.m
. .m
L. 2.5.; .
. s...

.0 .
... 2.;
. . I).
.T...r...,._li

_u..

J
. am»
a. 2.16....” .
.9.

..
. w.)

2 .fiuyw.n§m.fiwu&m.p
t .... 5 ....
1 . . r“

 

1.21.... .3: .
a... 31.

Hurrah-n.
why-mm. .
a...

I;

 

...-.... .3»

fig?! v

. -. flew-n. .«uvi
$.52.

 

’3:
b .0}!
.. ha_.u...y...:.mw-fll
1 . ”..., . . @1237 HEW»???
'I

 

.- .l !

[(29.5]..ka - - .
99!? 3.3%.0ICWI'JE‘U7 AW . .

._ - . .-..

2...... 11.- 2.... 3333.23“. 3......”

11,32?"

2,
V???

 

LIBP 1‘ W I WWW“I“\“Hililil‘ilil\IWIHHHIHN

Michigan mm..- 293 083
University

 

 

This is to certify that the

dissertation entitled

ADJUSTMENT TO COLLEGE: THE CONTRIBUTION
OF A LIVING-LEARNING PROGRAM FOR SCIENCE
AND ENGINEERING STUDENTS

presented by

Cynthia K. Helman

has been accepted towards fulfillment
of the requirements for

 

 

Ph.D. degree in Educational Administration
l -.

X/W Wm,

a r professor

Date 3/23/99

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

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

 

I DATE DUE DATE DUE DATE DUE

 

-. 3N 12 9 2005

 

 

 

 

'ECM 9 2006

 

 

 

 

 

 

 

 

 

 

 

 

 

1/” WWW“

 

ADJUSTIVIENT TO COLLEGE: THE CONTRIBUTION OF A LIVING-LEARNING
PROGRAM FOR SCIENCE AND ENGINEERING STUDENTS

By

Cynthia K. Helman

A DISSERTATION

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

DOCTOR OF PHILOSOPHY
Department of Educational Administration

1999

ABSTRACT

ADJUSTMENT TO COLLEGE: THE CONTRIBUTION OF A LIVING-LEARNING
PROGRAM FOR SCIENCE AND ENGINEERING STUDENTS

By

Cynthia K. Helman

This study examined the contribution of a residential program on adjustment to college
and fall semester grade point average for 174 first year science and engineering students.
Specifically, social and academic aspects of the living-learning program were examined to
determine their relationship with academic adjustment, social adj ustment, full adjustment, and
fall semester grade point average. The Student Adaptation to College Questionnaire was used to
measure student adjustment to college, and a survey designed for this study was used to measure
students' levels of involvement with the academic and social aspects of the program. The data
were analyzed using t-tests and multiple regression.

None of the academic or social aspects directly related to the living-leaming program
were identified by multiple regression as significant predictors of adjustment or fall GPA.
Significant predictors of academic adjustment were knowing one's roommate prior to college
attendance and the grade received for the seminar class required as a part of the living—leaming
program. The number of hours per week students spent in class and being satisfied with the
roommate relationship were significant predictors of social adjustment. Significant predictors of
full adjustment were knowing one's roommate prior to college attendance, the number of hours
per week spent in class, and being female. Predicted grade point average and the grade for the
seminar class were significant predictors of fall semester grade point average. Limitations of the

study were discussed with implications for both further research and professional practice.

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................. iii
LIST OF FIGURES ............................................................................................. v
CHAPTER 1

INTRODUCTION

Introduction and Statement of the Problem .......................................................... 1
Purpose of the Study ............................................................................................ 8
Research Questions ............................................................................................. 8
Methodology ....................................................................................................... 9
Significance of the Study ................................................................................... 10
Limitations ........................................................................................................ 1 1
Organization of the Dissertation ........................................................................ 12
CHAPTER 2

REVIEW OF THE LITERATURE

Introduction ....................................................................................................... 1 3
Attrition from Higher Education ........................................................................ 13
Tinto’s Model of Longitudinal Departure .......................................................... 18
Transition to College ......................................................................................... 22
Adjustment to College ....................................................................................... 23
Research about Student Adjustment to College .................................................. 25
Summary ........................................................................................................... 33
CHAPTER 3

METHODOLOGY

Participants ........................................................................................................ 37
Instruments ........................................................................................................ 38
Data Collection .................................................................................................. 43
Data Analysis .................................................................................................... 44
Hypotheses ........................................................................................................ 44
CHAPTER 4

FINDINGS

Description of the Sample .................................................................................. 46
Adjustment Scores for Respondents .................................................................. 48
Fall Semester Grade Point Averages for Respondents ........................................ 52
ROSES Experiences Survey Data for Respondents ............................................ 55
Results .............................................................................................................. 62
Academic Adjustment ....................................................................................... 63
Social Adjustment ............................................................................................. 68
Full Adjustment ................................................................................................. 73
Fall Semester Grade Point Average ................................................................... 79

Summary of Bivariate Analyses ......................................................................... 84

Multiple Regression Analysis ............................................................................ 86
Academic Adjustment ....................................................................................... 89
Social Adjustment ............................................................................................. 90
Full Adjustment ................................................................................................. 91
Fall Semester Grade Point Average ................................................................... 92
Summary ........................................................................................................... 93
CHAPTER 5
SUMMARY, DISCUSSION, AND RECOMMENDATIONS
Summary and Discussion .................................................................................. 97
Implications for Practice ................................................................................... 106
Limitations of the Study ................................................................................... 109
Recommendations for Further Research ........................................................... 1 10
APPENDICES
Appendix A: Science and Engineering Baccalaureate Degree Programs

Michigan State University .......................................................... 113
Appendix B: Survey Item Clusters .................................................................... 115
Appendix C: ROSES Experiences Survey ......................................................... 118
Appendix D: Correlation Matrix for Variables and Outcomes ........................... 123
Appendix E: UCRIHS Approval Letter ............................................................ 124
Appendix F: Letter to Western Psychological Services ..................................... 125
Appendix G: Letter to ROSES Students ........................................................... 126
BIBLIOGRAPHY ............................................................................................ 127

LIST OF TABLES

Table 1 - Components and Measures of ROSES Experiences ............................. 42
Table 2 - Distribution of Respondents by Gender, Ethnicity, and College

of Enrollment ..................................................................................... 47
Table 3 - Analysis of Variance of Predicted GPA by Minority Group ................. 48
Table 4 - Descriptive Statistics for Adjustment Scores ....................................... 49
Table 5 - Correlation Among Academic, Social, and Full Adjustment ............... 49
Table 6 - T-tests of Means of Adjustment Scores by Gender .............................. 50
Table 7 - T-Tests of Means of Adjustment Scores by Ethnicity .......................... 50
Table 8 - T-Tests of Means of Adjustment Scores by College ........................... 51
Table 9 - T-Tests of Means of Adjustment Scores by Predicted

Grade Point Average .......................................................................... 52
Table 10 - T-Tests of Means for Grade Point Averages by Gender .................... 53
Table 11 — T-Tests of Means for Grade Point Averages by Ethnicity .................. 53
Table 12 — T-Tests of Means for Grade Point Averages by College .................... 54
Table 13 - T-Tests for Fall Semester Grade Point Averages by

Predicted GPA .................................................................................. 55

Table 14 - Descriptive Statistics for ROSES Components .................................. 57
Table 15 - Means of ROSES Components by Gender ........................................ 58
Table 16 - Means of ROSES Components by Ethnicity ...................................... 59
Table 17 - Means of ROSES Components by College ........................................ 60
Table 18 - Means of ROSES Components by Predicted GPA ............................. 61

Table 19 - T-Tests for Participation with Academic Components
and Academic Adjustment ................................................................ 65

Table 20 - T-Tests for Participation with Social Components
and Academic Adjustment ................................................................ 68

Table 21 - T-Tests for Participation with Social Components
and Social Adjustment ...................................................................... 71

Table 22 - T-Tests for Participation with Academic Components
and Social Adjustment ...................................................................... 73

Table 23 - T-tests for Participation with Academic Components
and Full Adjustment ......................................................................... 76

Table 24 - T-tests for Participation with Social Components
and Full Adjustment ......................................................................... 79

Table 25 - T-tests for Participation with Academic Components
and Fall Semester GPA ..................................................................... 81

Table 26 - T-tests for Participation with Social Components
and Fall Semester GPA ..................................................................... 84

Table 27 - Summary of Relationships Between Components
and Outcomes .................................................................................. 86

Table 28 - Regression Coefficients for Model Predicting
Academic Adjustment ...................................................................... 90

Table 29- Regression Coefficients for Model Predicting
Social Adjustment ............................................................................ 91

Table 30 - Regression Coefficients for Model Predicting

Full Adjustment ............................................................................... 92
Table 31 - Regression Coefficients for Model Predicting Fall GPA .................... 93
Table 32 - Summary of Relationships Between Predictors and Outcomes .......... 96
Table 33 — Correlation Matrix for Variables and Outcomes ............................... 123

LIST OF FIGURES

Figure 1 — Tinto’s Model of Longitudinal Departure ......................................... 20

Figure 2 -— The Contribution of a Living—Learning Program on
Academic Adjustment, Social Adjustment, and Fall GPA ................ 34

Chapter 1
INTRODUCTION AND STATEMENT OF THE PROBLEM
Going to College

Leaving home to attend college can be a very exciting time. For some students,
going to college is the next logical and expected step after high school. For other
students, college attendance signifies a somewhat uncomfortable departure from the usual
norms and expectations of their communities and families. For all students, however, the
first few months of college is a time of transition as students manage the separation from
previous relationships and communities and begin to explore the norms and expectations
of the new culture. It is during this time that new students seek to learn the unique
intellectual and social behaviors of the college environment.

The transition from high school or work to college is an exceedingly

complex phenomenon. The nature and dynamics of the process vary

according to the student's social, family, and educational background;

personality; educational and occupational orientations and aspirations; the

nature and mission of the institution being attended; the kinds of peers,

faculty, and staff members encountered; the purpose and nature of those

encounters, and the interactions of all these variables. The process is a

highly interrelated, web-like series of interpersonal, academic, and

organizational pulls and pushes that shape student learning (broadly

conceived) and persistence. (Terenzini, Allison, Millar, Rendon, Upcrafi,

Gregg, & Jalomo, 1992, p. 39-40)

Research supports that the first year of college is a critical time for new student
adjustment (Christie & Dinham, 1991; Noel, 1985; Tinto, 1993; Upcraft & Gardner,
1989). Tinto (1993) cites data from the American College Testing Program (ACT) for
the fall 1990 entering class in which first-year attrition from four-year institutions was an

average of 26.8%. Of all institutional departures from four-year institutions, 53.3% occur

during or afier the first year.

Much of the research suggests that the first six weeks are the most important time
for new students. There is evidence that experiences in this early period determine
students’ likelihood of persistence to the second semester and beyond (Nelson, Scott, &
Bryan, 1984; Noel, 1985; Tinto, 1988). In the transition to college, many students
experience confusion, ambiguity, and uncertainty. The resulting stress may be
overwhelming for some and lead to their withdrawal from college. Tinto (1993) states:

Though most students are able to cope with the problems of transition,

many voluntarily withdraw from college very early in their first academic

year, less from an inability to become incorporated in the social and

academic communities of the college than from an inability to withstand

the stresses that such transitions commonly induce. (p. 98)

The focus of this study is student adjustment to college as situated in the research
on college student attrition. The theoretical perspective that is most instructive is the
longitudinal model of college student departure as proposed by Tinto (1975). Van
Gennep’s (1960) framework of transitions is also helpful in highlighting the importance
of the adjustment process in becoming integrated into a new environment. A review of
college student adjustment research presents the ways in which others have examined
student adjustment to college. Finally, the role of institutional strategies in promoting
student adjustment to college will be explored.

