interacting with peers and faculty, both in and beyond the classroom, the more educational gains students report (Astin, 19
1985, 1992; The Study Group on the Conditions of Excellence in American Higher Education,
1984). Degrees of involvement with peers and faculty are positively associated with gains in students’ academic and social self-concepts, in ability to relate to others, and in attitudes and values, with peers being “particularly influential” (Astin, 1993, p. 206). Since student involvement theory was popularized by the report Involvement in Learning: Realizing the
Potential of American Higher Education (1984), this concept has been providing an unfailing rationale for educational innovations.
Researchers also revealed the way the above three factors (i. e., peer interactions, faculty interactions, and involvement) interact. Terenzini, Pascarella, and Blimling (1996) observed that learning and development is the result of multiple, diverse, and interrelated experiences. “The greatest impact [on student learning] may stem from the students’ total level of campus engagement, particularly when academic, interpersonal, and extracurricular involvements are mutually supporting and relevant to a particular educational outcome” (Pascarella & Terenzini,
1991, p. 32). Students’ out-of-class experiences, particularly interactions with peers and faculty, as well as involvement in extracurricular activities, and opportunities to integrate information gained in and outside of the classroom, significantly influence the amount and quality of student learning and development (Kuh, Schuh, & Whitt, 1991; Pace, 1990; Schroeder et al., 1994). For a significant number of students on many campuses, the confluence of such factors occurs in the residential experience.
Impact of Living in Conventional Residence Halls
On-campus residence, as a locus of students’ out-of-class activities, can potentially serve as an important sphere of influence on student learning and development, in that it provides an environment rich in opportunities for peer interactions and for integration of in-class and out-of- 20
class experiences. Pascarella and Terenzini (1991) therefore argued that “living on campus
(versus commuting to college) is perhaps the single most consistent within-college determinant of impact” (p. 611). Despite such potential, it was not until the 1960s that books and journals on the impact of student housing proliferated (Riker, 1993). Out of this literature has emerged a consistent picture of the impact of residential living on four broad categories of student outcomes: academic achievement as reflected by GPA, retention, degree completion, and personal development, which are addressed in the same order in the following sections.
Impact on GPA
Living in conventional residence halls (referring to those living units that do not provide
intentional, well-structured interventions, other than routine hall staff programming) seems to have little effect on student academic performance (Blimling, 1989). Blimling synthesized 21
studies on the influence of living in residence halls on student GPAs. Among the only 10 studies
that made comparisons after adjusting for students’ initial differences in past academic
performance, he found scant consistent evidence that residential students perform better than
similarly gifted students who live off campus. The rest of the studies that did not control for
effects of students’ initial academic differences provided weak, less credible evidence for such
impact. However, given the small number of studies included in the meta-analysis, Blimling cautioned about the generalizeability of such data to other postsecondary institutions. Similar studies of freshmen-only residence halls have also obtained conflicting results concerning their impact on student academic achievement (Terenzini et al., 1996).
While findings pertaining to the impact of residential living on GPAs, when considered together, are mixed or conflicting (Clodfelter, Furr, & Wachowiak, 1984; May, 1974; Moos &
Lee, 1979; Pike, 1989; Pascarella & Terenzini, 1982; Robinson, 1999), the preponderance of the 21 evidence (Blimling, 1989; Grosz & Brandt, 1969; Pascarella, 1984; Simono, Waschowiak, &
Furr, 1984) suggests that on-campus students who participate in conventional residential programs do not perform significantly better academically than those living off campus.
Impact on Retention and Degree Completion
Research reveals a different picture regarding the impact of living on campus on retention and degree completion. Plentiful studies have produced compelling, consistent evidence for the significant, positive association of on-campus residential living with student retention and degree completion (Anderson, 1981; Astin, 1977, 1982; Chickering, 1974; Herndon, 1984; Howell,
Perkins, & Young, 1979; Levin & Clowes, 1982; Pascarella & Chapman, 1983; Robinson, 1999;
Velez, 1985), even after statistically controlling for differences in students’ past academic performance, aptitude, family socio-economic status, and other factors associated with educational attainment.
On-campus living indirectly affects retention and degree completion, operating through the intervening factors of social integration, involvement, and satisfaction. Research has shown that on-campus students report significantly more social interactions with peers and faculty and are significantly more likely to be involved in extracurricular activities and use campus facilities
(Billson & Terry, 1982; Chickering, 1974; Everett, 1979; Foster, Sedlaham, & Hardwick, 1977;
Nelson, 1982; Pascarella, 1984; Stockham, 1974; Welty, 1976). Such influences exist even after partialling out the effects of student pre-college differences, such as aptitude, social-economic status, and secondary school extracurricular involvement, as well as the size, affiliation, and selectivity of the institution attended.
With few exceptions, “the clear weight of evidence, particularly from national, multi- institution samples, indicates that residents are significantly more satisfied with college and are 22 more positive about the social/interpersonal environment of their campus than are their commuter counterparts” (Stroeder et al., 1994, p. 26). Astin (1985) suggested that higher involvement leads to higher levels of satisfaction and persistence to graduation. It also tends to result in a higher level of social integration into college life (Pascarella & Terenzini, 1991), which, in turn, significantly affects student retention and graduation (Pascarella, 1980; Tinto,
1975, 1987).
Impact on Student Personal Development
Some researchers (Lundgren & Schwab, 1979; Wilson, Anderson, & Fleming, 1987) found that on-campus residents are more trusting and better adjusted, show more initiative, and are more independent from parents than commuters or off-campus residents. According to Miller
(1982), sophomores who live on campus a second year, when compared with those who move off campus after the first year, report greater tolerance for human differences.
However, findings are inconclusive regarding other dimensions of student development, such as academic and social self-concept (Astin, 1977; Chickering, 1974). Likewise, conflicting results were reported regarding whether residence hall students demonstrate a decline in authoritarianism when compared with their off-campus counterparts (Chickering & Kuper, 1971;
Chickering, McDowell, & Campagna, 1969; Katz & Associates, 1968; Levin, 1967; Matteson,
1974; Rich & Jolicoeur, 1978). Little evidence is found on the positive impact of on-campus residential living on student interpersonal relationships (Chickering & Kuper; Rich & Julicoeur;
Riahinejad & Hood, 1984), personal adjustment, or psychological well-being (Pascarella &
Terenzini, 1991).
In summary, literature clearly supports claims for the indirect positive impact of living in conventional residence halls on student retention and degree completion through increasing 23 involvement and facilitating social integration. Nevertheless, it suggests that merely living in a residence hall does not automatically affect students’ learning and personal development positively, as indicated from the striking and disappointing findings concerning its apparent negligible effect on GPA. In the area of student personal development, evidence is less clear and consistent. It seems warranted to conclude that conventional residence hall living tends to affect students more indirectly than directly. Its socialization influence involving interactions with people—peers and faculty alike—is shown to be the principal factor affecting students’ degree of subsequent change in intellectual orientation (Pascarella & Terenzini, 1991).
Carefully designed and precisely measured studies investigating the net effects of on- campus living versus commuting remain limited. For example, while within-college effects on student values and attitudes seem to be related more frequently to personal interactions students have with faculty and peers in the context of residence halls, how such contexts affect students remains unclear (Strange, 2003). The scope of influence studied thus far remains narrow as well.
Still others (Terenzini et al., 1996) have pointed out that the direction and magnitude of the correlation between on-campus living and student learning and development might be moderated by the different types of living arrangements, the specific structure of residence hall programs, and the human aggregate environment of the residents within a certain hall. Indeed, based on their survey of literature, Terenzini and Pascarella (1994) concluded that “halls with the strongest impact on cognitive development and persistence are typically the result of purposeful, programmatic efforts to integrate students’ intellectual and social life during college” (p. 32).
Although the data on the impact of conventional residence halls are underwhelming, the practice is rapidly changing in terms of residential learning communities (RLCs), where key 24
environmental factors seem to create a synergy of effects as a consequence of intentional design.
Such designs are often found in residences informed by the RLC model.
Major Features and the Theoretical Foundations of the RLC Model
RLC, a term used prevalently since the 1990s, does not signify a completely new mind- set in the history of student housing. It evolved directly out of the living-learning center (LLC)
model—a popular name for such programs in the late 1960s and 1970s. Advocates for the
contemporary RLC model and the mission statements of most RLCs today largely echo the
rationale of LLCs articulated in the 1970s and 1980s (Hennessy, 1981; Rowe, 1981; Rowe et al.,
1979). Simply put, the LLC movement in the 1970s and 1980s largely defined the objectives and
key elements of this special residential arrangement. Essentially, they both represented a unique
alternative for on-campus residences and a most intensive, innovative form of residential
intervention. Today, terms such as “RLCs,” “LLCs,” “living-learning programs,” “living-
learning units,” and “living-learning residence halls” tend to be used interchangeably. Indeed,
different campuses may refer to programs that are essentially the same with slightly different
labels. For the sake of consistency, this dissertation adopted the nomenclature of “residential
learning community” (RLC) to describe a type of residential program that possesses all or some
of the following characteristics, regardless of the time such a program is developed and the label
actually applied to it.
RLCs in a broad sense share all the following core elements: (a) providing purposeful,
formally structured academic, social, cultural, and other extra-curricular enrichment activities in
the residential setting, be they in the form of field trips, peer mentoring, seminars, or academic
advising; such activities are coordinated by joint efforts from residential staff, faculty
advisor(s)/mentor(s), or peer mentor(s); (b) aiming to cultivate a sense of community among 25 residents and staff by requiring a common cohort of students to live in the same residence hall
(although not necessarily on the same floor); and (c) creating opportunities for students to integrate their collegiate experiences, to link classroom and out-of-class learning.
Meanwhile, such programs may vary in their extent of formal curricular intervention and faculty involvement. Some RLCs might involve curricular integration, interdisciplinary teaching, and collaborative learning by requiring residents to take one or two common courses together, mostly general education course(s) or course(s) linked to themes (sometimes called course clusters). Such courses, which may be formal, credit-bearing courses or non-credit seminars, are taught in residence halls where participants live. Regarding faculty intervention, some RLCs involve one or more resident faculty fellows, who teach, mentor, or advise students in the hall.
They may also hold academic discussions/classes/seminars or have their offices located in the same hall. Students and faculty in residence are expected to share common activities, social and cultural, in and outside the classroom, and to cultivate intellectual intimacy and positive interactions. In this dissertation, programs that demonstrate some or all of the features described here, in addition to those specified in the broad RLC category, are defined as RLCs in the narrow sense.
What are the theoretical foundations advocates for the RLC model draw on? As noted previously, among factors positively associated with the quality and quantity of student learning and personal development are peer interactions; student-faculty interactions; student involvement in campus activities inside and outside the classroom; and the mutual supporting effects and integration of students’ academic, interpersonal, and extracurricular experiences. The theoretical assumptions underlying RLCs draw heavily on literature (Astin, 1993; Pascarella & Terenzini,
1991) that highlights the importance of those factors in creating favorable conditions for student 26
learning and development to occur. For example, by requiring students to take one or more
common courses offered in their residence hall and to participate in classroom-related
enrichment activities, RLCs create opportunities for students to link instructional environments
and out-of-class (in residence halls) experiences. An explicit connection is thus established
between the formal curriculum and residence halls, which becomes an integrated part of
students’ overall educational experience. The close physical proximity of faculty and students in
residence increases the probability for enhanced intellectual and social contacts among students
and faculty around curricular matters, thus increasing students’ engagement in the learning
process. By pursuing the goal of building supportive communities, RLCs potentially enhance the
quality of the interactive process among faculty and students as well (Duke, 1996; Hennessy,
1981; Mable et al., 1977). The design of RLCs’ physical, human aggregate, organizational, and
constructed environmental components is also informed by recent developments in person-
environment theory (Strange & Banning, 2000) to achieve the goal of engaging students and
maximizing opportunities for learning and personal development.
Literature identifies six broad categories of RLCs: (a) foreign language or culture houses,
occupied by students who study or share a common interest in a certain foreign language or
culture; (b) theme houses, which gather students who share one academic interest, such as a
common major; (c) honors housing, which recruits academically talented students; (d) general
RLCs that aim to promote general academic achievement, recruiting students from diverse backgrounds; (e) talent or arts RLCs, which bring together students who have similar interests in developing arts or other talents; and (f) RLCs with a focus on activism, enrolling students who share similar social or political agendas, such as environmental concerns or women’s issues. 27
Different categories of RLCs may result in different human aggregate compositions, ranging
from highly homogeneous to heterogeneous.
The Impact of RLCs on Student Learning and Development
The preceding chapter establishes the premise that RLCs create a unique environment for
students. A probabilistic perspective (Moos, 1986) hypothesizes that RLCs will maximize
opportunities for student involvement and integration, which, in turn, will positively impact
student learning and development. How do those design features and propositions play out in the
actual RLC setting? Since the 1970s, a notable amount of research has accumulated regarding
the influences of RLCs, producing substantial evidence that RLCs affect student learning and
development in a positive way. Jerome (1971) and Clarke, Miser and Roberts (1988) reported
that freshmen in RLCs (actually labeled “living-learning halls,” with faculty involvement) are
more likely than their counterparts to change their career choices, value cultural events, and
make progress in developing social skills. They also found that residents in halls that feature
faculty involvement programs are more satisfied with college and general education courses and
report more interactions with friends.
Hamberlain (1979) studied an RLC (locally called “LLC”) at Indiana University in 1970,
which involved both classroom instruction in the hall and other educational activities. Using the
College Student Questionnaire and a sample of 100 students, he found that RLC students tend to
be more psychologically independent, creative, and liberal in their outlook than a comparison
group in conventional residence halls.
Most research has found that, compared with their peers in conventional residence halls,
RLC students report significantly more informal interactions with faculty and peers and perceive the presence of a significantly stronger intellectual dimension in their living environment (Clark 28 et al., 1988; Inkelas & Weisman, 2003; Magnarellas, 1976, Pascarella & Terenzini, 1981;
Terenzini et al., 1996). Moreover, the intellectual content of these interactions is much greater for RLC participants (Tinto & Goodsell, 1993). Additionally, RLC students report significantly higher cognitive and intellectual gains (Inkelas & Weisman; Lacy, 1978; Newcomb, Brown,
Kulick, Reimer, & Revelle, 1971; Pascarella & Terenzini). Similarly, with one exception
(Nosow, 1975), most evidence suggests that RLC students tend to report a much more personally satisfying social climate in their living arrangements (Moore & Ostrander, 1980). Such impact, nevertheless, could be a function of self-selection, given that these studies failed to control for students’ initial motivational and other characteristics.
It is not surprising that the overwhelming majority of studies has shown that RLC students tend to manifest higher retention (D’Souza, 2003; Pike, Schroeder, & Berry, 1996;
Thompson, 2002; Woods, 1999) than those in conventional residence halls. Moreover, they demonstrate better academic performance, even after controlling for past performance and aptitude (Barnes, 1977; Blimling, 1988; Felver, 1983; Kanoy & Bruhn, 1996; Pascarella &
Terenzini, 1981; Vanderwall, 1972; Vickerson, 2003). A more recent example is a study by).
For example, using a small sample of 29 students from a private women’s college, Kanoy and
Bruhn investigated the impact of a first-year RLC (under the local label of a “living-learning residence hall”). This RLC did not involve any curricular intervention other than formally structured peer mentoring, i. e., a well-trained sophomore peer educator facilitating RLC students’ social and academic transition by providing at least one social and one educational program per month and fostering individual relationships. Although the program lasted only one year, Kanoy and Bruhn completed a longitudinal study, reporting that these RLC participants achieved higher GPAs during their first two years in college than did a comparison group. 29
Though they did not find a higher retention rate among the RLC participants, these students outperformed their predicted GPA in each of the four semesters of the study.
With the exception of D’Souza (2003), evidence is consistent that RLCs demonstrate positive impact on other dimensions of student learning and personal development, such as higher levels of interactions with faculty, peers interactions, academic integration, overall academic self-efficacy, level of involvement in beneficial college activities, academic transition to college, enjoyment of academic challenges, openness to different perspectives, satisfaction with residential living, time spent on academic work, level of involvement in community service
(D’Souza, 2003; Inkelas & Weisman, 2003; Pike, et al., 1996; Woods, 1999).
Some types of RLCs, however, were found to have a mixed impact on students. Clarke,
Miser, and Roberts (1988), for example, confirmed a previous finding that RLC students (called
“students housed in halls with formal themes”) spend more time in formal study groups, participate more in class discussions, and are more satisfied with general education courses.
Nevertheless, “students’ involvement in thematic houses appeared to reduce both their interest in career development and satisfaction with friendships, perhaps because thematic houses attracted students with a fairly narrow view of their purpose” (p. 11).
All in all, the weight of evidence regarding the influence of RLCs on student learning and personal development is mostly positive. However, in terms of research design, many studies share similar drawbacks. For one, they typically used samples from a single institution, thus limiting the generalizeability of the results. For another, students most often self-select into different living arrangements, thus making it difficult to separate the influences of students’ input characteristics from the net impact of their RLCs. However, given the carefully selected samples and closely matched comparison groups, as well as satisfactory validity and reliability, research 30
still underscores the strong positive impact of RLCs on student learning and development.
Among the impacts most frequently examined by previous research are outcomes such as academic performance, retention, involvement, and overall satisfaction with college. Other important and legitimate outcomes, such as civic engagement, remain largely unexplored.
The Construct of Civic Engagement
The focus of this dissertation requires a precise understanding of the outcome construct measured—civic engagement. A clear definition of this construct, however, is not supplied by any author except perhaps Ehrlich (2000). In most literature, it tends to be used interchangeably with “civic responsibility,” “civic involvement,” “democratic citizenship,” and “civic values or behavior.”
Ehrlich (2000) defined civic engagement as “working to make a difference in the civic life of our communities and developing the combination of knowledge, skills, values, and motivation to make that difference. It means enhancing the quality of life in the community, through both political and non-political processes” (p. vi). He defined a civically engaged person, as one who feels and acts on his or her sense of responsibility to the community. He maintains that higher education should produce graduates who have a deep understanding and commitment to the arts of democracy, or skills for such civic engagement—dialogue, engagement, and responsible participation. However, Ehrlich did not clarify the meaning of “civic,” a definition later provided by Colby et al. (2000) who described it as covering all social spheres beyond the family, ranging from neighborhoods to local communities to state, national, and cross-national arenas.
With the exception of Ehrlich (2000), most authors provide definitions of constructs semantically overlapping with civic engagement. For example, Colby et al. (2000) outlined a 31 working definition of moral and civic responsibility that covers four dimensions: (a) personal integrity, i. e., developing the person as an accountable individual and engaged participant in society—local, state, national, and global, developing such personal attributes as honesty, trustworthiness, fairness, and respect, as well as concern for the rights of others; (b) social responsibility, i. e., developing one’s social consciousness, compassion/concern for others, and commitment to the welfare of others outside one’s immediate sphere; (c) civic responsibility, i. e., understanding the operation of one’s community and the problems it faces as well as its diversity, fostering a willingness to commit time and energy to improve one’s community life, and to work collectively to resolve community issues, such as through community service; and
(d) constructive political participation, e. g., voting.
The same issue of lack of distinction among conceptually overlapping terms is also apparent in the work by Sax (2000). When addressing college undergraduates’ civic responsibility, Sax examined two trends: (a) involvement in volunteerism and community service and (b) interest in politics, as indicated by voting in elections, keeping up to date with current political affairs, and participating in student government. Later, when discussing the college impact on students’ civic values and behaviors, Sax focused on the following attitudinal and behavioral aspects of citizenship: (a) commitment to social activism, as indicated by four measures: participating in community action programs, helping others who are in difficulty, influencing social values, and influencing political structure; (b) sense of empowerment, which is reflected in students’ level of disagreement with the survey statement: “Really, an individual can do little to bring about change in our society,”; and (c) community involvement, e. g., the number of hours a student reports participating in volunteer work or community service during the previous year. 32
While not offering an explicit definition of civic engagement, Guarasci and Cornwell
(1997) elaborated on moral and civic responsibility and democratic citizenship, with a central
focus on highlighting the need to prepare college students for responsible citizenship in an age of
difference. According to their definition, moral and civic responsibility involves individual integrity, social responsibility, constructive political participation, tolerance for racial, ethnic, religious, and political differences, and concern for equity and social justice, a definition that bears much resemblance to that of Colby et al. (2000). Key to Guarasci and Cornwell’s democratic citizenship is increasing undergraduates’ understanding of racial/ethnic, religious, political, sexual orientation, and class differences while building a sense of campus community.
In their view, students must learn how to engage in issues of diversity, to recognize, negotiate, and live with differences through the arts of democracy—structured conversations, inter-group
(racial, social, religious, etc.) dialogues, responsible participation, open inquiry, the development of communication skills, and the ability to make informed judgments and find one’s voice.
Finally, a civically engaged person recognizes the responsibilities to the larger community, understands the extent to which the groups he or she participates in contribute to the larger community, and believes in the obligations to protect the rights of groups from different racial/ethnic, religious, political, and social backgrounds (Guarasci & Cornwell, 1997).
Several other authors have used the term “citizenship” to describe attitudes and behaviors that are conceptually overlapping with civic responsibility, civic involvement, civic engagement, or civic values as discussed above. Boyte and Kari (2000), for instance, suggested that higher education can strengthen citizenship through voter registration efforts, programs to enhance students’ knowledge of public affairs, student government, skills for balancing between individual rights and responsibilities, concern for others, understanding of differences, 33 volunteerism, and confidence in collective action. They maintain that higher education should cultivate students’ civic skills, which they defined as the art of public argumentation, ability to evaluate information critically, interest in public affairs, and ability to work with different people, a definition similar to Ehrlich’s (2000) and Guarasci and Cornwell’s (1997) discussions of the arts of democracy.
On a more specific level, in identifying residence life student development goals,
Winston, Anchors, and Associates (1993) listed three major goals that are closely connected to citizenship. One is developing students to be responsible, contributing members of a society of multiple communities by acquiring the skills and knowledge needed to be productive citizen- leaders. Another is to demonstrate a commitment to ideals of altruism and social justice. The third goal is values education, i. e., challenging students to confront moral/ethical issues and creating opportunities for them to have dialogues on current social problems. Active citizenship, they held, takes the form of student participation in hall or campus government and involvement in community service.
While none of these scholars provides a definition claiming to encompass all the components of this construct, they share a basic underlying belief that civic engagement is a multidimensional concept involving the interaction of citizens with their society and government.
In this dissertation, I made no attempt to distinguish the interchangeable terms these scholars use.
Indeed, their discussions of semantically overlapping concepts provide a useful framework from which to derive the core elements of civic engagement. Thus, a working definition for the outcome construct of this study—civic engagement, coalesced around the following key dimensions, which can be translated to specific indicators most relevant to the context of college students. These include: (a) volunteerism and service to the community, as indicated by one’s 34
attitudes towards and actual involvement in volunteer work or community service projects, be it
one-time or ongoing; (b) social responsibility, as reflected from one’s sense of obligation to
contribute to the common good; (c) civic empowerment, as indicated from one’s perception that he/she has the capacity to effect change; a behavioral measure of this dimension is one’s participation in political or social activism; (d) understanding of and appreciation for differences,
as elaborated by Guarasci and Cornwell (1997), highlighting students’ understanding of and
appreciation for ethnic, racial, religious, political, sexual orientation, and class differences, while
building a sense of campus community; (e) moral values development, which is inexorably
intertwined with civic engagement in that both involve mutually interdependent sets of
knowledge and skills (Ehrlich, 2000). Ehrlich held that knowledge of basic ethical concepts and
principles, such as justice and equity, is integral to civic learning. In the same vein, Colby et al.
(2000) recognized that “our democratic principles, including tolerance and respect for others,
procedural impartiality, concern for both the rights of the individual and the welfare of the group,
are all grounded in moral principles” (p. xxi). For one thing, active political involvement should
be guided by a strong moral compass. The above five dimensions provide a basis from which to
evaluate the construct validity of the outcome measures used in this dissertation.
College Impact on Student Civic Engagement
In Pascarella and Terenzini’s (1991) landmark work on college impact, civic engagement
falls within one of the five categories of attitudes and values—social and political attitudes and
values. Pascarella and Terenzini organized research on political and social values in terms of
three general foci: (a) altruism, humanitarianism, and civic values; (b) political values and
attitudes, e. g., demonstrating for a cause, voting, discussing political affairs; and (c) general 35
tolerance for the civil rights and civil liberties of others. These themes covered many of the dimensions of civic engagement established in this dissertation.
Regarding the first focus, they concluded that, with a few exceptions, both studies using national representative samples (a total of 11 studies reviewed) and small-scale studies (a total of
11 studies reviewed) provided abundant and consistent evidence indicating that “changes toward
greater altruism, humanitarianism, and sense of civic responsibility and social conscience occur
during the college years” (Pascarella & Terenzini, 1991, p. 277). Regarding the second focus,
they drew similar conclusions, that is, with a few exceptions, both national (a total of 20 studies
reviewed) and small-scale studies (a total of 17 studies reviewed) “produced results that almost
invariably indicate changes during the college years in students’ political attitudes and values
toward more liberal political stances, greater interest in social and political issues, and greater
interest and involvement in the political process” (p. 278). Regarding the third focus, both
national (a total of 17 studies reviewed) and small-scale studies (16 studied reviewed) dealing
with changes during the college years related to general tolerance for conformity “uniformly
report shifts toward social, racial, ethnic, and political tolerance and greater support for the rights of individuals in a wide variety of areas” (p. 279).
Pascarella and Terenzini (1991) also synthesized studies estimating the net impact of college on the above three foci of social and political values and attitudes. With regard to the first focus, they concluded that the general weight of evidence, though not so compelling, supports a tentative conclusion that college attendance does have a modest net effect on social conscience and humanitarian values above and beyond the characteristics students bring with them to college. With respect to the second focus, they concluded that evidence is relatively clear and reliable indicating that the collegiate experience exerts an influence on political attitudes and 36 values after controlling for, to varying degrees, student background characteristics and initial political orientations, though such an effect is modest.
With regard to within-college effects, when controlling for pre-college characteristics, living in a residence hall appears to be consistently and positively associated with increases in altruism, support for civil liberties, and desirable change in political and social values (Pascarella
& Terenzini, 1991). Living in an experimental living-learning setting is also associated with net increases in liberalism, and, to a small degree, in social conscience (Lacy, 1978; Newcomb,
Brown, Kulik, Reimer, & Revelle, 1970, 1971), as well as greater increases in liberalism than students in conventional residential arrangements (Lacy, 1978; Newcomb et al., 1970; Stakenas,
1972). A modest but consistent body of research suggests that majoring in the social sciences has a positive association with an increase in a sense of social responsibility and support for civil rights and liberties, while majors in business, education, and engineering generally tend to show the smallest gains (Pascarella & Terenzini). However, evidence for the effects of academic major and coursework on political and social values is ambiguous.
Research on the conditional effects of college on political and social values has focused on those associated with gender. Pascarella and Terenzini (1991) found limited and inconclusive evidence on the interaction between gender and changes in political and social attitudes during college. “One cannot conclude with any confidence that differential, sex [gender]-related college effects on social or political values do or do not exist” (p. 318).
More up-to-date findings related to college impact on civic engagement were generated by Sax (2000), who conducted a longitudinal study of undergraduates’ changes in civic values and behaviors measured at three points—the first fall semester in college, four-year follow-up, and finally a follow-up nine years after college entry. According to her, many measures of civic 37
engagement exhibited considerable change during college, particularly four years after college
entry, which is consistent with prior findings showing college to be positively associated with
gains in altruism and civic responsibility (Astin, 1977; Bowen, 1977; Hyman, & Wright, 1979;
Pascarella, Smart, & Braxton, 1986; Pascarella & Terenzini, 1991). For example, the percentage
of students saying they were committed to the goal of “helping others in difficulty” increased
from 57.3% to 68.1% four years after college entry. There were exceptions, though. Regarding
another outcome measure of civic engagement—sense of empowerment, students’ confidence in their ability to make actual changes in society remained largely unaltered during and after the college experience. Nevertheless, the nine-year follow-up revealed a more complex picture. The percentage expressing commitment to the goal of “helping others in difficulty” dropped to
60.8%. Similar findings were obtained on two other indicators of civic engagement used in her survey: influencing the political structure and participating in a community action program. Sax therefore concluded that the increase in the commitment to social activism during the college years may in fact be temporary.
Sax (2000) also discovered a pattern of change over time among a pool of volunteers by examining the relationship between prior volunteering experience and volunteer activities during and after college. Not surprisingly, she found that frequent volunteering during high school doubles one’s likelihood of being a frequent volunteer both during and after college. Likewise, those who volunteer three or more hours per week in college are twice as likely as non-college volunteers to volunteer frequently after college. Sax further detected some inconsistency of change: Among frequent high school volunteers, more than half reported doing no volunteer work in college. The same is true of those who volunteer during college; that is, many do not volunteer after college. Sax observed that the apparent disappearance of some portion of the 38
volunteer force suggested the unstable nature of the habits of volunteerism fostered in high
school and college.
Research has demonstrated that a variety of factors affect students’ level of civic
engagement. Pascarella, Ethington, and Smart (1988) found that student-faculty interaction is
positively associated with changes in altruism and political liberalism. Nevertheless, the
magnitude of faculty influence is less clear. Sax (2000) identified several college environmental
influences on social activism, the most prominent of which is the accentuation effect of the peer
environment. Regardless of students’ pre-college commitment to social activism, espousing
activism among the student body at an institution is positively associated with students’ reported
level of activism. In addition, she found that time spent attending religious services, performing
volunteer work, attending classes and labs, and exercising or playing sports positively impact social activism as well. A negative association, however, was reported between this outcome and majoring in engineering and time spent in watching television.
Meanwhile, Sax (2000) reported a positive association between the socio-economic level of the students’ peer group and students’ sense of empowerment. In other words, students attending an institution that enrolls students from wealthier and more highly-educated families tend to report a higher degree of agreement with the post-college belief that individuals have the ability to change society. Socializing with people from different racial/ethnic backgrounds, discussing political and social issues, and attending religious services also positively affect students’ sense of empowerment. Students’ feeling of depression and their perception that college administrators do not care about their concerns, on the other hand, tend to have a negative impact on this outcome. 39
Sax (2000) identified the commitment to social activism among a student’s peers as the only aspect of the college environments that has a significant influence on that student’s community involvement. Several measures of student involvement during college, including attending religious services, attending racial and cultural awareness workshops, socializing with people from different racial and ethnic backgrounds, performing volunteer work, and talking with faculty outside the class, are positively associated with students’ post-college volunteerism.
Finally, Sax (2000) revealed several input moderating factors that affect the direction and magnitude of college impact on student civic engagement. Most notably, reported levels of incoming first-year students’ political involvement and the likelihood of their discussing politics, are moderated by students’ socioeconomic status and their intended academic major.
Specifically, those who report a higher family income and whose parents have a college degree are more likely to discuss politics on a frequent basis. Those majoring in English, political science, history, and humanities tend to discuss politics more frequently than other students.
Education majors, however, discuss politics at a relatively low frequency, a finding Sax described as disturbing. Recent research has also shown that college students who participate in course-based community service or service-learning tend to report a higher level of civic engagement than those participating in other forms of service conducted independently (Erhlich,
1997; Oates, 2001; Zaff & Midelson, 2001).
RLCs and Student Civic Engagement
Schroeder et al. (1994) maintained that enhancing an appreciation for cultural and racial diversity and developing civic leadership skills should be an integral part of residential education. In other words, promoting residents’ civic engagement is one of the espoused goals of residential education. This is particularly true for RLCs for the following reasons: First, a 40 cohesive campus community is the most likely environment for civic and moral learning (Colby et al., 2000). RLCs, by their very definition, parallel Dewey’s notion of a democratic society where “informed citizens interact with each other, learn from each other, grow with each other, and together make their communities more than the sum of their parts” (cited in Erhlich, 2000, p. ix). Furthermore, Dewey argued that a community of learners, just like an RLC—a form of micro-democratic society—is the primary mechanism through which this democratizing process emerges. Second, promoting students’ civic responsibility, as noted above, has been explicitly recognized as an inherent goal of many residence life programs and a significant objective of many RLCs in particular (Freese, 1997; Hennessy, 1981; Smith, 2001). An inclusive community, as engendered by an RLC, can impart not only a sense of belonging to its members, but also provide a vital context for promoting the common good and appreciation for differences. Third, the dynamic relationship between involvement and civic responsibility also supports the expectation that programs, such as RLCs, which are designed to provide opportunities for increased involvement, increased peer and faculty interactions, and increased integration between curricular learning and out-of-class learning, promote student civic engagement.