Tinto’s Longitudinal Theory of Departure

Tinto (1975) supported the work of Spady (1970; 1971) in asserting the

importance of both the academic and social systems of the university in the assimilation

or integration of students into the environment. Although Tinto recognized pre-entry

characteristics such as prior academic achievement and family background as factors in

student persistence, he focused on what happened to students after they entered college.
Tinto (1975) suggested

that the process of dropout fi'om college can be viewed as a longitudinal
process of interactions between the individual and the academic and social
systems of the college during which a person's experiences in those
systems (as measured by his normative and structural integration)
continually modify his goal and institutional commitments in ways which
lead to persistence and/or varying forms of dropout. (p. 94)

His model emphasizes the distinction between students who are academically dismissed
by the institution and those who voluntary leave the institution, stressing that the majority
of students leave college for non-academic reasons.

Less than 25 % of all institutional departures, nationally, take the form of
academic dismissal. Most departures are voluntary in the sense that they
occur without any formal compulsion on the part of the institution. Rather
than mirroring academic difficulties, they reflect the character of the
individual's social and intellectual experiences within the institution.
Generally, the more satisfying those experiences are felt to be, the more
likely are individuals to persist until degree completion. Conversely, the
less integrative they are, the more likely are individuals to withdraw
voluntarily prior to degree completion. (Tinto, 1993, pp. 49-50)

Transition to College

For many adolescents, going to college is a major life transition. This transition
can be described as simultaneously exhilarating and anxiety-producing; exciting and
overwhelming; stimulating and confiJsing. Feldman and Newcomb (1969) described the
new student in college as

a novice in an unfamiliar social organization, and therefore confronted

with the values, norms, and role stnrctures of a new social system and

various new subsystems. Such an experience usually involves

desocialization (pressures to unlearn certain past values, attitudes, and

behavior patterns) as well as socialization (pressures to learn the new
culture and participate in the new social structure). (p. 89)

All students are challenged by new academic demands; and most students
experience new social situations, a sense of increased independence, and greater freedom
than they had in their previous environment. Those who live in residence halls are also
required to negotiate new peer relationships in an environment quite unlike any they have
previously encountered. For many, this is the first time they will share a room with any
other person; let alone with a person from a different background or with values different
from their own.

The transition to college can be related to the framework proposed by van Gennep
(1960) in his famous work, Rites of Passage. Essentially, van Gennep suggested that
individuals who move from one social situation to another, or fiom one culture to
another, go through a process involving three phases: separation, transition, and
incorporation. Tinto (1988) proposed that individuals moving from high school to
college go through the same three phases.

Student Adjustment to College

According to Baker (1989), adjustment to college is the process of coping with
the multifaceted demands of the new environment. Adjustment is characterized by
separating from the past, learning new norms and behaviors, and becoming a member of
the new environment. This period is often accompanied by feelings of uncertainty,
confusion, and normlessness.

During their first few weeks of college life, freshmen see themselves (and

perhaps more important, are seen by host students, faculty members, and

administrators) more as nameless, faceless, members of a single

undifferentiated social category than at any subsequent time in their
college careers. (Wallace, 1966, p. 94)

Student adjustment to college has been associated with selecting an academic
major (Baker & Siryk, 1986; Smith & Baker, 1987); internal academic locus of control
and self-esteem (Mooney, Sherman, & LoPresto, 1991); having positive relationships
with parents (Lopez, 1991; Rice, 1992); and having parents whose marriage is not
distressed or conflicted (Lopez, Campbell, & Watkins, 1988).

Cooper & Robinson (1988) have suggested that adjustment to college is likely to
be related to factors not only within an individual, but also in the institutional
environment. Social effectiveness (Baker & Siryk, 1983; Christie & Dinham, 1991);
alienation (Baker & Siryk, 1980); and social and intellectual validation (Murguia, Padilla,
& Pavel, 1991; Stoecker, Pascarella, & Wolfle, 1988; Terenzini et al., 1996) are related to
experiences with others in the environment which influence new students’ adjustment to
college.

Institutional Strategies

Colleges and universities have used the research about attrition to develop
policies and strategies to reduce student departure and to assist students in their transition
to college. At some institutions, elaborate predictive models have been developed to
guide admissions decisions. Other institutions have designed retention strategies for
specific groups of students or for the entire campus (Noel, 1985). Orientation programs
have been improved or expanded to last an entire academic term.

Orientation Programs

Orientation programs are one effective strategy many institutions use to introduce

new students to college life. Students attending orientation have been found to have

significantly higher levels of social integration and commitment to the institution than

students not attending orientation, even when background characteristics were taken into
account (Pascarella, Terenzini, & Wolfle, 1986).

Extended orientation programs have taken the form of seminars which may last
from several weeks of the first academic term to the entire semester. These programs
include freshmen seminars, University 101 courses, and College Success seminars.
These programs typically include exercises to promote social interaction, topics such as
time management and study skills, an introduction to support resources, and some
exploration of academic or career topics (Jewler, 1989).

Tinto (1988) suggested that several other kinds of activities (e.g., fraternities,
sororities, extracurricular programs) " may all serve to provide individuals with
opportunities to establish repetitive contact with other members of the institution in
circumstances which lead to the possibility of integration" (Tinto, 1988, p. 446).
Residential Programs

Much research has focused on the relationship between living in residence halls
and college outcomes (see Blimling, 1993; Pascarella, 1991). Living in a residence hall
during the first year of college has been found to relate significantly to positive outcomes
such as persistence, as well as involvement on campus, gains in interpersonal skills,
attitudes, and values (Astin, 1977; Chickering, 1975).

Because of the apparent value of living in a residence hall on campus,

institutions with such facilities might want to study ways to enhance the

normal positive effect of residential living. Such studies should include an

assessment of the effects of roommates, peer groups, living-study

arrangements in the residence halls, programming, and staffing of

facilities. The results might well put institutions in a position to capitalize

still more on the potential value of the residence hall experience. (Astin,
1977,p.160)

Nationally, in the last 20 years, a variety of residential programs have been
designed and implemented with the common purpose of assisting students’ academic and
social adjustment to college. For example, living-learning centers were a hallmark of the
1970’s in student housing. New residence halls were built to include classroom space,
faculty office space, libraries, and other “academic” components. These centers provided
students with opportunities to take classes, interact with faculty, develop relationships
with students in the same field of study, and participate in co-curricular activities which
complemented their academic work. Planned activities integrating curricular and co-
curricular aspects were necessary to achieve maximum benefit from living-learning
centers.

Renewed emphasis on undergraduate education on many campuses in the 19903
has resulted in revitalized efforts to integrate the academic and social components within
the residential environment. In addition, national studies within the past several years
have documented the decline in the number of college students who complete
baccalaureate degrees in science and engineering (Atkinson, 1990). The Residential
Option for Science and Engineering Students (ROSES) at Michigan State University was
developed in 1993 and targets entering students intending to major in a science or
engineering field. The program provides academic and social experiences and is
intended to assist students in their transition to college and to enhance the retention of
students in science and engineering majors.

All students in the ROSES program live in the same residence hall. They are
required to take a one-credit seminar during the fall semester, which includes a weekly

class and co-curricular activities. Faculty and academic staff have primary responsibility

for the weekly class session, while the residence life staff implement co-curricular
seminars and activities which complement the class. Most ROSES students take at least
one other course with other ROSES students. There are tutoring services and special
tutoring and resource rooms in the residence hall. Additionally, academic advisers hold
periodic advising sessions in the residence hall.
Purpose of the Study

The purpose of this study was to determine the relative contribution of the
individual components (required course, relationships with peers, relationships with
academic advisers and instructors, involvement) of the ROSES program in predicting
student adjustment to college. The Fall 1997 cohort of ROSES students were the
participants in the study. Their levels of involvement and participation with the various
components of the ROSES program were examined in relation to their academic, social,
and fill] adjustment to college, as well as their fall semester grade point average.

Research Questions

This study primarily addressed the question of whether components of a semester-
long program combining academic and residential experiences enhance student
adjustment to college. Specifically, this study sought to determine the components of the
residential program (ROSES) that best predicted academic adjustment, social adjustment,
full adjustment, and fall semester grade point average. This study attempted to answer
the following questions:
1. Do specific components of the ROSES program contribute differentially to academic

adjustment, social adjustment, full adjustment, and fall semester grade point average?

2. Which components of the ROSES program make the most significant contributions in
predicting academic adjustment, social adjustment, firll adjustment, and fall semester
grade point average?

Methodology

Instruments

The Student Adaptation to College Questionnaire (Baker & Siryk, 1989) was used
in this study. The Student Adaptation to College Questionnaire (SACQ) asks respondents
to reflect on their adjustment once they are in college. This instrument yields an overall
adjustment score, as well as subscale scores on four facets of adjustment (academic
adjustment, social adjustment, personal-emotional adjustment, and attachment). The
academic and social adjustment subscales were used in this study because the subscales
parallel the academic and social integration components identified by Tinto’s theoretical
model. The full adjustment score was also examined. Several studies have supported the
use of the SACQ as a valid and reliable instrument for measuring college student
adjustment (Baker, 1986; Baker & Siryk, 1986; Cooper & Robinson, 1988; Dahmus,

Bemardin, & Bemardin, 1992; Krotseng, 1992; Mooney et. al., 1991; Smith & Baker,

1987)

Participants were also asked to complete a brief survey about their experiences
during the fall semester. The ROSES Experiences Survey, designed specifically for this
study, assessed study habits, interactions with academic and student affairs staff,

relationships with student peers, and perceptions of the ROSES program.

Collection of Data

The Student Adaptation to College Questionnaire (SACQ) and the ROSES
Experiences Survey were administered to all students enrolled in the ROSES program
during the last two weeks of fall semester, 1997. Surveys were distributed via student
mailboxes in the residence hall for students in the College of Natural Science and the
College of Agriculture and Natural Resources. Students in the College of Engineering
were participating in another study that incorporated this study; thus, the surveys were
distributed during the seminar class.

Demographic data (gender, ethnicity, and college of enrollment), predicted grade
point average, ROSES seminar grades, and fall semester grade point average were
obtained from institutional records.

Data Analysis

Relationships between individual components of the ROSES program and two
sets of outcomes—adjustment to college (academic, social, and fill] adjustment) and fall
semester grade point average—were examined. Regression analysis was utilized to
identify significant predictors of academic adjustment, social adjustment, firll adjustment,
and fall semester grade point average.

Significance of the Study

This study contributes to the literature about institutional strategies which may
influence student adjustment to college. Specifically, the focus of the study was a
residential program for entering science and engineering students and its contribution to
student adjustment. The results of this study may be most significant to science and

engineering students who are entering Michigan State University as they consider

10

programs and services which might assist them in meeting their educational goals.
Students may elect to participate in programs similar to the ROSES program because of
measurable factors which can be communicated to prospective students. These findings
may also be of interest to those concerned about the number of prospective scientists and
engineers. Institutional leaders and program designers may also be interested in these
findings for the improvement of strategies to assist new students.

Student retention remains a topic of interest on most campuses. It is estimated
that 85% of college student attrition is voluntary (Tinto, 1985); that is, not as a result of
an institutional action due to poor academic performance. Adjustment to college is a
factor in academic and social integration, which are positively related to goal and
institutional commitment; in turn, they are positively related to retention. Institutions
have implemented many types of programs designed to assist with student adjustment to
college. A residential program which integrates academic and social components may be
a particularly viable strategy.

On a local level, the results of this study are of interest to the faculty and staff
who have designed and implemented the ROSES program since fall, 1993. In addition,
replications or adaptations of this residential program could be implemented by other
disciplines to improve adjustment and contribute to retention. Students, institutional
decision-makers, and program designers may benefit from the results of this study.

Limitations

Findings from this study have limited generalizability. Because the study was

conducted at only one institution, results are not generalizable to other institutions. Only

students expressing a preference for science or engineering majors were included;

11

therefore, this study may not be generalizable to students in other fields of study. This
study only examined science and engineering majors in one first-year student class. Each
first-year student class may differ from one another; thus, caution must be exercised in
applying the findings of this study to subsequent groups of first-year science and
engineering students.

Another limitation is that the residential experiences of all students in this study
are only one part of the complex set of college experiences. While this study focused
exclusively on the experiences associated with participation in the residential program, it
is acknowledged that experiences beyond the scope of this study may influence
adjustment to college.

Organization of the Dissertation

The dissertation is organized into five chapters with the addition of appendices.
The second chapter presents a review of the literature relative to student departure, stages
of transition, and adjustment to college. The design and methodology used in collecting
and analyzing the data is provided in chapter three. Analysis of the data is presented in
chapter four. Chapter five includes a summary of the research findings, implications, and

recommendations for future research.

12

Chapter 2
REVIEW OF THE LITERATURE
Introduction

In this chapter, a review of literature related to college student adjustment is
presented. Adjustment to college is an important factor in college student persistence;
therefore, the first section provides a brief summary of student attrition literature. The
second section introduces Tinto’s (1975) model of longitudinal departure, with particular
attention to the importance of academic and social integration. Third, van Gennep’s
(1960) description of “rites of passage” is examined relative to student transition to
college. The fourth section provides a review of research about student adjustment to
college.

Attrition from Higher Education

College student attrition is a concern affecting institutions throughout the country.
All colleges and universities regardless of size, type, or geographical location experience
student attrition. "Of the nearly 2.4 million students who in 1993 entered higher
education for the ISI time, over 1.5 million will leave their first institution without
receiving a degree. Of those, approximately 1.1 million will leave higher education
altogether, without ever completing either a 2 or 4 year degree program.” (Tinto, 1993).
Levine (1989) suggested that less than half of the students enrolled in college graduate in
four years and less than 70% graduate in seven years.

Perhaps more disturbing is the fact that a large majority of all institutional
departures are voluntary. That is, from the institution’s perspective, students are eligible

to remain. "Nearly 85 percent of student institutional departures are voluntary. They

A-n urn-

 

occur despite the maintenance of adequate levels of academic performance" (Tinto, 1985,
p.32). Research has consistently revealed that less than 25% of all institutional
departures are due to poor academic performance (Astin, 1977; Tinto, 1993).
Understanding Student Attrition

Considerable research has attempted to uncover the reasons students leave
institutions. Information is often obtained through exit interviews with students or post-
departure surveys in which students indicate their reason(s) for leaving the institution by
selecting the reason from a pre-determined list, or responding to short answer questions.
Thus, students may be forced to choose the answer which most closely relates to their
situation. While this information may be easily reported, it may not fully reflect the
complexity of student departure.

In a national study conducted in 1977, involving students from 358 institutions,
dropouts most frequently cited boredom with courses, a change in career plans, financial
difficulties, and dissatisfaction with requirements as the reasons for institutional departure
(Astin, 1977). Academic boredom and uncertainty about academic plans, adjustment
problems, unrealistic expectations about college, and financial difficulties continue to be
themes among those students who leave (Noel, 1985; Upcraft & Gardner, 1989). These
categories highlight the reasons for departure; yet provide little assistance in
understanding why students leave college.

Financial difficulties may be overstated by students as a reason for their departure.
For some students, indicating financial problems may be more socially acceptable or may
be simpler than trying to explain a more complex set of reasons. While many students

may indeed have financial difficulties, money more often has to do with college access

14

 

and choice than with persistence (Noel, 1985). Indeed, many students incur significant
debt in order to stay in school.

One of the myths about attrition is that students who drop out of college actually
flunk out; that is, they are asked to leave the institution due to unsatisfactory academic
performance. Several studies have revealed that dropouts often have grade point
averages equal to or greater than the grade point averages of persisting students (Noel,
1985). Certainly, for some students, poor academic performance weighs heavily in their
own cost-benefit analysis of college attendance.

A significant number of researchers have tried to predict and explain attrition.
Various models have been suggested that emphasize different sets of variables and their
relation to attrition. Variables have included background characteristics such as gender,
ethnicity, social economic status, parents’ education, high school grade point average,
and commitments to the institution and to the goal of college completion. Other
predictive models have included measures of involvement and activities during the
college experience such as place of residence, number of informal contacts with faculty,
the nature of peer group interactions, and participation in extracurricular activities.
Despite the inclusion of over 100 variables in models of attrition, tests of the models have
only explained 10 to 20% of the variance in attrition (Astin, 1977; Panos & Astin, 1968;
Terenzini & Pascarella, 1978; Tinto, 1975).

In a national study involving students at 248 institutions, Panos and Astin (1968)
investigated the relationship between 120 student background variables and persistence
over four years of college. Their findings highlighted the complexity of accurately

predicting student attrition. Of the 120 variables, only 20 entered into the final regression

15

equation, and accounted for only 9% of the variance in the group of students who had
dropped out of college. They also found several environmental effects (e.g.,
interpersonal relationships and institutional policies) to be significantly related to
persistence. Thus, completion of four years or more of college seems to be determined
by the students’ personal characteristics and the environmental context of the institution
(Panos & Astin, 1968).

In a sample of 400 freshmen, variables related to students’ backgrounds and early
college experiences were used to predict attrition. When only background variables were
used in the prediction, six of the eight dropouts were predicted correctly. When the early
college experience variables were included in the prediction model, however, all eight
dropouts were predicted correctly (Nelson et al., 1984).

Tinto (1993) proposed three categories of factors which may lead to early
departure: individual, institutional, and external. The individual factors include the goals
and intentions of the students upon entry into the institution. The greater the student’s
commitment to the institution and to goals of obtaining a degree, the greater the
persistence. Institutional factors include the experiences of students once enrolled.
Issues of adjustment, degree of academic difficulty and congruence between the
individual and the environment, and the amount of isolation experienced by students are
all institutional factors. Finally, external factors which may contribute to departure
include finances and obligations (e.g., personal and family) which pull the student away

from the institution.

16

 

Attrition from Science and Engineering Majors

 

Of specific interest for this study is research which documents the projected
shortage of scientists and engineers over the next several years. Atkinson (1990)
suggests that the problem is one of initial recruitment into science and engineering
majors as well as students who drop out of college or who change from science and
engineering majors to other fields. For the high school class of 1980, only 46% of the
first year students declaring a major in science or engineering actually graduated with
those degrees (Atkinson, 1990).

For women and minority students, participation rates in science and engineering
are not increasing, despite significant grth of those groups in the general population
(Atkinson, 1990; Pool, 1990). The attrition rates for women from science and
engineering are higher than those for men, even though women are not less well
prepared academically, nor do they have lower grade point averages (Seymour, 1992). A
theme identified in research by Seymour and Hewitt (Seymour, 1992) was that women in
science and engineering encountered more difficulties in their educational experiences
than their male peers did. Female students were more critical of the science and
engineering teaching and reported it difficult to learn from faculty who took no personal
interest in them, seemingly representing a desire for more affective orientation to
teaching.

Pool (1990) suggests that the underrepresentation of minority students in science
and engineering is not an easily corrected one; the difficulties for minority group

students begin much earlier than the college level. Atkinson (1990) suggests that the

17

nation's schools must provide a more supportive environment and one in which minority
students are encouraged to pursue the sciences as fields of study.

Many students who enter college declaring majors in science and engineering
actually switch to majors outside of those fields. Seymour ( 1995) has investigated
reasons students give for switching out of science and engineering majors. Findings
from her research that are particularly meaningful in the context of the ROSES program
include the following reasons given by students who switch out of these majors:
inadequate high school preparation in study skills and basic courses; poor academic
advising and lack of academic assistance; absence of peer study group support; and a
competitive culture which leads to discouragement (Seymour, 1992).

Tinto’s Model of Longitudinal Departure

In contrast to identifying individual variables which lead to student departure,
Tinto (1975) proposed that decisions to leave were made over time and were a result of
the interactions between the student and the academic and social systems of the
institution. Tinto recognized that students enter institutions with a variety of family
background characteristics such as social status and parental education. Students also
bring their own unique attributes and abilities (e.g., sex, ethnicity, and academic ability),
as well as different expectations and motivations. Tinto suggested that the combination
of these background attributes leads to a set of initial plans (intentions) and commitments
to the institution and to the goal of college completion. He further suggested that
interactions between the individual student and the academic and social systems
continually modify the goal and institutional commitments in ways which lead to

persistence or dropout. External factors, such as work or other commitments, are also

18

acknowledged as factors which may play a role in decisions to leave school (Tinto,
1975). The Tinto model focuses primarily on the nature of experiences and interactions
that occur after students enter the institution rather than on pre-college characteristics.
Tinto identified formal and informal components of the academic and social systems of
the institution. The academic system includes those activities centered around formal
education. The social system is comprised of interactions among students, faculty, and
staff that occur outside of the formal academic setting. In both systems, there are formal
(more structured) and informal (less structured) components. It is the nature of
interactions in the academic and social systems, which influences the degree of academic
integration and social integration which, in turn, contribute to revised intentions and
commitments. Thus, positive experiences serve as integrative experiences and lead to
strengthened intentions and commitments, while negative experiences are non-integrative
and weaken the intentions and commitments. Over time, decisions to remain or leave the

institution result from this process. Tinto’s model is presented in Figure 1.

’19

:2: .3 $225
ammo-EU we 3.58255 of. ”ems-EU doc-52. Even—Hm no 850 use 8550 2: mac—550m Homo—BU w5>a3 .33: 25... ”coed—om

93330 REES-$55 me 552 922.5. - 5 833m

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A B2:
589m .208
a; -
12525
828885
25:58:80 955 doom 35825800
35me L .8:me
=23~w85 \ V
0 38m 8553. H mczoonom
5353821; I- I--- I is I \ .25
3:255:80 A I .-I EFF—om / 3:05-5:50
3:28:35 Ii I -1 3:23:55
use :80 F 3585 23 .25 . . .
E2280 AI 0 c2828.: 28 £55
Bataan bmwmkzsomm H
. coca-.325
_m=2E25_ 220332 4/ 82202: H
r Ill. -. III-II III - I L i. III-...: II- IIIIIIIIII. IL
/ vascuwv—omm
€52
583m 252390..
3555800 c2535: moocotaxm 3:252:80 8.3.52

oEooSO can 280 o>smEoZ>m=oflcm 3:25:65 was 280 bEm-Em

20

Academic and Social lntggration

Tinto’s theoretical contribution to the study of voluntary attrition is the centrality
of academic and social integration and the longitudinal effects of interactions between
individuals and the academic and social systems. "Given individual characteristics, prior
experiences, and commitments, the model argues that it is the individual's integration into
the academic and social systems of the college that most directly relates to his
continuance in that college" (Tinto, 1975). Tinto does not suggest that full integration in
both systems is necessary for persistence; however, some degree of membership in both
the academic and social systems is important. Individual students may belong to several
different systems or sub-communities and have different experiences in each of them.

Much research has been conducted to test Tinto’s model of student departure.
While different studies have focused on different aspects of the model, many of them
have found support for the importance of academic and social integration (Nelson et al.,
1984; Pascarella & Terenzini, 1980; Stoecker et al., 1988; Terenzini & Pascarella, 1976;
Terenzini & Pascarella, 1977; Terenzini & Pascarella, 1978).