A Summary of Literature
To summarize, the review of literature establishes that the college experience can produce an “impact” on students. One manifestation of college impact is the overall positive influence on student civic engagement. An extensive body of research uses the word “impact” or
“effect” to identify the influences of college environments and experiences on a wide range of educational outcomes. Some studies examine such impacts by using correlational-comparative designs, while others estimate the net effects by statistically controlling for some other confounding influences, such as students’ pre-college characteristics; some studies track 41 longitudinal changes or growth on a certain outcome (long-term effects), while others are limited to a one-point assessment of that outcome during the academic cycle. Given that using the word
“impact” to describe influences of educational programs, either net or combined influences, has become prevalent in literature, I used “impact” in this dissertation to describe the results obtained from a correlational-comparative research design.
Multiple, diverse, and interrelated experiences affect the scope, direction, and strength of college impact, and living in residence halls is one of the primary determining factors in such interplay. The RLC, an intentionally designed alternative to conventional residence halls, is theoretically conducive to fostering civic engagement. Nevertheless, there is an apparent paucity of empirical research addressing the proposition that RLCs positively impact student civic engagement—an important outcome that has been and will continue to be expected from higher education. Clearly some knowledge gaps exist in this regard. To fill those gaps, this dissertation applied a methodology to determine whether a sample of RLCs actually affect levels of student civic engagement.
42
CHAPTER III: METHODS
Overall Research Design
The purposes of this dissertation were to investigate the relationship between
participation in an RLC and students’ civic engagement, and to identify those aspects of RLC
students’ inputs and environments that best predict their level of civic engagement. This study
employed a research design using posttest-only on select outcome variables, involving two
groups of first-year, full-time, degree-seeking students at five four-year, public, Midwest
universities. The final sample consisted of 1,822 RLC students and a comparison group of 1,820
students living in conventional residence halls from the same institutions. Data from a national
survey assessing the residential experience were obtained and applied to answer the research
questions.
Data Source, Participants, Sampling Methods, and Delimitations
Data Source
The results of this dissertation were based on secondary analyses of a subset of existing
data collected by the 2004 National Study of Living-Learning Programs (hereafter, NSLLP) staff
through their instrument—The 2004 Residence Environment Survey (hereafter, The Survey).
NSLLP, funded by the Association of College and University Housing Officers-International
(ACUHO-I), is the first multi-institutional study of RLCs (synonymous with “living-learning
programs” used by the NSLLP staff) in the nation. It was conducted by a national team of
researchers. A total of 34 American colleges and universities, the majority of which were four-
year, public, research extensive institutions, participated in the NSLLP. From January 2004 through March 2004, The Survey was fielded on the World Wide Web by the NSLLP National
Data Collection Office. In October 2004, I wrote a letter to the NSLLP Principal Investigator 43
(PI) at the University of Maryland, requesting permission to use The Survey data from six
Midwestern institutions for secondary analyses. A copy of the request letter is provided in
Appendix A.
Participants, Sampling Methods, and Delimitations
Participants for The Survey were selected from two on-campus student populations at
each of the 34 institutions: (a) students living in a conventional residence hall and not enrolled
in any RLC at the time of sampling; and (b) students enrolled in an RLC (either in the broad or
narrow sense of the term, as discussed in section “Major Features and the Theoretical
Foundations of the RLC Model” in the preceding chapter) and living together in the designated
unit for their RLC on campus. Participants for this dissertation were first-year respondents to The
Survey from five out of 12 Midwest universities, those with the largest number of total responses. The overall sample prior to data screening included 3,745 participants.
The RLC sample for The Survey was created by inviting the entire population of eligible
RLC students at each participating campus to complete The Survey. To obtain a closely matched comparison group, wherever possible, non-RLC students were first randomly selected from those who lived in the same residential unit as the RLC group (2003-2004 NSLLP Participating School
Guide, 2004). The rest of the comparison group was randomly selected from the remaining on- campus residents, using stratified sampling to ensure that the proportion of the students in the comparison group was equivalent, as much as possible, to the RLC group in gender composition, race/ethnicity status, and academic class standing. Such matching on multiple, stable variables can improve the posttest-only research design of the study (Shadish, Cook, & Campbell, 2002).
This dissertation included only first-year, full-time, degree-seeking respondents who were living on campus at the time of completing The Survey. The exclusion of upper-class RLC 44
students was based on the considerations that: (a) the number of upper-class students from those
five participating institutions was small; and (b) some differences between the upper-class
students in the RLC sample and their peers in the comparison group might be attributed to their
experiences prior to participating in an RLC in the Fall 2003 Semester. Thus, including them in
the study would more confound than clarify the net effects of participation in an RLC.
Instrument
The Survey was developed by the NSLLP team and is comprised of 295 items. It is a self-report questionnaire covering student demographics, pre-college perceptions, college
environments and experiences, and growth and gains as a result of the college experience. The
majority of the items in The Survey provide Likert-scale or Likert-type scale response formats,
e. g., with ratings from 1 (low) to 5 (high). A copy of this instrument is provided in Appendix B.
More specifically, The Survey contains nine sections: (a) perceptions before enrolling in college, (b) experiences in college, (c) residence hall environment, (d) perceptions of diversity,
(e) citizenship perceptions, (f) experience with alcohol, (g) future activities, (h) overall satisfaction with college, and (i) background information. Given that this dissertation did not use any items under the sections “experience with alcohol” or “future activities,” only questions and items under the remaining seven sections were introduced here. Given that principal component analyses were conducted on many items under these seven sections to create new variables, readers are advised to refer to Table C1 (provided in Appendix C) for a complete list of components generated.
The section, “perceptions before enrolling college”, is comprised of two questions—
Question 1 (“Thinking back to before you started college, what activities did you think were going to be very important to you during college?” 1=Not at all important; 2=Somewhat 45
important; 3=Important; 4=Very important) and Question 2 (“Looking back to before you started college, how confident were you that you would be successful at the following?” 1=Not at all confident; 2=Somewhat confident; 3=Confident; 4=Very confident). Under Question 1 are 10 items, on which a principal component analysis was performed, yielding four components. These
four components constituted four input variables to be used in subsequent analyses (names of
these variables created based on principal component analyses and all other variables used in this
study were italicized when mentioned in the text): importance of growth in understanding diversity and interacting with peers (Component #1), whose value was the sum of scores on three items under Question 1—1c (Getting to know people from backgrounds different than your
own), 1d (Learning about cultures different from your own), and 1e (Discussing ideas and
intellectual topics with other students); perceived importance of academic and social support in
residence halls (Component #2), whose value was the sum of scores on two items under
Question 1—1h (Finding your residence hall to be academically supportive) and 1i (Finding your
residence hall to be socially supportive); importance of participating in co-curricular activities and interacting with faculty (Component #3), whose value was the sum of scores on three items under Question 1—1a (Participating in extra-curricular activities), 1b (Participating in volunteer or community service activities), and 1f (Getting to know your professors outside of class); and importance of drinking alcohol during social occasions, which was actually a single item under
Question 1—1j.
Under Question 2 are 11 items, on which a principal component analysis was performed, yielding two input variables: confidence in handling new intellectual challenges and appreciating diversity (Component #5), whose value was the sum of scores on six items under
Question 2—2a (Handling the challenge of college-level work), 2b (Feeling as though you 46
belong to the campus), 2c (Analyzing new ideas and concepts), 2d (Applying something learned
in class to the real world), 2e (Enjoying the challenge of learning new materials), and 2f
(Appreciating new and different ideas and beliefs); and confidence in academic and personal
growth and satisfaction (Component #6), whose value was the sum of scores on five items under
Question 2—2g (Developing your own values and beliefs), 2h (Gaining skills in working with
others), 2i (Growing and developing academically), 2j (Making a difference in the community),
and 2k (Being satisfied with your college experience).
The section, “your experiences in college”, is comprised of nine questions: Question 3
(“Using a continuum of 1=Very difficult to 6=Very easy, please indicate how you felt the
following activities to be during your first year in college.”), Question 4 (“During the past year,
how much time did you spend during a typical week doing the following activities?” 1=None;
2=1 to 5 hours; 3=6 to 10 hours; 4=11 to 15 hours; 5=16 to 20 hours; 6=21 + hours), Question 5
(“During the past year, how involved are/were you in any of the following activities?” 1=Not at
all involved; 2=Somewhat involved; 3=Involved; 4=Very involved), Question 6 (“Who did you
primarily socialize with during the current school year”), Question 7 (“During interactions with
other students outside of class, how often have you done each of the following during the current
school year?” 1=Never; 2=A few times a semester; 3=A few times a month; 4=Once or more a
week), Question 8 (“About how often have you done each of the following during the current
school year?” 1=Never; 2=Once to a few times a semester; 3=A few times a month; 4=Once or
more a week), Question 9 (“Please indicate the level to which you agree with the following
statements.” 1=Strongly disagree; 2=Disagree; 3=Agree; 4=Strongly agree), Question 10 (“In
thinking about how you have changed during college, to what extent do you feel you have grown
in the following areas?” 1=Not grown at all; 2=Grown somewhat; 3=Grown; 4=Very much 47
grown), and Question 11 (“Now that you have been in college for a while, how confident do you
feel in the following areas?” 1=Not at all confident; 2=Somewhat confident; 3=Confident;
4=Very confident). This dissertation used items under Question 4, Question 5, Question 7,
Question 8, Question 9, and Question 10.
Question 4 includes 11 items. Item 4g (Volunteer work) was used as an outcome measure
for one dimension of civic engagement—volunteerism and service to the community. A principal
component analysis was performed on the remaining 10 items, yielding four environmental
variables: time spent on socializing and recreational activities (Component #7), whose value was the sum of scores on three items under Question 4—4c (Socializing with friends), 4d
(Exercising/Sports), and 4e (Partying); time spent on academic work (Component #8), whose value was the sum of scores on two items under Question 4—4a (Attending classes) and 4b
(Studying/Doing homework); time spent on media-related communications or entertainments
(Component #9), whose value was the sum of scores on three items under Question 4—4i
(Watching TV alone), 4j (E-mail or instant messaging), and 4k (Playing video/computer games); and time spent on work or student or clubs (Component #10), whose value was the sum of scores on two items under Question 4—4f (working (for pay) and 4h (student clubs/groups).
Question 5 contains 16 items. Four items—5g (Student government), 5h (Political or social activism), 5o (One-time community service activity), and 5p (On-going community service activity) were used as outcome measures for civic engagement. Another eight items were used as
single environmental variables—5a (Fraternity/sorority), 5d (Arts/music performances and
activities), 5e (Intramural or club sports), 5i (Religious clubs and activities), 5j (Ethnic/cross- cultural activities/clubs), 5k (Media activities), 5l (Work-study or work on-campus), and 5m
(Work off-campus). The remaining items (i. e., 5b, 5c, 5f, and 5n) were not included in this study 48
given that only one response to these items—1 (Not at all involved)—was within the acceptable
range of distribution and the rest of responses were defined as outliers. In other words, recoding
the large number of outliers would practically reduce these items from being interval variables to
dichotomous variables.
Question 7 is comprised of 11 items. A principal component analysis of 10 items
(excluding item 7b) yielded two environmental variables: frequency of diverse peer interactions
(Component #11), whose value was the sum of scores on six items under Question 7—7c
(Talked about different lifestyles/customs), 7e (Held discussions with students whose personal
values were very different from your own), 7f (Discussed major social issues such as peace,
human rights, and justice), 7h (Held discussions with students whose religious beliefs were very
different from your own), 7i (Discussed your views about multiculturalism and diversity), and 7k
(Held discussions with students whose political opinions were very different from your own); and frequency of academic and career-related peer interactions (Component #12), whose value was the sum of scores on four items under Question 7—7a (Discussed something learned in class), 7d (Shared your concerns about classes and assignments), 7g (Talked about your future plans and career ambitions), and 7j (Studied in groups).
Question 8 contains 10 items, out of which a principal component analysis generated three environmental variables: academic and career-related interactions with faculty (Component
#13), whose value was the sum of scores on five items under Question 8—8a (Asked your instructor for information related to a course your were taking), 8b (Visited informally with an instructor before or after class), 8c (Made an appointment to meet with an instructor in his/her
office), 8d (Communicated with your instructor with e-mail), and 8f (Discussed your career
plans and ambitions with an instructor); personal and cultural interactions with faculty 49
(Component #14), whose value was the sum of scores on three items under Question 8—8e
(Visited informally with an instructor using a social occasion), 8g (Discussed personal problems or concerns with an instructor), and 8h (Went to a cultural event with an instructor or class); and research-related interactions with faculty (Component #15), whose value was the sum of scores on three items under Question 8—8i (Worked with an instructor on an independent project) and
8j (Worked with an instructor involving his/her research).
A principal component analysis of the 20 items listed under Question 9 generated four environmental variables: (a) enjoyment of integrated learning, intellectual challenge, and application of knowledge (Component #16), whose value was the sum of scores on eight items under Question 9—9i (I have been excited about a specific field or major as a result of taking a course in that field), 9k (When I don’t understand something in a course, I work at it until I do),
9l (Something learned in one class helped me understand something from another class), 9n (I enjoy the challenge of learning complicated new material), 9p (I often have discussions with other students about ideas or concepts in class), 9q (Learning is important to me because it will give me greater control over my life), 9s (I enjoy courses that are intellectually challenging), and
9t (I have applied materials learned in one class to other areas in my life); enjoyment of integration of academic learning and self-discovery (Component #17), whose value was the sum of scores on four items under Question 9—9b (I prefer courses in which the materials help me understand something about myself), 9e (I consider the best teachers to be those who can tie things learned in the class to things that are important to me in my personal life), 9o (I prefer reading things that are relevant to my personal experience), and 9r (For me, one of the most important benefits of a college education is a better understanding of myself and my values); enjoyment of multiplicity of thinking (Component #18), whose value was the sum of scores on 50
three items under Question 9—9g (I try to explore the meaning and interpretation of facts when
introduced to a new idea), 9h (A good way to develop my own opinions is to critically analyze the strength and limitations of different points of view), and 9m (I try to look at everybody’s side of a disagreement before making a decision); and (d) enjoyment of questioning others’ opinions and going beyond dualistic thinking (Component #19), whose value was the sum of scores on four items under Question 9—9a (I frequently question or challenge professors’ statements and ideas before accepting them as right), 9d (There have been times when I have disagreed with the
author of a book or article that I was reading), 9f (I enjoy discussing issues with people who don’t agree with me), and 9c (I prefer courses requiring me to organize and interpret ideas over courses that ask me only to remember facts).
Question 10 includes 14 items. Item 10b (Developing your own values and ethical standards) was used as an outcome measure for one dimension of civic engagement—moral values development. A principal component analysis on these 14 items retained three components—Component #20 (Labeled “Intellectual growth”), Component #21 (Labeled
“Personal growth), and Component #22. Based on Component #22, an outcome measure for one dimension of civic engagement—understanding of and appreciation for diversity—was constructed, whose value was the sum of scores on five items under Question 10—10a
(Becoming more aware of different philosophies, lifestyles, and cultures), 10g (Appreciation of racial/ethnic differences), 10j (Appreciation of art, music, and drama), 10l (Openness to views that you oppose), and 10m (Ability to discuss controversial issues). This study did not use
Component #20 or Component #21 for any analyses.
The section “your residence hall environment” contains two questions—Question 12
(“How often do you utilize the following resources or participate in the following activities 51
inside your residence hall?” 1=Never; 2=A few times a semester; 3=A few times a month;
4=One or more a week; 9=Not available in my residence hall) and Question 13 (“Consider how
well each of the following statements describes your residence hall environment.” 1=Strongly
disagree; 2=Disagree; 3=Agree; 4=Strongly agree). A principal component analysis of the nine
items under Question 12 generated two environmental variables: frequency of using academic
advising and faculty resources in residence halls (Component #23), whose value was the sum of scores on four items under Question 12—12a (Computer labs), 12b (Academic advisors), 12d
(Interactions with professors), and 12e (Seminars and lectures); and frequency of using peer and co-curricular resources in residence halls (Component #24), whose value was the sum of scores on five items under Question 12—12c (Peer counselors), 12f (Peer study groups), 12g (Social activities), 12h (Career workshops), and 12i (Community service projects).
A principal component analysis on the 14 items under Question 13 produced two environmental variables: academic support in the residence environment (Component #25), whose value was the sum of scores on eight items under Question 13—13a (I can find adequate quiet study space available in my residence hall), 13d (Life in my residence environment is intellectually stimulating), 13i (I have enough peer support in my residence environment to do well academically), 13j (Most students in my residence study a lot), 13k (I think the majority of students in my residence think academic success is important), 13l (My residence environment clearly supports my academic achievement), 13m (The staff in my residence spend a great deal of time helping students succeed academically), and 13n (I think it’s easy for students to form
study groups in my residence environment); and social support for diverse peer interactions in
the residence environment (Component #26), whose value was the sum of scores on six items
under Question 13—13b (I feel that students in my residence environment have an appreciation 52
for people from different races or ethnic groups), 13c (Students in my residence are concerned
with helping and supporting one another), 13e (I find that students in my residence have an
appreciation for people with different sexual orientations), 13f (I would recommend this
residence environment to a friend), 13g (I find that students in my residence environment have an appreciation for people from different religions), and 13h (I see students with different backgrounds having a lot of interactions with one another in my residence environment).
The section “perceptions of diversity” includes three questions—Question 14 (“To what
extent have you done the following with students from a racial/ethnic group that is different from
your own?” 1=Not at all; 2=A little; 3=A lot; 4=All of the time), Question 15 (“Please rate the
extent to which each of the following is descriptive of your college campus.” 1=Little or none;
2=Some; 3=Quite a lot; 4=A great deal), and Question 16 (“Please indicate the extent to which
you agree or disagree with the following statement.” 1=Strongly disagree; 2=Disagree; 3=Agree;
4=Strongly agree; 9=Don’t know/Never thought about this). A principal component analysis of
the 11 items under Question 14 generated three environmental variables: amount of intellectual,
social, and personal interactions with peers from a different racial/ethnic group (Component
#27), whose value was the sum of scores on eight items under Question 14—14a (Studied
together), 14b (Shared a meal together), 14c (Were roommates), 14d (Attended social events
together), 14e (Had intellectual discussions out of class), 14g (Shared personal feelings and
problems), 14h (Participation in extra-curricular activities), and 14i (Had meaningful discussions
about race relations outside of class); absence of unfriendly interactions with peers from a
different racial/ethnic group (Component #28), whose value was the sum of scores on two items
under Question 14 (the scoring of these two items were reversed prior to the principal component
analysis)—14j (Had guarded, cautious interactions) and 14k (Had intense, or even hostile 53 interactions); and amount of intimate interactions with peers from a different racial/ethnic group
(Component #29), whose value was actually the score on the item—14f (Dated someone from a different racial/ethnic group).
A principal component analysis performed on the nine items under Question 15 yielded three environmental variables: relationship between students from different racial/ethnic backgrounds (Component #30), whose value was the sum of scores on five items under Question
15—15b (Dating between students of color and White students on campus), 15d (Friendship between students of color and White students), 15f (Separation among students from different racial/ethical backgrounds on campus; scoring reversed), 15g (Trust and respect between students from different racial/ethnic backgrounds), and 15h (Interaction between students of color and White students); absence of racial tensions in the residence halls or on campus
(Component #31), whose value was the sum of scores on two items under Question 15 (the scoring of these two items were reversed prior to the principal component analysis)—15c (Inter- racial tension in the residence hall) and 15i (Racial conflict on campus); and campus commitment to the success of students of color (Component #32), a variable whose value was the sum of scores on two items under Question 15— 15a (Respect by White professors for students of color) and 15e (Campus commitment to develop an environment that is conducive to the success of students of color).
A principal component analysis conducted on the eight items under Question 16 yielded two environmental variables and one outcome measure for one dimension of civic engagement.
The outcome measure is gains in inter-racial understanding (Component #33), whose value was the sum of scores three items under Question 16—16a (Since coming to college, I have learned a great deal about other racial/ethnic groups), 16b (I have gained a greater commitment to my 54
racial/ethnic identity since coming to college), and 16d (Since coming to college, I have become
aware of the complexities of inter-group understanding). The two environmental variables
include: scope and quality of one’s racial interactions with peers (Component #34), whose value
was the sum of scores on three items under Question 16—16e (My relationships with students
from different racial/ethnic backgrounds during college have been positive), 16g (My social
interactions on this campus are largely confirmed to students of my race), and16h (At times, it is
important to be with people of my own racial/ethnic group for the chance to be myself); and
campus commitment to racial diversity (Component #35), whose value was the sum of scores on
two items under Question 16 (the scoring of these two items were reversed prior to the principal
component analysis)—16c (My campus’ commitment to diversity fosters more division among
racial/ethnic groups than inter-group understanding) and 16f (I think this campus’s focus on
diversity pays too much emphasis on the differences between racial/ethnic groups).
The section “citizenship perceptions” contains one question—Question 17 (“Please
indicate your agreement or disagreement with the following statements.” 1=Strongly disagree;
2=Disagree; 3=Neural; 4=Agree; 5=Strongly agree), which includes 14 items. A principal
component analysis of these 14 items generated three outcome measures: perceptions on
volunteerism and service to the community (Component #36), whose value was the sum of scores
on seven items under Question 17—17a (I understand the extent to which the groups I participate
in contribute to the larger community), 17b (It is important to me that I play an active role in my
communities), 17c (I volunteer my time to the community), 17f (I believe I have responsibilities
to my community); 17g (I give time to make a difference for someone else), 17i (I work with others to make the community better places), and 17m (I believe my work has a greater purpose for the larger community); sense of responsibility to the common good (Component #37), whose 55
value was the sum of scores on four items under Question 17—17k (I am willing to act for the
rights of others), 17l (I participate in activities that contribute to the common good), 17m (I believe I have a civic responsibility to the greater public), and 17n (I value opportunities that allow me to contribute to my community); and sense of civic empowerment (Component #38), whose value was the sum of scores on three items under Question 17—17e (There is little I can do that makes a difference for others; scoring reversed), 17h (Ordinary people can make a difference in their community), and 17j (I have the power to make a difference in my community).
The section “overall satisfaction with college” contains three questions—Question 24
(“Indicate the extent to which you agree or disagree with the following statements.” 1=Strongly disagree; 2=Disagree; 3=Agree; 4=Strongly agree; 9=Don’t know/Never thought about this) and
Question 25 (“How satisfied have you been with each of the following aspects of your academic experience at your college or university?” 1=Very dissatisfied; 2=Dissatisfied; 3=Satisfied;
4=Very satisfied), and Question 26 (“Do you plan to return to the same college or university next fall?”). Only one item under Question 24—24e (I feel a sense of belonging to the campus community) was included in this study as an environmental variable.
The section “background information” includes questions on student demographics, of which the following were used in this study: gender, sexual orientation, race/ethnicity, citizenship, religion, father’s highest level of education, mother’s highest level of education, parents’ total annual income, average high school grade, and the RLC a student was participating in at the time of completing The Survey (Question 40).
In summary, of those 295 items in The Survey, twenty-six single items were used directly as variables for statistical analyses in this study; principal component analyses were performed 56
on 154 items, generating 6 input variables, 26 environmental variables, and 12 outcome
measures.
Major Variables Used in this Study
All the variables for this dissertation were embedded in The Survey, which provides an overall structure drawing on Astin’s (1977, 1993) conceptual model for assessment: the Input—
Environment—Output model (or the I—E—O Model). Astin’s model assumes that students’
background and characteristics at the point of entering college (Input) can influence their college
experiences (Environment, e. g., courses, programs, facilities, faculty, peer groups, etc.), which,
in turn, can subsequently influence their gains from college (Output), including growth in civic
engagement. Astin argued that to construct as accurate as possible a picture of the net effects of
college on students, researchers should identify and account for as many relevant student input
differences as feasible. The following sections introduce the major variables used in this
dissertation within the framework of the I—E—O Model. As indicated above, most of the input,
environmental, and outcome variables were created based on principal component analyses.
Table 1 displays the variables used in this dissertation within the framework of the I—E—O
model.
57
Table 1
Variables Used in this Study within the Framework of the I—E—O Model ______Variable type Variable name ______Input
Demographic
Gender
Sexual orientation
Race/ethnicity
Citizenship
Religion
Father’s education
Mother’s education
Parents’ income
High school grade
Pre-college importance of
Growth in understanding diversity and interacting with peers
Academic and social support in residence halls
Participating in co-curricular activities and interacting with faculty
Drinking alcohol during social occasions
Pre-college confidence in
Handling new intellectual challenges and appreciating diversity
Academic and personal growth and satisfaction ______
58
Table 1 (Continued)
______Variable type Variable name ______Environmental
Participating in an RLC or not
Time spent on socializing and recreational activities
Time spent on academic work
Time spent on media-related communications or entertainments\
Time spent on work or student clubs/groups
Involvement in fraternity/sorority
Involvement in arts/music performance/activities
Involvement in intramural or club sports
Involvement in religious clubs and activities
Involvement in ethnic/cross-cultural activities/clubs
Involvement in media activities
Involvement in work-study or work on-campus
Involvement in work off-campus
Frequency of diverse peer interactions
Frequency of academic and career-related peer interactions
Amount of intellectual, social, and personal interactions with peers from a different racial/ethnic group
Absence of unfriendly interactions with peers from a different racial/ethnic group
Amount of intimate interactions with peers from a different racial/ethnic group ______59
Table 1 (Continued)
______Variable type Variable name ______
Frequency of academic and career-related interactions with faculty
Frequency of personal and cultural interactions with faculty
Frequency of research-related interaction with faculty
Enjoyment of integrated learning, intellectual challenge, and application of knowledge
Enjoyment of integration of academic learning and self-discovery
Enjoyment of multiplicity of thinking
Enjoyment of questioning others’ opinions and going beyond dualistic thinking
Frequency of using academic advising and faculty resources in residence halls
Frequency of using peer and co-curricular resources in residence halls
Academic support in the residence environment
Social support for diverse peer interactions in residence in the residence environment
Relationship between students from different racial/ethnic backgrounds
Absence of racial tensions in residence halls or on campus
Campus commitment to the success of students of color
Scope and quality of one’s racial interactions with peers
Campus commitment to racial diversity
Sense of belonging to the campus community ______
60
Table 1 (Continued)
______Variable type Variable name ______
Outcome
Time spent on volunteer work per week
Involvement in one-time community service
Involvement in on-going community service
Perceptions on volunteerism and service to the community
Involvement in student government
Sense of responsibility to the common good
Involvement in political or social activism
Sense of civic empowerment
Growth in understanding of and appreciation for diversity
Gains in inter-racial understanding
Growth in developing one’s own values and moral ethical standards
Overall level of civic engagement ______
61
Input Variables
Students entering college can be differentially motivated and prepared for their development in civic engagement during college. This dissertation used 14 input variables that were potentially related to students’ level of civic engagement during college. Eight of them were demographic variables—gender, sexual orientation, race, citizenship, religion, father’s education, parents’ total income, and high school grades. The rest of the input variables concerned students’ pre-college level of perceived importance and confidence, variables created through principal component analyses: importance of growth in understanding diversity and interacting with peers, importance of academic and social support in residence halls, importance of participating in co-curricular activities and interacting with faculty, importance of drinking alcohol during social occasions, confidence in handling new intellectual challenges and appreciating diversity, and confidence in academic and personal growth and satisfaction.
Environmental Variables
This dissertation employed a total of 35 environmental variables, the majority of which were created through principal component analyses. One environmental variable identified whether a student participated in an RLC or not at the time of completing The Survey. Its value was determined by response to Question 40 (“Which living-learning program are you currently participating in? Circle one response only.”). Those who marked one of the RLCs listed were treated as members of the RLC sample, coded as 1, and the rest as members of the comparison group, coded as 2. This variable served as the classification variable for analyses of variance determining the main effects of RLC participation on civic engagement.
The remaining environmental variables were related to students’ use of time during a typical week (including four variables: time spent on socializing and recreational activities, time 62 spent on academic work, time spent on media-related communications or entertainments, and time spent on work or student clubs), involvement in various co-curricular activities (including eight variables: [involvement in] fraternity/sorority, arts/music performance/activities, intramural or club sports, religious clubs and activities, ethnic/cross-cultural activities/clubs, media activities, work-study or work on-campus, and work off-campus), frequency of out-of- class peer interactions (including two variables: frequency of diverse peer interactions and academic and career-related peer interactions), amount of interactions with peers from a different racial/ethnic group (including three variables: intellectual, social, and personal interactions with peers from a different racial/ethnic group, absence of unfriendly interactions with peers from a different racial/ethnic group, and intimate interactions with peers from a different racial/ethnic group), frequency of interactions with faculty (including three variables: academic and career-related interactions with faculty, personal and cultural interactions with faculty, and research-related interactions with faculty), intellectual development/curricular learning (including four variables: enjoyment of integrated learning, intellectual challenge, and application of knowledge, enjoyment of integration of academic learning and self-discovery, enjoyment of multiplicity of thinking, and enjoyment of questioning others’ opinions and going beyond dualistic thinking), frequency of using residence hall resources (including two variables: frequency of using academic advising and faculty resources in residence halls and frequency of using peer and co-curricular resources in residence halls), perceptions of residence environment
(including two variables: academic support in the residence environment and social support for diverse peer interactions in the residence environment), perception of campus racial climate
(including three variables: relationship between students from different racial/ethnic backgrounds, absence of racial tensions in residence halls or on campus, and campus 63
commitment to the success of students of color), perceptions with regard to racial diversity
(including two variables: scope and quality of one’s racial interactions with peers and campus
commitment to racial diversity), and lastly, sense of belonging to the campus community.
Outcome Variables
The criterion measures of the construct—civic engagement—include 12 variables
assessing five dimensions of civic engagement. Four of these variables assessed the dimension
volunteerism and service to the community, including three behavioral measures—time spent on
volunteer work per week, involvement in one-time community service, and involvement in on-
going community service and one overall attitudinal measure—perceptions on volunteerism and
service to the community. Two variables measured the dimension—responsibility to the common
good, including a behavioral measure: involvement in student government, and an attitudinal
measure: sense of responsibility to the common good. Another two dependent variables assessed
students’ civic empowerment, including one behavioral measure—involvement in political or
social activism, and an attitudinal measure—sense of civic empowerment. Two dependent
variables measured the dimension—understanding of and appreciation for diversity: growth in
understanding of and appreciation for diversity during college and gains in inter-racial
understanding. This dissertation used one variable—growth in developing one’s own values and
moral ethical standards (10b) to measure the last dimension of civic engagement: moral values
development. The last dependent variable is overall level of civic engagement, a variable created
whose value was the sum of the scores on the above eleven individual dependent variables.
Validity and Reliability of Data and Findings
Validity and reliability are both essential qualities in research (Charles & Mertler, 2002).
The former refers to the degree to which the researcher measures what he/she intends, or 64
purports, to measure, and the latter refers to “the degree to which a set of items consistently
measures the same thing across respondents and institutional settings” (Kuh, 2002, p. 4-5). This
section addresses the validity and reliability of this study by (a) discussing the accuracy of self-
report data, (b) establishing content validity and construct validity, (c) discussing the internal and
external validity of research findings, and (d) establishing the reliability of the data.
Accuracy of Self-Report Data
This dissertation relied on student self-reports for analyses. In recent decades, self-reports
have become a widely used means of data collection in large-scale national surveys of college
students, e. g., the College Student Experience Questionnaire (Pace, 1979), the College Student
Survey (Higher Education Research Institute, 1989), and the National Survey of Student
Engagement (NSSE, 2000). Indeed, “Using self-reports from students to assess the quality of
undergraduate education is common practice” (Kuh, 2002, p. 3) and self-reported gains or
growth of college students, in particular, have become more prominent in research assessing
college impact (Pascarella, 2001; Pascarella & Terenzini, 1991).
A number of researchers have generally agreed on the credibility of self-reports (Anaya,
1992, 1999; Baird, 1976; Berdie, 1971; Ewell & Jones, 1993; Falchikov & Boud, 1989; Kol &
Verhulst, 1987; Pace, 1985; Pike, 1995, 1996; Pohlmann & Beggs, 1974; Quinto & Weener,
1983; Turner, 1983; Turner & Martin, 1984). Falchikov and Boud, for instance, did a meta- analysis of quantitative self-assessment studies that compared (college student) self- and teacher ratings of course achievement. They identified three variables correlated with the degree of correspondence between self- and teacher marks:
The quality of design of the study (with better designed studies having closer
correspondence between student and teacher than poorly designed ones); the level of the 65
course of which the assessment was a part (with students in advanced courses appearing
to be more accurate assessors than those in introductory courses); and the broad area of
study (with studies within the area of science appearing to produce more accurate self-
assessment generally). (p. 395)
Additionally, Quinto and Weener (1983) found that college students’ self-reported general and specific meta-cognitive skills in problem solving are good indicators of their level of performance on such tasks. Pace (1985), Pike (1995, 1996), and Anaya (1999), in particular, addressed the issue of using self-reports in measuring college impact. As early as 1985, Pace asserted that:
We know from both internal and external evidence that [students’] recall of activities and
their estimates of gains are credible, and that they respond carefully and perhaps in many
cases with personal interest to the content of the questionnaire. Because their responses
are congruent with other judgments and because for some goals the students may well be
the only qualified judges of whether they are any different today from what they were
when they arrived, we must pay attention to what they say. (p. 103)
More recently, Pike (1995) “reexamined the relationships between self-reports of academic development and college experiences [using CSEQ items] and scores on a widely used test of general-education knowledge and skills, the College Basic Academic Subjects
Examination (College BASE)” (p. 3). Finding some evidence of congruence in mathematics, weak evidence for the English and science domains, and no evidence for the social sciences domain, he concluded that “reasonably strong evidence was found for using self-reports of collegiate experiences as policy indicators, particularly in the domains of mathematics and science” (p. 17). 66
To strengthen his early findings, Pike (1996) conducted another study with 1,568 students from 10 institutions of higher education. The results “provide some important information about the validity of using self-reports of cognitive development during college as proxies for test scores in a national assessment of college student outcomes” (p. 107). He therefore concluded that the use of self-reports as a “general indicator of achievement can be justified” (p. 110).
Anaya (1999) provided additional evidence for the validity of self-reports on college impact. After comparing three learning indicators: self-reported verbal and quantitative growth, college GPAs, and GRE scores (Verbal, quantitative, and composite) of a national sample, she found that “student-reported cognitive growth survey items have a modest relative validity ... it is concluded that the alternate measure can be used as proxies for more direct measures of learning” (p. 499). She further suggested that “each measures some aspect of student learning and each appears to be a valid measure of learning” (p. 515).
Despite its wide use and the general agreement on its accuracy, researchers meanwhile pointed out that two factors pose as threats to the accuracy of self-reports: the inability of respondents to provide accurate information (Wentland & Smith, 1993) and their unwillingness to provide truthful information (Aeker, Kumar, & Day, 1998; Northrup, 1997). According to
Kuh (2000), the first threat results from the situation where students simply may not have sufficient experience with their institution to reach a precise judgment or they may not understand the question itself. The second case arises from the possibility that respondents intentionally report inaccurate data, mostly in answering questions related to sensitive subjects that put them in an awkward, potentially embarrassing situation (Bradburn & Sudman, 1988;
Northrup, 1997). 67
Recognizing the above threats, researchers have reached general agreement that self-
reports are likely to be valid when the following conditions are met: (a) the respondents
understand the information being requested on the survey; (b) they think the questions are
worded clearly rather than ambiguously (Laing, Sawyer, & Noble, 1988); (c) they think that the
survey questions deserve a thoughtful and honest response (Pace, 1985); (d) survey questions
cover recent activities (Converse & Presser, 1989); and (e) questions do not explore socially
undesirable, embarrassing, or personally sensitive behaviors (e. g., drug use) (Bradburn &
Sudman, 1988; Hu & Kuh, 2001; Kuh et al., 2002). After reviewing the literature on respondent
honesty in survey research, Northrup (1997) reached a general conclusion that misreporting is
associated with the extent of perceived question sensitivity or threat. “There is no evidence of
dishonest reporting for questions that are neither sensitive nor threatening … it is reasonable to
conclude that erroneous reporting for non-sensitive questions is very limited” (p. 15).
In short, considerable evidence exists showing that “students are accurate, credible
reporters of their activities and how much they have benefited from their college experience”
(Kuh, 2002, p. 4), provided that the five conditions specified above are satisfied. It is both
reasonable and appropriate to use student self-reports to estimate their gains from college on the
following grounds: (a) There is reasonably strong evidence for the congruence between student
responses and other judgments obtained through standardized tests; and (b) for some areas,
students may be best qualified to judge how they have changed from the point of entering college
(Kuh, 2002; Pace, 1984; Pascarella, 2001).
Taken as a whole, The Survey has largely fulfilled the five conditions identified above except perhaps for the third condition. Although the NSLLP researchers did not use student
focus groups or cognitive interviews to solicit students’ perspectives of the original questionnaire 68
in their pilot tests (Inkelas, Brower, Crawford, Hummel, Pope, & Zeller, 2004), following their
pilot tests, they interviewed RLC administrators and clarified certain items based on their
feedback. The Survey was administered in March 2004. Despite the questionable reliability of a
small portion of questions on the retrospective recall of pre-college perceptions, the rest of The
Survey covers first-year students’ activities of the recent past—their first fall semester or the previous seven months during college. By the time of The Survey administration, all first-year respondents had had sufficient exposure to their institution to render an informed judgment.
While the use of self-report data for this study can be generally justified, the length of The
Survey might have somewhat damaged the accuracy of data in that some participants might not have provided thoughtful and serious responses.
Validity of the Research Data and Findings
Charles and Mertler (2002) indicated that there are four types of validity obtained from the administration of tests: content validity, predictive validity, concurrent validity, and construct validity. Given that this study relied on a one-time administration of one instrument, it is not relevant to address predictive and concurrent validity. The focus of this section was, therefore, on determining the degree of content validity, construct validity, internal validity, and external validity.
Content Validity
“Content validity is present when the contents of an instrument such as an achievement test appear to be very similar to the information contained in a course or training program …
Content validity is determined by expert judgment” (Charles & Mertler, 2002, p. 157).
Two indicators existed as evidence for the content validity of The Survey. First, the environmental and outcome variables used in The Survey were similar to those used in other 69 well-regarded national surveys, e. g., the NSSE and the College Student Experience
Questionnaire, which have demonstrated their validity over the years. Second, the items on the original version of The Survey were reviewed by administrators from approximately 15 RLCs prior to the 2003 pilot test administration (Inkelas et al., 2004); revisions were also made in
Spring 2003 following the pilot tests of the instrument on four flagship research campuses with a strong tradition of RLCs.
Construct Validity
In a general sense, construct validity “involves making inferences from the sampling particulars of a study to the higher-order constructs they represent” (Shadish et al., 2002, p. 65).
It seeks a match, or correspondence, between an abstract, theoretical concept and specific measuring devices, instances, or indicators (Construct validity, 2004; Shadish et al., 2002).
Sampling particulars can apply to persons, settings, treatments, and outcomes. This section primarily deals with validity of the outcome construct—civic engagement.
While it is “never possible to establish a one-to-one relationship between the operations of a study and corresponding construct” (Shadish et al., 2002, p. 68), construct validity is enhanced by a clear, precise, and adequate explication of the construct under study and a careful selection of instances that represent the central features, or traits, of the target construct. Furthermore, determining which features are central depends on the context in which a construct is used
(Shadish et al.). Based on a thorough review of literature, this dissertation put forth a working definition for civic engagement, gleaning its five key dimensions out of the existing literature on which researchers have reached consensus. The multiple outcome measures used in The Survey reflected these core dimensions in the context of college students, excluding only a few features that were impractical to measure in the college context when The Survey was administered, e. g., 70 knowledge of civics and voter registration (i. e., 2003 was not an election year). Construct validity was therefore present in this research. In short, the outcome measures in The Survey draw upon the conceptual framework of civic engagement and represent the central features of this outcome construct identified in the literature.
Moreover, to address one of the threats to construct validity—mono-method bias, items in The Survey were worded both positively and negatively. Lastly, to reduce another threat to construct validity—reactivity to the experimental situation, the NSLLP researchers used “2004
Residence Environment Survey” as the instrument name when communicating with participants.
In addition, they asked each participating school to use only the name “2004 Residence
Environment Survey” in advertising The Survey. Further, the Informed Consent stated that “the primary purpose of this study is to understand college students’ perception of their residence environments and the impact of residence environments on students’ academic and social development.” Such measures were intended to serve as a masking procedure to prevent participants from knowing the hypothesis (Shadish et al).
To determine the presence of construct validity, researchers should also examine empirical relationships between the measures of the constructs by using a statistical technique— factor analysis (Tabachnich & Fidell, 1996). To provide evidence for the construct validity of
The Survey, factor analyses using the principal component extraction method and varimax rotation were performed to investigate the extent to which common conceptual structures underlay the measures comprising the major questions in The Survey.
Internal Validity of Findings
Internal validity is related to “conditions present in the participants or their environment while the experiment is in progress” (Charles & Mertler, 2002, p. 334). The present study did not 71
use an experimental design. The following issues might pose limitations on the internal validity
of findings from this study: (a) the influences of unknown confounding environmental variables
arising from history and maturation. In other words, given that treatment (i. e., participation in an
RLC) extended more than one semester, factors other than the treatment had time to influence
the results. During the treatment period, RLC participants “may undergo psychological changes
that produce differential effects in the criterion variable” (Charles & Mertler, 2002, p. 334); such
influences were beyond statistical control; (b) attrition or the loss of sample members after the
Fall 2003 semester; that is, some students who were originally included in the sample may have
dropped out of their institutions by the time The Survey was fielded, thus resulting in a biased
sample; (c) treatment diffusion, i. e., Participants in the comparison group may have received
some or all of the treatment which only the treatment group was supposed to experience (Shadish
et al.). The sampling method used by the NSLLP researchers to create the comparison group
might have posed a problem for internal validity. To obtain a closely matched comparison sample, wherever possible, conventional students were first randomly selected from those who lived in the same residence halls as the RLC group (Inkelas et al., 2004). In this case, the RLC
and the comparison groups were in physical proximity and could communicate; some activities
or resources intended for the RLC students could exert common influences on the comparison
group. To sum up, unexplored variables might have confounded the results and alternative
explanations may exist for the observed treatment effects.
External Validity of Findings
External validity refers to the extent to which results of a study can be generalized across
persons, settings, or treatments, be such generalizations from broad to narrow, from narrow to
broad, or across settings at about the same level of aggregation (Charles & Mertler, 2002; 72
Shadish et al., 2002). It has to do with the degree of similarity among the sample used in a study,
the population from which it is drawn, and the target population to which results are to be
generalized. This dissertation used a formal probability sampling method—random sampling, a
method most often recommended to achieve generalization. However, as indicated in Chapter
IV, certain categories of students were over- or under-represented within the RLC sample, thus
affecting the degree of generalizeability of the research findings. Lastly, this study involved only
four-year, public, Midwest institutions; whether results could be generalized to similar institutions in other locations remains at issue. Despite that, the facts that slightly half of the
RLCs existed at Midwest institutions at the time of administering The Survey and the high
response rates served to enhance external validity.
Reliability of the Data
Charles and Mertler (2002) suggested three different methods to estimate the reliability of
data—test-retest, equivalent forms, and split-half. As with other large-scale surveys, it is hardly
feasible to use a test-retest method to establish the reliability (or stability reliability, as Kuh
[2002] called it) of The Survey, e. g., by re-administering it in the same institution, due to the
substantial expense and effort needed. More importantly, a test-retest method is problematic in
that “student experience is somewhat of a moving target; a month’s time for some students can
make a non-trivial difference in how they respond to some items because of what has transpired
between the first and the second administration of the survey” (Kuh, 2002, p. 5). Nor is the
equivalent forms method feasible, given the unavailability of an alternate form for The Survey.
Using the split-half method to establish the reliability of the research data is appropriate. This
method “determines a specific form of reliability known as internal consistency” (Charles &
Mertler, 2002, p. 158). This dissertation used one commonly reported measure of internal 73
consistency—Cronbach’s alpha measure of reliability (Charles & Mertler, 2002). This is
basically an average of all possible split-half reliabilities, with a higher alpha indicating better
reliability, showing that items comprising a scale cluster around one or more central construct(s)
and are conceptually interrelated.
Specifically, the pilot tests of the original version of The Survey by the NSLLP
researchers at multiple campuses produced a substantial weight of evidence for its reliability
(Inkelas et al., 2004). NSLLP researchers tested the reliability of the pilot questionnaire primarily through statistical methods. They reported,
Composite measures representing the major constructs were developed using exploratory
factor analysis and Cronbach alpha reliability testing. Additionally, the consistency of
the scales across the campuses was tested using data from each individual institution in
the pilot study. Cronbach alpha reliabilities of the scales for the 2003 pilot test ranged
from .623 to .898. Reliability of the scales was re-tested with the 2004 NSLLP data, and
Cronbach alpha scores ranged from .624 to .918. (Inkelas et al., 2004, p. I.7)
Major Research Questions
The research questions outlined here were intended to fill those knowledge gaps
identified in the preceding chapter. Specifically, this study addressed the following major questions, which issued from the central focus of the study: relationship of participating in an
RLC to student civic engagement:
1. What demographic and pre-college characteristics describe the students in the RLC sample as compared to the students in the comparison group? Do RLC students differ from convention students with regard to their pre-college perceptions by gender, sexual orientation,
race, religion, citizenship, parents’ education, parents’ income, and high school grades? 74
2. Do RLC students and conventional students differ in their reported levels of civic
engagement, as indicated by responses to the five dimensions of this outcome construct?
3. How does the impact of participating in an RLC on civic engagement differ by gender, sexual orientation, race, religion, citizenship, parents’ education, parents’ income, and high school grade of RLC students?
4. What aspects of RLC students’ inputs and environments best predict their overall level of civic engagement and the specific attitudinal measures of civic engagement? Do the predictors of the RLC students’ overall level of civic engagement differ by gender, sexual orientation, race, religion, and citizenship?
Methods of Data Analysis
The Statistical Analysis System (SAS) for Windows 8.0 was used to perform all the statistical analyses for this dissertation. An alpha level of .05 was used for all statistical inference
tests. To answer the first research question, frequencies, Chi-Square tests, T-tests, and one-way
analyses of variance (ANOVAs) were conducted by using the Generalized Linear Model (GLM)
procedure. To address the second question, for this dissertation, I originally proposed to perform
analyses of covariance (ANCOVAs) to estimate the net effect of RLC participation on their
reported levels of civic engagement, by controlling for pre-college characteristics. However, the
significant interactions between the factor (whether participating in an RLC or not) and the
covariates (pre-college perceptions) suggested that ANCOVAs were not appropriate for the data
used in this study. Therefore, a series of ANOVAs was performed to answer both question 2 and
Question 3, i. e., investigating significant main effects of RLC participation and its conditional
effects by demographic characteristics on each dependent variable. Tukey tests for pairwise
comparisons were used to identify which subgroup was different from the other subgroup(s). To 75
address the fourth research question, hierarchical regression analyses were conducted. Astin’s
(1977, 1993) I─E─O model and previous research imply an order for the appropriate sequencing
of blocks of variables to be entered into such analyses. The use of hierarchical regression
analysis made it possible to identify which inputs and environments contributed most (amount of net variance) to RLC students’ level of civic engagement while controlling for other variables.
76
CHAPTER IV: RESULTS
This chapter reports the major findings from this dissertation in the order of the four
major research questions. First, the data were examined for potential differences between RLC
students and the comparison group in terms of input characteristics, including demographic
features and pre-college perceptions. Second, RLC students and conventional students were
compared on reported levels of civic engagement, as indicated from scores on the five dimensions of civic engagement: volunteerism and service to the community, responsibility to
the common good, civic empowerment, understanding of and appreciation for diversity, and
moral values development. Third, the impact of RLC participation on the overall level of civic
engagement was assessed for differences by gender, sexual orientation, race, religion,
citizenship, father’s education, parents’ income, and high school grades. Fourth, aspects of the
RLC students’ input features and college environments that best predict overall level and specific
measures of civic engagement were examined, with particular focus on differences by gender,
sexual orientation, race, religion, and citizenship.
Pre-Analysis Data Screening
Data Recoding
Raw data on several items were recoded for accuracy. First, the response option “Don’t
know/Never thought about this” for items under Question 16 and Question 24 were reset as
missing values. Similarly, those who responded “Don’t know” on father’s and mother’s
education were recoded as missing values as well.
Second, data on some items were reorganized to establish more equivalent subgroups.
Two students who identified themselves as transgender were deleted from the dataset because of
their extremely small number. For the same reason, for the variable—sexual orientation, gay 77
(G), lesbian (L), and bisexual (B) students were combined into one subgroup—GLB. For the
variable—race/ethnicity, respondents who identified themselves as American–Indian or Alaska
Native, Hispanic/Latino, multi-racial/ethnic, and respondents whose race/ethnicity was not
included in the answer options were combined into one subgroup—“Other.” For citizenship,
respondents who identified themselves as foreign-born naturalized citizens, foreign-born resident
aliens, or student visa holders formed one subgroup—“Other.” Respondents who marked their
religion as Buddhist, Hindu, or Muslim were combined into one subgroup—“Asian Religions.”
Lastly, since Chi-Square tests assume that the expected value for each cell is five or more, respondents who reported their high school grade as C or C-, D+ or lower, or no high school
GPA were combined with the subgroup of B- or C+.
Third, to assist interpretation, the scores on six items that are negatively worded in The
Survey were reversed. Under Question 14, the original rating scale (1=Not at all; 2=A little; 3=A lot; 4=All of the time) for two items—14 j (Had guarded, cautious interactions) and 14k (Had tense, or even hostile interactions)—was reversed so that the new values for these two items were five minus the original scores. Under Question 15, the original rating scale (1=Little or
None; 2=Some; 3=Quite a lot; 4=A great deal) for three items—15c (Inter-racial tension in the residence halls), 15f (Separation among students from different racial/ethnic backgrounds on campus), and 15i (Racial conflict on campus)—was reversed by the NSLLP PI so that the new values for these three items were five minus the original scores. Under Question 17, the original rating scale of one item—17e (There is little I can do that makes a difference for others)—was reversed by the NSLLP PI so that its new value was six minus its original score. All subsequent data transformations, data reductions, and statistical analyses involving these six items in this dissertation were based on these reversed scores. 78
Data Screening
Data from the NSLLP PI were screened by taking the following measures, most of which
were recommended by Mertler and Vannatta (2002). First, frequency distributions on all the
items were examined to identify erroneous values. All cases showed values falling within the
possible ranges defined by the NSLLP PI.
Second, missing values were checked for both the RLC sample and the comparison
group. Frequencies showed that, across the two samples, items having a significant number of
missing values concentrated on SAT Composite scores and ACT Composite scores. Given that
the high school grade is sometimes accepted as an imperfect proxy for SAT and ACT scores and
had fewer missing values here, SAT and ACT scores were dropped from the dataset.
Third, ineligible cases and outliers were addressed. Given that the sample members for
this dissertation were defined as first-year, full-time, degree-seeking students at five four-year,
public, Midwest universities, twenty-six students who reported spending zero hours or 1-5 hours
during a typical week attending class (item 4a) were deleted from the dataset, based on the belief
that their full-time student status was potentially suspect.
Logic was applied in identifying univariate outliers. A new variable, named totalfortime,
was created, whose value was the sum of scores on the eleven items under Question 4 (4a-4k).
Two students whose score on totalfortime was 55 or higher were dropped from the dataset.
(Total hours for a week: 24*7=168; if a student’s score on totalfortime is 55, then his/her average score on the eleven items was 5, which corresponds to “16 to 20 hours per week”; therefore, this student spent 16*11=176 hours per week on the activities listed, which is impossible.)
Another variable, named totalfortime2, was created, whose value was the sum of scores on the seven items under Question 4 (from 4d to 4k). Seven students whose score on 79
totalfortime2 was larger than 28 (highly unlikely) were considered as not being serious in
completing The Survey, and therefore were dropped from the dataset. (Total hours for a week:
24*7=168; if a student’s score on totalfortime2 is larger than 28, then his/her average score on
the seven items was 5 or 6, which corresponds to “16 to 20 hours per week” or higher; therefore
this student spent at least 16*7=112 hours per week on the activities in question, leaving only
eight hours per day available for attending class, studying, socializing, and other activities
needed for daily life, such as sleeping and eating [168-112=56/7=8].
Also identified were contradictory combinations of responses. Students who reported
spending 0 hours per week doing volunteer work during a typical week (item 4g) but meanwhile reported “Strongly agree” with the statement “I volunteer my time to the community” (item 17c) were taken as inconsistent in completing these two items. Thus, they were eliminated from the sample. Similarly, two students who reported spending over 21 hours in doing volunteer work
during a typical week (item 4g), but marked “Strongly disagree” to the statement “I volunteer my
time to the community” (item 17c) were dropped from the sample; one student who reported
“Very involved” in intramural or club sports (item 5e) but reported spending zero hours in
exercising/sports (item 4d) was deleted from the final sample as well.
Outliers were then checked through examining stem and leaf plots and Boxplots. Cases
with values between 1.5 and 3 box lengths were pulled into a database together with the
following information: their data ID, the item on which he/she was an outlier, and his/her sample
group (i. e., a member of the RLC group or the comparison group). A frequency analysis
indicated that a total of 340 outlying responses (with values between 1.5 and 3 box lengths) were
identified on 25 items (under Question 1, 2, 10, 16, and 17), on some of which principal
component analyses were to be performed to generate new input and outcome variables. Twenty- 80
four students, accounting for 29.1% of these 340 outlying scores, were eliminated from the final
dataset, since they persisted as outliers (with values between 1.5 and 3 box lengths) on over 10% of these 25 items.
Since 70 items in The Survey (under Question 4, 7, 8, 9, 12, 13, 14, and 15) were to be included in principal component analyses to construct new environmental variables used in the hierarchical regressions involving the RLC sample, only RLC outlying responses on these 70 items were checked for frequencies. Results showed that out of a total of 631 such outlying responses (with values between 1.5 and 3 box lengths) on these 70 items in the RLC sample, twenty students persisted as outliers on 6 to 15 items and were thus most appropriately deleted from the sample. All further analyses, both descriptive and inferential, were based on the final sample of 3,642 students, with 1,822 comprising the RLC sample and 1,820 making up the comparison group.
With regard to extreme observations (identified by the stem and leaf plots as those that fall outside the acceptable range of distribution) as well as outliers (with values between 1.5 and
3 box lengths) that were not deleted, various strategies were implemented to reduce their relative influence. For those 25 items discussed above, if the number of extreme observations from both the RLC and the comparison group, when added together, was approximately equal to or less than 10% of the final usable sample (3,642*0.10=364), then these extreme observations were altered to a value that was within the extreme tail of the acceptable distribution, a method recommended by Mertler and Vannatta (2002). For the 70 environmental items discussed above, if the number of RLC extreme observations alone was approximately equal to or less than 10% of the final usable RLC sample (1,822*0.10)=182), then the same recoding was applied 81
(i. e., replacing them with an acceptable minimum and maximum value). When the number of
extreme observations, whether RLC members alone or two groups added together, exceeded
10% of the respective total sample, only cases with values between 1.5 and 3 box lengths were
addressed, by setting them as missing values on that particular item. Data transformations were
also applied to reduce the influence of outliers and extreme observations, which are discussed in the next section.
Testing Normality, Linearity, and Homogeneity
The adequacy of fit between the final usable data and three basic assumptions, i. e., normality, linearity, and homogeneity, was assessed by using methods suggested by Mertler and
Vannatta (2002) to improve the accuracy of statistical results. Given that the degree of normal distribution of scores affects both linearity and homogeneity, the normality assumption was first assessed and the testing of the other two assumptions in ANOVAs and hierarchical regressions was based on the improved normality.
After data screening, both statistical and graphical methods were used to test univariate normality of the distribution of data on all quantitative items. Four factors were considered in evaluating the degree of univariate normality: the skewness and kurtosis values, the
Kolmogorov-Smirnov statistic, histograms, and the normal Q-Q plots. Significance tests for the
Kolmogorov-Smirnov statistic revealed that all quantitative items violated the assumption of normality. However, an examination of normal Q-Q plots indicated that distributions of values on most items appeared to be approximately normal and values for both their skewness and kurtosis fell within the acceptable range of + 1 and -1 (Mertler & Vannatta, 2002).
Slight deviation from the normal may not make a meaningful difference in the analysis
(Mertler & Vannatta, 2002), particularly in the case of a large sample size. With this in mind, 82 only items whose skewness and kurtosis values were well beyond the range of +1 and -1 and whose normal Q-Q plots showed a substantial deviation from the normal were transformed. Log transformations were performed on the following items: (1) nine items under Question 5—5a
(Fraternity/sorority), 5d (Arts/music performances and activities), 5g (Student government), 5h
(Political or social activism), 5i (Religious clubs and activities), 5h (Ethnic/cross-cultural activities/clubs), 5l (Work-study or work on-campus), 5m (Work off-campus), and 5p (Ongoing community service); (2) three items under Question 8—8b (Visited informally with an instructor during a social occasion), 8f (Discussed personal problems with an instructor), and 8h (Went to a cultural event with an instructor); and (3) one item under Question 14—14f (Dated someone).
Inverse transformations were applied to the following three items—5k (Media activities), 5i
(Worked with an instructor on an independent project), and 5j (Worked with an instructor involving her/his research). Lastly, reflect and log transformations were performed on two items under Question 14—14j (Had guarded, cautious interactions) and 14k (Had tense, or even hostile interactions; based on their reversed scores).
Data transformations reduced the skewness values of the above items. A re-evaluation of their normal Q-Q plots indicated that their distributions appeared much more normal. Despite the moderate deviation from normality (in that their skewness values were mostly between -2 and
+2), no further transformations were performed on these items, given that both ANOVAs and regressions are robust to moderate violations of normality as long as group sizes were fairly large and equivalent, which was largely the case in this dissertation.
To meet the assumption of linearity, the residuals plots for each pair of dependent and independent variables for each ANOVA and hierarchical regression were examined by comparing the standardized residuals to the predicted values for the dependent variable. 83
Examinations of residuals plots indicated that for each pair, the linearity assumption was largely met since the residuals points clustered around the zero line and there was no apparent serious curvilinearity. The assumption of homogeneity of the variance of residuals for dependent variables was evaluated by running the Levene’s test as part of each ANOVA analysis.
Data Reduction and Construct Validity
The large number of items in The Survey dictated data reduction. Factor analyses using the principal component extraction method and varimax rotation were performed to serve two purposes. First, the principal components extracted from the items served as bases to create new input, environmental, and outcome variables for ANOVAs and hierarchical regression analyses, to be used in replacement of single items in The Survey. As indicated in Chapter III, the value of these newly created variables was mostly the sum of scores on the original items that were predominantly loaded onto a particular component in the rotated factor pattern. Second, principal component analyses provided evidence for construct validity through suggesting common conceptual structures underlying the items listed under the following questions: Question 1
(containing items pertaining to pre-college importance), Question 2 (containing items related to pre-college confidence), Question 4 (containing items pertaining to use of time during a typical week), Question 7 (including items pertaining to frequency of out-of-class peer interactions),
Question 8 (containing items measuring frequency of out-of-class interactions with faculty),
Question 9 (containing items assessing intellectual development/curricular learning), Question
10 (containing items asking about growth during the first year of college), Question 12
(containing items measuring frequency of using residence hall resources), Question 13
(containing items related to residence hall environments), Question 14 (containing items pertaining to the amount of interactions with peers from different racial/ethnic groups), Question 84
15 (containing items pertaining to perceptions of campus racial climate), Question 16 (containing
items pertaining to perceptions with regard to racial diversity), and Question 17 (containing
items related to citizenship perceptions). For items under Question 1, Question 2, Question 10,
Question 16, and Question 17, both the RLC and the comparison group were included in the
principal component analyses; for the remaining items, only the RLC group was included in the
principal component analyses, given that components extracted from those items were used to create variables to be entered into hierarchical regression analyses that involved the RLC sample only.
Five criteria (Mertler & Vannatta, 2002) were considered and balanced in determining
the appropriate number of components to retain for each question: eigenvalue (rule of thumb:
>1.0), proportion of variance accounted for by the component(s), the scree plot (i. e., from which
component the eigenvalue levels off drastically), the size of non-redundant residuals (those
exceeding the cut-off value of .05), and the degree of interpretability (i. e., significant and
predominant loading; the rotated factor pattern allowing clear interpretation; items sharing
common conceptual grounding). Wherever one or more of the above criteria suggested the
exploration of a solution other than the initial model retained by the default eigenvalue (>1.0),
another principal component analysis was conducted by either extracting an additional
component, or, in cases of ambiguous loadings or interpretation problems, excluding one or more
items, in order to improve the model fit (i. e., reducing residuals, increasing variance explained).
Results from the principal component analyses largely evidence the interrelations among
the items under each question specified above, indicating that those items are measuring different
aspects of one common construct, particularly the items under Question 9 and Question 17. For
items under a few questions, however, the size of residuals seemed to suggest a moderate degree 85 of construct validity, most notably, items under Question 12 and Question 16. Table C1
(provided in Appendix C) presents a summary of principal component analyses, including the full name of each component extracted (serving as bases of creating new variables), proportion of variance explained by each overall model and each component (after rotation), and the size of residuals exceeding the .05 value. Table 2 through Table 14 display items that were significantly loaded onto each component and their component loadings.
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Table 2
Component Loadings of Items under Question 1 ______Components Loadings ______
Component #1: Importance of growth in understanding diversity and interacting with peers
Learning about cultures different from your own (1d) .90
Getting to know people from different backgrounds (1c) .87
Discussing ideas and intellectual topics with other students (1e) .66 ------Component #2a: Importance of academic and social support in residence halls
Finding your hall to be academically supportive (1h) .81
Finding you hall to be socially supportive (1i) .78 ------Component #3: Importance of participating in co-curricular activities and interacting with faculty
Participating in extra-curricular activities (1a) .84
Participating in volunteer or community service activities (1b) .81
Getting to know your professors outside of class (1c) .47 ------Component #4: Importance of drinking alcohol during social occasions
Drinking alcohol during social occasions (1j) .93 ______aThe loading of item 1g (Learning more about yourself), presented a problem of interpretation in the rotated factor pattern. It was loaded onto Component #2, with a loading of .52. However, it seems to have no common conceptual grounding with the other two items under Component #2. Therefore this item was not included in creating the new input variable based on Component #2.
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Table 3
Component Loadings of Items under Question 2 ______Components Loadings ______Component #5: Confidence in handling new intellectual challenges and appreciating diversity
Analyzing new ideas and concepts (2c) .81
Enjoying the challenge of learning new materials (2e) .76
Applying something learned in class to the real world (2d) .70
Handling the challenge of college-level work (2a) .69
Appreciating new and different ideas and beliefs (2f) .56
Feeling as though you belong to the campus (2b) .46 ------Component #6: Confidence in academic and personal growth and satisfaction
Gaining skills in working with others (2h) .81
Making a difference in the community (2j) .70
Developing your own values and beliefs (2g) .63
Growing and developing academically (2i) .63
Being satisfied with your college experience (2k) .60 ______
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Table 4
Component Loadings of Items under Question 4a ______Components Loadings ______Component #7: Time spent on socializing or recreational activities
Partying (4e) .77
Socializing with friends (4c) .76
Excising/sports (4d) .59 ------Component #8: Time spent on academic work
Studying/doing homework (4b) .76
Attending classes (4a) .72 ------Component #9: Time spent on media-related communications or entertainments
E-mail or instant messaging (4j) .69
Watching TV alone (4i) .68
Playing video/computer games (4k) .62 ------Component #10: Time spent on work or student clubs/groups
Working (for pay) (4f) .81
Student clubs/groups (4h) .55 ______a Item 4g (Doing volunteer work) was used as an outcome variable and therefore was not included in the principal component analysis.