Despite the different ways academic integration and social integration are
operationally defined, Pascarella and Terenzini (1991) draw two general conclusions
about academic and social integration from their summary of the research on this topic:

First, at primarily residential institutions, social integration tends to have a

compensatory interaction with academic integration and vice versa. A

second generalization is that levels of either social or academic integration

tend to have a compensatory influence on freshman-to—sophomore

persistence for students who either enter a residential institution with

characteristics predictive of withdrawal (for example, low family

educational status, low educational aspirations) or who subsequently have

low commitment to the institution or the goal of graduation from college.
(pp. 411-412)

21

Transition to College

The academic and social integration at the core of Tinto’s model of college
student attrition is drawn from van Gennep’s (1960) model of life transitions. Van
Gennep, an anthropologist, was especially interested in the ceremonies which often
accompany an individual’s movement from one life position to another or from one
social situation to another. Though the activities of the specific ceremonies varied
depending on the ceremony, it was possible to identify three major phases in terms of the
order and content of the ceremonial activities. Van Gennep (1960) labeled the phases
separation, transition, and incorporation; together, he referred to the overall pattern as
“rites of passage.”

The rites of passage framework may be applied to the process by which a high
school student becomes a college student (Tinto, 1988; 1993). Relative to student
departure, the focus is on the early stages of the interactions between entering students
and members of the institution. The separation phase involves separating from the past.
More specifically, for students entering college, this includes a separation from the
activities and habits of high school, and most likely includes some degree of separation
from home, family, and friends. The transition phase is characterized by interactions with
people (e.g., students, faculty, and staff) who are members of the college community.
Finally, incorporation is the degree to which the student becomes a competent member of
the new community. This requires learning the norms and establishing connections with
others.

While each stage has its defining characteristics, the stages may not be clearly

distinguished from one another. Though there is considerable variability among

22

individual students as they pass through the stages, there are some commonalties. It is
during this process that new students must learn the necessary skills to become a college
student, despite their competence as a high school student. They may interact with
different kinds of people, or in ways quite different from their previous interactions.
Students may experience feelings of isolation, confusion, loneliness, and normlessness as
they pass from one life and social position to another (Tinto, 1993).

Zeller (1993) suggested the transition is analogous to the culture shock
experienced by people moving into an unfamiliar culture, during which highpoints and
lowpoints are experienced. He described new students as moving from the exciting days
of orientation and welcoming activities to the shocking realities of academic work and
meeting new people. Students find stability and comfort as they develop routines, but
they experience doubts as their academic ability is challenged by first semester grades
and the honeymoon period of new relationships wanes. As students begin to form
relationships with other people and become involved in the university, they become
integrated members of the environment.

Adjustment to College

Adjustment, as defined in this study, is the process of meeting the various

demands in the collegiate setting in order to become academically and socially integrated

in the university.

The transition to university traditionally regarded as positive, involving
new opportunities, nevertheless involves change for all students. There is
the need to break with old routines and to adjust to the demands of a new
environment including the need to adapt to the new intellectual and social
challenges which present themselves. (Fisher & Hood, 1987, p. 425)

23

Draper (1991) suggested that adjustment takes time and requires students to try
new behaviors, building on patterns of behavior that are successful. He also suggested
that adjustment is “associative in the sense that these patterns are reinforced as freshmen
interact with other students who share the same needs and goals” (p.73)-

Successful adjustment significantly enhances the success and persistence of new
students. For new students, there is transition and adjustment academically, socially, and
personally. Students need to feel connected to other people in the institution; they need to
have a sense of comfort with their academic and social environments; and they need
assistance with issues related to their transition (Upcrafi & Gardner, 1989).

Adjustment, then, is multifaceted, and is concerned with the “ability to cope
effectively with the varying demands of the new college setting”(Baker & Siryk, 1989, p.
465). Adjustment during the first semester has been found to be a useful predictor of
second semester persistence (Nelson et al., 1984). In fact, Krotseng (1992) found that
scores on adjustment measures correctly classified 85 percent of all respondents as
persisters or nonpersisters after one semester. Bragg (1994) found that student adjustment
to college was highly correlated with student intent-to-persist, and was negatively
correlated with consideration of institutional withdrawal.

In summary, the adjustment process is the process through which students
negotiate their transition from high school to college to become academically and socially
integrated into the institution. Since the nature of interactions in the academic and social

systems is critical to student persistence, research about adj ustment to college is valuable.

24

Research about Student Adjustment to College

Adjustment to college has been the focus of two general categories of research
studies. Relationships between a number of individual or background variables and
various facets of adjustment to college have been examined. A smaller number of studies
have treated adjustment as a dependent variable, investigating whether specific
interventions or environmental characteristics influence adjustment to college.
Correlates of Adjustment

In a study of 56 first-year students, both individual and environmental variables
were found to correlate with different aspects of adjustment. Problem-solving skills and
ACT scores significantly predicted academic adjustment; while age, family income,
perceived social support, and distance from home all related to positive social adjustment
(Brooks II & DuBois, 1995 )-

Mooney et al- (1991) surveyed 88 female college students to assess academic
locus of control, self-esteem, and geographical distance from home as predictors of
adjustment to college. They found that an internal locus of control, a high level of self-
esteem, and the perception that the distance from home was “just right” (regardless of the
actual distance) all contributed significantly to accurate predictions of college adjustment.

It may be that distance from home measured by miles is less important than the
feelings students have about being away from home. Feelings of homesickness are often
reported by students, especially in the first few weeks of the semester. Fisher and Hood
(1987) found that homesick students showed higher levels of psychological disturbance

and lower levels of college adjustment than students who were not homesick.

25

Several studies have investigated family relationships and student adj ustment to
college. Lapsley, Rice, and FitzGerald (1990) found that adolescents with strong
attachment relationships with parents had a more positive adjustment to college than
students who were insecurely attached. In another study, psychological separation was
unrelated to college adjustment in men and negatively correlated with adjustment in
women (Lopez, Campbell, & Watkins, 1986).

There is some evidence of variation in the relationship between attachment with
parents and adjustment to college depending on the class standing of students. Lapsley et
al. (1990) reported that for freshmen, parental attachment variables accounted for a
significant amount of variation only in academic adjustment, while for juniors, parental
attachment variables accounted for significant amounts of variation in academic, social,
and personal adjustment as well as goal commitment. In another study, Lapsley, Rice,
and Shadid (1989) found that freshmen were more psychologically dependent on their
parents and had lower levels of social and personal adjustment to college than upperclass
students.

The nature of family relationships may also play a role in student adjustment to
college. Lopez et al. (1988) found a relationship between conflicted parent-student
attachments and college adjustment for both men and women. While this relationship
may have been affected by variables not controlled for, it still suggested that a conflicted
relationship with parents may create emotional difficulties for the students which, in turn,
may impact aspects of college adjustment. In Lopez’s (1991) study, women and students
who reported high levels of marital conflict in their families displayed lower levels of

personal adjustment to college-

26

In three separate studies, Smith and Baker (1987) found a positive relationship
between freshman decidedness regarding academic major and adj ustment to college. In
all three studies, students who were more certain about their choice of academic major, as
compared to those who were less certain, scored higher in at least one area of adjustment.
There was some evidence that this relationship was more evident in the second rather
than the first semester.

There is also evidence that adjustment to college is likely to be related to factors
not only within the person, but also in the institutional environment (Barthelemy & Fine,
1995; Brooks II & DuBois, 1995; Cooper & Robinson, 1988). This is consistent with
Tinto’s view that what happens after a student arrives on campus is critical.

Freshmen who report a high degree of alienation are less likely to be involved in
campus activities, are more likely to be dissatisfied with their college experience, and are
more likely to experience adjustment difficulties. Alienated students are also more likely
to discontinue their enrollment, either for a short time or permanently (Baker & Siryk,
1980). Social effectiveness and social adjustment seem to be significantly related to
overall adjustment to college and to persistence (Baker & Siryk, 1983; Christie &
Dinham, 1991). While Harris (1991) found social and academic adj ustment to predict
goal and institutional attachment, social adjustment explained more variance in
attachment (30%) than academic adjustment (6%).

In The Transition to College Project (Terenzini et al., 1992), focus groups with
diverse groups of students from four distinctly different institutions revealed the
importance of social and intellectual validation.

In some ways, perhaps no theme was more persistent throughout the
interviews—regardless of race or ethnicity, gender, age, or institution

27

attended—than new students’ need for self-esteem in its many forms:

self-confidence, a sense of being in control, pride in oneself and what one

does, respecting oneself and being respected by others, valuing oneself

and being valued by others. (Terenzini et al., 1996)

The validation may come from parents, peers, faculty, or staff and can take the form of
simple words of encouragement. For students of color attending primarily white,
residential institutions, social validation and adjustment seem particularly important
(Murguia et al., 1991; Stoecker et al., 1988; Terenzini et al., 1996).

Astin (1977) suggested that environmental circumstances could significantly
increase the chance of students completing college. Living in residence halls during the
first year of college has a positive effect on adjustment. In a study by Wilson, Anderson,
and Fleming (1987), first year students who commuted from home demonstrated poorer
personal adjustment than freshmen who lived in residence halls. Bragg (1994) also found
that commuters, compared to students who lived on campus, did not make as many
friends, were less active, did not adjust to college as well, and gave more consideration to
dropping out.

Blimling (1993), in a review of research about residential living, suggested that
the nature of the social environment in a residence hall encourages greater personal
development of students than living at home. “Immersion in the college experience
requires students to adapt to the demands of a new environment and, in doing so, forces
them to alter perceptions and to learn new ways of interacting in that environment "
(Blimling, 1993, p. 263). At the same time, residential students find comfort in the fact

that others around them are also in transition, thus, transition is viewed as a c00perative

endeavor (Johnson, Staton, & Jorgensen—Earp, 1995; Terenzini et al., 1992).

28

In an investigation of the effect of residence hall climate on college adjustment,
Barthelemy and Fine (1995) found hall climate variables of personal support and group
cohesiveness positively correlated with adjustment, while a climate of conflict was
negatively related to adjustment. Although this study was correlational in nature,
Barthelemy suggested that residence hall climate variables do play a role in student
adjustment to college, and could be manipulated to maximize adjustment.

Effects of Interventions on Adjustment

There are some studies which treat student adjustment to college as a dependent
variable. All students experience transition from high school and home to college. The
identification of strategies that could influence positive adjustment would be very helpful
to students and institutions.

In Baker’s (1986) investigation of the effect of an intervention on adjustment,
students who scored below the means on four subscales of an adj ustment survey were
divided into control and experimental groups. Students in the experimental group were
invited to an individual interview to discuss their scores. Students who participated in the
interview, compared with students in the control group, showed significantly greater
improvement in adjustment scores on the post-test survey. Additionally, significantly
fewer of the interviewed students withdrew from college. The researchers realized that
the observed effect may have had little to do with the content of the conversation. It
could have been that the retention effect was instead due to a feeling by the interviewed
students that someone at the institution cared about them.

The literature reports mixed results regarding the effects of summer orientation

programs on adjustment. Orientation programs are generally designed to assist new

29

students in their transition to college. Pascarella et a1. (1986) found that students who
attended an orientation program had significantly higher levels of social integration and
subsequent commitment to the institution than those who did not attend orientation.
Orientation attendance, however, had no effect on adjustment to college or on student
persistence in a study by Martin and Dixon (1989). In both cases, orientation attendance
was voluntary, which makes it more difficult to eliminate any pre-orientation intentions
or motivations which might explain the findings.

Schwitzer, McGovern, and Robbins (1991) investigated the effects of a freshman
orientation course and found that participation in the course was associated with
improved academic and social adj ustment. Participation in the course was voluntary and
there was no comparison group of freshmen, so the actual effect of the course is unclear.
High school students who enrolled in a college orientation course (University 101) during
high school anticipated being able to adjust to college more successfully than a group of
high school students who were enrolled in a college government course (Buchanan,
1991). Data from this study indicated that students in the University 101 group had
greater actual adjustment to college than students in either the group taking the
government course or students in a control group taking no college course; however, the
finding was not statistically significant.

Research comparing the experiences of students in residence halls to those who
live in living-learning centers suggests that student adjustment is enhanced by the living-
learning environment. Pemberton (1969) found no significant differences after one year
of college between the academic performance of freshmen in a living—learning center and

those in conventional halls. However, students in the living-learning center believed their

30

transition to college was made easier due to the fiiendly, cohesive, and supportive
atmosphere of the living-learning center. Surveying seniors at Michigan State University,
Nosow (1975) found that seniors in three living-learning centers were more positive in
their attitudes about their personal adjustment, well-being, and intellectual growth than
seniors in conventional residence halls.

Draper (1991) spent a year in a predominately freshman residence hall during the
1978-1979 academic year. His ethnographic work focused on nine first-year students and
their transition to the university. As a result of his study, he makes the following
recommendations about on-campus housing for first-year students. Freshmen should be
housed in proximity to one another for purposes of support and group identity, yet they
should not be isolated from upper division students or faculty or staff of the institution.

In fact, he suggested that academic and student affairs offices should be located in
residence halls to provide casual contact with students. He encouraged the development
of strategies to overcome the real and perceived barriers between new students and the
academic life of the institution. Finally, he suggested that faculty and staff should have
opportunities to interact informally with students, and that the number of co-curricular
activities in the halls should be increased.

Residential Option for Science and Engineering Students (ROSES)

The ROSES program for science and engineering students incorporates many of
the recommendations made by Draper and addresses some of the factors cited by students
who switch out of science and engineering majors. The purpose of the ROSES program,
as described in the pilot program proposal, is

“. . . to actively pursue the improvement in the quality of the undergraduate
experience for those students who choose science and engineering as

31

academic and professional careers where academic subject matter is both

common and challenging as well as to provide a sense of belongingness

and community where too often the university environment and academic

rigor come into conflict for undergraduates.” (E. M. Wilson, personal

communication, Spring, 1993)

F irst-year students who have expressed interest in science and engineering majors
may elect to participate in the ROSES program. Students in the program are housed
together in the same residence hall, and most are assigned roommates who are also in the
ROSES program. All students in the ROSES program are required to enroll in a ROSES
seminar class during the fall semester. The seminar is a one-credit course and is designed
to assist students in their transition to college by exposing them to resources at the
institution, helping them learn academic skills, and introducing them to their field of
study. The class meets once per week in a classroom and students are expected, as part of
the class, to attend co-curricular activities planned by the residence life staff Each
participating college is responsible for the seminar class for their students. The specific
topics covered in the class may vary somewhat among the three colleges.

Resident assistants (undergraduate staff members) receive some additional
training related to the ROSES program so they can be of assistance to new students.
They are also involved in the implementation of the co-curricular portions of the ROSES
seminar class. Several returning students serve as peer mentors and tutors for new
students. Faculty and academic advisers serve as instructors for the ROSES seminar
class and are encouraged to interact with students in the residence hall, via advising

appointments or informal conversations. Special tutoring rooms are also available in the

residence hall for group study and for tutoring at designated times.

32

Summary

In this chapter, the transition from high school to college has been examined in
the context of students’ academic and social integration into the institution. Students’
experiences with the academic and social systems of the institution may be instrumental
in helping them adjust to college. There is evidence that the first year of college,
especially the first six weeks, are key in shaping the remainder of the undergraduate
experience.

While a number of studies document relationships between background variables
and adjustment to college, fewer studies have examined strategies which might positively
affect adjustment. Several studies have suggested that the peer environment and social
climate in residence halls are related to positive adjustment to college. This study sought
to determine which components of a residential program, structured to integrate academic
and social elements, significantly predicted student adjustment to college. A schematic

representation of this study is presented in Figure 2.

zen Es .Eogméé =sm u:uE%:€< 35cm J:o§§€< Essences :o 88.on meats»:

 

 

m0<mm><
HEOm mQ<MO
mmbmmzmm 44<m

 

 

 

 

HngDR—ay
443m

 

 

 

 

HZMEHmDmQ/x
A<~UOm

 

 

 

 

Egmag
UHEmQ40<

 

'\'\//

 

 

Ear—Sum $501

4

 

 

22529:: no manor
whom
PEEP—Eng BmEEoom
Emhmmwm AfiUOm

 

 

 

 

 

mEboBm Esom
awe—U E 8.53
68:00 co£>u< BEonno<
228885 332$
Empmwm UHEmQ<D<

 

 

 

ENE tho—Em
I E 9.5 ”Back”

 

mmmom E =oEm

<m0

-mFSE a go 53:95.50 2:. i m oSwE

 

 

 

 

 

$535
I wctoofiwcm was
00:25 wctofim

 

 

 

34

Chapter 3
METHODOLOGY

The purpose of this study was to assess the relationships between various
components of a residential program for science and engineering students (ROSES) and
student adjustment to college. The Student Adaptation to College Questionnaire (Baker
& Siryk, 1989) was used to measure self-reported adjustment to college. The Student
Adaptation to College Questionnaire (SACQ) yields an overall adjustment score, as well
as scores for each of four subscales: academic adjustment, social adjustment,
personal/emotional adjustment, and attachment. For the purposes of this study, the
academic adjustment and social adjustment subscales were used. A ROSES Experiences
Survey, designed for this study, was used to gather information about student
participation with various academic and social components of the ROSES program.

This chapter describes the methodology and procedures used in this study. The
participants are described, along with the instrumentation, data collection procedures, and
design of the study. The research hypotheses are stated and data analysis is described.
Background

In 1993, the College of Engineering, College of Natural Science, and College of
Agriculture and Natural Resources, in conjunction with the Departments of Residence
Life and University Housing, offered a residential program for entering science and
engineering students. Students admitted to the university are not required to be admitted
to a college, but may declare a “major preference”. If students declare a major
preference, the college offering the major area of study shares administrative

responsibility for academic matters and records. For the purposes of this residential

35

program, the students are generally referred to as science and engineering students,
although they may have very different specific majors. The College of Engineering has
11 different majors, the College of Natural Science has 18, and the College of Agriculture
and Natural Resources has 16 majors (see Appendix A for a list of majors). Because
science and engineering majors in the Colleges of Engineering, Natural Science, and
Agriculture and Natural Resources have a similar curriculum for their first year, these
colleges joined together to sponsor and support a single residential program.

Entering students declaring a preference for a major in one of the participating
colleges (Engineering, Natural Science, or Agriculture and Natural Resources) are
screened by the college for invitation to the ROSES program. Because of space
limitations in the program, each college establishes criteria for acceptance into the
ROSES program. The College of Natural Science generally accepts students who have
declared a major in a natural science field and who have an ACT score of at least 20. The
College of Engineering typically accepts only those major preference students who have
an ACT score of at least 24. Because the number of entering students expressing
preference for a major in the College of Agriculture and Natural Resources is so small, all
of these students are usually invited to participate in the ROSES program.

Information about the ROSES program, including an application, is sent to the
students who meet the criteria established by the colleges. Students who apply by the
deadline are assigned to Bailey Hall, an undergraduate residence hall at Michigan State
University that houses approximately 400 men and women.

The Residential Option for Science and Engineering Students (ROSES) is

. . designed to provide a stronger sense of community and academic support within the

36

greater University” (Zmich, Lux, DeRosa, & Gordon, 1997). In addition to living in the
same residence hall, students in the ROSES program are required to enroll in a one-credit
class, which consists of a weekly class session taught by faculty and academic staff and
regularly scheduled programs by the residence life staff. Students in the ROSES program
are also encouraged to enroll in many of the same course sections for biology, chemistry,
computer science, math, social science, and writing. Most of the students in the ROSES
program do enroll in a reserved section of at least one course. Tutoring rooms, for
individual and group study, are designated in the residence hall. Many of the ROSES
students have roommates who are also in the ROSES program. Returning students who
were in the ROSES program their first year live in the hall and serve as peer leaders for
the new students. There are special events during new student orientation at which new
ROSES students are welcomed by faculty and academic staff of the three colleges, the
residence life staff, and the ROSES peer leaders.
Participants

This study was limited to first time freshmen enrolled at Michigan State
University for the 1997 fall semester. All of the students were participating in the
ROSES program and had declared a preference for a science or engineering major in one
of three colleges: College of Engineering, College of Natural Science, or College of
Agriculture and Natural Resources.

Students in the ROSES program typically enroll for an average of 15 semester
credits. Most of the ROSES students take at least one general education or common
major course (i.e. math, biology) with other ROSES students. Sections of these courses

are reserved for ROSES students, and faculty in these sections are encouraged to

37

reinforce cooperative learning. In addition, students are encouraged to take advantage of
the tutoring rooms available in the residence hall.

Instruments
Student Adaptation to College Questionnaire

The Student Adaptation to College Questionnaire (Baker & Siryk, 1989) was used
to measure student adjustment to college. The SACQ yields an overall score, as well as
scores for the following subscales: academic adjustment, social adjustment,
personal/emotional adjustment, and goal commitment/institutional attachment (generally
referred to as the attachment subscale). The SACQ was selected because of its close
parallel to factors in Tinto’s ( 1975) model of student departure, specifically social and
academic integration, and goal and institutional commitments.

The SACQ consists of 67 items. Students mark their responses to items along a
nine-point Likert scale (from “doesn’t apply to me at all” to “applies very closely to
me”). Half of the items are positively keyed and half are negatively keyed. On all
scales, the higher total scores correspond to more positive adjustment.

The academic adjustment subscale consists of 24 items and assesses the student’s
academic motivation, perceptions about academic performance, and ability to cope with
academic demands. The social adjustment subscale consists of 20 items and includes
items related to the social environment, interpersonal relationships, and social activities.
The personal-emotional subscale has 15 items related to the pressure of college and asks
students about their physical and psychological health and well-being. The attachment
subscale consists of 15 items which assess the student’s satisfaction with the college,

thoughts about dropping out, and commitment to completing a degree. Individual items

38

are organized into 12 critical clusters, that combine to form the subscales. The items
composing the subscales are presented in Appendix B.
Baker (1986) suggests the SACQ can be used to identify students who are having

difficulty and as

...a source of dependent variables in studies of factors affecting
student adjustment to college. These kinds of studies could be for strictly
research purposes, or they could include very practical attempts to assess
effects on students of such factors as living arrangements, special
counseling programs, variations in financial support, or, in other words,
virtually any of those factors that fall in the domain of the student
personnel worker. (p. 3)

Reliability

Adequate reliability and validity studies have been conducted with the Student
Adaptation to College Questionnaire. Cronbach’s (1951) alpha, an estimate of internal
consistency reliability, has yielded values on the academic subscale from .78 to .90; and
on the social subscale from .73 to .91 (Baker & Siryk, 1989). According to Borg (1979),
these values are considered adequate for research purposes.
W

In criterion validity studies conducted by Baker and Siryk (1984), subscales of the
SACQ correlated significantly with behavioral variables expected to relate differentially
to each subscale. Baker and Siryk ( 19984) found that the academic adjustment subscale
was significantly correlated with freshman grade point average for five of six
administrations of the SACQ. Election to an academic honor society during the junior
and senior years was significantly related to only the academic adjustment subscale, with
the exception of one administration in which the social adjustment subscale was also

significantly related to honor society election. A social activities checklist, an index of

39

involvement in the social life of college, was only found to correlate significantly with
the social adjustment subscale. The social adjustment subscale was also significantly
correlated with being selected as a dormitory assistant (student staff member) after the
freshman year. Scores on the personal—emotional subscale significantly correlated with
students being known to a psychological services center in all six administrations of the
SACQ on which the validity studies were conducted. The general subscale (or
attachment subscale) was significantly correlated with attrition in all six administrations.
ROSES Experiences Survey

The ROSES Experiences Survey was designed for this study. See Appendix C for
the ROSES Experiences Survey. Items on the survey collected information about
students’ participation with various components of the ROSES program. Items on the
survey asked students about their study habits, involvement, interactions with academic
and support staff, relationships with student peers (roommates, RA) and their perceptions
of the ROSES program.