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Table 5
Component Loadings of Items under Question 7a ______Components Loadings ______Component #11: Frequency of diverse peer interactions
Discussed major social issues such as peace, human rights, and justice (7f) .78
Held discussions with students whose political opinions were .76 very different from your own (7k)
Discussed multiculturalism and diversity (7i) .75
Held discussions with students whose personal values were .75 very different from your own (7e)
Held discussions with students whose religious beliefs were .75 very different from your own (7h)
Talked about different lifestyles/customs (7c) .56 ------Component #12: Frequency of academic and career-related peer interactions
Shared your concerns about classes and assignments (7d) .77
Discussed something learned in class (7a) .75
Studied in groups (7j) .59
Talked about your future plans and career ambitions (7g) .52 ______a Item 7b (Talked about current news events) loaded almost equally onto each of the initial two components. Thus this item was deleted from the principal component analysis, which improved the model fit.
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Table 6
Component Loadings of Items under Question 8 ______Components Loadings ______
Component #13: Academic and career-related interactions with faculty
Made an appointment to meet with an instructor in his/her office (8c) .74
Asked your instructor for information related to a course you were taking (8a) .73
Communicated with your instructor using e-mail (8d) .71
Visited informally with an instructor before or after class (8b) .69
Discussed your career plans and ambitions with an instructor (8f) .49 ------Component #14: Personal and cultural interactions with faculty
Went to a cultural event with an instructor (8h) .75
Discussed personal problems or concerns with an instructor (8g) .61
Visited informally with an instructor during a social occasion (8e) .55 ------Component #15: Research-related interactions with faculty
Worked with an instructor involving his/her research (8i) .85
Worked with an instructor on an independent research (8j) .77 ______
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Table 7
Component Loadings of Items under Question 9 ______Components Loadings ______
Component #16: Enjoyment of integrated learning, intellectual challenge, and application of knowledge
I have applied materials learned in one class to other areas in my life (9t) .64
When I don’t understand something in a course, I work at it until I do (9k) .60
Something learned in one class helped me understand something .59 from another class (9l)
I enjoy courses that are intellectually challenging (9s) .57
Learning is important to me because it will give me greater control over my life (9q) .53
I often have discussions with other students about ideas/concepts in classes (9p) .51
I enjoy the challenge of learning complicated new material (9n) .49
I have been excited about a specific field or major as a result of taking a course in that field (9i) .47 ------Component #17: Enjoyment of integration of academic learning and self-discovery
I consider the best teachers to be those who can tie things learned in the class .73 to things that are important to me in my personal life (9e)
I prefer courses in which the materials help me understand something .72 about myself (9b)
I prefer reading things that are relevant to my personal experience (9o) .66
For me, one of the most important benefits of a college education is a better understanding of myself and my values (9r) .58 ______
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Table 7 (Continued) ______Components Loadings ______
Component #18: Enjoyment of multiplicity of thinking
I try to explore the meaning and interpretation of facts when introduced to a new idea (9g) .71
A good way to develop my own opinions is to critically analyze the strengths and limitations of different points of view (h) .69
I try to look at everybody’s side of a disagreement before making a decision (9m) .61 ------Component #19: Enjoyment of questioning others’ opinions and going beyond dualistic thinking
I frequently question or challenge professors’ statements and ideas before accepting them as right (9a) .75
There have been times when I have disagreed with the author of a book or article that I was reading (9d) .67
I enjoy discussing issues with people who don’t agree with me (9f) .50
I prefer courses requiring me to organize and interpret ideas over courses that ask me only to remember facts (9c) .46 ______
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Table 8
Component Loadings of Items under Question 10 ______Components Loadings ______
Component #20: Intellectual growth
Ability to learn on your own, pursue ideas, and find information you need (10f) .72
Ability to critically analyze ideas and information (10b) .68
Motivation to further explore ideas presented in class (10n) .61
Learning more about things that are new to you (10i) .60
Gaining a broad general education about different fields of knowledge (10k) .60 ------Component #21: Personal growth
Understanding yourself, and your abilities, interests and personality (10c) .75
Improving your ability to get along with people different from yourself (10d) .71
Developing your own values and ethical standards (10b) .70
Ability to put ideas together and to see relationships between ideas (10e) .54 ------Component #22: Growth in understanding of and appreciation for diversity
Openness to views that you oppose (10l) .71
Ability to discuss controversial issues (10m) .68
Appreciation of racial/ethnic differences (10g) .58
Appreciation of art, mucus, and dramaa (10j) .57
Becoming more aware of different philosophies, lifestyles and cultures (10a) .54 ______a Item 10j (Appreciation of art, music, and drama) was loaded onto a component with which it does not seem to
share a common conceptual grounding. Thus, this item was dropped from subsequent analyses.
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Table 9
Component Loadings of Items under Question 12 ______Components Loadings ______
Component #23: Frequency of using academic advising and faculty resources inside residence halls
Interactions with professor (12d) .72
Computer labs (12a) .65
Seminars and lectures (12e) .64
Academic advisors (12c) .60 ------Component #24: Frequency of using peer and co-curricular resources inside residence halls
Peer study groups (12f) .72
Social activities (12g) .72
Community service projects (12i) .65
Career workshops (12h) .53
Peer counselors (12c) .53 ______
95
Table 10
Component Loadings of Items under Question 13 ______Components Loadings ______
Component #25: Academic support in the residence environment
My residence environment clearly supports my academic study (13l) .79
Most students in my residence hall study a lot (13j) .76
I think the majority of students in my residence environment think academic success is important (13k) .76
I think it’s easy for students to form study groups in my residence (13n) .63
I have enough peer support in my residence to do well academically (13i) .60
Life in my residence environment is intellectually stimulating (13d) .58
I think the staff in my residence environment spends a great deal of time helping students succeed academically (13m) .57
I can find adequate study space available in my residence environment (13a) .37 ------Component #26: Social support for diverse peer interactions in the residence environment
I find that students in my residence environments have an appreciation for people from different races or ethnic groups (13b) .74
I see students with different backgrounds having a lot of interaction with one another in my residence hall (13h) .70
I find that students in my residence environments have an appreciation for people from different religions (13g) .69
I find that students in my residence environments have an appreciation for people with different sexual orientations (13e) .62
Students in my residence environment are concerned with helping and supporting one another (13c) .54
I would recommend this residence environment to a friend (13f) .51 ______96
Table 11
Component Loadings of Items under Question 14 ______Components Loadings ______
Component #27: Intellectual, social, and personal interactions with peers from a different racial/ethnic group
Had intellectual discussions out of class (14e) .86
Attended social events foregather (14c) .86
Shared a meal together (14b) .86
Studied together (14a) .76
Shared personal feelings and problems (14g) .74
Had meaningful discussions about race relations out of class (14i) .67
Participated in extra-curricular activities (e g., clubs) (14h) .61
Were roommates (14c) .51 ------Component #28: Absence of unfriendly interactions with peers from a different racial/ethnic group (scoring reversed)
Had guarded, cautions interaction (14j) .84
Had tense, or even hostile interactions (14k) .84 ------Component #29: Intimate interactions with peers from a different racial/ethnic group
Dated someone (14f) .85 ______
97
Table 12
Component Loadings of Items under Question 15 ______Components Loadings ______
Component #30: Relationship between students from different racial/ethnic backgrounds
Interaction between students of color and White students (15h) .79
Friendship between students of color and White students (15d) .73
Separation among students from different racial/ethical backgrounds on campus (15f) .67
Trust and respect between students from different racial/ethnic backgrounds (15g) .63
Dating between students of color and White students on campus (15b) .62 ------Component #31: Absence of racial tensions in residence halls or on campus
Inter-racial tension in the residence halls (15c) .81
Racial conflict on campus (15i) .78 ------Component #32: Campus commitment to the success of students of color
Respect by White professors of students of color (15a) .81
Campus commitment to develop environment that is conducive to the success of students of color (15e) .70 ______
98
Table 13
Component Loadings of Items under Question 16 ______Components Loadings ______
Component #33: Gains in inter-racial understanding
Since coming to college, I have learned a great deal about other racial/ethnic groups (16a) .81
I have gained a greater commitment to my racial/ethnical identity since coming to college (16b) .80
Since coming to college, I have become aware of the complexities of inter-group understanding (16d) .79 ------Component #34: Scope and quality of one’s racial interactions with peers
At times, it is important to be with people of my own racial/ethnic group for the chance to be myself (16h) .77
My social interactions on this campus are largely confined to students of my race (16g) .74
My relationships with students from different racial/ethnic backgrounds during college have been positive (16e) .61 ------Component #35: Campus commitment to racial diversity (scoring reversed)
I think this campus’s focus on diversity pays too much emphasis on the differences between racial/ethnic groups (16f) .90
My campus’ commitment to diversity fosters more division among racial/ethnic groups than inter-group understanding (16d) .66 ______
99
Table 14
Component Loadings of Items under Question 17 ______Components Loadings ______
Component #36: Perceptions on volunteerism and service to the community
I volunteer my time to the community (17c) .83
I believe my work has a greater purpose for the larger community (17d) .72
It is important to me that I play an active role in my communities (17b) .71
I work with others to make the community better places (17i) .70
I understand the extent to which the groups I participate in contribute to the larger community (17a) .57
I give time to make a difference for someone else (17g) .52
I believe I have responsibilities to my community (17f) .45 ------Component #37: Sense of responsibility to the common good
I believe I have a civic responsibility to the greater public (17m) .77
I am willing to act for the rights of others (17k) .74
I value opportunities that allow me to contribute to my community (17n) .65
I participate in activities that contribute to the common good (17l) .65 ------Component #38: Sense of civic empowerment
There is little I can do that makes a difference for others (scoring reversed) (17e) .79
Ordinary people can make a difference in their community (17h) .77
I have the power to make a difference in my community (17j) .71 ______
100
Characteristics of the RLC Sample
Demographic Distributions
Descriptive analyses of the screened and transformed data unfolded the demographic
characteristics and pre-college perceptions of students who were in the RLC sample. In terms of
their demographic characteristics, the majority of RLC students were heterosexual (96.80%),
White (84.02%), female (68.28%), and Christian (67.53%) students whose grandparents, parents or themselves were all born in the U. S. (85.48%), who had an average high school grade of B+ and above (84.36%), and whose parents’ highest level of education, on average, was Bachelor’s degree or higher (60.38%); 54.34% of them reported their parents’ annual total income was
$75,000 or higher. Table 15 displays the frequency distributions of RLC students in relation to the conventional students by gender, sexual orientation, race/ethnicity, citizenship, religion,
father’s education, mother’s education, parents’ total income, and high school grades.
Chi-Square tests indicated a statistically significant relationship between a student’s RLC
participation status and his/her gender (Chi-Square=7.59, df=1, p=.006), religion (Chi-Square
=31.14, df=4, p<.001), father’s education (Chi-Square=23.92, df=5, p<.001), and mother’s education (Chi-Square =31.40, df=5, p<.001). Specifically, a higher than expected proportion of
(a) male students; (b) students who reported either having no religion, or reported their religion as Asian religions, Jewish, or “Other”; (c) students who reported their father having a doctorate or professional degree; and (d) students who reported their mother having a Bachelor’s,
Master’s, or a doctorate or professional degree, participated in the RLCs. In other words, students of the above four categories were over-representative of the RLC population studied in this dissertation.
101
Table 15
Frequency Distributions of Respondents by Selected Demographic Characteristics ______Characteristic Percentage (%) Sig. Difference RLC Conventional Chi-Square p (N=1,822) (N=1,820) ______Gender 7.59 .006 Male 31.72 27.55
Female 68.28 72.45 ------Sexual orientation 2.29 .130
GLB 3.20 2.37
Heterosexual 96.80 97.63 ------Race/Ethnicity 2.96 .398
Black 4.74 4.10
Asian 5.95 6.60
Other 5.29 6.16
White/Caucasian 84.02 83.23 ------Citizenship 0.39 .822
Natural-born 85.48 84.94
One not 9.55 10.17
Other 4.97 4.89 ______
102
Table 15 (Continued) ______Characteristic Percentage (%) Sig. Difference RLC Conventional Chi-Square p (N=1,822) (N=1,820) ______Religious affiliation 31.14 .001 None 18.77 16.68
Asian religions 2.21 2.09
Christian 67.53 74.35
Jewish 5.80 2.92
Not included 5.69 3.96 ------Father’s highest education 23.92 .001
High school or less 16.57 18.63
Some college 16.69 18.00
Associate’s 4.52 5.22
Bachelor’s 27.32 28.85
Master’s 19.51 19.91
Doctorate/professional 15.38 10.11 ------Mother’s highest education 31.40 .001
High school or less 15.65 20.35 Some college 17.66 18.71 Associate’s 8.13 8.33 Bachelor’s 32.14 31.46 Master’s 20.78 18.37 Doctorate/professional 5.63 2.78 ______
103
Table 15 (Continued) ______Characteristic Percentage (%) Sig. Difference RLC Conventional Chi-Square p (N=1,822) (N=1,820) ______Parents’ total income ($) 2.35 .672 29,999 or less 9.54 10.93
Between 30,000 and 49,999 14.11 13.18
Between 50,000 and 74,999 22.00 22.32
Between 75,000 and 99,999 17.71 17.43
100,000 or higher 36.63 36.13 ------High school grade 6.70 .082
A+ or A 47.04 45.27
A- or B+ 37.32 35.93
B 11.14 12.97
B- or C+, D or lower, or None 4.50 5.82 ______
104
Differences on Pre-College Perceptions between the RLC Group and the Comparison Group
In addition to the demographic characteristics, RLC students’ pre-college perceptions were also compared with those of conventional students. T-tests suggested that RLC students
differed significantly from the comparison group on all the six pre-college variables. More
specifically, they scored significantly higher on importance of growth in understanding diversity
and interacting with peers (t(3612)=5.07, p<.001), importance of academic and social support in
residence halls (t(3611)=3.57, p<.001), importance of participating in co-curricular activities
and interacting with faculty (t(3614)=3.69, p<.001), confidence in handling new intellectual
challenges and appreciating diversity (t(3579)=5.10, p<.001), and confidence in academic and
personal growth and satisfaction (t(3589)=2.47, p=.013). RLC students scored significantly lower on importance of drinking alcohol during social occasions (t(3628)=-6.12, p<.001). Table
16 displays the mean scores and standard deviations of the RLC sample and the comparison group and the t statistics on the above six variables.
105
Table 16
Group Means on Pre-college Perceptions: RLC versus the Comparison Group ______Variable RLC Conventional Sig. Diff. (N=1,822) (N=1,820) t p M SD M SD ______
Pre-college importance of…
Growth in understanding diversitya and interacting with peers 8.90 2.09 8.55 2.10 5.07 <.001
Academic and social support in residence hallsb 5.80 1.35 5.64 1.37 3.57 <.001
Participating in co-curricular Activities and faculty interactionc 7.94 1.93 7.70 1.96 3.69 <.001
Drinking alcohol on social occasions 1.65 0.80 1.82 0.84 -6.12 <.001 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversityd 17.39 3.09 16.87 3.09 5.10 <.001
Academic and personal growth satisfactione 15.06 2.47 14.86 2.49 2.47 .010 ______The following ranges of values were used cross all the tables where the same variables were used:
a The range of values for this variable is from 3 to 12.
b The range of values for this variable is from 2 to 8.
c The range of values for this variable is from 3 to 12.
d The range of values for this variable is from 6 to 24.
e The range of values for this variable is from 5 to 20.
106
Differences on Pre-College Perceptions within the RLC Group by Demographics
Gender and sexual orientation.
T-tests and ANOVAs were also performed on the six pre-college variables to examine
differences within the RLC sample by demographic features—gender, sexual orientation,
race/ethnicity, citizenship, religion, father’s education, and high school grade. T-tests indicated
female RLC students reported a significantly higher score on importance of academic and social
support in residence halls (t(1802)=-3.91, p<.001) and importance of participating in co- curricular activities and interacting with faculty (t(1804)=-7.24, p<.001). However, they reported a significantly lower score on importance of drinking alcohol during social occasions
(t(1811)=2.36, p<.001) and confidence in handling new intellectual challenges and appreciating diversity (t(1794)=5.66, p<.001). Table 17 displays the mean scores and standard deviations for each group and t statistics. Regarding sexual orientation, T-tests indicated that GLB students scored significantly higher than heterosexual students on importance of growth in understanding diversity and interacting with peers (t(1798)=2.66, p=.008). Table 18 displays the mean scores and standard deviations for each group and t statistics.
107
Table 17
RLC Group Means on Pre-college Perceptions: Male versus Female Students ______Variable Male Female Sig. Diff. (N=577) (N=1,242) t p M SD M SD ______
Pre-college perceived importance of…
Growth in understanding diversity and interacting with peers 8.86 2.13 8.93 2.08 -0.66 .512
Academic and social support in residence halls 5.62 1.38 5.89 2.08 -3.91 <.001
Participating in co-curricular activities and interacting with faculty 7.47 1.95 8.17 1.89 -7.24 <.001
Drinking alcohol on social occasions 1.72 0.83 1.62 0.78 2.36 .020 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 17.99 3.03 17.11 3.08 5.66 <.001
Academic and personal growth and satisfaction 15.01 2.44 15.08 2.48 -0.54 .590 ______
108
Table 18
Group Means on Pre-college Perceptions: GLB versus Heterosexual Students ______Variable GLB Heterosexual Sig. Diff. (N=58) (N=1,757) t p M SD M SD ______
Pre-college importance of…
Growth in understanding diversity and interacting with peers 9.62 1.85 8.88 2.10 2.66 .008
Academic and social support in residence halls 5.51 1.40 5.82 1.35 -1.69 .091
Participating in co-curricular activities and interacting with faculty 7.72 1.89 7.95 1.94 -0.88 .382
Drinking alcohol on social occasions 1.83 0.84 1.64 0.80 1.71 .087 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 17.89 3.02 17.39 3.09 1.22 .221
Academic and personal growth and satisfaction 14.96 2.53 15.06 2.47 -0.30 .768 ______
109
Race.
Levene’s tests indicated that the equal variance assumption was violated on importance of growth in understanding diversity and interacting with peers, importance of academic and social support in residence halls, and importance of drinking alcohol during social occasions.
ANOVAs revealed that the four racial groups—Black, Asian, Other (American Indian, Hispanic, multi-racial, and those not included), and White RLC students differed on five out of six pre- college variables: (a) importance of growth in understanding diversity and interacting with peers
(F(3, 1796)=12.53, p<.001, R Square=.021), with White students reporting a lower score than all the other three groups; (b) importance of participating in co-curricular activities and interacting with faculty (F (3, 1798)=6.30, p<.001, R Square=.010), with Black students reporting a higher score than White and “Other” students; (c) importance of drinking alcohol on social occasions (F
(3, 1805)=4.04, p=.007, R Square=.007), with White students reporting a higher score than Black students; (d) confidence in handling new intellectual challenges and appreciating diversity (F (3,
1787)=3.57, p=.014, R Square=.006), with Black students reporting a higher score than Asian-
American students; and (e) confidence in academic and personal growth and satisfaction (F (3,
1777)=6.33, p<.001, R Square=.011), with Black students scoring higher than Asian-American and White students, and White students scoring higher than Asian-American students. Table 19 displays the mean scores and standard deviations for each group, and Table 20, the ANOVA results.
110
Table 19
RLC Group Means on Pre-College Perceptions by Race ______Variables Black Asian Other White M SD M SD M SD M SD (N=86) (N=108) (N=96) (N=1,525) ______
Pre-college importance of…
Growth in understanding diversity and interacting with peers 9.51 1.86 9.66 1.82 9.56 1.93 8.77 2.11
Academic and social support in residence halls 5.60 1.62 5.73 1.35 5.80 1.43 5.82 1.33
Participating in co-curricular activities and interacting with faculty 8.70 1.94 8.30 1.94 7.75 2.02 7.89 1.92
Drinking alcohol on social 1.38 0.67 1.59 0.74 1.60 0.79 1.67 0.81 occasions ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 18.26 3.06 16.80 3.07 17.50 3.05 17.38 3.09
Academic and personal growth and satisfaction 15.92 2.44 14.35 2.64 15.11 2.61 15.06 2.44 ______
111
Table 20
ANOVA Summary Table: Effects of Race on RLC Students’ Pre-college Perceptions ______Source SS df MS F p ES ______
Pre-college importance of …
Growth in understanding diversity and interacting with peers 161.70 3 53.90 12.53 <.001 .021
Academic and social support in residence halls 4.75 3 1.58 0.87 .456 .001
Participating in co-curricular activities and interacting with faculty 70.20 3 23.40 6.30 <.001 .010
Drinking alcohol on social occasions 7.72 3 2.57 4.04 .007 .007 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 102.12 3 34.04 3.57 .014 .006
Academic and personal growth and satisfaction 114.88 3 38.29 6.33 <.001 .011 ______
112
Citizenship.
Levene’s tests indicated that the equal variance assumption was met on all the six pre- college variables. ANOVAs revealed that the three groups—“Natural-born” (i. e., those whose grandparents, parents, and themselves were all born in the U. S.), “One not” (i. e., those who were born in the U. S, but at least one of their parents was not), and “Other” (i. e., those who are foreign-born naturalized citizens, foreign-born resident aliens, or student visa holders)—differed on two variables: (a) importance of growth in understanding diversity and interacting with peers
(F(2, 1793)=7.49, p=.001, R Square=.008), with “Natural-born” scoring significantly lower than the rest of students; and (b) confidence in academic and personal growth and satisfaction (F (2,
1775)=3.71, p=.025, R Square=.004), with “Natural-born” scoring significantly higher than
“Other.” Table 21 displays the mean scores and standard deviations for each group and Table 22, the ANOVA summary.
113
Table 21
RLC Group Means on Pre-college Perceptions by Citizenship ______Variables Natural-born One Not Other (N=1,548) (N=173) (N=90) M SD M SD M SD ______
Pre-college importance of…
Growth in understating diversity and interacting with peers 8.83 2.10 9.32 1.97 9.44 2.01
Support in residence halls 5.81 1.35 5.86 1.34 5.61 1.35
Participating in co-curricular activities and interacting with faculty 7.94 1.93 8.01 1.88 7.80 2.04
Drinking alcohol on social occasions 1.66 0.80 1.67 0.80 1.57 0.75 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 17.42 3.08 17.33 3.07 17.07 3.36
Academic and personal growth and satisfaction 15.11 2.45 14.96 2.65 14.38 2.45 ______
114
Table 22
ANOVA Summary Table: Effects of Citizenship on RLC Students’ Pre-college Perceptions ______Source SS df MS F p ES ______
Pre-college importance of …
Growth in understanding diversity and interacting with peers 65.37 2 32.68 7.47 .001 .008
Support in residence halls 4.07 2 2.03 1.12 .326 .001
Participating in co-curricular activities and interacting with faculty 2.68 2 1.34 0.36 .699 <.001
Drinking alcohol on social occasions 0.70 2 0.35 0.54 .581 .001 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 11.28 2 5.64 0.59 .555 .001
Academic and personal growth and satisfaction 45.12 2 22.56 3.71 .025 .004 ______
115
Religion.
Levene’s tests indicated that the equal variance assumption was met on all the pre-college variables. ANOVAs revealed that the five religious groups—“None” (i. e., having no religion),
“Asian religions” (including Buddhist, Hindu, Muslim), Christian, Jewish, and “Other” students
(whose religion was not listed) differed on five out of the six variables: (a) importance of growth in understanding diversity and interacting with peers (F(4, 1791=7.67, p<.001, R Square=.017), with Christian students reporting a lower score than “Asian religions” and “Other”; (b) importance of participating in co-curricular activities and interacting with faculty (F (4,
1793)=11.93, p<.001, R Square=.026), with “None” students reporting a lower score than three out of the remaining four groups; (c) importance of drinking alcohol on social occasions (F (4,
1800)=3.45, p=.008, R Square=.008), with Jewish students reporting a higher score than
Christian and “Other” students; (d) confidence in handling new intellectual challenges and appreciating diversity (F (4, 1782=2.73, p=.028, R Square=.007), and (e) confidence in academic and personal growth and satisfaction (F (4, 1772)=2.45, p=.045, R Square=.005). However,
Tukey tests did not specify which group was significantly different from other group(s) regarding these last two variables. Table 23 displays the mean scores and standard deviations for each group, and Table 24, the ANOVA results.
116
Table 23
RLC Group Means on Pre-College Perceptions by Religion
______Variables None Asian Christian Jewish Other (N=340) (N=40) (N=1,223) (N=105) (N=103) M SD M SD M SD M SD M SD ______Pre-college importance of … Growth in understanding diversity and interacting with peers 9.08 2.12 9.90 2.06 8.74 2.08 9.28 2.08 9.50 1.95
Support in residence halls 5.66 1.35 5.73 1.43 5.84 1.33 5.99 1.39 5.64 1.39
Participating in co-curricular activities and interacting with faculty 7.34 1.93 8.48 2.06 8.11 1.88 8.06 2.00 7.72 2.09
Drinking alcohol on social occasions 1.68 0.80 1.55 0.75 1.63 0.80 1.91 0.83 1.57 0.76 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 17.61 3.24 17.78 3.01 17.24 3.07 17.86 2.89 17.94 3.09
Academic and personal growth and satisfaction 14.77 2.56 15.62 2.67 15.10 2.45 14.88 2.43 15.42 2.36 ______
117
Table 24
ANOVA Summary Table: Effects of Religion on RLC Students’ Pre-college Perceptions ______Source SS df MS F p ES ______
Pre-college importance of …
Growth in understanding diversity and interacting with peers 132.31 4 33.08 7.67 <.001 .017
Academic and social support in residence halls 15.81 4 3.95 2.18 .069 .005
Participating in co-curricular activities and interacting with faculty 174.11 4 43.53 11.93 <.001 .026
Drinking alcohol on social occasions 8.80 4 2.20 3.45 .008 .008 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 104.46 4 26.11 2.73 .028 .006
Academic and personal growth 59.61 4 14.90 2.45 .045 .005 and satisfaction ______
118
Father’s education and high school grades.
Levene’s tests indicated that the equal variance assumption was met on all pre-college variables. ANOVAs revealed that the six groups—High school or less, Some college,
Associate’s, Bachelor’s, Master’s, and Doctorate/professional—differed on: (a) importance of growth in understanding diversity and interacting with peers (F (5, 1747)=3.05, p=.010, R
Square=.009); the Tukey test, however, did not specify which group(s) differed significantly from other group(s); (b) importance of participating in co-curricular activities and interacting with faculty (F (5, 1750)=3.21, p=.007, R Square=.009), with Master’s reporting a higher score than High school or less; and (c) confidence in handling new intellectual challenges and appreciating diversity (6, 1739)=5.02, p<.001, R Square=.014), with Bachelor’s, Master’s, and
Doctorate/professional reporting a higher score than High school or less; and
Doctorate/professional a higher score than Some college.
Levene’s tests indicated that the equal variance assumption was violated on pre-college importance of participating in co-curricular activities and interacting with faculty. ANOVAs revealed that the “A+ or A,” “A- or B+,” “B,” and “B- or lower or no high school grade”differed on: (a) importance of participating in co-curricular activities and interacting with faculty (F (3,
1805)=16.45, p<.001, R Square=.027), with “A+ or A” reporting a higher score than all the other groups, and “A- or B+” reporting a higher score than “B” students; (b) importance of drinking alcohol on social occasions (F (3, 1812)=3.57, p=.014, R Square=.006), with “A+ or A” students reporting a lower score than “B” students; and (c) confidence in being successful in handling new intellectual challenges and appreciating diversity (F (3, 1794)=2.79, p=.039, R Square=.005), with “A+ or A” reporting a higher score than “B.” Table 25 through Table 28 display the mean scores and standard deviations for each group and the ANOVA results. 119
Table 25
RLC Group Means on Pre-college Perceptions by Father’s Education ______
=< HS Some College Associate’s Bachelor’s Master’s Doctorate (N=293) (N=295) (N=80) (N=483) (N=345) (N=272) M SD M SD M SD M SD M SD M SD ______Pre-college importance of … Growth in understanding diversity and interacting with peers 8.63 2.19 8.73 2.11 8.50 2.21 9.00 1.96 9.10 2.04 9.04 2.14
Academic and social support in residence halls 5.81 1.32 5.68 1.37 5.72 1.23 5.86 1.33 5.86 1.38 5.62 1.37
Participating in co-curricular activities and faculty interaction 7.68 1.89 7.96 2.07 7.75 1.89 7.89 1.89 8.26 1.84 7.88 2.03
Drinking alcohol on social occasions 1.55 0.74 1.65 0.81 1.56 0.79 1.70 0.83 1.71 0.81 1.65 0.79 ------Pre-college confidence in …
Handling new intellectual challenges and appreciating diversity 16.78 3.02 17.23 3.10 17.17 3.32 17.46 3.05 17.50 3.07 18.02 2.94
Academic and personal growth 15.05 2.40 15.20 2.57 14.95 2.61 14.90 2.41 15.11 2.35 15.20 2.60 and satisfaction ______120
Table 26
ANOVA Summary Table: Effects of Father’s Education on RLC Students’ Pre-college Perceptions ______Source SS df MS F p ES ______Pre-college importance of … Growth in understanding diversity and interacting with peers 65.84 5 13.17 3.05 .010 .009
Academic and social support in residence halls 7.41 5 1.48 0.82 .537 .002
Participating in co-curricular activities and interacting with faculty 59.83 5 11.97 3.21 .007 .009
Drinking alcohol on social occasions 5.95 5 1.19 1.86 .099 .006 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 233.80 5 46.76 5.02 .001 .014
Academic and personal growth and satisfaction 24.19 5 4.84 0.80 .550 .002 ______
121
Table 27
RLC Group Means on Pre-college Perceptions by High School Grades ______Variables A+ or A A- or B+ B B- or lower (N=857) (N=680) (N=203) (N=82) M SD M SD M SD M SD ______Pre-college importance of…
Growth in understanding diversity and interacting with peers 8.94 2.11 8.90 2.07 8.80 2.13 8.84 1.98
Academic and social support in residence halls 5.84 1.35 5.83 1.34 5.58 1.35 5.79 1.39
Participating in co-curricular activities and interacting with faculty 8.21 1.93 7.88 1.78 7.32 2.10 7.23 2.23
Drinking alcohol on social occasions 1.59 0.78 1.68 0.81 1.76 0.82 1.73 0.77 ------Pre-college confidence in…
Handling new intellectual challenges and appreciating diversity 17.56 3.12 17.31 3.03 16.90 3.25 17.56 2.87
Academic and personal growth and satisfaction 15.11 2.51 15.11 2.36 14.82 2.62 14.70 2.56 ______
122
Table 28
ANOVA Summary Table: Effects of High School Grades on RLC Students’ Pre-college Perceptions ______Source SS df MS F p ES ______
Pre-college importance of …
Growth in understanding diversity and interacting with peers 3.57 3 1.19 0.27 .846 .000
Academic and social support in residence halls 11.95 3 3.98 2.20 .086 .004
Participating in co-curricular activities and faculty interaction 179.99 3 179.99 60.00 <.001 .027
Drinking alcohol on social occasions 6.82 3 2.27 3.57 .014 .006 ------Level of confidence in…
Handling new intellectual challenges and appreciating diversity 79.87 3 26.62 2.79 .039 .005
Academic and personal growth 26.71 3 8.90 1.46 .224 .002 and satisfaction ______
123
Summary of the Characteristics of the RLC Sample
The majority of RLC students studied here were heterosexual, White, female, and
Christian students whose grandparents, parents or themselves were all born in the U. S., who had an average high school grade of B+ and above, and whose parents’ highest level of education, on average, was Bachelor’s or higher. RLC students scored significantly higher than the comparison group on five out of six variables regarding their pre-college perceptions: importance of growth in understanding diversity and interacting with peers, importance of academic and social support in residence halls, importance of participating in co-curricular activities and interacting with faculty, confidence in handling new intellectual challenges and appreciating diversity, and confidence in academic and personal growth and satisfaction. They scored significantly lower on importance of drinking alcohol during social occasions.