Several of the experiences of ROSES students are directly related to their
participation in the ROSES program. They are unique to ROSES because of the design
or special emphasis of the program. These components include having a roommate who
is also in the ROSES program. Since all ROSES students are assigned to the same
residence hall, many do have ROSES students as roommates. Students are living with
other students who are going through similar experiences and as a result, may experience
personal support and feelings of belonging.

Satisfaction with the contact with a resident assistant is also a direct component of

the ROSES program because of the special role of the resident assistants. They receive

40

special training and focus, and are involved in the co-curricular component of the
required ROSES seminar class. They serve as peer models for new students.

Faculty and academic staff contact with students is also a feature of the ROSES
program. Incoming ROSES students meet their academic advisers during the summer
orientation process. Several sections of the ROSES seminar class are taught by advisers
and faculty from the three colleges. Because of the relatively small class size of the
ROSES seminar class, students have more contact with their adviser or seminar instructor
and may develop a more significant relationship with the adviser and/or seminar
instructor. Satisfaction with the contact with an academic adviser and the degree to
which students feel known by their seminar instructors are measures of these
components.

Because ROSES students live in the same hall and many take reserved sections of
common courses together (i.e. math, science, writing), studying with other ROSES
students is another unique component of the ROSES program. In this study, this measure
is expressed as the proportion of time students study with other ROSES students to the
total amount of time they study per week.

Finally, the ROSES seminar class is a unique component of the ROSES program.
The seminar is designed to assist students in their transition to college, introduce them to
the resources on campus and to faculty members, help students develop academic skills,
and assist students in exploring their major and career. As a part of the seminar class,
students are required to attend evening programs offered in the residence hall. The
programs include topics on campus resources, study skills, time management, and stress

management. The grade for the seminar is based on an accumulation of points students

41

earn for attending class, attending evening seminars in the residence hall, and completing
in-class and out-of-class assignments. Therefore, the grade serves as a reasonable
measure of the degree to which students were involved in the seminar.

There are other activities that all undergraduate students may be engaged in, such
as going to class, that were also examined for their contribution to adjustment and grade
point average. For purposes of this study, these are indirect components of the ROSES
program.

The total number of hours per week students reported being in class and studying
were both measured as indirectly related to the ROSES program. The quality of the
roommate relationship was also assessed as an indirect component. There were two
measures of this component: whether the student had known their roommate prior to
attending MSU, and how satisfied the student was with their roommate relationship.
Finally, the total number of hours per week students reported being involved in non-
instructional activities (i.e. student groups and activities, work, community service) was a
measure of involvement. Table 1 presents the ROSES components used in this study as

well as the items from the ROSES Experiences Survey used to measure the component.

Table 1 - Components and Measures of ROSES Experiences

 

 

 

Direct ROSES Component Measure Scoring
Having a ROSES roommate ROSES roommate (item 1a) Yes or no
Peer relationship Satisfaction with RA contact (item 12g 0-5“

 

Faculy/academic staff contact Known by ROSES instructor (item 13b) 1-5"

 

Satisfaction with adviser contact Qtem 12m O-5*

 

Study with other ROSES students Study with ROSES students (item 4Q Hours

 

 

 

 

 

 

 

 

 

Perception of ROSES ROSES helped academically (item 14a) 1-5**
ROSES helped socially Qtem 149 1-5"
ROSES seminar class Seminar class grade 0.0-4.0
Indirect Component Measure Scoring
Hours in class Class hours per week (item 2g) Hours

 

42

Table 1 (con’t.)

 

 

 

 

 

Hours studying Stud)! hours per week (item 2h) Hours

Roommate relationship Prior knowledge of roommate (item 1b) Yes or no
Satisfaction with roommate (item 12a) O-5*

Involvement Involvement (sum of items 2a - 2f) Hours

 

 

 

Note. * scored on a Likert scale and recoded with O = does not apply; 5 = very satisfied

** scored on a Likert scale with 1 = not at all; 5 = very well

Students were also asked for their permission to use selected institutional data
(ethnicity, gender, college of enrollment, predicted gpa, and fall semester grades and
overall GPA) for research purposes. Ethnicity, gender, college of enrollment, and
predicted gpa were used to control for pre-entry characteristics of students in the ROSES
program.

Data Collection

During the week of December 1, 1997, the SACQ and ROSES Experiences
Survey, along with a letter explaining the study, were distributed to all ROSES students.
Students enrolled in the Engineering sections of the ROSES program were involved in a
related research project; therefore, surveys were distributed as a part of the larger project
through the ROSES seminar class. Surveys for the ROSES students enrolled in
Agriculture and Natural Resources, and Natural Science received the surveys in their
residence hall mailboxes. Participation in the study was voluntary for all students.
Engineering students were asked to complete the surveys in class, while the other
students were asked to return the completed surveys to the hall director’s office by
December 8, 1997. The ROSES seminar instructors agreed to award a bonus point
toward students’ in-class activity points for completing the surveys. This was one of

several options available to students to earn extra points toward their seminar grade.

43

 

Thus, when students turned in the completed surveys, they signed a slip of paper
(separate from the surveys). The signed slips of paper were forwarded to the seminar
instructors so that credit could be awarded.
The letter accompanying the surveys explicitly stated that responses and personal
information would remain confidential and be used for research purposes only.
Data Analysis
The primary goal of data analysis was to determine relationships between
students’ experiences in the ROSES program and their adjustment to college. Bivariate
analysis provided a general overview of relationships and tested for effects of background
variables. Regression analysis was utilized to test the full model and to identify the
experiences which were significant predictors of academic adjustment, social adjustment,
and fall semester grade point average (gpa). The .05 alpha level of significance was used
in both analyses; for regression results, .05 - .10 was also examined to determine
marginally significant results.
Research Hypotheses
The following research hypotheses tested bivariate relationships and were tested
using multiple regression:

1. Students with a greater degree of participation with the academic components of the
ROSES program will achieve higher academic adjustment, as measured by the
academic adjustment subscale of the SACQ.

2. There will be no significant difference in academic adjustment, as measured by the
academic adjustment subscale of the SACQ, between students who participate more

with the social components of the ROSES program and those who participate less.

44

Students with a greater degree of participation with the social components of the
ROSES program will achieve higher social adjustment, as measured by the social
adjustment subscale of the SACQ.

. There will be no significant difference in social adjustment, as measured by the social
adjustment subscale of the SACQ, between students who participate more with the
academic components of the ROSES program and those who participate less.

. Students with a greater degree of participation with the academic components of the
ROSES program will achieve higher full adjustment, as measured by the SACQ.

. Students with a greater degree of participation with the social components of the
ROSES program will achieve higher full adjustment, as measured by the SACQ.

. Students with a greater degree of participation with the academic components of the
ROSES program will earn higher fall semester grade point averages.

. There will be no significant difference in the fall semester grade point average
between students who participate more with the social components of the ROSES

program and those who participate less.

45

Chapter 4
FINDINGS

The purpose of this study was to explore the contribution of a semester-long
residential program combining academic and social experiences on student adjustment to
college. Specifically, this study sought to determine the components of a living-learning
program which best predict academic, social, and overall adjustment to college, and fall
semester grade point average. Student participation with the components of the ROSES
program was assessed by the ROSES Experiences Survey, a survey designed for this
study. Adjustment to college was identified by the academic adjustment and social
adjustment subscales, and the full adjustment score of the Student Adaptation to College
Questionnaire (SACQ). Fall semester grades were obtained from institutional records.
The data analysis and interpretation for the research questions and hypotheses are
presented in this chapter. The chapter is divided into four sections: 1) description of the
sample, 2) tests of bivariate relationships, 3) multiple regression analyses, and 4)
summary of the findings.

Description of the Sample

Research instruments were distributed to 221 first year students who were
enrolled in the Residential Option for Science and Engineering Students (ROSES) during
fall semester, 1997. A total of 199 surveys were returned; representing a 90% response
rate. Of the 199 surveys, 174 were complete and used in the statistical analyses, yielding
a usable return rate of 79%.

Table 2 presents the frequency data for the demographic variables of gender,

ethnicity, and college of enrollment for the survey respondents. Percentages do not total

46

one hundred percent due to rounding. The demographics (gender, ethnicity, and college
of enrollment) of the survey respondents closely resembled that of the entire ROSES

student population for fall semester, 1997.

Table 2 - Distribution of Respondents by Gender, Ethnicity, and College of Enrollment

 

 

 

 

 

 

Demographic Variable Survey Respondents All ROSES
F reguency Percentage Frequency Percentage
Gender
Female 64 36.8 74 33.5
Male 110 63.2 147 66.5
Total 174 100.0 221 100.0
Ethnicity
Caucasian 147 84.5 184 83.3
African American 11 6.3 17 7.7
Hispanic 3 1.7 4 1.8
Native American 3 1.7 4 1.8
Asian American 9 5.2 1 l 5.0
Other 1 .6 1 .5
Total 174 100.0 221 ‘ 100.0
College
Agriculture and Natural
Resources 5 2.9 9 4. 1
Engineering 132 75.9 163 73.8
Natural Science 37 21.3 49 22.2
Total 174 100.0 221 100.0

 

 

 

 

 

 

For purposes of data analysis, categories were created for the demographic
variables of ethnicity and college of enrollment. Because of the small number of
respondents in some of the racial/ethnic groups, ethnicity was divided into two
categories: non-minority and minority. A one-way analysis of variance revealed no
significant difference in predicted grade point average among the different groups within
the minority category (F = 1.797; p > .05). Table 3 presents the mean predicted grade
point averages for each racial/ethnic group, as well as the results of the ANOVA. Due to

the small number of respondents enrolled in the College of Agriculture and Natural

47

Resources, their responses were combined with responses from the College of Natural
Science to yield two categories for college of enrollment: Engineering and non-

Engineering.

Table 3 —— Analysis of Variance of Predicted Grade Point Average by Minority Group

 

 

 

 

 

 

 

Racial/Ethnic group Predicted gpg_
African American (11 = 11) 2.61
Hispanic (n = 3) 2.81
Native American Q1 = 3) 2.57
Asian American (11 = 9) 2.84
Other (11 = 1) 3.22
Total (n = 27) 2.73

 

 

 

 

F = l.787;p> .05

Adjustment Scores for Respondents

All respondents completed the Student Adaptation to College Questionnaire
(Baker & Siryk, 1989), which yields scores for academic adjustment, social adjustment,
attachment, personal-emotional adjustment, and full adjustment. For this study, scores
from the academic adjustment and social adj ustment subscales, and the full score were
used. Table 4 presents descriptive statistics for the adjustment scores for this sample.
The descriptive statistics (i.e. means, standard deviations, and ranges) for the two
subscales and the full score for this sample are similar to those obtained for samples from
a number of colleges and universities throughout the United States (see Baker & Siryk,
1989). The scores for all of the adj ustment scores are normally distributed, as indicated
by measures of skewness and kurtosis. Skewness and kurtosis values between +/- 1.0 are

considered excellent for psychometric purposes (George and Mallery, 1995).