Significant differences were also found within the RLC group concerning their pre- college perceptions. More specifically, female RLC students reported a higher score on importance of academic and social support in residence halls and participating in co-curricular activities and interacting with faculty. However, they reported a lower score on importance of drinking alcohol during social occasions and confidence in handling new intellectual challenges and appreciating diversity. GLB students reported a higher score than heterosexual students on importance of growth in understanding diversity and interacting with peers.
With regard to race, White students reported a lower score on importance of growth in understanding diversity and interacting with peers than all the other groups and a lower score on importance of participating in co-curricular activities and interacting with faculty than Black and “Other” students. However, they reported a higher score than Black students on importance of drinking alcohol on social occasions. Black students reported a higher score than Asian- 124
American students on confidence in handling new intellectual challenges and appreciating diversity; they also scored higher than Asian-American and White students on confidence in academic and personal growth and satisfaction; White students scored higher than Asian-
American students on this variable as well.
With regard to citizenship, students whose grandparents, parents, and themselves were all born in the U. S. scored significantly lower than the rest of students on importance of growth in understanding diversity and interacting with peers; however, they scored higher than resident aliens/international students on confidence in academic and personal growth and satisfaction.
Regarding religion, Christian students reported a lower score than “Asian religions” and “Other”
(those whose religions were not listed) on importance of growth in understanding diversity and interacting with peers; “None” students reported a lower score than three out of the remaining four groups on importance of participating in co-curricular activities and interacting with faculty; Jewish students reported a higher score than the Christian and “Other” students on importance of drinking alcohol on social occasions.
With regard to father’s education, “Master’s” students reported a higher score than “High
School or less” students on importance of growth in understanding diversity and interacting with peers and participating in co-curricular activities and interacting with faculty. “Bachelor’s,”
“Master’s,” and “Doctorate/Professional” students reported a higher score than “High School or less” students on confidence in handling new intellectual challenges and appreciating diversity.
Regarding high school grades, “A+ or A” students reported a higher score than all the remaining groups on importance of participating in co-curricular activities and interacting with faculty, and “A- or B+” students reported a higher score than “B” students on this variable as well. “A+ or A” students also reported a higher score than “B” students on confidence in handling new 125
intellectual challenges and appreciating diversity. However, they reported a lower score than
“B” on importance of drinking alcohol on social occasions.
In short, prior to entering college, female students seemed more likely to report that
involvement and interacting with faculty during college was important. In comparison to
heterosexual, White, and Christian students, as well as students whose grandparents, parents, and
themselves were all born in the U. S., GLB students, students of color, students who were
immigrant citizens/resident aliens/international students, students whose religion was other than
Christianity, and students with better high school grades were more likely to perceive growth in understanding diversity and interacting with peers as important. Asian-American students tended to report a lower level of confidence in handling new intellectual challenges and appreciating diversity and confidence in academic and personal growth and satisfaction than Black students and White students. Students reporting having no religion seemed less likely to agree that participating in co-curricular activities and interacting with faculty during college was important.
Main Effects of RLC Participation on Civic Engagement
ANOVAs were conducted on 12 outcome measures of civic engagement, so as to determine the significant main effect of RLC participation on students’ reported level of civic engagement. The following sections display both the descriptive results and significant mean differences between the RLC sample and conventional students on each dependent variable.
Means and standard deviations of these 12 dependent variables by group and the ANOVA results are presented in Table 29 and Table 30.
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Table 29
Group Means on Levels of Civic Engagement: RLC versus the Comparison Group ______Variables RLC Conventional (N=1,822) (N=1,820) M SD M SD ______
Time spent on volunteer work 1.48 0.60 1.42 0.58
Involvement in one-time community service 1.60 0.78 1.45 0.71
Involvement in ongoing community servicea 0.07 0.13 0.05 0.11
Perceptions on volunteerism and service to the communityb 24.65 4.09 23.92 3.97
Involvement in student governmentc 0.05 0.11 0.03 0.09
Sense of responsibility to the common goodd 15.15 2.24 14.71 2.20
Involvement in political or social activisme 0.06 0.12 0.03 0.10
Sense of civic empowermentf 12.06 1.77 11.81 1.72
Growth in understanding of and appreciation for diversityg 10.17 2.43 10.15 2.39
Gains in inter-racial understandingh 7.71 1.91 7.84 1.82
Growth in moral values development 2.69 0.75 2.69 0.76
Overall level of civic engagementi 75.65 9.88 73.94 9.62 ______ace Variables were transformed. bThe range of values for this variable is 7-35. dThe range of values for this variable is 4-20. fThe range of values for this variable is 3-15. gThe range of values for this variable is 4-16. hThe range of values for this variable is 3-12. iThe range of values for this variable is 29-137.
127
Table 30
ANOVA Summary Table: Main Effects of RLC Participation on Civic Engagement ______Source SS df MS F p R Square ______
Time spent on volunteer work 3.18 1 3.18 9.15 .003 .003
One-time community service 19.74 1 19.74 35.22 <.001 .010
On-going community service 0.32 1 0.32 22.37 <.001 .006
Perceptions on volunteerism and service to the community 471.13 1 471.13 29.02 <.001 .008
Involvement in student 0.22 1 0.22 22.05 <.001 .006 government
Sense of social responsibility 174.49 1 174.49 35.48 <.001 .010
Involvement in political or social activism 0.49 1 0.49 1.92 <.001 .011
Sense of civic empowerment 54.60 1 54.50 17.98 <.001 .005
Growth in understanding of and appreciation for diversity 0.42 1 0.42 0.07 .787 .000
Gains in inter-racial understanding 12.59 1 12.59 3.62 .057 .001
Growth in moral values 0.00 1 0.00 0.00 .989 <.001
Overall level of civic engagement 1951.55 1 1951.55 20.52 <.001 .008 ______
128
Main Effects on Volunteerism and Service to the Community
Four measures for volunteerism and service to the community were examined: time spent
on volunteer work during a typical week, involvement in one-time community service,
involvement in on-going community service, and perceptions on volunteerism and service to the
community. Levene’s tests indicated that the homogeneity assumption was violated on involvement in one-time community service (F (1, 3610) =23.29, p=.001) and on-going community service (F (1, 3610) =22.71, p=.001). ANOVA results demonstrated that participation in an RLC had a significant main effect on all the three behavioral measures of volunteerism and service to the community—time spent doing volunteer work during a typical week (F(1, 3637)=9.15, p=.003, R Square=.003), involvement in one-time community service
(F(1, 3610)=35.22, p<.001, R Square=.010), involvement in on-going community service (F(1,
3606)=22.37, p<.001, R Square=.006)—and on the attitudinal measure of this dimension— perceptions on volunteerism and service to the community (F (1, 3545)=29.02, p<.001, R
Square=.008). RLC students reported a higher score on all of these variables. However, the effect sizes were all extremely small: RLC participation accounted for only 0.3% of the variance
in time spent doing volunteer work; 1% of the variance in involvement in one-time community
service; 0.6% of the variance in involvement in on-going community service, and 0.8% of the
variance in perceptions on volunteerism and service to the community.
Main Effects on Responsibility to the Common Good
Levene’s tests indicated that for the behavioral measure of this dimension─involvement in student government, the homogeneity assumption was violated, (F (1, 3611) =22.49, p<.001).
ANOVA results demonstrated that participation in an RLC had statistically significant main effects on involvement in student government (F (1, 3611) =22.05, p<.001, R Square=.006) and 129
sense of social responsibility (F (1, 3574) =35.48, p<.001, R Square=.010). RLC students reported a statistically higher score on these two variables. However, the effect sizes were both extremely small: RLC participation accounted for only 0.6% of variance in involvement in student government; and 1.0% of the variance in sense of social responsibility.
Main Effects on Civic Empowerment
Levene’s tests indicated that for a behavioral measure of civic empowerment— involvement in political or social activism, the homogeneity assumption was violated, (F (1,
3609) =43.41, p=.001). ANOVA results demonstrated that RLC participation had statistically significant main effects on involvement in political or social activism (F (1, 3609)=41.92, p<.001, R Square=.011) and sense of civic empowerment (F (1, 3559) =17.98, p<.001, R
Square=.005). On both measures, RLC students reported a significantly higher score. However, the effect sizes were both extremely small: Participating in an RLC accounted for only 1.1% of the variance in involvement in political or social activism and 0.5% of the variance in sense of civic empowerment.
Main Effects on Understanding of and Appreciation for Diversity
Two measures of understanding of and appreciation for diversity were used as dependent variables: growth in understanding of and appreciating for diversity during college and gains in inter-racial understanding. Levene’s tests indicated that for both variables, equal variance was assumed. ANOVA results indicated that RLC participation did not demonstrate any statistically significant main effect on either of the variables.
Main Effects on Moral Values Development
One individual item under Question 15—growth in moral values development—was used as the indicator for one of the five dimensions of civic engagement: moral values development. 130
Levene’s tests indicated that for this variable, equal variance was assumed (F (1, 3622) =0.32,
p=.572). ANOVA results suggested that RLC participation did not demonstrate a statistically
significant main effect on growth in moral values development (F(1, 3622)=.00, p=.99, R
Square=.000).
Main Effect on the Overall Level of Civic Engagement
Levene’s tests indicated that for overall level of civic engagement, equal variance was
assumed (F(1, 2648) =0.84, p=.359). ANOVA results showed that participation in an RLC
demonstrated a statistically significant main effect on students’ overall level of civic
engagement, F(1, 2648) =20.52, p<.001, R Square=.008. More specifically, RLC students
reported a statistically higher score on this variable. However, the effect size was extremely
small. Participation in an RLC explained only 0.8% of the variance in overall level of civic
engagement.
Summary of Main Effects
ANOVA results indicated that participation in an RLC demonstrated a statistically
significant, positive main effect on students’ overall level of civic engagement. More specifically, it showed positive main effects on three out of the five dimensions of civic engagement: volunteerism and service to the community, responsibility to the common good, and civic empowerment. Such impact was demonstrated through both behavioral and attitudinal measures. With regard to volunteerism and service to the community, the RLC group reported a significantly higher mean score on time spent on volunteer work per week, involvement in one- time and on-going community service, and perceptions on volunteerism and service to the community. For responsibility to the common good, the RLC group reported a significantly higher mean score on involvement in student government and sense of responsibility to the 131
common good. Regarding civic empowerment, the RLC group reported a significantly higher
mean score on involvement in political and social activism and sense of civic empowerment.
However, despite these significantly higher mean scores, the effect sizes were all extremely small.
Conditional Effects of RLC Participation on Civic Engagement
by Demographic Characteristics
To examine the conditional effects of RLC participation, ANOVAs were conducted to compare the RLC students’ mean scores on measures of civic engagement by gender, sexual orientation, race, religion, citizenship, father’s education (given that the RLC group and the comparison group were more comparable on this variable than on mother’s education), parents’ income, and high school grades. The following sections report both the descriptive results and
ANOVA summaries.
Significant Mean Differences by Gender
Levene’s tests indicated that the equal variance assumption was met on two dependent variables—growth in understanding of and appreciation for diversity and growth in moral values development. ANOVA results demonstrated that within the RLC sample, significant conditional effects were observed on 11 variables. Specifically, with the exception of involvement in political and social activism, females reported statistically higher scores on the following 10 dependent variables: time spent on volunteer work (F(1, 1815)=26.54, p<.001, R Square=.014), involvement in one-time community service (F(1, 1801)=41.78, p<.001, R Square=.023), involvement in ongoing community service (F(1, 1801)=20.66, p<.001, R Square=.011), perceptions on volunteerism and service to the community (F(1, 1770)=29.29, p<.001, R
Square=.016), involvement in student government (F(1, 1803)=4.66, p=.03, R Square=0.003), 132
sense of social responsibility (F(1, 1791)=8.06, p=.005, R Square=.004), involvement in political
or social activism (F(1, 1803)=10.96, p=.001, R Square=.006), sense of civic empowerment (F(1,
1776)=7.02, p<.001, R Square=.004), gains in inter-racial understanding (F(1, 1458)=4.17, p=.041, R Square=.003), growth in moral values development (F(1, 1806)=7.59, p=.006, R
Square=.004), and the overall level of civic engagement (F(1, 1333)=21.38, p<.001, R
Square=.016). Females reported a significantly lower level of involvement in political or social activism. However, the effect sizes were all extremely small. Table 31 displays the means and standard deviations of the RLC group on these 12 dependent variables by gender, and Table 32,
the ANOVA summary.
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Table 31
Group Means for Male and Female RLC Students’ Levels of Civic Engagement ______Variables Female Male (N=1,242) (N=577) M SD M SD ______
Time spent on volunteer work 1.37 0.56 1.52 0.62
Involvement in one-time community service 0.42 0.70 0.68 0.81
Involvement in ongoing community service 0.05 0.11 0.08 0.13
Perceptions on volunteerism and service to the community 23.88 4.44 25.00 3.86
Involvement in student government 0.04 0.10 0.05 0.11
Perceptions on social responsibility 14.94 2.46 15.26 2.12
Involvement in political or social activism 0.07 0.13 0.05 0.11
Sense of civic empowerment 11.90 1.89 12.13 1.70
Growth in moral values development 2.62 0.77 2.72 0.74
Growth in understanding of and appreciation for diversity 10.12 2.50 10.20 2.40
Gains in inter-racial understanding 7.56 2.04 7.78 1.84
Overall level of civic engagement 73.86 10.66 76.51 9.35 ______
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Table 32
ANOVA Summary Table: Main Effects of Gender on RLC Students’ Levels of Civic Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 9.50 1 9.50 26.54 <.001 .014
Involvement in one-time community service 25.15 1 25.15 41.78 <.001 .023
Involvement in ongoing community service 0.32 1 0.32 20.66 <.001 .011
Perceptions on volunteerism and service to the community 481.26 1 481.26 29.29 <.001 .016
Involvement in student government 0.06 1 0.06 4.66 .031 .003
Sense of social responsibility 40.14 1 40.14 8.06 .005 .004
Involvement in political or social activism 0.15 1 0.15 10.96 .001 .006
Sense of civic empowerment 21.81 1 21.81 7.02 .008 .004
Growth in moral values 4.26 1 4.26 7.59 .006 .004
Growth in understanding of and appreciation for diversity 2.28 1 2.28 0.39 .535 .000
Gains in inter-racial understanding 15.20 1 15.20 4.17 .041 .003
Overall level of civic engagement 2053.44 1 2053.44 21.38 <.001 .016 ______
135
Significant Mean Differences by Sexual Orientation
Levene’s tests indicated that the equal variance assumption was violated on involvement in political or social activism (F(1, 1799)=9.50, p=.002) and gains in inter-racial understanding
F(1, 1455) =3.98, p=.046). ANOVA results demonstrated that within the RLC sample, sexual orientation produced a statistically significant main effect on: (a) involvement in political or social activism (F(1, 1799)=29.30, p=.001, R Square=.016); (b) sense of responsibility to the common good (F(1, 1787)=4.35, p=.037, R Square=.002); (c) growth in understanding of and appreciation for diversity F(1, 1794)=8.99, p=.003, R Square=.005); and (d) growth in moral values development (F(1, 1803)=4.35, p=.037). On all of these variables, GLB students reported a significantly higher score than heterosexual students. However, the effect sizes were all extremely small. Table 33 displays the means and standard deviations of the RLC group on these
12 dependent variables by sexual orientation, and Table 34, the ANOVA summary.
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Table 33
RLC Group Means on Levels of Civic Engagement by Sexual Orientation ______Variables GLB Heterosexual (N=58) (N=1,757) M SD M SD ______
Time spent on volunteer work 1.45 0.57 1.48 0.60
Involvement in one-time community service 1.48 0.82 1.60 0.79
Involvement in ongoing community service 0.05 0.11 0.07 0.13
Perceptions on volunteerism and service to the community 24.93 4.04 24.64 4.09
Involvement in student government 0.06 0.12 0.05 0.11
Sense of social responsibility 15.77 2.22 15.14 2.24
Involvement in political or social activism 0.14 0.15 0.06 0.12
Sense of civic empowerment 12.21 1.88 12.06 1.76
Growth in moral values development 2.89 0.75 2.68 0.75
Growth in understanding of and appreciation for diversity 11.12 2.73 10.14 2.41
Gains in inter-racial understanding 7.78 2.33 7.70 1.90
Overall level of civic engagement 77.45 10.90 75.60 9.86 ______
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Table 34
ANOVA Summary Table: Main Effects of Sexual Orientation on RLC Students’ Levels of Civic Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 0.04 1 0.04 0.11 .738 .000
Involvement in one-time community service 0.80 1 0.80 1.29 .256 .001
Involvement in ongoing community service 0.02 1 0.02 0.99 .320 .001
Perceptions on volunteerism and service to the community 4.76 1 4.76 0.28 .594 .000
Student government 0.01 1 0.01 0.53 .465 .000
Sense of social responsibility 21.72 1 21.72 4.35 .037 .002
Involvement in activism 0.41 1 0.41 29.30 .001 .016
Sense of civic empowerment 1.33 1 1.33 0.43 .514 .000
Growth in moral values 2.45 1 2.45 4.35 .037 .002
Growth in appreciation for diversity 52.84 1 52.84 8.99 .003 .005
Gains in inter-racial understanding 0.26 1 0.26 0.07 .788 .000
Overall level of civic engagement 130.50 1 130.50 1.33 .248 .001 ______
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Significant Mean Differences by Race
Levene’s tests indicated that the equal variance assumption was violated on gains in inter-racial understanding (F(3, 1455) =3.85, p=.009), sense of social responsibility (F(3, 1784)
=3.08, p=.026), and overall level of civic engagement (F(3, 1330) =4.07, p=.007). Within the
RLC sample, race demonstrated a statistically significant main effect on the following variables:
(a) level of involvement in political or social activism (F (3, 1797) =2.71, p=.044, R
Square=.004), with “Other” students (i.e., American Indian, Hispanic, multi-racial, and those not included) reporting a higher mean score than White students; (b) sense of civic empowerment (F
(3, 1769) =5.35, p=.001, R Square=.009), with Black, White, and “Other” students reporting a higher score than Asian-American students; (c) growth in understanding of and appreciation for diversity (F (3, 1791) =10.03, p<.001, R Square=.017), with Black students reporting a higher score than White and “Other” students, and Asian-American students reporting a higher score than White students; (d) gains in inter-racial understanding (F (3, 1455) =34.14, p<.001, R
Square=.066), with Black, Asian-American, and “Other” students reporting a higher score than
White students, and Black students reporting a higher score than Asian-American and “Other” students; (e) overall level of civic engagement (F (3, 1330) =3.90, p=.009, R Square=.009), with
Black students reporting a significantly higher mean score than White students; and (f) growth in moral values development ((F (3, 1800) =3.01, p=.029, R Square=.005), with Black students reporting a higher mean score than White students. Table 35 displays the means and standard deviations of the RLC group on these 12 dependent variables by race, and Table 36, the ANOVA summary.
139
Table 35
RLC Group Means on Levels of Civic Engagement by Race ______Variables Black Asian Other White M SD M SD M SD M SD (N=86) (N=108) (N=96) (N=1,525) ______
Time spent on volunteer work 1.44 0.59 1.49 0.62 1.46 0.67 1.48 0.60
Involvement in one-time community service 1.61 0.84 1.57 0.80 1.50 0.79 1.61 0.78
Involvement in on-going community service 0.04 0.11 0.07 0.13 0.07 0.13 0.07 0.13
Perceptions on volunteerism and service to community 24.35 3.63 24.53 3.70 24.83 4.55 24.66 4.11
Involvement in student government 0.07 0.13 0.05 0.11 0.05 0.11 0.05 0.11
Sense of social responsibility 14.99 2.43 15.16 2.17 15.57 2.66 15.14 2.20
Involvement in political or social activism 0.06 0.12 0.07 0.13 0.09 0.14 0.06 0.12
Sense of civic empowerment 12.11 1.91 11.41 1.86 12.26 1.96 12.09 1.73
Growth in moral values 2.89 0.74 2.77 0.70 2.74 0.70 2.67 0.76
Growth in understanding of and appreciation for diversity 11.35 2.44 10.82 2.27 10.16 2.54 10.07 2.41
Gains in inter-racial understanding 9.54 1.38 8.58 1.56 8.24 2.06 7.51 1.88
Overall level of Civic engagement 79.07 8.76 76.76 9.22 77.46 12.25 75.28 9.77 ______
140
Table 36
ANOVA Summary Table: Main Effects of Race on RLC Students’ Levels of Civic Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 0.16 3 0.05 0.14 .934 .000
Involvement in one-time community service 1.21 3 0.40 0.66 .580 .001
Involvement in on-going community service 0.06 3 0.02 1.17 .321 .002
Perceptions on volunteerism and service to community 2.34 3 4.11 0.25 .865 .000
Involvement in student government 0.04 3 0.01 1.18 .315 .002
Sense of social responsibility 19.49 3 6.50 1.30 .274 .002
Involvement in political or social activism 0.11 3 0.04 2.71 .044 .004
Sense of civic empowerment 49.76 3 16.59 5.35 .001 .009
Growth in moral values 5.08 3 1.69 3.01 .029 .005
Growth in understanding of and appreciation for for diversity 175.12 3 58.37 10.03 <.001 .017
Gains in inter-racial understanding 350.41 3 116.80 34.14 <.001 .066
Overall level of civic engagement 1135.95 3 378.65 3.90 .009 .009 ______
141
Significant Mean Differences by Religion
Levene’s tests indicated that the equal variance assumption was violated on the following six variables: involvement in political or social activism (F(4, 1793)=13.66, p=.001), perceptions
on volunteerism and service to the community (F(4, 1758)=4.43, p=.002), sense of social
responsibility (F(4, 1779)=2.63, p=.033), sense of civic empowerment (F(4, 1764)=3.52, p=.007), growth in understanding of and appreciation for diversity (F(4, 1786)=2.58, p=.036), and gains in inter-racial understanding (F(4, 1448)=2.57, p=.036). ANOVA results showed that within the
RLC sample, religion demonstrated a statistically significant main effect on 11 out of 12 dependent variables: (a) time spent on volunteer work (F(4, 1804)=4.60, p=.001, R
Square=.010); specifically, those having no religion reported spending significantly less time on volunteer work than Christian and Jewish students; (b) involvement in one-time community service (F (4, 1790) =2.65, p=.032, R Square=.006); specifically, Christian students reported a higher score on this variable than those who reported having no religion; (c) perceptions on volunteerism and service to the community (F(4, 1758)=10.34, p<.001, R Square=.023); specifically, those having no religion reported a lower score on this variable than students from all the other religious groups; (d) sense of social responsibility (F (4, 1779) =3.51, p=.007, R
Square=.008); specifically, “Asian religions” students reported a higher score on this variable than those having no religion; (e) involvement in political or social activism (F(4, 1793)=15.83, p<.001, R Square=.034); specifically, students of three religious groups—those having no religion, Jewish students, and students whose religion was not listed, reported a higher score on this variable than Christian students; (f) sense of civic empowerment (F (4, 1764) =4.45, p=.001,
R Square=.010); specifically, Christian students reported a significantly higher score on this variable than those having no religion; (g) growth in understanding of and appreciation for 142
diversity (F(4, 1786)=6.02, p<.001, R Square=.013); specifically, “Asian religions” students
reported a higher score on this variable than students from all the other four religious groups; (h)
gains in inter-racial understanding (F (4, 1448) =6.21, p<.001, R Square=.017). Specifically,
“None” students reported a significantly lower score on this variable than Christian and “Asian
religions” students; (i) growth in moral values development (F (4, 1795) =3.92, p=.004, R
Square=.009); specifically, “Asian religions” students reported a significantly higher score on
this variable than those having no religion and Christian students; and (j) overall level of civic
engagement (F (4, 1323) =7.75, p<.001, R Square=.023). Specifically, “Asian religions” students reported a higher score on this variable than Christian students and students having no religion.
Christian students reported a significantly higher score on their overall level of civic engagement
than students having no religion as well. Table 37 displays the means and standard deviations of
the RLC group on these 12 dependent variables by religion, and Table 38, the ANOVA
summary.
143
Table 37
RLC Group Means on Levels of Civic Engagement by Religion ______Variables None Asian Christian Jewish Other (N=340) (N=40) (N=1,223) (N=105) (N=103) M SD M SD M SD M SD M SD ______Time spent on volunteer work 1.36 0.55 1.55 0.64 1.49 0.61 1.61 0.61 1.48 0.59 Involvement in one-time community service 1.48 0.73 1.63 0.87 1.63 0.80 1.67 0.82 1.57 0.77
Involvement in ongoing community service 0.05 0.12 0.08 0.14 0.07 0.13 0.09 0.14 0.06 0.12
Perceptions on volunteerism 23.40 4.54 25.78 4.68 24.93 3.86 24.99 3.91 24.74 4.24
Involvement in student government 0.04 0.10 0.03 0.09 0.05 0.11 0.04 0.11 0.04 0.10
Sense of social responsibility 14.86 2.39 16.05 2.51 15.19 2.14 15.38 2.34 15.29 2.46
Involvement in political/social activism 0.09 0.14 0.06 0.12 0.04 0.11 0.09 0.14 0.10 0.14
Sense of civic empowerment 11.74 1.93 11.63 1.94 12.15 1.69 12.15 1.83 12.25 1.86
Growth in moral values development 2.63 0.80 3.08 0.58 2.69 0.75 2.81 0.73 2.74 0.67
Growth in appreciation of diversity 10.15 2.57 12.03 1.67 10.11 2.39 10.30 2.31 10.33 2.45
Gains in inter-racial understanding 7.29 2.10 8.68 2.04 7.78 1.82 7.71 2.04 7.93 1.82 Overall level of civic engagement 73.13 10.70 81.72 10.22 76.12 9.41 76.25 9.52 76.51 10.30 ______144
Table 38
ANOVA Summary Table: Main Effect of Religion on RLC Students’ Levels of Civic Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 6.64 4 1.66 4.60 .001 .010
Involvement in one-time community service 6.50 4 1.62 2.65 .032 .006
Involvement in ongoing community service 0.13 4 0.03 2.00 .092 .004
Perceptions on volunteerism and service to community 673.45 4 168.36 10.34 <.001 .023
Involvement in student government 0.06 4 0.01 1.21 .303 .003
Sense of social responsibility 69.70 4 17.43 3.51 .007 .008
Involvement in political or social activism 0.86 4 0.22 15.83 <.001 .034
Sense of civic empowerment 55.22 4 13.80 4.45 .001 .010
Growth in moral values 8.77 4 2.19 3.92 .004 .009
Growth in understanding of and appreciation for diversity 140.15 4 35.04 6.02 <.001 .013
Gains in inter-racial understanding 89.54 4 22.39 6.21 <.001 .017
Overall level of civic engagement 2945.52 4 736.38 7.75 <.001 .023 ______
145
Significant Mean Differences by Citizenship
Levene’s tests indicated that the equal variance assumption was violated on gains in inter-racial understanding, F(2, 1449) =4.33, p=.013. ANOVA results demonstrated that within the RLC sample, citizenship produced statistically significant main effects on: (a) perceptions on volunteerism and service to the community (F(2, 1762)=3.26, p=.04, R Square=.004); (b) sense of civic empowerment (F (2, 1767)=8.09, p<.001, R Square=.009); on both of these variables, those whose grandparents, parents, and themselves were all born in the U. S. reported a higher score than students who are foreign-born naturalized citizens, foreign-born resident aliens, or student visa holders; (c) gains in inter-racial understanding (F(2, 1449)=9.67, p<.001, R
Square=.013); specifically, students who were born in the U. S, but at least one of their parents was not, as well as “Other” students reported a higher score on this variable than those whose grandparents, parents, and themselves were all born in the U. S. Table 39 displays the means and standard deviations of the RLC group on these 12 dependent variables by citizenship, and Table
40, the ANOVA summary.
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Table 39
RLC Group Means on Levels of Civic Engagement by Citizenship ______Variables Natural-born One Not Other (N=1,548) (N=173) (N=90) M SD M SD M SD ______
Time spent on volunteer work 1.48 0.60 1.52 0.64 1.38 0.59
Involvement in one-time community service 1.61 0.78 1.55 0.79 1.49 0.77
Involvement in ongoing community service 0.07 0.13 0.08 0.13 0.06 0.12
Perceptions on volunteerism and service to the community 24.72 4.07 24.62 4.04 23.55 4.40
Involvement in student government 0.05 0.11 0.04 0.10 0.03 0.10
Sense of social responsibility 15.18 2.21 15.21 2.31 14.59 2.54
Involvement in political or social activism 0.06 0.12 0.07 0.13 0.06 0.12
Sense of civic empowerment 12.12 1.76 11.91 1.80 11.37 1.79
Growth in moral values 2.68 0.76 2.75 0.68 2.67 0.80
Growth in understanding of and appreciation for diversity 10.14 2.42 10.26 2.39 10.63 2.59
Gains in inter-racial understanding 7.61 1.87 8.19 2.21 8.27 1.83
Overall level of civic engagement 75.67 9.78 76.15 10.15 74.33 11.15 ______
147
Table 40
ANOVA Summary Table: Main Effects of Citizenship on RLC Students’ Levels of Civic Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 1.21 2 1.60 1.66 .190 .002
Involvement in one-time community service 1.63 2 0.82 1.33 .266 .001
Involvement in ongoing community service 0.03 2 0.01 0.81 .444 .001
Perceptions on volunteerism and service to the community 108.79 2 54.40 3.26 .039 .004
Involvement in student government 0.04 2 0.02 1.84 .159 .002
Sense of social responsibility 29.57 2 14.78 2.96 .052 .003
Involvement in political or social activism 0.06 2 0.03 1.97 .139 .002
Sense of civic empowerment 50.20 2 25.10 8.09 <.001 .009
Growth in moral values 0.74 2 0.37 0.65 .521 .001
Growth in understanding of and appreciation for diversity 20.75 2 10.37 1.76 .172 .002
Gains in inter-racial understanding 69.88 2 34.94 9.67 <.001 .013
Overall level of civic engagement 153.63 2 76.81 0.79 .456 .001 ______
148
Significant Mean Differences by Father’s Education
Levene’s tests indicated that the equal variance assumption was violated on involvement in political or social activism (F(5, 1748)=5.31, p<.001) and involvement in ongoing community service (F(5, 1746) =2.30, p=.043). ANOVA results indicated that within the RLC sample, father’s level of education demonstrated a statistically significant main effect on: (a) involvement in political or social activism, (F(5, 1748)=5.32, p<.001, R Square=.015); specifically, students whose father’s highest level of education was Doctorate/Professional reported a higher score on their level of involvement in political or social activism than “High School or Less,” “Some
College,” “Associate’s,” and “Bachelor’s” students. In addition, “Bachelor’s” students reported a higher score on this variable than “Some college” students; and (b) gains in inter-racial understanding (F(5, 1414) =2.27, p=.046, R Square=.008). However, the Tukey test did not identify specific group differences on this variable. Table 41 displays the means and standard deviations of the RLC group on these 12 dependent variables by citizenship, and Table 42, the
ANOVA summary.
149
Table 41
RLC Group Means on Levels of Civic Engagement by Father’s Education ______=< HS Some College Associate’s Bachelor’s Master’s Doctorate (N=293) (N=295) (N=80) (N=483) (N=345) (N=272) M SD M SD M SD M SD M SD M SD ______Time spent on volunteer work 1.42 0.58 1.51 0.59 1.54 0.65 1.50 0.61 1.47 0.61 1.44 0.57 Involvement in one-time community service 1.58 0.79 1.58 0.79 1.61 0.76 1.63 0.80 1.63 0.79 1.57 0.75
Involvement in ongoing community service 0.05 0.11 0.07 0.13 0.06 0.12 0.08 0.13 0.07 0.13 0.06 0.12
Perceptions on volunteerism 24.19 3.92 24.82 4.18 20.60 4.19 24.64 4.04 25.04 4.04 24.62 4.35 Involvement in student government 0.03 0.10 0.05 0.11 0.06 0.12 0.05 0.11 0.05 0.11 0.05 0.11 Sense of social responsibility 14.95 2.09 14.97 2.28 14.89 2.28 15.18 2.21 15.39 2.20 15.30 2.36 Involvement in political or social activism 0.05 0.11 0.04 0.10 0.03 0.09 0.06 0.12 0.07 0.13 0.08 0.13 Sense of civic empowerment 11.95 1.87 12.12 1.70 11.80 1.85 12.09 1.68 12.23 1.78 11.93 1.82 Growth in moral values 2.70 0.70 2.66 0.80 2.59 0.81 2.67 0.75 2.67 0.74 2.78 0.74 Growth in understanding of and appreciation for diversity 10.37 2.38 9.99 2.47 10.08 2.50 10.05 2.35 10.22 2.42 10.22 2.56
Gains in inter-racial understanding 7.99 1.81 7.70 2.09 7.91 1.78 7.59 1.85 7.54 1.92 7.52 1.91 Overall level of civic engagement 75.80 9.45 75.72 10.97 75.09 10.07 75.53 9.80 75.88 9.55 75.40 10.01 ______150
Table 42
ANOVA Summary Table: Main Effects of Father’s Education on RLC Students’ Levels of Civic Engagement ______
Source SS df MS F p ES ______
Time spent on volunteer work 2.10 5 0.42 1.17 .323 .003
Involvement in one-time community service 1.20 5 0.24 0.39 .858 .001
Involvement in ongoing community service 0.17 5 0.03 2.10 .063 .006
Perceptions on volunteerism and service to the community 120.75 5 24.15 1.44 .208 .004
Involvement in student government 0.07 5 0.01 1.19 .312 .003
Sense of social responsibility 51.52 5 10.30 2.08 .066 .006
Involvement in political or social activism 0.37 5 0.07 5.32 <.001 .015
Sense of civic empowerment 23.78 5 4.76 1.53 .179 .004
Growth in moral values 3.33 5 0.67 1.18 .316 .003
Growth in understanding of and appreciation for diversity 30.40 5 6.08 1.03 .397 .003
Gains in inter-racial understanding 41.04 5 8.21 2.27 .046 .008
Overall level of civic engagement 56.12 5 11.22 0.11 .989 .000 ______
151
Significant Mean Differences by Parents’ Income
Under this classification variable—income—were five groups: Group 1: 29,999 or less;
Group 2: Between 30,000 and 49,999; Group 3: Between 50,000 and 74,999; Group 4: Between
75,000 and 99,999; and Group 5: 100,000 or higher. Levene’s tests indicated that the equal variance assumption was violated on sense of civic empowerment (F(4, 1707) =2.45, p=.044).
ANOVA results suggested that within the RLC sample, parents’ income demonstrated a statistically significant main effect on gains in inter-racial understanding, F(4, 1408)=2.40,
p=.048, R Square=.007. However, the Tukey test did not reveal which group(s) significantly differed from other group(s). In addition, the effect size was extremely small. Parent’s income
explained .7% of the variance among RLC students on this variable. Table 43 displays the means
and standard deviations of the RLC group on these 12 dependent variables by parents’ income,
and Table 44, the ANOVA summary.
152
Table 43 RLC Group Means on Levels of Civic Engagement by Parents’ Income ______Variables <=29,999 30,000-49,999 50,000-74,999 75,000-99,999 >=100,000 (N=167) (N=247) (N=385) (N=310) (N=641) M SD M SD M SD M SD M SD ______Time spent on volunteer work 1.43 0.60 1.43 0.57 1.45 0.58 1.46 0.59 1.53 0.63 Involvement in one-time community service 1.51 0.76 1.61 0.81 1.59 0.76 1.58 0.78 1.65 0.80
Involvement in ongoing community service 0.05 0.11 0.06 0.12 0.07 0.13 0.07 0.13 0.08 0.13
Perceptions on volunteerism and service to the community 24.27 4.39 24.42 4.11 24.50 4.03 24.67 4.08 25.00 4.04
Involvement in student government 0.04 0.11 0.04 0.11 0.05 0.11 0.04 0.11 0.05 0.11 Sense of social responsibility 15.10 2.49 15.05 2.24 15.03 2.20 15.19 2.23 15.30 2.21 Involvement in political/social activism 0.06 0.12 0.06 0.12 0.06 0.12 0.06 0.12 0.06 0.12 Sense of civic empowerment 11.98 2.00 12.03 1.80 12.08 1.76 12.06 1.74 12.10 1.71 Growth in moral values 2.76 0.80 2.65 0.76 2.68 0.75 2.66 0.75 2.72 0.72 Growth in understanding of and appreciation for diversity 10.42 2.66 10.20 2.55 10.31 2.43 10.02 2.31 10.17 2.36 Gains in inter-racial understanding 8.11 2.15 7.85 1.83 7.78 2.01 7.57 1.87 7.62 1.83 Overall level of civic engagement 77.07 11.53 74.92 10.03 75.73 9.77 75.24 9.75 76.04 9.49 ______
153
Table 44
ANOVA Summary Table: Main Effects of Parents’ Income on RLC Students’ Levels of Civic Engagement
______Source SS df MS F p ES ______
Time spent on volunteer work 3.43 4 0.86 2.37 .051 .005
Involvement in one-time community service 3.20 4 0.80 1.29 .271 .003
Involvement in ongoing community service 0.104 4 0.26 1.63 .163 .004
Perceptions on volunteerism and service to the community 116.54 4 29.14 1.74 .138 .004
Involvement in student government 0.02 4 0.01 0.42 .796 .001
Sense of social responsibility 21.73 4 5.43 1.08 .365 .003
Involvement in political or social activism 0.02 4 0.00 0.30 .879 .001
Sense of civic empowerment 2.12 4 0.53 0.17 .954 .000
Growth in moral values 2.01 4 0.50 0.90 .464 .002
Growth in understanding of and appreciation for diversity 23.36 4 5.84 1.00 .409 .002
Gains in inter-racial understanding 34.94 4 8.73 2.40 .048 .007
Overall level of civic engagement 416.79 4 104.20 1.07 .369 .003 ______
154
Significant Mean Differences by High School Grades
Under high school grade were four groups—“A+ or A,” “A- or B+,” “B,” “B- or lower or
no high school grade”. Levene’s tests indicated that the equal variance assumption was violated
on involvement in one-time community service (F( 3, 1802)=10.61, p=.001), involvement in
ongoing community service (F (3, 1802)=10.17, p=.001), perceptions on volunteerism and
service to the community (F(3, 1770)=2.66, p=.047), sense of responsibility to the common good
(F(3, 1791)=4.12, p=.006), and gains in inter-racial understanding (F(3, 1458)=4.65, p=.003).
ANOVA results revealed that within the RLC sample, students’ high school grades demonstrated
statistically significant main effects on the following variables: (a) time spent on volunteer work
(F (3, 1816) =4.01, p=.007, R Square=.007), with “A+ or A” students reporting spending more
time than “B” students, (b) involvement in one-time community service (F (3, 1802)=13.89,
p<.001, R Square=.023), with “A+ or A” students reporting a higher score than the rest of
students, and “A- or B+” students reporting a higher score than “B” students; (c) involvement in
ongoing community service (F (3, 1802) =9.20, p<.001, R Square=.015), with “A+ or A”
students reporting a higher score than “A- or B+” and “B” students; (d) perceptions on
volunteerism and service to the community (F (3, 1770) =6.96, p<.001, R Square=.012), with
“A+ or A” students reporting a higher score than students from all the remaining three groups;
(e) sense of social responsibility (F(3, 1791)=2.70, p=.044, R Square=.005); (f) sense of civic
empowerment (F(3, 1776)=3.09, p=.026, R Square=.005), and (g) overall level of civic
engagement (F(3, 1332)=4.27, p=.005, R Square=.010), with “A+ or A” students reporting a
higher score than “B” students. Table 45 displays the means and standard deviations of the RLC group on these 12 dependent variables by high school grade, and Table 46, the ANOVA summary. 155
Table 45
RLC Group Means on Levels of Civic Engagement by High School Grades ______Variables A+or A A-or B+ B B- or lower (N=857) (N=680) (N=203) (N=82) M SD M SD M SD M SD ______
Time spent on volunteer work 1.52 0.59 1.47 0.61 1.36 0.62 1.43 0.59
Involvement in one-time community service 1.71 0.82 1.55 0.75 1.36 0.65 1.46 0.77
Involvement in ongoing community service 0.08 0.13 0.06 0.12 0.04 0.10 0.05 0.11
Perceptions on volunteerism and service to the community 25.07 4.02 24.44 4.06 23.89 4.50 23.82 3.42
Involvement in student government 0.05 0.11 0.05 0.11 0.05 0.11 0.03 0.09
Sense of social responsibility 15.31 2.15 15.04 2.21 14.92 2.57 15.02 2.39
Involvement in political or social activism 0.06 0.12 0.06 0.12 0.06 0.12 0.05 0.11
Sense of civic empowerment 11.18 1.77 12.00 1.74 11.91 1.78 11.73 1.88
Growth in moral values 2.72 0.76 2.66 0.75 2.64 0.71 2.75 0.68
Growth in understanding of and appreciation for diversity 10.17 2.38 10.16 2.50 10.16 2.45 10.44 2.30
Gains in inter-racial understanding 7.74 1.81 7.66 1.90 7.48 2.11 8.22 2.33
Overall level of Civic engagement 76.57 9.55 75.16 10.04 73.65 10.35 75.07 9.90 ______
156
Table 46
ANOVA Summary Table: Main Effects of High School Grades on RLC Students’ Levels of Civic
Engagement ______Source SS df MS F p ES ______
Time spent on volunteer work 4.34 3 1.45 4.01 .007 .007
Involvement in one-time community service 25.13 3 8.38 13.89 <.001 .023
Involvement in ongoing community service 0.43 3 0.14 9.20 <.001 .015
Perceptions on volunteerism and service to the community 345.02 3 115.01 6.96 <.001 .012
Involvement in student government 0.03 3 0.01 0.84 .474 .001
Sense of social responsibility 40.36 3 13.45 2.70 .044 .005
Involvement in political or social activism 0.02 3 0.01 0.58 .627 .001
Sense of civic empowerment 28.88 3 9.63 3.09 .026 .005
Growth in moral values 2.15 3 0.72 1.27 .283 .002
Growth in understanding of and appreciation for diversity 6.25 3 2.08 0.35 .787 .001
Gains in inter-racial understanding 28.00 3 9.33 2.57 .053 .005
Overall level of civic engagement 1241.70 3 413.90 4.27 .005 .010 ______
157
Summary of Conditional Effects
Seven demographic characteristics demonstrated significant main effects on one or more
measures of civic engagement: gender, sexual orientation, race, religion, citizenship, father’s
education, and high school grades. Despite the significant differences, all the effect sizes were
extremely small. More specifically, with regard to gender, females reported a higher mean score
on time spent on volunteer work, involvement in one-time community service and on-going community service, perceptions on volunteerism and service to the community, sense of responsibility to the common good, involvement in student government, sense of civic empowerment, growth in inter-racial understanding, growth in moral values development, and overall level of civic engagement; however, they reported a lower score on involvement in political or social activism. With regard to sexual orientation, GLB students reported a higher mean score on involvement in political or social activism, sense of responsibility to the common good, growth in understanding of and appreciation for diversity, and growth in moral values development.
With regard to race, six conditional effects were found: (a) involvement in political or social activism, with “Other” students (i.e., American Indian, Hispanic, multi-racial, and those not included) reporting a higher score than White students; (b) sense of civic empowerment, with
Black, White, and “Other” students reporting a higher score than Asian-American students; (c) growth in understanding of and appreciation for diversity, with Black and Asian-American students reporting a higher score than White students; and Black students reporting a higher score than “Other” students; (d) gains in inter-racial understanding, with Black, Asian-
American, and “Other” students reporting a higher score than White students; and Black students reporting a higher score than Asian-American and “Other” students; and (e) growth in moral 158
values development, and (f) overall level of civic engagement, with Black students reporting a
higher score than White students on both measures.
With respect to religion, conditional effects were identified on 11 out of 12 measures of
civic engagement among the five religious groups. Christian and Jewish students reported
spending significantly more time on volunteer work than those having no religion. Christian
students also reported a higher level of involvement in one-time community service, stronger
sense of civic empowerment, more gains in inter-racial understanding, and a higher overall level
of civic engagement than those having no religion. In addition to Christian students, students
from the other three religious groups also reported a higher score on perceptions on volunteerism and service to the community than those having no religion. However, Christian students were less likely to be involved in political or social activism than students having no religion, Jewish students, and students whose religion was not listed. “Asian religions” students reported a higher score on growth in understanding of and appreciation for diversity than all the other four religious groups. They also reported significantly more growth in moral values development than those having no religion and Christian students, and a stronger sense of social responsibility than those having no religion.
With respect to citizenship, students whose grandparents, parents, and themselves were all born in the U. S. reported a higher score than students who are foreign-born naturalized citizens, foreign-born resident aliens, or student visa holders regarding their perceptions on volunteerism and service to the community and sense of civic empowerment. However, they reported a lower score on gains in inter-racial understanding than the rest of students.
With regard to father’s education, a conditional effect was found on involvement in political and social activism, with students whose father earned doctorate or had a professional 159
degree reporting a higher score than most of the remaining groups, and “Bachelor’s” students reporting a higher score than “Some college” students. Regarding high school grades, students whose high school grade was A or above reported a higher score on the overall level of civic engagement than students whose high school grade was B. On a more specific level, they reported spending significantly more time on volunteer work than “B” students, and a higher level of involvement in one-time and on-going community service than the rest of the students.
Predictors for RLC Students’ Levels of Civic Engagement
To determine which aspects of RLC students’ input characteristics and college environments best predict their level of civic engagement, a series of hierarchical regression
analyses was conducted. The sequencing of blocks of variables to be entered into analyses was
guided by Astin’s (1977, 1993) I—E—O model as well as previous research that identified
significant predictors for this outcome. Separate regressions were performed on six dependent
variables—overall level of civic engagement, perceptions on volunteerism and service to the
community, sense of responsibility to the common good, sense of civic empowerment, growth in
understanding of and appreciation for diversity and gains in inter-racial understanding
(combined into one variable), and growth in moral values development.
In accordance with the principle of parsimony and the 15:1 ratio of subjects: predictors
(Mertler & Vannatta, 2002), Pearson correlations and a preliminary regression were run to
examine the strength of correlations and tolerance statistics involving 48 input and environmental variables intended to be entered for the regression analyses. The following criteria were considered in making decisions regarding excluding or combining variables: value of
Pearson r (>.40), importance to the research questions, previous research, and degree of multicollinearity as indicated by tolerance statistics and the variance inflation factor (VIF). As a result, three variables were excluded from the regression analyses—parents’ income, (pre- 160
college) importance of drinking alcohol on social occasions, and amount of dating with peers
from a different racial/ethnic group. The following variables were combined: (a) three
variables—frequency of diverse peer interactions, amount of intellectual, social, and personal
interactions with peers from a different racial/ethnic group, and scope and quality of one’s
racial interactions with peers—were combined to create a new variable; (b) two variables—
frequency of academic and career-related interactions with faculty and personal and cultural
interactions with faculty—were combined to create a new variable; (c) another two variables—
frequency of using academic advising and faculty resources inside residence halls and frequency of using peer and co-curricular recourses inside residence halls—were combined to form a new variable; (d) two variables—academic support in the residence environment and social support for diverse peer interactions in the residence environment—were combined as one variable; and
(e) two variables—enjoyment of integrated learning, intellectual challenge, and application of knowledge and enjoyment of multiplicity of thinking—were combined as one variable.
Next, multicollinearity was tested by examining tolerance and VIF statistics. All the values for tolerance were larger than .4 and all VIF values were less than 4, indicating that multicollinearity was not a problem.
For each regression analysis, the same set of input and environmental variables was entered mostly as blocks of variables in the same order—input variables were entered into the regression first, followed by various environmental variables. Figure 1 displays the order of blocks of variables entered into the regression analyses.
161
Figure 1
Blocks of Variables Entered into the Hierarchical Regression Analyses
Block One–Demographic variables: gender, sexual orientation, race, citizenship, religion, father’s education, parents’ income, and high school grade ↓ Block Two–Variables on pre-college importance of: growth in understanding diversity and interacting with peers, academic and social support in residence halls, and partici patin g in co-curricular activities and interacting with faculty. ↓
Block Three–Variables on pre-college confidence in: handling new intellectual challenges and appreciating diversity, and academic and personal growth and satisfaction.
↓
Block Four–Variables on peer interactions: frequency of diverse peer interactions and the amount, scope and quality of racial interactions with peers and absence of unfriendly interactions with peers from a different racial/ethnic group.
↓
Block Five–Variables on faculty interactions: frequency of academic, career-related, personal, and cultural interactions with faculty, and frequency of research-related interactions with faculty.
↓
Block Six–Variables on intellectual development/curricular learning: enjoyment of integrated learning, intellectual challenge, application of knowledge, and multiplicity of thinking, enjoyment of integration of academic learning and self-discovery, and enjoyment of questioning others’ opinions and going beyond dualistic thinking. ↓ 162
Figure 1 (Continued)
Block Seven–Variables related to residence halls: frequency of using academic advising, faculty, peer, and co-curricular resources inside the residence hall, and degree of academic support and social support for diverse peer interactions in the residence environment.
↓ Block Eight–Variables on use of time and co-curricular involvement: time spent on socializing and recreational activities, time spent on academic work, time spent on media-related communications and entertainments, time spent on work or student clubs/groups, involvement in fraternity/sorority, involvement in arts/music performances and activities, involvement in intramural or club sports, involvement in religious clubs and activities, involvement in ethnic/cross-cultural activities/clubs, involvement in media-activities, involvement in work-study or work on-campus, and involvement in work off-campus. ↓ Block Nine–Variables related to campus racial climate: relationship between students of different racial/ethnic backgrounds, absence of racial tensions in residence halls or on campus, campus commitment to the success of students of color, campus commitment to racial diversity, and sense of belonging to the campus community
163
The following sections provide the final regression model summaries for the six dependent variables examined—overall level of civic engagement, perceptions on volunteerism and service to the community, sense of responsibility to the common good, sense of civic empowerment, growth in understanding of and appreciation for diversity and gains in inter- racial understanding (combined into one variable), and growth in moral values development. All the final models consisted of 39 variables. The significant predictors for each final model were presented in the order based on their absolute β value from the highest to the lowest, indicating the strength of relationship between a predictor and the criterion variable, or a predictor’s relative explanatory power. Table 47 displays R Square, Adjusted R Square, and R Square changes for each step and each final model for the above dependent variables.
Predictors for RLC Students’ Overall Level of Civic Engagement
The final model significantly contributed to RLC students’ overall level of civic engagement, R Square=.546, Adjusted R Square=.516, F (39, 599) =18.47, p<.001. The 16 significant predictors included: enjoyment of intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking (β=.187, t(599)=4.44, p<.001), pre-college importance of participating in co-curricular activities and interacting with faculty (β=.186, t(599)=5.68, p<.001), enjoyment of the integration of academic learning and self-discovery
(β=.171, t(599)=5.32, p<.001), frequency of diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.152, t(599)=4.03, p<.001), frequency of using residence hall academic advising, faculty, peer, and co-curricular resources (β=.135, t(599)=3.88, p<.001), pre-college confidence in academic and personal
growth and satisfaction (β=.121, t(599)=3.27, p=.001), sense of belonging to the campus community (β=.119, t(599)= 3.68, p<.001), involvement in religious activities and clubs (β=.115, 164
t(599)=3.84, p<.001), pre-college importance of growth in understanding diversity (β=.097, t(599)=2.88, p<.001), academic support and social support for diverse peer interactions in residence environments (β=.086, t(599)=2.55, p=.011), involvement in ethnic/cross-cultural activities and clubs (β=.083, t(599)=2.57, p=.010), involvement in fraternities/sororities
(β=.074, t(599)=2.45, p=.015), pre-college confidence in handling new intellectual challenges
and appreciating diversity (β=-.075, t(599)=-2.01, p=.045), time spent on socializing and
recreational activities (β=-.071, t(599)=-2.29, p=.022), pre-college importance of academic and
social support in residence halls (β=-.062, t(599)=-2.00, p=.046), and father’s education (β=-
.059, t(599)=-1.99, p=.047). Four variables were found to be negatively associated with the overall level of civic engagement—time spent on socializing and recreational activities, pre- college confidence in handling new intellectual challenges and appreciating diversity, pre- college importance of academic and social support in residence halls, and father’s education.
The rest of the significant variables were all positively associated with the dependent variable.
Predictors for Perceptions on Volunteerism and Service to the Community
The final model significantly predicted RLC students’ perceptions on volunteerism and service to the community, R Square=.386, Adjusted R Square=.351, F (39, 693) =11.15, p<.001.
Overall, this model explains approximately 38.6% of the variance on this outcome measure. Ten variables significantly contributed to the final model: pre-college importance of participating in co-curricular activities and interacting with faculty (β=.260, t(693)=7.30, p<.001), enjoyment of
intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking
(β=.175, t(693)=3.84, p=.001), sense of belonging to the campus community (β=.161,
t(693)=4.60, p<.001), involvement in religious activities and clubs (β=.126, t(693)=3.87,
p=.001), involvement in fraternity/sorority (β=.104, t(693)=3.19, p=.002), enjoyment of the 165
integration of academic learning with self-discovery (β=.102, t(693)=2.97, p=.003), campus commitment to racial diversity (β=.087, t(693)=2.69, p=.007), involvement in ethnic/cross- cultural activities and clubs (β=.085, t(693)=2.53, p=.011), time spent on socializing and recreational activities (β=-.085, t(693)=-2.53, p=.012), and pre-college confidence in handling new intellectual challenges and appreciating diversity (β=-.081, t(693)=-2.04, p=.042). Time spent on socializing and recreational activities and pre-college confidence in handling new intellectual challenges and appreciating diversity were negatively associated with perceptions on volunteerism and service to the community; the remaining eight significant variables added positive predictive power to the final model.
Predictors for Sense of Responsibility to the Common Good
The final model significantly predicted RLC students’ sense of responsibility to the
common good, R Square=.344, Adjusted R Square=.307, F (39, 696) =9.34, p<.001. Overall, this
model explains approximately 34.4% of the variance in this outcome measure. Eleven variables
significantly contributed to the final model: enjoyment of intellectual challenge, integrated
learning, application of knowledge, and multiplicity of thinking (β=.177, t(696)=3.77, p<.001),
pre-college importance of participating in co-curricular activities and interacting with faculty
(β=.151, t(696)=4.11, p<.001), enjoyment of the integration of academic learning with self-
discovery (β=.144, t(696)=4.05, p<.001), frequency of diverse peer interactions and amount and
scope and quality of interactions with peers from a different racial/ethnic group (β=.135,
t(696)=3.23, p=.001), pre-college importance of academic and personal growth and satisfaction
(β=.099, t(696)=2.39, p=.017), involvement in religious activities and clubs (β=.098,
t(696)=2.94, p=.003), campus commitment to the success of students of color (β=.084,
t(696)=2.14, p=.033), sense of belonging to the campus community (β=.082, t(696)=2.26, p=.024), campus commitment to racial diversity (β=.081, t(696)=2.45, p=.014), frequency of 166
academic, social and career-related interactions with faculty (β=.081, t(696)=2.23, p=.026), and time spent on socializing and recreational activities (β=-.079, t(696)=-2.29, p=.022). Time spent on socializing and recreational activities was negatively associated with sense of social responsibility; the remaining 10 significant variables added positive predictive power to the final model.
Predictors for Sense of Civic Empowerment
The final model significantly predicted RLC students’ sense of civic empowerment, R
Square=.349, Adjusted R Square=.312, F (39, 694) =9.52, p<.001. Overall, this model explains approximately 34.9% of the variance in sense of civic empowerment. Ten variables significantly contributed to the final model: enjoyment of intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking (β=.192, t(694)=4.09, p<.001), campus commitment to racial diversity (β=.175, t(694)=5.29, p<.001), pre-college importance of participating in co-curricular activities and interacting with faculty (β=.161, t(694)=4.37, p<.001), campus commitment to the success of students of color (β=.144, t(694)=3.72, p<.001), enjoyment of the integration of academic learning with self-discovery (β=.112, t(694)=3.14, p=.002), frequency of diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.108, t(694)=2.57, p=.010), pre-college confidence in academic and personal growth and satisfaction (β=.103, t(694)=2.49, p=.013), citizenship (β=-.093, t(694)=-2.55, p=.011), involvement in religious activities and clubs
(β=.090, t(694)=2.70, p=.007), and absence of racial tensions in residence halls or on campus
(β=.079, t(694)=2.29, p=.023). Citizenship was negatively associated with sense of civic empowerment.
167
Predictors for Understanding of and Appreciation for Diversity
The final model significantly predicted RLC students’ growth in understanding of and
appreciation for diversity and inter-racial understanding, R Square=.408, Adjusted R
Square=.372, F (39, 633) =11.18, p<.001. Overall, this model explains approximately 40.8% of
the variance in this variable. Ten variables significantly contributed to the final model: enjoyment
of the integration of academic learning with self-discovery (β=.205, t(633)=5.77, p<.001), frequency of using residence hall academic advising, faculty, peer, and co-curricular resources
(β=.183, t(633)=4.78, p<.001), pre-college importance of growth in understanding diversity and interacting with peers (β=.180, t(633)=4.84, p<.001), frequency of diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group
(β=.156, t(633)=3.72, p<.001), academic and social support for diverse peer interactions in residence environments (β=.150, t(633)=3.99, p<.001), sense of belonging to the campus community (β=.105, t(633)=2.93, p=.004), pre-college confidence in academic and personal growth and satisfaction (β=.098, t(633)=2.41, p=.016), campus commitment to racial diversity
(β=-.097, t(633)=-2.93, p=.004), involvement in working off campus (β=-.075, t (633)=-2.24, p=.026), and father’s education (β=-.068, t(633)=-2.08, p=.038). Campus commitment to racial diversity, involvement in working off campus, and father’s education were negatively associated with RLC students’ understanding of and appreciation for diversity; the remaining predictors positively related to this outcome measure.
Predictors for Growth in Moral Values Development
The final model significantly predicted growth in moral values development, R
Square=.224, Adjusted R Square=.181, F (39, 702) =5.19, p<.001. Overall, this model explains approximately 22.4% of the variance in this outcome measure. Six variables significantly contributed to the model: enjoyment of intellectual challenge, integrated learning, application of 168
knowledge, and multiplicity of thinking (β=.191, t(702)=3.75, p<.001), enjoyment of the
integration of academic learning with self-discovery (β=.186, t(702)=4.83, p<.001), pre-college confidence in academic and personal growth and satisfaction (β=.156, t(702)=3.48, p<.001), pre-college importance of growth in understanding diversity and interacting with peers (β=.119, t(702)=2.97, p=.003), involvement in religious activities/clubs (β=.103, t(702)=2.85, p=.005), and absence of unfriendly interactions with peers from a different racial/ethnic group (β=.083, t(702)=2.17, p=.030). All of these six significant variables were positively associated with growth in moral values development.
169
Table 47
Summary of Hierarchical Regression Analyses for Variables Predicting Civic Engagement ______Overall Volunteerism Responsibility Empower Diversity Moral ______Step one R2 .039 .029 .021 .018 .050 .014 2 R adj .028 .019 .012 .009 .040 .005
Step two R2 .249 .185 .154 .124 .170 .071 2 R adj .237 .174 .142 .112 .157 .059 ∆R2 .210 .156 .133 .106 .120 .057 Step three R2 .296 .212 .184 .161 .196 .104 2 R adj .282 .199 .171 .147 .181 .090 ∆R2 .047 .027 .030 .037 .026 .033 Step four R2 .375 .247 .228 .203 .260 .118 2 R adj .360 .231 .212 .187 .243 .100 ∆R2 .079 .035 .044 .041 .064 .014 Step five R2 .384 .254 .242 .207 .265 .121 2 R adj .367 .236 .224 .188 .246 .010 ∆R2 .010 .007 .014 .004 .005 .003 Step six R2 .460 .300 .302 .258 .316 .192 2 R adj .442 .280 .282 .237 .295 .169 ∆R2 .076 .046 .060 .051 .051 .071 Step seven R2 .495 .317 .305 .266 .377 .203 2 R adj .477 .296 .283 .243 .355 .178 ∆R2 .035 .017 .003 .008 .061 .011 Step eight R2 .528 .357 .329 .288 .385 .223 2 R adj .501 .325 .296 .253 .352 .185 ∆R2 .033 .040 .024 .022 .008 .020 Step nine R2 .546 .386 .344 .349 .408 .224 2 R adj .516 .351 .307 .312 .372 .181 ∆R2 .018 .029 .015 .061 .023 .001 ______
170
Predictors for the RLC Students’ Overall Level of Civic Engagement
by Demographic Characteristics
The finding that RLC participation contributed conditional effects on civic engagement
by gender, sexual orientation, race, citizenship, and religion prompted the investigation of the different predictors for civic engagement by different demographic groups. To determine how the inputs and environments of RLC students from different demographic groups predicted their score on the overall level of civic engagement, separate hierarchical regressions were performed
on different groups. Groups that had fewer than 30 non-missing responses in the final model
were excluded from analyses. The entering of the same set of input and environmental variables
(totaling 38 variables, excluding the demographic variable classifying that particular student
group) followed the same nine steps specified in Figure 1. The following sections report the final
model summary for each of these demographic groups. The significant predictors for each final
model were presented based on their absolute β value from the highest to the lowest. The R
Square, Adjusted R Square, and R Square changes for each model generated for each
demographic group are presented in Table 48 and Table 49.
Predictors for RLC Female Students’ Overall Level of Civic Engagement
The final model significantly predicted RLC female students’ overall level of civic
engagement, R Square=.517, Adjusted R Square=.469, F (38, 385)=10.83, p<.001. Overall, this
model explains approximately 51.7% of the variance in female RLC students’ overall level of
civic engagement. Fifteen variables significantly contributed to the final model: pre-college importance of participating in co-curricular activities and interacting with faculty (β=.211, t(385)=4.99, p<.001), enjoyment of the integration of academic learning with self-discovery
(β=.170, t(385)=4.07, p<.001), enjoyment of intellectual challenge, integrated learning, 171
application of knowledge, and multiplicity of thinking (β=.166, t(385)=2.96, p=.003),
involvement in ethnic/cross-cultural activities/clubs (β=.125, t(385)=3.09, p=.002), frequency of
using residence hall academic advising, peer, and faculty resources (β=.117, t(385)=2.60,
p=.010), sense of belonging to the campus community (β=.113, t(385)=2.74, p=.006), citizenship
(β=-.108, t(385)=-2.47, p=.014), involvement in religious activities/clubs (β=.100, t(385)=2.55,
p=.011), involvement in fraternity/sorority (β=.100, t(385)=2.46, p=.014), diverse peer
interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.117, t(385)=2.45, p=.014), pre-college confidence in academic and personal growth and satisfaction (β=.098, t(385)=2.02, p=.044), academic and social support in residence environments (β=.097, t(385)=2.27, p=.024), time spent on socializing or recreational activities (β=-.093, t(385)=-2.32, p=.021), campus commitment to the success of students of color (β=.093, t(385)=2.03, p=.043), and pre-college importance of growth in understanding diversity and interacting with peers (β=.091, t(385)=2.12, p=.035). Citizenship
and time spent on socializing or recreational activities were negatively related to female
students’ overall level of civic engagement. In other words, female students whose grandparents,
parents, or themselves were all born in the U. S. were more likely to report a higher overall level
of civic engagement than those who were born in the U. S, but at least one of their parents was
not a foreign-born naturalized citizen, and than those who were foreign-born resident aliens, or
student visa holders; females reporting spending more time in socializing tended to report a
lower overall level of civic engagement. The remaining 13 significant predictors were positively
associated with the dependent variable examined.