43

Table 4 - Descriptive Statistics for Adjustment Scores

 

 

 

 

 

 

 

 

Adjustment Score n Range Mean Std. Skewness Kurtosis
Deviation

Academic 174 77-201 140.14 23.21 .079 .259

Social 174 71-174 132.95 21.71 -.516 .010

Full 174 254-568 418.49 60.98 .009 -.421

 

 

 

 

 

Table 5 presents the intercorrelations among the two subscales and full
adjustment score. The intercorrelations are similar to those obtained in other
administrations of the SACQ (see Baker & Siryk, 1989). Baker and Siryk (1989) assert
that the “. .. correlations are large enough to indicate that the subscales are indeed
measuring a common construct, but small enough to support the conceptualization of that

construct as having different facets as represented by the subscales” (p.34).

Table 5 - Correlations Among Academic, Social, and Full Adjustment

 

 

 

 

Academic Social Full
Academic 1 .446" .826"
Social .446” 1 .806”
Full .826" .806" 1

 

 

 

 

 

 

Note. it = 174; **g< .01

Adjustment Scores and Background Variables

Descriptive and inferential statistics are presented for the adjustment scores and
the background variables of gender, ethnicity, college of enrollment, and predicted grade
point average.

Gender

Table 6 indicates the mean adj ustment scores for males and females, and provides

the results of two—tailed t-tests for each adjustment score and gender. The t-tests revealed

that females scored significantly higher on the academic adjustment subscale (t = 2.31;

49

that females scored significantly higher on the academic adjustment subscale (t = 2.31;

p_< .05). There were no gender effects for the social adjustment subscale or the full

SCOIC.

Table 6 - T-tests of Means of Adjustment Scores by Gender

 

 

 

 

 

 

 

 

 

 

Adjustment Males Females
Score n= 110 n=64
x sd x sd t prob.
Academic 137.02 22.21 145.52 24.07 2.31 .02*
Social 131.70 20.43 135.11 23.76 .96 .34
Full 411.78 59.53 430.03 62.18 1.90 .06
*p_<.05
Ethnicity

Table 7 presents the mean adj ustment scores for non-minority and minority
students, as well as the results of two-tailed t-tests. There were no significant differences

in adjustment scores between non-minority and minority participants in the ROSES

program.

Table 7 - T-tests of Means of Adjustment Scores by Ethnicity

 

 

 

 

 

 

 

 

 

 

Adjustment Scores Non-minority Minority
n = 147 n= 27
x sd x sd 1 prob.
Academic 140.60 22.60 137.67 26.62 .538 .59
Social 132.15 21.85 137.33 20.78 -1.182 .25
Full 418.73 59.92 417.33 67.67 .108 .92
College of Enrollment

Table 8 presents the means for adj ustment scores for students enrolled in the

College of Engineering and those who were not in the College of Engineering, as well as

50

the results of two-tailed t-tests. There were no significant differences in the adjustment
scores between students in the College of Engineering and those who were not in the

College of Engineering.

Table 8 - T-tests of Means of Adjustment Scores by College

 

 

 

 

 

Adjustrnent Engineering Non-Engineering
Scores n = 132 n = 42
x sd x sd t prob.
Academic 140.07 23.86 140.38 21.32 -.O80 .94
Social 132.92 21.18 133.07 23.56 -.038 .97
Full 418.09 62.44 419.76 56.85 -.162 .87

 

 

 

 

 

Predicted Grade Point Average

Predicted grade point average is based upon high school grade point average, test
scores (ACT or SAT), and the quality of the high school attended. The median predicted
grade point average for all respondents was 2.81, which was used to divide the
respondents into two groups. Table 9 presents the means for adjustment scores for
students with a predicted grade point average of 2.81 or higher and those with a predicted
grade point average below a 2.81, as well as the results of two-tailed t-tests. Students in
the higher predicted GPA group scored significantly higher on the academic adjustment
subscale than students in the lower predicted GPA group (t = 2.276; p_< .05). There were

no predicted grade point average effects on the social adjustment subscale or full score.

51

Table 9 - T-tests of Means of Adjustment Scores by Predicted Grade Point Average

 

 

 

 

 

 

 

 

 

 

Adjustment Scores Predicted GPA Predicted GPA

22.81 <2.81

n=85 n=87

x sd x sd t prob.

Academic 144.29 25.72 136.30 20.06 2.276 .02“
Social 133.86 21.72 131.66 21.72 .664 .51
Full 426.47 67.19 410.52 54.19 1.716 .09
*p_<.05
Summagy

Academic adjustment scores were significantly higher for females (t =
2.31; p_< .05) and for respondents with predicted GPAs of 2.81 or higher (t =
2.276; p_< .05). There were no significant effects for any of the other background
variables.
Fall Semester Grade Point Averages for Respondents
Fall semester grade point averages for all respondents ranged from .38 to 4.0, with

the mean for the group being 2.86. This was very close to the 2.81 predicted grade point

average for the entire group.

Fall Semester Grade Point Average and Background Variables

Descriptive and inferential statistics are presented for fall semester grade point
average and the background variables of gender, ethnicity, college of enrollment, and
predicted grade point average.

Gender

The fall semester grade point average for females was 3.03, which was

significantly higher than the 2.76 fall grade point average for males (t = 2.34; p_< .05),

52

even though there were no significant differences between the predicted grade point

averages for males and females (see Table 10).

Table 10 - T-test of Means for Grade Point Averages by Gender

 

 

 

 

 

 

 

 

 

Females Males
n = 64 n = 110

x sa' x sd t prob.
Predicted Grade
Point Average 2.81 .257 2.80 .317 .33 .74
Fall Semester Grade
Point Average .03 .688 2.76 .797 2.34 .02“
*g< .05
Ethnicity

Non-minority students had a fall semester grade point average of 2.93, which was
significantly higher than the 2.51 received by minority students (t = .64; p_< .05). There
was no significant difference in the predicted grade point average between minority and

non—minority respondents (see Table 11).

Table 11 - T-tests of Means for Grade Point Averages by Ethnicity

 

 

 

 

 

 

 

 

 

Non-minority Minority
n = 147 n = 27

x sd x sd t prob.
Predicted Grade Point
Average 2.82 .293 2.73 .302 1.391 .17
Fall Semester Grade
Point Average 2.93 .675 2.51 1.103 2.63 .01“

*p_< .05

53

College of Enrollment

A two-tailed t-test revealed no significant difference in the fall semester grade
point averages between students enrolled in Engineering and students not in Engineering,
even though the predicted grade point average for students in Engineering was
significantly higher than students not in Engineering (t = 2.034; p_< .05). The means and

results of the t-tests are presented in Table 12.

Table 12 - T-Tests for Fall Grade Point Averages by College

 

 

 

 

 

 

 

 

 

Non-
Engineering Engineering
n = 132 n = 42
x sd x sd t Jrob.
Fall Semester
Grade Point
Average 2.87 .803 2.84 .654 .192 .85
Predicted Grade
Point Average 2.83 .293 2.72 .293 2.034 .05*
*p_= .05

Predicted Grade Point Average

Students with higher predicted grade point averages earned a fall semester grade
point average of 3. 14, which was significantly higher than the 2.61 fall grade point
average earned by respondents who had lower predicted grade point averages (t = 4.798;

g< .01). Table 13 presents the mean grade point averages and the results of a two-tailed

t-test.

54

Table 13 - T-Test for Fall Semester Grade Point Average by Predicted GPA

 

 

 

 

 

 

 

 

Predicted GPA Predicted GPA
2 2.81 < 2.81
n = 85 n = 87
x sd x sd 1 prob.
Fall Semester
GPA 3.14 .669 2.61 .769 4.798 .00**
**p_< .01
Summagy

Fall semester grade point averages were significantly higher for females (t = 2.34;
p_< .05), non-minority respondents (t = 2.64; p_< .01), and for respondents with higher
predicted grade point averages (t = 4.798; p_< .01).

ROSES Experiences Survey Data for Respondents

All respondents completed a ROSES Experiences Survey, which was designed for
this study. The purpose of the survey was to ascertain the levels of involvement by the
respondents in the various components of the ROSES program. Some of these
components are unique to the ROSES program and are not available to other students at
the university. For purposes of this study, these components are considered directly
related to the ROSES program. There are other activities that most students are engaged
in, such as spending time in class. Though they are only indirectly related to the ROSES
program, the programmatic design and emphasis of the ROSES program suggested that
these components also be explored for their contribution to adjustment and grade point
average. The components were grouped into two categories: academic and social.

The academic components included the directly related components of students’

satisfaction with the contact with their academic adviser, how well students felt their

55

ROSES seminar instructor knew them, and the degree to which students felt the ROSES
program had helped them academically. These components were scored on a Likert
scale. The academic components indirectly related to the ROSES program included the
number of hours spent in academic activities (i.e. class, studying).

The social components directly related to the ROSES program included whether
or not the roommate was in the ROSES program; the proportion of time students spent
studying with other ROSES students; and the degree to which they felt the ROSES
program had helped them socially. The indirect social components included whether
students knew their roommate prior to attending MSU; their satisfaction with their
roommate relationship and with the contact with a resident assistant; and the number of
hours students spent in non-instructional activities (i.e. work, student groups, community
service). Satisfaction items were scored on a Likert scale.

The final component is the ROSES seminar, a unique component required of all
ROSES students. The seminar grade was based on an accumulation of points students
earned for attending class, attending evening seminars in the residence hall, and
completing in-class and out-of-class assignments. The grade received in the seminar
serves as a reasonable proxy of the degree to which students were involved in the
seminar. Table 14 presents descriptive statistics for the academic and social components

of the ROSES program, as well as the ROSES seminar grade.

56

Table 14 - Descriptive Statistics for ROSES Components

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Component N Range Mean Std.
Deviation

ACADEMIC
Class (hours/week) 172 0-30 14.9 4.0
Study (hours/week) 173 1-45 15.2 8.28
Satisfied with adviser 173 0-5* 3.1 1.53
Known by ROSES instructor 173 1-5** 2.7 1.02
ROSES helped academically 173 1-5** 3.0 1.21
SOCIAL
Involvement (hours/week) 174 0-41 8.8 7.64
Study with ROSES (proportiog 172 00-75 .17 .17
Satisfied with roommate 172 0—5* 3.7 1.39
Satisfied with RA 173 0-5* 3.9 1.28
ROSES helped socially 173 1-5** 3.4 1.31
ROSES seminar grade (4.0 scale) 174 0.0-4.0 3.6 .81

 

Note. * scored on a Likert scale and recoded with O = does not apply; 5 = very satisfied
** scored on a Likert scale with 1 = not at all; 5 = very well

ROSES Exgriences Survey and Background Variables

Descriptive and inferential statistics are presented for the measures associated
with the ROSES components and the background variables of gender, ethnicity, college
of enrollment, and predicted grade point average.

Gender

Table 15 presents the mean responses for each of the ROSES components for
males and females, and provides the results of two-tailed t-tests for each item and gender.
The t-tests revealed that females were significantly more satisfied with their contact with
an academic adviser (t = 2.28; p_< .05). Females were also more positive than males in
their feeling that the ROSES program had helped them academically (t = 4.20; p_< .01)

and socially (t = 4.89; p_< .01).