172
Predictors for RLC Male Students’ Overall Level of Civic Engagement
The final model significantly predicted male RLC students’ overall level of civic
engagement, R Square=.646, Adjusted R Square=.570, F (38, 176) =8.47, p<.001. Overall, this
model explains approximately 64.6% of the variance in male RLC students’ overall level of civic
engagement. Nine variables significantly contributed to the final model: enjoyment of intellectual
challenge, integrated learning, application of knowledge, and multiplicity of thinking (β=.264,
t(176)=3.72, p<.001), diverse peer interactions and amount and scope and quality of
interactions with peers from a different racial/ethnic group (β=.227, t(176)=3.22, p=.002),
enjoyment of the integration of academic learning with self-discovery (β=.171, t(176)=3.11,
p=.002), use of residence hall academic advising, faculty, peer, and co-curricular resources
(β=.168, t(176)=2.74, p=.007), pre-college importance of participating in co-curricular
activities and interacting with faculty (β=.154, t(176)=2.75, p=.007), involvement in religious
activities/clubs (β=.149, t(176)=3.12, p=.002), sense of belonging to the campus community
(β=.148, t(176)=2.57, p=.011), pre-college confidence in academic and personal growth and
satisfaction (β=.144, t(176)=2.24, p=.027), and pre-college confidence in handling new intellectual challenges and appreciating diversity (β=-.142, t(176)=-2.14, p=.034). Pre-college confidence in handling new intellectual challenges and appreciating diversity was negatively related to male students’ overall level of civic engagement. In other words, male students who reported a higher score on this pre-college variable tended to report a lower score on their overall level of civic engagement. The remaining eight significant predictors were positively associated with the dependent variable examined.
173
Predictors for RLC White Students’ Overall Level of Civic Engagement
The final model significantly predicted RLC White students’ overall level of civic
engagement, R Square=.553, Adjusted R Square=.519, F (38, 509) =16.55, p<.001. Overall, this
model explains approximately 55.3% of the variance in RLC White students’ overall level of
civic engagement. Thirteen variables significantly contributed to the final model: pre-college
importance of participating in co-curricular activities and interacting with faculty (β=.202,
t(509)=5.67, p<.001), enjoyment of intellectual challenge, integrated learning, application of
knowledge, and multiplicity of thinking (β=.184, t(509)=3.99, p<.001), enjoyment of the
integration of academic learning with self-discovery (β=.177, t(509)=4.99, p<.001), sense of belonging to the campus community (β=.146, t(509)=4.18, p<.001), use of residence hall academic advising, faculty, peer, and co-curricular resources (β=.145, t(509)=3.90, p<.001), diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.119, t(509)=2.93, p=.004), pre-college confidence in academic and personal growth and satisfaction (β=.118, t(509)=2.87, p=.004), involvement in ethnic/cross-cultural activities/clubs (β=.100, t(509)=3.10, p=.002), involvement in religious activities/clubs (β=.100, t(509)=3.04, p=.003), citizenship (β=-.097, t(509)=-3.14, p=.002), relationship between students of different racial/ethnic backgrounds (β=.081, t(509)=2.04,
p=.042), and time spent on socializing and recreational activities (β=-.069, t(509)=-2.09, p=.038). White students who reported spending more time on socializing, partying, and exercising tended to report a lower score on their overall level of civic engagement. The remaining 11 significant predictors were positively associated with the dependent variable examined.
174
Predictors for the Overall Level of Civic Engagement Reported by RLC Students of Color
The final model significantly predicted overall level of civic engagement of RLC students
of color, R Square=.768, Adjusted R Square=.599, F (38, 52) =4.54, p<.001. Overall, this model
explains approximately 76.8% of the variance in RLC students of color’s overall level of civic
engagement. Six variables significantly contributed to the final model: pre-college importance
of growth in understanding diversity and interacting with peers (β=.350, t(52)=3.03, p=.004),
enjoyment of intellectual challenge, integrated learning, application of knowledge, and
multiplicity of thinking (β=.346, t(52)=2.52, p=.015), enjoyment of the integration of academic
learning with self-discovery (β=.298, t(52)=3.19, p=.002), involvement in intramural or club
sports (β=.267, t(52)=2.91, p=.005), academic support and social support for diverse peer
interactions in the residence environment (β=.260, t(52)=2.64, p=.011), and involvement in work off-campus (β=-.210, t(52)=-2.23, p=.030). Work off-campus was negatively related to RLC students of color’s overall level of civic engagement. The remaining five significant predictors were all positively associated with the outcome measure examined.
175
Table 48
Summary of Hierarchical Regression Analyses by Gender and Race ______Male Female White Color ______
Step one R2 .079 .016 .047 .036 2 R adj .053 .002 .037 -.033
Step two R2 .304 .210 .244 .372 2 R adj .274 .193 .232 .302 ∆R2 .225 .194 .197 .336 Step three R2 .355 .255 .292 .406 2 R adj .320 .235 .277 .324 ∆R2 .049 .045 .052 .034 Step four R2 .457 .327 .368 .466 2 R adj .419 .303 .351 .367 ∆R2 .102 .072 .076 .060 Step five R2 .467 .334 .376 .489 2 R adj .424 .308 .357 .378 ∆R2 .010 .007 .008 .023 Step six R2 .559 .406 .457 .573 2 R adj .516 .378 .438 .458 ∆R2 .092 .072 .081 .084 Step seven R2 .589 .445 .496 .591 2 R adj .544 .416 .475 .467 ∆R2 .030 .039 .039 .018 Step eight R2 .627 .491 .524 .727 2 R adj .559 .448 .493 .569 ∆R2 .038 .046 .028 .136 Step nine R2 .646 .517 .553 .768 2 R adj .570 .469 .519 .599 ∆R2 .019 .026 .029 .041 ______
176
Predictors for RLC Christian Students’ Overall Level of Civic Engagement
The final model significantly predicted RLC Christian students’ overall level of civic
engagement, R Square=.563, Adjusted R Square=.520, F (38, 379) =12.87, p<.001. Overall, this
model explains approximately 56.3% of the variance in RLC Christian students’ overall level of
civic engagement. Thirteen variables significantly contributed to the final model: enjoyment of
intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking
(β=.167, t(379)=3.27, p=.001), pre-college importance of participating in co-curricular
activities and interacting with faculty (β=.157, t(379)=3.89, p<.001), use of residence hall academic advising, faculty, peer, and co-curricular activities (β=.157, t(379)=3.59, p<.001), academic support and social support for diverse peer interactions in the residence environment
(β=.135, t(379)=3.12, p=.002), pre-college confidence in growth in understanding diversity and interacting with peers (β=.131, t(379)=3.05, p=.003), enjoyment of the integration of academic learning with self-discovery (β=.121, t(379)=2.96, p=.003), involvement in ethnic/cross-cultural activities/clubs (β=.110, t(379)=2.77, p=.006), diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.109, t(379)=2.31,
p=.022), pre-college confidence in academic and personal growth and satisfaction (β=.108,
t(379)=2.19, p=.029), sense of belonging to the campus community (β=.106, t(379)=2.64, p=.009), campus commitment to the success of students of color (β=.096, t(379)=2.28, p=.023),
pre-college importance of academic and social support in residence halls (β=-.079, t(379)=-
2.03, p=.043), and involvement in religious activities/clubs (β=.011, t(379)=2.56, p=.011). Pre- college importance of academic and social support in residence halls was negatively associated with RLC Christian students’ overall level of civic engagement. The remaining 12 significant predictors were positively related to the outcome measure examined. 177
Predictors for the Overall Level of Civic Engagement
of RLC Students Reporting Having No Religion
The final model significantly predicted the overall level of civic engagement of RLC students reporting having no religion, R Square=.676, Adjusted R Square=.529, F (38, 84)=4.61, p<.001. Overall, this model explains approximately 67.6% of the variance in these students’ overall level of civic engagement. Five variables significantly contributed to the final model: enjoyment of intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking (β=.318, t(84)=2.88, p=.005), academic, career-related, personal, and cultural interactions with faculty (β=.227, t(84)=2.51, p=.014), involvement in intra-mural or club sports (β=.223, t(84)=2.84, p=.006), sense of belonging to the campus community (β=.207, t(84)=2.32, p=.023), and enjoyment of the integration of academic learning with self-discovery
(β=.185, t(84)=2,21, p=.030). All of these significant predictors added positive predictive power to the final model.
Predictors for the Overall Level of Civic Engagement
of RLC Students Who Were Natural-Born Citizens
The final model significantly predicted the overall level of civic engagement of RLC students who were natural-born citizens (i. e., students whose grandparents, parents, and themselves were all born in the U. S.), R Square=.537, Adjusted R Square=.501, F (38, 494)
=15.06, p<.001. Overall, this model explains approximately 53.7% of the variance in these students’ overall level of civic engagement. Ten variables significantly contributed to the final model: enjoyment of intellectual challenge, integrated learning, application of knowledge, and multiplicity of thinking (β=.198, t(494)=4.13, p<.001), pre-college importance of participating in co-curricular activities and interacting with faculty (β=.182, t(494)=4.95, p<.001), enjoyment 178
of the integration of academic learning with self-discovery (β=.173, t(494)=4.70, p<.001), use of academic advising, faculty, peer, and co-curricular resources in residence halls (β=.141, t(494)=3.69, p<.001), sense of belonging to the campus community (β=.134, t(494)=3.69, p<.001), pre-college confidence in academic and personal growth and satisfaction (β=.127, t(494)=3.05, p<.001), diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group (β=.115, t(494)=2.73, p=.007), involvement tin religious activities/clubs (β=.094, t(494)=2.74, p=.006), pre-college importance of growth in understanding diversity and interacting with peers (β=.093, t(494)=2.47, p=.014), and involvement in ethnic/cross-cultural activities/clubs (β=.081, t(494)=2.41, p=.017). All of these significant predictors added positive predictive power to the final model.
Predictors for the Overall Level of Civic Engagement
of RLC Students Who Were Immigration Citizens
The final model significantly predicted the overall level of civic engagement of RLC students who were immigration citizens (i. e., students who were born in the U. S, but at least one of their parents was not), R Square=.821, Adjusted R Square=.616, F (38, 33) =3.99, p<.001.
This model explains approximately 82.1% of the variance in these students’ overall level of civic engagement. Six variables significantly contributed to the final model: diverse peer interactions and amount and scope and quality of interactions with peers from a different racial/ethnic group
(β=.417, t(33)=2.76, p=.009), campus commitment to racial diversity (β=.365, t(33)=2.84, p=.008), use of residence hall academic advising, faculty, peer, and co-curricular resources
(β=.277, t(33)=2.28, p=.029), involvement in religious activities/clubs (β=.255, t(33)=2.23, p=.033), involvement in work-study or work on-campus (β=.251, t(33)=2.10, p=.043), and time spent on media-related communications and entertainments, e. g., watching TV alone, playing 179 video/computer games, E-mail or instant messaging (β=-.210, t(33)=-2.06, p=.048). Time spent in media-related communications and entertainments was negatively related to civic engagement; the other four significant predictors added positive predictive power to the final model.
180
Table 49
Summary of Hierarchical Regression Analyses by Citizenship and Religion ______Natural-born One not Christian None ______Step one R2 .046 .047 .051 .080 2 R adj .035 -.041 .037 .032
Step two R2 .257 .276 .266 .245 2 R adj .244 .171 .250 .184 ∆R2 .211 .229 .215 .165 Step three R2 .303 .323 .304 .269 2 R adj .288 .199 .285 .196 ∆R2 .046 .047 .038 .024 Step four R2 .367 .447 .378 .352 2 R adj .350 .311 .356 .268 ∆R2 .064 .124 .074 .083 Step five R2 .376 .480 .391 .407 2 R adj .356 .328 .367 .317 ∆R2 .009 .033 .013 .055 Step six R2 .455 .570 .459 .543 2 R adj .435 .414 .433 .459 ∆R2 .079 .090 .068 .136 Step seven R2 .488 .597 .511 .552 2 R adj .467 .428 .485 .459 ∆R2 .033 .027 .052 .009 Step eight R2 .514 .770 .546 .634 2 R adj .482 .571 .507 .499 ∆R2 .026 .173 .035 .082 Step nine R2 .537 .821 .563 .676 2 R adj .501 .616 .520 .529 ∆R2 .023 .051 .017 .042 ______
181
Summary of Hierarchical Regression Analyses
Nearly 40 input and environmental variables, comprising nine blocks, were entered into
the regression analyses in nine steps based on the order implied by Astin’s I—E—O Model
(1977, 1993) and previous research. The final model significantly predicting students’ overall
level of civic engagement explained over half of the variance in this measure. Three blocks of
variables contributed the largest amount of net variance to the predictive power of the final
model for the overall level of civic engagement: pre-college motivation for participating in
educationally beneficial activities during college, intellectual development/curricular learning,
and peer interactions. More specifically, the model specified 16 significant predictors: pre-
college importance of participating in co-curricular activities and interacting with faculty,
enjoyment of the integration of academic learning with self-discovery, enjoyment of intellectual
challenge, integrated learning, application of knowledge, and multiplicity of thinking, frequency
of diverse peer interactions and amount and scope and quality of interactions with peers from a
different racial/ethnic group, frequency of using residence hall academic advising, faculty, peer,
and co-curricular resources, involvement in religious activities and clubs, sense of belonging to
the campus community, pre-college confidence in academic and personal growth and satisfaction, pre-college importance of growth in understanding diversity and interacting with
peers, involvement in ethnic/cross-cultural activities and clubs, academic and social support for
diverse peer interactions in residence environments, involvement in fraternities/sororities, time spent on socializing and recreational activities, pre-college confidence in handling new intellectual challenges and appreciating diversity, pre-college importance of academic and social support in residence halls, and father’s education. Time spent on socializing and recreational activities, pre-college confidence in handling new intellectual challenges and 182
appreciating diversity, pre-college importance of academic and social support in residence halls, and father’s education were found to be negatively associated with the overall level of civic engagement; the rest of the predictors were all positively related to the dependent variable.
Significant regression models were also generated for five specific attitudinal measures of civic engagement and for the overall level of civic engagement of eight RLC student groups by gender, race, citizenship, and religion. The following variables consistently (i. e., found significant in the final model for three or more dependent measures or found significant in the final model for at least three student groups) contributed most (in terms of the amount of net variance explained) to the final models: pre-college importance of participating in co-curricular activities and interacting with faculty, pre-college confidence in academic and personal growth and satisfaction, enjoyment of the integration of academic learning with self-discovery,
enjoyment of intellectual challenge, integrated learning, application of knowledge, and
multiplicity of thinking, diverse peer interactions and amount and scope and quality of
interactions with peers from a different racial/ethnic group, campus commitment to racial
diversity, sense of belonging to the campus community, use of residence hall advising, faculty,
peer, and co-curricular resources, and involvement in religious activities/clubs.
Summary of Major Results
The analyses of data yielded a portrait of RLC students as mostly heterosexual, White,
female, and Christians who were natural-born citizens. These students reported an average high school grade of B+ or above and their parents’ level of education, on average, was bachelor’s degree or higher. Over half of them reported their parents’ annual total income was $75,000 or higher. Male students, students having no religion or whose religion was other than Christianity, and students who had more highly educated parents, were over-representative of the RLC 183 population but still in the minority. In addition, RLC students reported a significantly higher mean score than the comparison group with regard to their positive pre-college perceptions of educational activities and confidence in success in college. Significant differences were also found within the RLC sample pertaining to pre-college perceptions by gender, sexual orientation, race, citizenship, religion, father’s education, and high school grades.
Regarding the second research question, RLC participation demonstrated a significant, positive main effect on students’ overall level of civic engagement, and more specifically, on volunteerism and service to the community, sense of responsibility to the common good, and sense of civic empowerment. Regarding the third research question, gender, sexual orientation, race, religion, citizenship, father’s education, and high school grades all demonstrated significant conditional effects on one or more measures of RLC students’ level of civic engagement. Despite the significant differences, sizes of all the main and conditional effects were extremely small.
Regarding the fourth research question, pre-college motivations and confidence (i. e., importance of growth in understanding diversity and interacting with peers, participating in co- curricular activities and interacting with faculty, confidence in academic and personal growth and satisfaction) and a string of environmental variables—enjoyment of integrated learning, intellectual challenge, application of knowledge, and multiplicity of thinking, enjoyment of integration of academic learning and self-discovery, diverse peer interactions, use of academic advising, faculty, peer, and co-curricular resources in residence halls, involvement in religious and ethnic activities, and sense of belonging to the campus community—consistently contributed most to the variance in RLC students’ overall level of civic engagement, in their specific attitudinal indicators of civic engagement, and in the overall level of civic engagement for each demographic group of RLC students examined. 184
CHAPTER V: DISCUSSION, IMPLICATIONS, AND RECOMMENDATIONS
This chapter is organized in four sections. The first section highlights and explains the key findings from the data, in relation to previous relevant research; the second section discusses their significance and potential implications for higher education policy and practice; the third section offers recommendations for further research; and the last section provides some concluding remarks.
Discussion of Key Findings
This dissertation focused on investigating the impact of participating in an RLC on first- year, full-time, and degree-seeking students’ self-reported levels of civic engagement at four- year, public, Midwest universities. This impact was assessed by comparing RLC students’ and conventional students’ scores on various indicators of the outcome construct, by examining within-group differences among RLC students, and by specifying the factors that were most closely associated with this outcome. The following key findings are discussed here in response to each of the four research questions posed.
RLC Participants
The fact that these RLC students are mostly heterosexual, White, female, and Christian and whose grandparents, parents, or themselves were all born in the U. S. is not surprising, given that students of these categories constitute the mainstream population at large, research, public universities such as those included here. In addition, most of these RLC students seem to be from more highly educated families. It is likely that their parents, putting a premium on the value of a college education, are attracted by the benefits of RLCs and therefore encourage their sons and daughters to enroll in such programs. 185
The data suggest that, prior to entering college, these RLC students had already
distinguished themselves from the conventional students in attitudes and beliefs. They tend to be more motivated and inclined to participate in educationally beneficial activities in college, e. g., those involving growth in understanding diversity, interacting with peers, involvement in
co-curricular activities, interacting with faculty, and taking advantage of their residence hall
environment for academic success. Moreover, they seem to be better prepared for success during
college.
In short, the treatment group and the comparison group were not entirely comparable at
the point of entering the university. Obviously, these RLC students possess different pre-college characteristics from the students living in conventional residence halls. It is clear that, overall, these students seem to self-select into this experience for reasons compatible with their predilection. In other words, these students apparently join an RLC with distinctive attitudes and values, and their initial attitudes and beliefs appear to predispose them to participate in activities consistent with those attitudes. This finding also indicates that the marketing and recruiting strategies of RLC programs studied here seem to succeed in attracting the type of students expected. Findings evidencing the differences within the RLC sample pertaining to their pre- college perceptions may provide some clues in understanding the conditional effects of RLC participation.
RLC Participation and Civic Engagement
Findings from this study support an expectation that participation in an RLC demonstrates a significant positive main effect on students’ overall level of civic engagement, on
their volunteerism and service to the community, responsibility to the common good, and civic
empowerment. Such positive evidence seems to suggest that RLCs examined here are achieving 186
their espoused goal of enhancing civic engagement. By virtue of their programmatic emphases,
many RLCs intentionally offer co-curricular and/or curricular opportunities with an explicit
purpose of enhancing civic engagement. This positive evidence seems to indicate that RLC
students meet their RLC expectations. Indeed, one would be disappointed if no such evidence
was found. It may also be true that RLC participants’ pre-dispositions to be involved in college
find an outlet in an RLC setting for their interest in enhancing civic engagement, an interest that
is already higher than that of conventional students as argued above. It is unclear whether such positive effects reflect the changes that RLC participants undergo during their enrollment in the experience, or it is merely a reinforcement of their pre-entry inclinations. Regardless, there appears to be a certain synergy between student characteristics and program emphases in these
RLCs.
RLC participation main effects were found on three out of five dimensions of civic engagement—volunteerism and service to the community, responsibility to the common good, and civic empowerment. Perhaps the other two dimensions—understanding of and appreciation for diversity and moral values development—are substantively different, and therefore the environmental factors contributing to them are qualitatively different from those affecting the other three dimensions where significant main effects were observed. Apparently, volunteerism and service to the community, responsibility to the common good, and civic empowerment seem to be conceptually very comparable measures.
Analyses of variance also afforded a basis for estimating the magnitudes of impact of
RLC participation on students’ civic engagement. Despite the statistically significant differences between the RLC sample and the comparion group, the main effect sizes were all extremely small. Practically speaking, those differences are indeed negligible. Plausible explanations for 187
such small effect sizes would seem to be: First, RLC students studied here were all first-year students. At the time of completing The Survey, they had relatively brief exposure to their program—approximately six months. Therefore, the participation effect might not be fully reflected in their scores. Indeed, given the short period of participation, it may be unreasonable to expect greater magnitudes of effects than those found in this study. Second, it is possible that the large number of extreme observations that were not recoded or deleted skewed the group means up or down. Similar reasons can be argued to explain the absence of RLC participation main effects on understanding of and appreciation for diversity and growth in moral values development. Students’ variability on these two dimensions might require more time to rise to a level of statistical significance.
The findings regarding the RLC participation main effects are largely consistent with the evidence synthesized by Pascarella and Terenzini (1991) and, in their more recent review of college impact, How college affects students: A third decade of research (2005). Based on their
review of studies related to the overall impact of college, Pascarella and Terenzini (1991, 2005)
concluded that, with a few exceptions, both national and small-scale studies provide abundant
and consistent evidence for the positive effects of college on students’ altruism,
humanitarianism, sense of civic responsibility, social activism, and civic and community
attitudes and values. Despite the fact that this study did not examine changes as a result of
participating in RLCs, it still serves as an additional piece of evidence affirming the positive
impact of RLC participation on the three dimensions of civic engagement where significant main
effects were found. More specifically, findings from this dissertation confirm earlier research
regarding the positive effects of living/learning programs on volunteerism. 188
However, it is difficult to determine whether findings from this study support Pascarella
and Terenzini’s (1991, 2005) conclusion that shifts toward social, racial, ethnic, and political
tolerance and greater support for the rights of individuals occur during the college years. For one
thing, the time frame studied in this dissertation is not comparable to those covering one or more
college years. Such ambiguity of assessments in the research addressing the effect “during the
college years” dictates some caution in comparing research results. The same reason can be argued in comparing the effect sizes of RLC participation with those reported by Pascarella and
Terenzini (1991); i. e., college attendance is estimated to have a modest net effect on political and social values.
Conditional RLC Participation
Pascarella and Terenzini (1991) observed that “the fact remains, however, the literature has little to say about the differential effects of college on values and attitudes for different kinds of students” (p. 329). This dissertation adds fresh evidence for the conditional effects of RLC participation on the civic engagement levels of different student groups.
Most strikingly, the effect of RLC participation on civic engagement seems to be more apparent for females than for males. This may be partly due to female students’ higher pre- college motivation level for participating in activities leading to higher levels of civic engagement. Such an explanation seems warranted given the fact that female RLC students were more likely to agree that participating in co-curricular activities and interacting with faculty is important—one of the significant predictors for the RLC sample that contributed most to the various indicators of civic engagement. In other words, female students’ pre-disposition to be more involved in college finds on outlet in the RLC setting, thus reinforcing the effect of participation. Moreover, Gilligan’s (1982) theory on women’s socialization and development 189
might also offer a plausible explanation. According to Gilligan, women are socialized in an ethic of care that might lead to different values and attitudes potentially affecting their civic engagement levels.
The RLC participation effects on involvement in political and social activism, sense of social responsibility, and appreciation for diversity seem to be more pronounced for GLB students and students of color. Such findings are not unusual. For one thing, prior to entering college, both RLC students and students of color were more likely than heterosexual or White students to perceive growth in understanding diversity during college as important, which proved
to be one of the significant predictors that contributing most to the variance in the various
indicators of civic engagement. In other words, the pre-disposition or motivation argument for
females may well also apply to these two groups of students. For another, as a minority student
group, they may be more keenly aware of the importance of appreciating diversity and fighting
for social justice. Indeed, very often they are forced to take an activist posture in order to create a
voice for themselves on campus and in society at large.
With regard to religion, the RLC participation effect on volunteerism and civic
empowerment seems to be more apparent among Christian students than students reporting
having no religion. First, the pre-disposition argument as discussed above may be a plausible
explanation. Second, this finding might be understood in relation to the Judaic-Christian tradition
which emphasizes service and responsibility to one’s community. Perhaps, the Christian students
in these RLCs are exposed, to a greater extent, to such ideas through their home environments
and formalized church teachings, and their own belief system might have something to do with
such a more apparent effect on their community service and civic empowerment. Lastly, findings
from other empirical research (Astin, Vogelesang, Ikeda, & Yee, 2000; Rhee & Dey, 1996) 190
might also provide some plausible explanations. Findings from the above research indicate that attendance at both Catholic and Protestant colleges (versus sectarian institutions) has “direct and
positive effects over a four-year period on the importance students attach to civic responsibility,
volunteerism, and civic and social values” (Pascarella & Terenzini, 2005). It remains unknown
from the present data why students reporting having no religion scored significantly lower on
many of the indicators of civic engagement. Nonetheless, it is a striking and interesting finding deserving further investigation.
The data also revealed that students whose fathers had a doctorate or professional degree are more likely to be involved in political and social activism. Apparently, these students’ parents are more likely to come from the professorial rank that is often associated with liberal-
minded ideas and actions and consequently encourage their children to do the same. Lastly, the
effect on community service and volunteerism was more obvious among students who had better
high school grades. The pre-disposition argument may apply here, given that these students tend
to perceive participating in co-curricular activities and interacting with faculty as important,
which proved to be one of the significant predictors for this outcome measure. Perhaps their
superior high school academic groundwork afforded such students more time to do volunteer
work in college.
Predictors of Civic Engagement
Hierarchical regression analyses revealed the factors that best predicted these RLC
students’ levels of civic engagement. In addition, they provided a basis to estimate the net effects
of various input and environmental factors. Clearly, what these RLC students brought with them
to their respective programs—their level of motivation for involvement and level of confidence
for success during college—consistently contributed most to their reported levels of civic 191 engagement. Such findings are not unexpected, though. RLC student recruitment may well create a human aggregate environment that accentuates and reinforces the already higher levels of civic values and attitudes of these entering students. It appears that this human aggregate produces an effect on student level of civic engagement equal to that produced by their environments and experiences during their RLC participation.
This finding apparently concurs with a theory of accentuation. The accentuation hypothesis asserts that “if students initially having certain characteristics choose a certain setting
(a college, a major, a peer group) in which those characteristics are prized and nurtured, accentuation of such characteristics is likely to occur” (Feldman & Newcomb, 1969, p. 333).
Among the nine generalizations regarding college impact (Feldman & Newcomb) is one that
“’the degree and nature of different colleges’ impacts vary with their student inputs, … those characteristics in which freshman-to-senior change is distinctive for a given college will also have been distinctive for its entering freshmen” (p. 327). In Strange’s (2003) words, “the most prominent changes among students owe much to an accentuation or reinforcement of their initial characteristics” (p. 333). Although this dissertation did not assess longitudinal change, such statements ring true. The degree of value consensus and homogeneity among students in an RLC appears to exert an equally powerful influence on students’ reported levels of civic engagement as the intentionally designed RLC environments and experience.
Despite the apparent and dominant influence of RLC students’ pre-college motivational factors, the evidence is also clear that students’ experiences supposedly afforded by their RLC experience and other college environments significantly related to the magnitude of their levels of civic engagement, exerting an equally powerful influence as their pre-college characteristics.
Above and beyond the perceptions students bring with them to college and to their RLC, 192
evidence is apparent for the impact of general college experiences and RLC environmental
factors. The consistent and compelling evidence for the positive predictive power of enjoyment of integrated learning, intellectual challenge, multiplicity of learning, and the integration of
academic learning and self-discovery, along with use of academic advising, faculty, peer, and co-
curricular resources inside residence halls suggests that some environments and experiences
unique to RLCs may exert a net impact on RLC students’ civic engagement. As discussed in
Chapter II, many RLCs are characterized by the integration of curricular and co-curricular learning, which may also be true with the RLCs examined here. One can also infer that use of academic advising, faculty, peer, and co-curricular resources in residence halls are among RLCs’ intended goals for increased involvement.
The findings from the regression analyses further establish the importance of diverse peer interactions, faculty interactions, and involvement in co-curricular activities (Astin, 1977, 1993).
It is interesting to note that the influence of diverse peer interactions on civic engagement seems greater than that of interactions with faculty. In addition, this study reinforces observations by
Astin (1993), Sax (2000), and Pascarella and Terenzini (2005) that involvement in religious and ethnic/cross-cultural clubs and activities, peers interactions, and Greek membership positively affect civic engagement.
Implications for Policy and Practice
RLCs, as a significant component of the learning community movement, are expected to be, and indeed applauded as, an effective tool to improve undergraduate education, especially in large, public, research universities. Based on a regional sample and cross-sectional data, this study provided one piece of empirical evidence for the presence of positive RLC participation effects on one important educational outcome—civic engagement. Despite the small size of the 193
estimated main effects, this evidence still serves to suggest that the RLCs examined here largely
attained their espoused goals and objectives in this regard, particularly in the three dimensions of
civic engagement—volunteerism and service to the community, responsibility to the common
good, and civic empowerment. It seems to follow that institutions should continue to support
these types of programs in terms of providing resources and staffing.
Predictors for RLC students’ level of civic engagement identified in this study provide
some guidance for the design of such programs. Findings from this dissertation seem to suggest
that for RLCs to actualize and demonstrate more impressive impact on civic engagement, the
following strategies might warrant some attention.
First, this study clearly suggests that RLC students’ pre-college expectations, attitudes, and values are closely associated with the magnitude and direction of their level of civic engagement. Based on an assumption of accentuation, the impact of RLC participation on students’ level of engagement is apparently positively related to the fit between a potential RLC participant and a RLC in which he/she intends to enroll. It is important that institutions attend to students’ pre-dispositions and continue to offer programs that resonate with students’ inclinations and expectations. Moreover, to better achieve such a fit, institutions and RLC staff should proactively assess, invite, and orient students who are willing and ready to engage in such programs. For example, during the orientation phase of matriculation, RLC staff can actively reach out to interested students and their parents and follow through to recruit those who expect to benefit from their RLC experience. In addition, they may conduct a needs assessment articulating the expectations, attitudes, and values that are likely to be predictive of levels of civic engagement to identify potential participants. Similar assessments may also serve to understand whether such attitudes and values characterize the current enrollment so as to plan 194
programs accordingly. Clarifications of program missions, purposes, programmatic components,
and expectations through advertising and communications may help draw intentional, serious
participants as well. RLCs should also set clear expectations for potential participants, either
through a formal application and selection process or through individual interviews. In short,
RLCs should pay close attention to who will benefit from the program, to whom they market it, whom they invite to apply, and whom they admit rather than randomly accepting any applicant.
Students’ level of motivation, together with environments and experiences meeting those expectations, may well be a powerful set of predictors for civic engagement. While recognizing that students’ pre-dispositions appear to be essential for enhancing this outcome, RLC staff should also carefully implement strategies to motivate and challenge those admitted participants with less apparent inclinations for involvement in educational activities, depending on the characteristics of their campus student population, such as through the potential influence of peer environment, which is discussed below in more detail.
Second, greater emphases on the integration of curricular learning and out-of-class learning might yield better educational benefits on RLC student’s levels of civic engagement.
This stems from the evidence that intellectual development, i. e., enjoyment of intellectual challenge and integration of learning, application of knowledge, multiplicity of thinking, and integration of academic learning and self-discovery, proved to be significant, consistent predictors of civic engagement, contributing a large amount of net variance. For example, RLCs might intentionally design courses focusing on critical thinking and service learning to yield more benefits to the outcome of civic engagement. They might also incorporate co-curricular components emphasizing applications of what students learn from the coursework and explorations of how course content relates to students’ self-identity and life experiences. One can 195
imagine that the presence of resident faculty, courses taught within an RLC, and availability of
program space provided in the halls will facilitate the fulfillment of such purposes.
Third, these findings highlight the importance of diversifying RLC programs in the sense of providing participants opportunities to interact with peers from different racial/ethnic backgrounds and with different social, political, and religious views. Such findings also underscore the value of diversity initiatives prevalent on many campuses today. This is grounded on the finding that RLC students’ diverse peer interactions outside the class, the amount, scope, and quality of their racial interactions with peers, were consistently among the major predictors of levels of civic engagement, explaining a large amount of variance on the outcome measures examined. More specifically, RLCs should promote students’ interactions with peers with different personal values, religious beliefs, and political opinions, facilitate discussions of multiculturalism, diversity, and major social issues such as human rights and justice among students, encourage students’ intellectual, social, and personal interactions with peers from a different racial/ethnic group. The conditional effects of RLC participation found here also seem to warrant such a recommendation. On the one hand, RLCs can intentionally recruit certain subgroups of students among whom participation effects were observed to be more apparent on a certain dimension and take advantage of their potential influences on other RLC members to enhance the impact on that dimension. For example, overall, the impact on growth in understanding of and appreciation for diversity, growth in inter-racial understanding, and level of involvement in political and social activism seems to be more apparent among students of color than White students. This seems to suggest that affirmative strategies to recruit students of color might pay significant dividends on those dimensions, particularly for an RLC that enrolls a homogeneous group of White students. 196
On the other hand, the conditional effects present particular challenges for educators to
understand how such effects might help shape the outcome of civic engagement within an RLC.
To achieve inclusiveness and assist each and every participant to accomplish the desired
outcome, RLCs should reinforce their efforts to build a sense of community and meanwhile
provide interventions that may compensate for certain conditions, especially those conditions
that appear to be barriers to achieving a certain outcome. For example, for those students who
constitute the minority group in an RLC, efforts can be made to help them create sub-
communities within the larger community (Spitzberg & Thorndike, 1992). For those students on
whom participation effects seem less apparent (e. g., civic empowerment on Asian-American students; volunteerism and service to the community for those having no religion), RLC staff should affirm the value of their presence and purposefully provide opportunities to overcome or reduce the influence of those barriers. One strategy would be to use the potential influence of peer interactions or peer mentoring. Another one would be to consider the common and unique predictors for civic engagement for each group of students. In short, conditional effects present both opportunities and challenges for educators and dictate that RLCs with different human aggregate characteristics call for different, specific interventions.
Fourth, the fact that use of academic advising and faculty resources inside residence halls was found to be a consistent, significant predictor of civic engagement affirms the value of the current practices prevalent in many RLCs characterized by direct faculty involvement. The finding from this dissertation clearly supports the importance of engaging faculty in RLCs, such as having them teach courses in the halls, provide advising and mentoring, use office space, and plan and organize co-curricular activities to reinforce students’ intellectual development, which, in turn, was found to relate to higher levels of civic engagement. 197
Recommendations for Future Research
This study provides insight into the characteristics of RLC students, their level of civic
engagement in comparion to students living in conventional residence halls, demographic and pre-college features that shape their experience, and environmental factors that contribute to their overall level of civic engagement. Upon completing this study, five recommendations for future research seem appropriate.
First, this dissertation examined the impact of RLC participation on one particular student population—first-year students, by analyzing cross-sectional data collected during their second semester in college. Given the limits of such a short time frame, longitudinal studies with similar research designs should be conducted to investigate the patterns of change and durability of such impact across time. More specifically, a longitudinal focus could provide more insights into the direction and magnitude of such impact at various points in the academic cycle (e.g., by tracking changes between the freshman and senior year) and beyond (i. e., following graduation), resulting in an increased understanding of how such impact changes, whether it persists, and how predictors for civic engagement may vary and evolve. The present study revealed the small but impressive main effects seven months after matriculation. One would expect to find main effects of larger magnitude and a longitudinal study can satisfy such a curiosity.
Second, this study was based on the analyses of a broad array of input and environmental variables, all of which are related to college environments and experiences common to both RLC students and students living in conventional residence halls. As discussed in Chapter II, “Major
Features and the Theoretical Foundations of the RLC Model,” RLCs, defined in both a broad and narrow sense, vary in the extent of their formal curricular intervention, the degree of faculty involvement, expectations for students’ participation in activities (e. g., required or optional), and 198
students’ aggregate characteristics. Given that this dissertation did not make distinctions between the RLCs included here, in terms of being identified in a broad or narrow sense, a similar study incorporating variables pertaining to the features peculiar to an RLC might yield interesting information. Such variables could include: number of participants; programmatic emphases; whether participation in co-curricular activities offered within an RLC is required or optional; the degree of faculty involvement and their roles; whether an RLC offers service learning courses; whether it offers peer mentoring; and the distribution of students in terms of demographics and other relevant characteristics. Including such environmental measures in the regression analyses might unveil significant predictors for civic engagement in addition to those already identified in the present study, serving to guide allocation of resources for such programs. Following the administration of The Survey in March 2004, the NSLLP researchers designed a questionnaire and administered it to each NSLLP participating school contact to generate information on the participating RLCs’ program features. It is recommended that future studies monitor and incorporate those variables in their design, inasmuch as they might potentially affect the outcomes as measured in this study.
Future research may also benefit from incorporating another student demographic variable—academic major, one which has been shown to bear a significant association with students’ civic attitudes, values, and behaviors (Astin, 1993; Pascarella & Terenzini, 1999, 2005;
Sax, 2000). Furthermore, this study relied on students’ self-reported civic behaviors, attitudes, and values. Future research may incorporate independent measures of students’ civic behavior
(e. g., objective tracking records of a student’s volunteer activities by a university office) to explore whether students’ self-reported civic attitudes and values are concurrent with their independent behavioral measures. 199
Third, this dissertation used an instrument that contains an impressive number of variables attempting to capture a great deal of information. As mentioned in Chapter III, The
Survey, developed by a national team of researchers, has been pilot-tested on multiple campuses.
While it has demonstrated relatively strong evidence of reliability and validity, some revisions to the instrument might be considered. Future researchers using this instrument need to address the
following issues. To begin with, the number of outliers and extreme observations identified
during the analyses and the enormous task of data-screening implies that the instrument could
benefit from being shortened. The Survey, containing a total of 295 items, is much longer than
any other major national surveys assessing college students. While the large number of variables
might generate data on a wide range of environmental factors and outcomes, The Survey appears
endless for students to complete, which, to a certain extent, might potentially compromise the
quality of their self-reports, as indicated from the violations of equal variance assumptions in
several analyses reported in this dissertation. Survey respondents, becoming impatient or bored
with the length of The Survey, might rush through the items or randomly respond to them without seriously thinking about each question. Although carefully implemented data screening strategies may help remedy this problem, future researchers might consider using a more concise version of The Survey.
In addition, certain redundant variables need to be dropped from the instrument. More specifically, under Question 4 (containing items asking about use of time during a typical week), items 4f (Working for pay), 4g (Volunteer work), and 4h (Student clubs/groups) appear in a conceptually redundant way under Question 5 (containing items asking about level of involvement in various co-curricular activities), though worded in a slightly different way, e. g.,
5g (Student government, as one indicator of joining student clubs/groups), 5i (Religious clubs 200 and activities, as one form of student clubs/group), 5j (Ethnic/cross-cultural activities, clubs, as one type of student clubs/group), 5land 5m (Work study or work on-campus and working off- campus; both could be working for pay), 5o and 5p (One-time and on-going community service; both could be understood as volunteer work). It is recommended that Question 4 and Question 5 be combined in the future administration of The Survey, using the uniform rating scale 1=Not at all involved; 2=Somewhat involved; 3=Involved; 4=Very involved and dropping items asking students to report hours spent. Essentially, one’s level of involvement in a certain activity is reflected by both the quantity and quality of the time spent on it. In addition, literature suggests that items asking students to report exact hours spent on various activities have poor reliability.
Altogether, some redundancy might serve the need for monitoring consistency of response; the trade-off seems to come at the expense of an instrument that is less parsimonious than it could be.
Lastly, additional evidence needs to be reported and monitored concerning the construct validity of this instrument. Although most of the items on which factor analyses were performed in this dissertation showed moderately strong presence of construct validity, a few factor analyses showed that a relatively higher percentage of residuals exceeded the .05 criterion. This might be caused by the number of outliers and extreme observations not recoded or eliminated, or might arise from the design of the items in the instrument itself. Factor analyses suggest that the following variables should be carefully examined, depending on additional evidence reported by similar subsequent studies: 1g (Learning more about yourself), 7b (Talked about current news events), 9j (When I discover new ways of understanding things, I feel even more motivated to learn), 10j (Appreciation of art, music, and drama), 13a (I can find adequate quiet study space available in my residence environment), and 17f (I believe I have responsibilities to my 201
community). Each of these items could be reworded, replaced, or dropped in future
administrations of this instrument to improve its construct validity.
Fourth, this dissertation utilized quantitative data to generate information focusing on
central tendencies. How RLC experiences shape students’ levels of civic engagement remains
largely unknown. Qualitative studies could be conducted to afford a more in-depth understanding
of the unique experiences of RLC participants and to capture the nuances of their growth and
change in relation to this outcome. Indeed, stories of different students from various types of
RLCs might serve to unveil the mysteries of their development pertaining to this outcome. Such
qualitative approaches might produce another benefit: It may enrich our understanding of the
dimensions of civic engagement and feed into a subsequent and better-constructed quantitative
instrument.
Finally, in terms of research design, this dissertation is essentially a comparative- correlational study. Impact of RLC participation was approximated by comparing mean scores and identifying various predictors. Given that the study did not involve a pre-test or random
assignment, readers should not draw causal inferences from the findings. The data analysis
methods used here are not sufficiently rigorous to determine the net effects of RLC participation
on students’ levels of civic engagement, given that other potential sources of influences—
conventional, or even non-college influences, e. g., parents’ civic values, were not controlled for
and might affect the outcome measures. In particular, given that ANOVAs were inappropriate, I was unable to control for students’ pre-college perceptions. In other words, although this present study used the word “impact,” as an extensive body of literature does, to describe the relationship between participation in an RLC and students’ levels of civic engagement, its research design does not differentiate between the effects that are entirely due to participation in 202
an RLC (net effects) and those that are due to other influences. The hierarchical regression
analyses performed on the RLC sample only afford a basis for identifying the most reliable
predictors for these RLC students’ self-reported levels of civic engagement. The net effects
contributed by the environmental factors above and beyond students’ pre-college characteristics
are supposedly attributed to their unique RLC experience. It is possible that, depending on the
degree of structure and intensity of an RLC program, some environmental factors might not be uniquely present in that RLC. In other words, students’ self-reported gains, growth, and beliefs during their participation in the RLC in the first year of college is not the same thing as gains and growth exclusively attributed to their participation in that RLC.
Future researchers might consider conducting analyses of covariance (ANCOVAs) to achieve this purpose of estimating the net effects of RLC participation on this outcome. Future research might also pull out the significant predictors and conduct a path analysis to examine the dynamic interplay among those predictors. By specifying the direct and indirect positive/negative relationships among variables, such an analysis may allow RLC educators to better understand the sequencing of causal interventions and factors, providing further guidance in designing program components.
Concluding Thoughts
The RLC, as an alternative residential model, has become a significant feature of contemporary undergraduate education reform on American college and university campuses.
An increasing number of institutions are employing this model as a strategy to address a broad range of challenging problems and elusive outcomes. The present study contributes some empirical evidence, though not compelling, affirming the worth of such programs in shaping one important educational outcome—civic engagement. It seems reasonable then to suggest that 203
institutions could benefit greatly from continuing their investment in such facilities that can serve students’ interests.
It is true that RLC students’ motivational factors undoubtedly play an important part in shaping such outcomes. Despite that, however, institutional commitment to maximizing student learning and growth experiences can be reinforced through offering such opportunities to students who come to campus with high expectations for what they will encounter. Indeed,
innovative programs such as RLCs represent a positive direction for American higher education
to pursue in setting higher expectations for student learning and development. In particular,
RLCs, as a potentially powerful and engaging form of learning, will serve well the emerging
Millennial generation of students, who are often characterized by their inclinations for active
engagement in diversity, service, building campus community, and making a difference to the
community (Coomes & DeBard, 2004). To conclude, it appears, at the very least, that such
programs carry much promise for achieving the kinds of educational outcomes deemed
important.
204
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Appendix A. A Copy of the Request Letter to the NSLLP Principal Investigator
Suhua Dong 440 Saddlemire Building Bowling Green State University Bowling Green, OH 43403 November 8, 2004 Karen Kurotsuchi Inkelas, PhD 3214 Benjamin Building University of Maryland College Park, MD 20742
Dear Dr. Karen K. Inkelas,
I am currently a fourth-year doctoral student in the Higher Education Administration Program at Bowling Green State University (BGSU). I am writing to request your permission to use a portion of the data which you and your collaborators collected through the Web-based 2004 Residence Environment Survey in March 2004. Specifically, I intend to use the requested data for my dissertation that proposes to examine the impact of participating in residential learning communities on students’ self-reported level of civic engagement in four-year, public, Midwest universities. I was wondering if I could access data from 6 Midwest institutions that fall under this category. Given that BGSU has approved my use of its data, would you please select another 5 Midwest institutions with the largest number of total responses? I also hope that you can link the data collected through another instrument—the Follow-up Program Questionnaire which you administered to the primary contacts at these institutions in May 2004—with the extracted Survey data.
If you grant my request, I recommend that in the dataset, you strip those variables that would either compromise the identities of the individual schools (e. g., school number) or the confidentiality of respondents themselves (e. g., student ID). However, I was hoping that you could allow me to identify these six schools as an aggregate group.
I understand the inconvenience I will cause you in creating the merged file. If I can be of any assistance in the dataset merge, please feel free to ask me. I am also ready to provide financial resources entailed in the data merge. If you have any questions regarding my proposed study, you may contact me at 419-372-9057 (E-mail address: [email protected] ) or my advisor—Dr. Carney Strange, at 419-372-7388 (E-Mail address: [email protected]). I would be happy to provide any additional information needed.
I appreciate your consideration of my request and look forward to hearing from you.
Sincerely,
Suhua Dong
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Appendix B. The 2004 Residence Environment Survey (Sections and questions that were not used in the dissertation were not included here.)
YOUR PERCEPTIONS BEFORE ENROLLING IN COLLEGE
Question 1. Thinking back to before you started college, what activities did you think were going to be very important to you during college? (Circle one response for each.)
1 = Not at all important 3 = Important 2 = Somewhat important 4 = Very important
1a. Participating in extra-curricular activities 1b. Participating in volunteer or community service activities 1c. Getting to know people from backgrounds different than your own 1d. Learning about cultures different from your own 1e. Discussing ideas and intellectual topics with other students 1f. Getting to know your professors outside of class 1g. Learning more about yourself 1h. Finding your residence hall to be academically supportive 1i. Finding your residence hall to be socially supportive 1j. Drinking alcohol during social occasions
Question 2. Looking back to before you started college, how confident were you that you would be successful at the following: (Circle one response for each.)
1 = Not at all confident 3 = Confident 2 = Somewhat confident 4 = Very confident
2a. Handling the challenge of college-level work 2b. Feeling as though you belong on campus 2c. Analyzing new ideas and concepts 2d. Applying something learned in class to the “real world” 2e. Enjoying the challenge of learning new material 2f. Appreciating new and different ideas, beliefs 2g. Developing your own values and beliefs 2h. Gaining skills in working with others 2i. Growing and developing academically 2j. Making a difference in the community in which you live 2k. Being satisfied with your college experience
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YOUR EXPERIENCES IN COLLEGE
Question 4. During the past year, how much time did you spend during a typical week doing the following activities? (Circle one response for each.)
1=None; 2=1 to 5 hours; 3=6 to 10 hours; 4=11 to 15 hours; 5=16 to 20 hours; 6=21 + hours
4a. Attending classes 4b. Studying/doing homework 4c. Socializing with friends 4d. Exercising/sports 4e. Partying 4f. Working (for pay) 4g. Volunteer work 4h. Student clubs/groups 4i. Watching TV alone 4j. E-mail or instant messaging 4k. Playing video/computer games
Question 5. During the past year, how involved are/were you in any of the following activities? (Circle one response for each.)
1 = Not at all involved 3 = Involved 2 = Somewhat involved 4 = Very involved
5a. Fraternity/sorority 5b. Service fraternity/sorority 5c. Marching band 5d. Arts/music performances & activities 5e. Intramural or club sports 5f. Varsity sports 5g. Student government 5h. Political or social activism 5i. Religious clubs and activities 5j. Ethnic/cross-cultural activities, clubs 5k. Media activities (e.g., newspaper, radio) 5l. Work-study or work on-campus 5m. Work off-campus 5n. Armed Services ROTC 5o. One-time community service activity 5p. Ongoing community service activity 5q. Other (specify:
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Question 7. During interactions with other students outside of class, how often have you done each of the following during the current school year? (Circle one response for each.)
1 = Never 3 = A few times a month 2 = A few times a semester 4 = Once or more a week
7a. Discussed something learned in class 7b. Talked about current news events 7c. Talked about different lifestyles/customs 7d. Shared your concerns about classes and assignments 7e. Held discussions with students whose personal values were very different from your own 7f. Discussed major social issues such as peace, human rights, and justice 7g. Talked about your future plans and career ambitions 7h. Held discussions with students whose religious beliefs were very different from your own 7i. Discussed your views about multiculturalism and diversity 7j. Studied in groups 7k. Held discussions with students whose political opinions were very different from your own
Question 8. About how often have you done each of the following during the current school year? (Circle one for each.)
1 = Never 3 = A few times a month 2 = Once to a few times a semester 4 = Once or more a week
8a. Asked your instructor for information related to a course you were taking 8b. Visited informally with an instructor before or after class 8c. Made an appointment to meet with an instructor in his/her office 8d. Communicated with your instructor using e-mail 8e. Visited informally with an instructor during a social occasion (e.g., over coffee or lunch) 8f. Discussed your career plans and ambitions with an instructor 8g. Discussed personal problems or concerns with an instructor 8h. Went to a cultural event (e.g., concert or play) with an instructor or class 8i. Worked with an instructor on an independent project 8j. Worked with an instructor involving his/her research
Question 9. Please indicate the level to which you agree with the following statements. (Circle one response for each.)
1 = Strongly disagree 3 = Agree 2 = Disagree 4 = Strongly agree
9a. I frequently question or challenge professors' statements and ideas before I accept them as "right" 9b. I prefer courses in which the material helps me understand something about myself 9c. I prefer courses requiring me to organize and interpret ideas over courses that ask me only to remember facts or information ... 227
9d. There have been times when I have disagreed with the author of a book or article that I was reading 9e. I consider the best teachers to be those who can tie things learned in class to things that are important to me in my personal life 9f. I enjoy discussing issues with people who don’t agree with me 9g. I try to explore the meaning and interpretations of the facts when I am introduced to a new idea 9h. A good way to develop my own opinions is to critically analyze the strengths and limitations of different points of view 9i. I have become excited about a specific field or academic major as a result of taking a course in that field 9j. When I discover new ways of understanding things, I feel even more motivated to learn 9k. When I don't understand something in a course, I work at it until I do 9m. Something I learned in one class helped me understand something from another classes 9n. I try to look at everybody’s side of a disagreement before I make a decision 9o. I enjoy the challenge of learning complicated new material 9p. I prefer reading things that are relevant to my personal experiences 9q. I often have discussions with other students about ideas or concepts presented in classes 9r. Learning is important to me because it will give me greater control over my life 9s. For me, one of the most important benefits of a college education is a better understanding of myself and my values 9t. I enjoy courses that are intellectually challenging I have applied material learned in a class to other areas in my life, such as in my job, internship, interactions with others
Question 10. In thinking about how you have changed during college, to what extent do you feel you have grown in the following areas? (Circle one response for each.)
1 = Not grown at all 3 = Grown 2 = Grown somewhat 4 = Very much grown
10a. Becoming more aware of different philosophies, lifestyles, and cultures 10b. Developing your own values and ethical standards 10c. Understanding yourself and your abilities, interests, and personality 10d. Improving your ability to get along with people different than yourself 10e. Ability to put ideas together and to see relationships between ideas 10f. Ability to learn on your own, pursue ideas, and find information you need 10g. Appreciation of racial/ethnic differences 10h. Ability to critically analyze ideas and information 10i. Learning more about things that are new to you 10j. Appreciation of art, music, and drama 10k. Gaining a broad general education about different fields of knowledge 10l. Openness to views that you oppose 10m. Ability to discuss controversial issues 10n. Motivation to further explore ideas presented in class
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YOUR RESIDENCE HALL ENVIRONMENT
Question 12. How often do you utilize the following resources or participate in the following activities inside your residence hall? (Circle one response for each.)
1 = Never 3 = A few times a month 2 = A few times a semester 4 = Once or more a week 9 = Not available in my residence hall
12a. Computer labs 12b. Academic advisors 12c. Peer counselors 12d. Interactions with professors 12e. Seminars and lectures 12f. Peer study groups 12g. Social activities 12h. Career workshops 12i. Community service projects
Question 13. Consider how well each of the following statements describes your residence hall environment. (Circle one response for each.)
1 = Strongly disagree 3 = Agree 2 = Disagree 4 = Strongly agree
13a. I can find adequate quiet study space available in my residence environment 13b. I find that students in my residence environment have an appreciation for people from different races or ethnic groups 13c. Students in my residence environment are concerned with helping and supporting one another 13d. Life in my residence environment is intellectually stimulating 13e. I find that students in my residence environment have an appreciation for people with different sexual orientations 13f. I would recommend this residence environment to a friend 13g. I find that students in my residence environment have an appreciation for people from different religions 13h. I see students with different backgrounds having a lot of interaction with one another in my residence environment 13i. I have enough peer support in my residence environment to do well academically 13j. Most students in my residence environment study a lot 13k. I think the majority of students in my residence environment think academic success is important 13l. My residence environment clearly supports my academic achievement 13m. I think the staff in my residence environment spend a great deal of time helping students succeed academically 13n. I think it’s easy for students to form study groups in my residence environment 229
PERCEPTIONS OF DIVERSITY
Question 14. To what extent have you done the following with students from a racial/ethnic group that is different from your own? (Circle one response for each.)
1 = Not at all 3 = A lot 2 = A little 4 = All of the time
14a. Studied together 14b. Shared a meal together 14c. Were roommates 14d. Attended social events together 14e. Had intellectual discussions out of class 14f. Dated someone 14g. Shared personal feelings and problems 14h. Participated in extracurricular activities together (e.g., clubs) 14i. Had meaningful discussions about race relations outside of class 14j. Had guarded, cautious interactions 14k. Had tense, or even hostile interactions
Question 15. Please rate the extent to which each of the following is descriptive of your college campus. (Circle one response for each.)
1 = Little or none 3 = Quite a bit 2 = Some 4 = A great deal
15a. Respect by White professors for students of color 15b Dating between students of color and white students on campus 15c. Inter-racial tension in the residence halls 15d. Friendship between students of color and White students 15e. Campus commitment to develop an environment that is conducive to the success of students of color 15f. Separation among students from different racial/ethnic backgrounds on campus 15g. Trust and respect between students from different racial/ethnic backgrounds 15h. Interaction between students of color and White students 15i. Racial conflict on campus
Question16. Please indicate the extent to which you agree or disagree with the following statements. (Circle one response for each.)
1 = Strongly disagree 3 = Agree 2 = Disagree 4 = Strongly agree 9 = Don’t know/Never thought about this
16a. Since coming to college, I have learned a great deal about other racial/ethnic groups 16b. I have gained a greater commitment to my racial/ethnic identity since coming to college 230
16c. My campus’s commitment to diversity fosters more division among racial/ethnic groups than intergroup understanding 16d. Since coming to college, I have become aware of the complexities of inter-group understanding 16e. My relationships with students from different racial/ethnic backgrounds during college have been positive 16f. I think this campus’s focus on diversity puts too much emphasis on the differences between racial/ethnic groups 16g. My social interactions on this campus are largely confined to students of my race/ethnicity 16h. At times, it is important to be with people of my own racial/ethnic group for the chance to be myself
CITIZENSHIP PERCEPTIONS
Question 17. Please indicate your agreement or disagreement with the following items. (Circle one response for each.)
3 = Neutral 1 = Strongly disagree 4 = Agree 2 = Disagree 5 = Strongly agree
For the items that refer to a “community,” please refer to the community to which you feel the most affiliated, whatever that may be.
17a. I understand the extent to which the groups I participate in contribute to the larger community 17b. It is important to me that I play an active role in my communities 17c. I volunteer my time to the community 17d. I believe my work has a greater purpose for the larger community 17e. There is little I can do that makes a difference for others 17f. I believe I have responsibilities to my community 17g. I give time to making a difference for someone else 17h. Ordinary people can make a difference in their community 17i. I work with others to make my communities better places 17j. I have the power to make a difference in my community 17k. I am willing to act for the rights of others 17li. I participate in activities that contribute to the common good 17m. I believe I have a civic responsibility to the greater public 17n. I value opportunities that allow me to contribute to my community
OVERALL SATISFACTION WITH COLLEGE
Question 24. Indicate the extent to which you agree or disagree with the following statements. (Circle one response for each.)
1 = Strongly disagree 3 = Agree 2 = Disagree 4 = Strongly agree 231
9 = Don’t know/Never thought about this
14a. I feel comfortable on campus.. 14b. My college/university is supportive of me 14c. If I had to do it over again, I would choose the same college or university 14d. I feel that I am a member of the campus community 14e. I feel a sense of belonging to the campus community
BACKGROUND INFORMATION
Question 27. What is your gender? (Circle one.)
1. Male 2. Female 3. Transgendered
Question 28. Please indicate your sexual orientation. (Circle one.)
1. Bisexual 2. Gay or Lesbian 3. Heterosexual
Question 29. Please circle the one response that you think best applies to your race/ethnicity. (Circle one.)
1. African American/Black (not of Hispanic origin) 2. Asian or Pacific Islander (includes the Indian sub-continent) 3. American Indian or Alaskan Native 4. Hispanic/Latino (Spanish culture or origin) 5. White/Caucasian (Persons not of Hispanic origin, having origins in any of the original peoples of Europe, North Africa, or the Middle East) 6. Multi-racial or multi-ethnic 7. Race/ethnicity not included above
Question 30. Please indicate your citizenship and/or generation status. (Circle one.)
1. Your grandparents, parents, and you were born in the U.S. 2. Either or both your parents and yourself were born in the U.S. 3. You were born in the U.S., but at least one of your parents was not 4. You are a foreign born, naturalized citizen 5. You are a foreign born, resident alien/permanent resident 6. You are on a student visa
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Question 31. What is your current religious affiliation? (Circle one.)
1. None 4. Hindu
2. Buddhist 5. Jewish 3. Christian 6. Muslim (e.g., Catholic, Protestant, etc.) 7. Other: ______
Question 32. What is the highest level of education completed by one or both of your parent(s) or guardian(s)? (Circle one in each column, if applicable.)
Father or Mother or Male Guardian Female Guardian
1. Don’t know 2. High school or less 3. Some college 4. Associate’s degree 5. Bachelor’s degree 6. Master’s degree 7. Doctorate or professional degree (JD, MD, PhD)
Question 33. What is your best estimate of your parents’ total income last year? Consider income from all sources before taxes. (Circle one.)
1. 29,999 or less 2. Between 30,000 and 49,999 3. Between 50,000 and 74,999 4. Between 75,000 and 99,999 5. 100,000 or higher
HIGH SCHOOL INFORMATION
Question 34. What were your average grades in high school? (Circle one.)
1. A+ or A 2. A- or B+ 5. C or C- 3. B 6. D+ or lower 4. B- or C+ 7. No high school GPA
Question 40. Which living-learning program are you currently participating in? (Circle one response only.) (Responses were customized for each participating institution) 233
Appendix C1
Summary of Principal Component Analyses (C=Component; V=Variable; Residuals=Size of residuals exceeding the .05 criterion) ______Names of C Total variance explained by the model Variance explained by each C Residuals (%) (%) (%) ______Question 1 65.76 34.0
Component #1: (Pre-college) Importance of growth in understanding diversity and interacting with peers 21.62 Component #2: (Pre-college) Importance of academic and social support in residence halls 16.97 Component #3: (Pre-college) Importance of participating in co-curricular activities and interacting with faculty 16.26 Component #4: (Pre-college) Importance of drinking alcohol during social occasions 10.91 ------Question 2 56.44 44.26
Component #5: (Pre-college) Confidence in handling new intellectual challenges and appreciating diversity 29.81 Component #6: (Pre-college) Confidence in academic and personal growth and satisfaction 26.64 ------Question 4 54.34 54.0
Component #7: Time spent on socializing or recreational activities 16.24 Component #8: Time spent on academics work 14.22 Component #9: Time spent on media-related communications or entertainments 13.44 Component #10: Time spent on work or student clubs 10.44 ______
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Appendix C1 (Continued)
Summary of Principal Component Analyses (C=Component; V=Variable; Residuals=Size of residuals exceeding the .05 criterion) ______Names of C Total variance explained by the model Variance explained by each C Residuals (%) (%) (%) ______Question 7c 54.78 40.0
Component #11: Frequency of diverse peer interactions 33.47 Component #12: Frequency of academic and career-related peer interactions 21.30 ------Question 8 54.66 46.0
Component #13: Academic and career-related interaction with faculty 24.37 Component #14: Personal and cultural interactions with faculty 16.27 Component #15: Research-related interactions with faculty 14.02 ------Question 9 92.33 35.5
Component #16: Enjoyment of integrated learning, intellectual challenge, 28.81 and application of knowledge Component #17: Enjoyment of integration of academic learning and self-discovery 22.24 Component #18: Enjoyment of multiplicity of thinking 20.71 Component #19: Enjoyment of questioning others’ opinions and going 20.57 beyond dualistic thinking ______
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Appendix C1 (Continued)
Summary of Principal Component Analyses (C=Component; V=Variable; Residuals=Size of residuals exceeding the .05 criterion) ______Names of C Total variance explained by the model Variance explained by each C Residuals (%) (%) (%) ______Question 10d 81.02 38.78
Component #20: Intellectual growth 28.02 Component #21: Personal growth 27.20 Component #22: Growth in understanding of and appreciation for diversity 25.80 ------Question 12 42.56 51.22
Component #23: Using academic advising and faculty resources in halls 22.98 Component #24: Using peer and co-curricular resources in halls 19.57 ------Question 13 69.21 34.69 Component #25: Academic support in the residence environment 37.92 Component #26: Social support for diverse peer interactions in the residence environment 31.29 ------Question 14 72.52 34.42
Component #27: Intellectual, social, and personal interactions with peers from a different racial/ethnic group 44.93 Component #28: Absence of unfriendly interactions with peers from a different racial/ethnic group 16.78 Component #29: Intimate interactions with peers from a different racial/ethnic group 10.81 ______
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Appendix C1 (Continued)
Summary of Principal Component Analyses (C=Component; V=Variable; Residuals=Size of residuals exceeding the .05 criterion) ______Names of C Total variance explained by the model Variance explained by each C Residuals (%) (%) (%) ______Question 15 57.44 46.34
Component #30: Relationship between students from different racial backgrounds 25.22 Component #31: Absence of racial tensions in residence halls/on-campus 16.26 Component #32: Campus commitment to the success of students of color 15.97 ------Question 16 51.41 53.13
Component #33: Gains in inter-racial understanding 22.87 Component #34: Scope and quality of one’s racial interactions with peers 15.99 Component #35: Campus commitment to racial diversity 12.54 ------Question 17 87.70 31.63
Component #36: Perceptions on volunteerism and service to the community 36.57 Component #37: Sense of responsibility to the common good 27.36 Component #38: Sense of civic empowerment 23.77 ______