57

Table 15 - Means of ROSES Components by Gender

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Component Males Females
n=110 n=64

x sd x sd I prob.
ACADEMIC
Class (hours/week) 15.0 3.68 14.7 4.51 .502 .62
Study (hours/week) 14.6 8.86 16.1 7.15 1.238 .22
Satisfied with adviser 2.9 1.54 3.5 1.46 2.276 .02*
Known by ROSES instructor 2.7 1.04 2.8 .96 .706 .48
ROSES helped academically 2.7 1.26 3.5 .96 4.201 .00"
SOCIAL
Involvement (hours/week) 9.1 7.65 8.2 7.67 .799 .43
Study with ROSES (proportion) .18 .17 .16 .18 .700 .49
Satisfied with roommate 3.6 1.29 3.8 1.55 .722 .47
Satisfied with RA 3.9 1.29 3.8 1.28 .383 .70
ROSES helped socially 3.1 1.34 4.0 1.01 4.888 .00"
ROSES seminar grade 3.6 .88 3.8 .64 1.769 .08

 

*p_< .05; **p_< .01

Ethnicity

Table 16 presents the mean responses for the ROSES components for non-

minority and minority reSpondents, as well as the results of two-tailed t-tests. The only

significant difference between non-minority and minority students was the ROSES

seminar grade (t = 3.44; p_< .01) with non-minority students earning significantly higher

grades in the seminar than minority students.

58

 

Table 16 - Means of ROSES Components by Ethnicity

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Component Non-minority Minority
n = 147 n = 27
x sd x sd 1 prob.
ACADEMIC
Class (hours/week) 14.9 3.89 14.8 4.64 .175 .86
Study (hours/week) 15.2 8.11 15.1 9.32 .042 .97
Satisfied with adviser 3.1 1.50 3.2 1.69 .178 .86
Known by ROSES instructor 2.7 1.01 2.8 1.09 .352 .73
ROSES helped academically 3.0 1.21 3.2 1.21 .784 .43
SOCIAL
Involvement (hours/week) 8.5 7.67 10.5 7.43 1.299 .20
Study with ROSES (proportion) .16 .17 .23 .19 1.557 .13
Satisfied with roommate 3.7 1.40 3.7 1.41 .001 .99
Satisfied with RA 3.9 1.25 3.7 1.44 .632 .53
ROSES helped socially 3.4 1.30 3.6 1.37 .784 .43
ROSES seminar grade 3.7 .61 3.2 1.38 3.437 .00*
*p_< .01
College of Enrollment

The means for the ROSES components for students enrolled in the College of
Engineering and those not enrolled in Engineering are presented in Table 17, as well as
the results of two-tailed t-tests. The t-tests revealed that students enrolled in the College
of Engineering were significantly less satisfied with their contact with an academic
adviser (t = 3.405; g< .01) than were non-engineering students. The non-engineering
students were also more positive in their feeling that the ROSES program had helped

them academically (t = 5.224; p_< .01); and socially (t = 3.251; p_< .01).

59

 

Table 17 - Means of ROSES Components by College

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Component Engineering Non-Engineering
n = 132 n = 42

- x sd x sd t prob.
ACADEMIC
Class (hours/week) 14.9 3.96 14.8 4.16 .149 .88
Study (hours/weelg 14.7 8.19 16.7 8.46 1.383 .17
Satisfied with adviser 2.9 1.56 3.8 1.17 3.405 .00"
Known by ROSES instructor 2.6 1.00 2.9 1.05 1.566 .12
ROSES helped academically 2.8 1.19 3.8 .92 5.224 .00"
SOCIAL
Involvement (hours/week) 8.5 6.96 9.8 9.51 .828 .41
Study with ROSES (proportig) .17 .16 .19 .20 .648 .52
Satisfied with roommate 3.7 1.33 3.7 1.60 .098 .92
Satisfied with RA 3.8 1.34 4.0 1.07 .944 .35
ROSES helped socially 3.2 1.34 3.9 1.08 3.251 .00“
ROSES seminar grade 3.6 .83 3.6 .72 .020 .98‘
**p_< .0]

Predicted Grade Point Average

The median of all predicted grade point averages (2.81) was used to divide the

respondents into two groups: those with predicted grade point averages greater than or

equal to 2.81 and those with predicted grade point averages below 2.81. The means for

the ROSES components for respondents in the two categories are presented in Table 18,

as well as the results of two-tailed t-tests. The t-tests revealed that respondents with a

predicted grade point average of 2.81 or higher felt significantly more well known by

their ROSES instructor (t = 2.38; g< .05); reported spending significantly more hours per

week in class (t = 1.987; p_= .05), and earned a significantly higher grade in the ROSES

seminar class (t = 2.616; p_< .05).

6O

 

Table 18 - Means of ROSES Components by Predicted GPA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Component Predicted GPA Predicted GPA

2 2.81 < 2.81

n = 84 n = 87

x sd x Sd t prob.

ACADEMIC
Class (hours/week) 15.54 4.45 14.32 3.46 1.987 .05“
Study (hours/week) 16.36 8.63 13.98 7.88 1.881 .06
Satisfied with adviser 3.30 1.45 2.94 1.58 1.530 .13
Known by ROSES instructor 2.89 1.01 2.53 1.00 2.38 .02M
ROSES helped academically 3.06 1.28 2.98 1.15 .442 .66
SOCIAL
Involvement (hours/week) 9.56 7.91 7.71 6.93 1.632 .10
Study with ROSES (proportion) .15 .14 .19 .20 1.519 .13
Satisfied with roommate 3.81 1.43 3.59 1.38 1.007 .32
Satisfied with RA 3.93 1.34 3.77 1.23 .805 .42
ROSES helped socially 3.48 1.27 3.35 1.31 .645 .52
ROSES seminargrade 3.81 .58 3.49 .94 2.616 .01“

 

*p_= .05; **p_< .05

Summag

Comparisons of mean differences on gender, ethnicity, predicted GPA, and

college of enrollment showed significant differences in the degree of participation in the

ROSES program. Females (t = 2.276; p< .05) and non-Engineering students (t = 3.405;

g< .01) were significantly more satisfied with the contact with an academic adviser.

Females (t = 4.201; p_< .01) and non-Engineering students (t = 5.224; p_< .01) were also

significantly more positive about the degree to which they felt the ROSES program had

helped them academically. Females (t = 4.888; g< .01) and non-Engineering students

(t = 3.251; p_< .01) were significantly more positive about the degree to which they felt

the ROSES program had helped them socially as well. Students with a predicted grade

point average of 2.81 or higher felt known by their ROSES instructor to a significantly

higher degree than those students with a predicted grade point average below a 2.81

61

 

(t = 2.38; g< .05). Finally, minority students (t = 3.437; p_< .01) and students with a
predicted grade point average below a 2.81 (t = 2.616; p_< .05) received significantly
lower grades in the ROSES seminar class.
Research Questions and Hypotheses

Two research questions guided this study: 1) Do individual components of the
ROSES program contribute differentially to academic adj ustment, social adjustment, full
adjustment, and fall semester grade point average; and 2) Which components of the
ROSES program make the most significant contributions to predicting academic
adjustment, social adjustment, full adjustment, and fall semester grade point average.

Research hypotheses were stated in Chapter 3. In this chapter, they are
formulated as statistical hypotheses stated in the null form to test relationships between
individual components of the ROSES program and adjustment and fall semester grade
point average.

Results

The relationships between individual components of the ROSES program and two
sets of outcomes-- adjustment scores (academic, social, and full) and fall semester grade
point average-- were explored. Bivariate analyses between individual variables and
outcomes provided a general overview of these relationships. To test relationships
between individual components and outcomes, respondents were split into two groups at
the median: those who had a greater degree of participation with the component and those
who had a lesser degree of participation with the component. Multiple regression was
used to identify significant determinants of adjustment and of fall semester grade point

average.

62

Academic Adjustment

The academic components directly related to the ROSES program included
satisfaction with the contact with an academic adviser, the degree to which students felt
known by their ROSES seminar instructor, and the degree to which students felt the
ROSES program had helped them academically (i.e. classes, studying). Indirect
academic components included the number of hours per week students reported being in
class and studying. Table 19 presents the means for academic adjustment for the two
groups, as well as the results of t-tests.

Hymthesis 1:

There is no difference in academic adjustment scores, as measured by the
academic adjustment subscale of the SACQ, between students with a greater degree
of participation in any of the academic components directly related to the ROSES
program and those with a lesser degree of participation.

_Sa_ti§f_action with aLdviser:

A two-tailed t-test revealed no significant difference in academic adjustment
scores between those who were more satisfied and those who were less satisfied with the
contact with an academic adviser (t = 1.177; p_> .05).

Feeligg_known by the ROSES instructor:

There was no significant difference in academic adjustment scores for students
who felt known to a greater degree by their ROSES instructor and those who felt known
to a lesser degree (t = 1.692; p> .05).

Feelinthat the ROSES program helped academically:
There was no significant difference in academic adjustment scores between

students who were most positive and those who were less positive in their feeling that the

ROSES program had helped them academically (t = 1.859; p_> .05).

63

Hypothesis 1 is accepted. None of the academic components that were directly
related to the ROSES program were significantly related to academic adjustment scores.

Hypothesis 2:

There is no difference in academic adjustment scores, as measured by the
academic adjustment subscale of the SACQ, between students with a greater degree
of participation in any of the academic components indirectly related to the ROSES
program and those with a lesser degree of participation.

_I-_I_Qt_r_rs per week in cla__s_s_:

Students who reported being in class 15 hours per week or more achieved
significantly higher academic adjustment scores than students who were in class for less
than 15 hours per week (t = 2.044; g< .05).
flggrfler week studying:

Students who reported studying 15 hours per week or more achieved significantly
higher academic adj ustment scores than students who studied less than 15 hours per week
(t = 2.582; g< .05).

Hypothesis 2 is rejected. The academic components indirectly related to the
ROSES program were significantly related to academic adjustment. Students who spent
more hours per week in class achieved significantly higher academic adjustment

(t = 2.044; g< .05), as did students who spent more hours per week studying (t = 2.582;

p_< .05).

64

Table 19-T-tests for Participation with Academic Components and Academic Adjustment

 

 

ROSES Academic
Component Adjustment
x sd 1 prob.
Satisfied with adviser 2 3 141.27 22.68

<3 136.07 24.99 1.177 .24

 

Known by ROSES instructor 2 3 142.66 23.40
< 3 136.68 22.79 1.692 .09

 

ROSES helped academically 2 3 142.33 22.79
< 3 135.22 23.72 1.859 .07

 

Hoursperweekinclass 2.15 142.78 24.19
<15 135.54 21.08 2.944 04*

 

 

Hours per week studying Z 15 144.34 22.48
< 15 135.29 23.36 2.582 .01*

 

 

 

 

*p_< .05

The social components unique to the ROSES program included having a ROSES
roommate, studying with other ROSES students, satisfaction with the contact with a
resident assistant, and feeling that the ROSES program had helped socially (i.e. meeting
people, getting involved). The social components indirectly related to the ROSES
program included knowing one’s roommate prior to attending MSU, satisfaction with the
roommate relationship, and the number of hours per week students were involved in non-
instructional activities (i.e. student groups, work, community service). Table 20 presents
the means for academic adjustment as well as the results of t-tests for participation with
the social components of the ROSES program and academic adjustment.

Hypgthesis 3:

There is no difference in academic adjustment scores, as measured by the
academic adjustment subscale of the SACQ, between students with a greater degree
of participation in any of the social components directly related to the ROSES
program and those with a lesser degree of participation.

65

ROSES roommat_e_:

There was no significant difference in the academic adjustment scores between
students who had a roommate who was also in the ROSES program and those whose
roommate was not in the ROSES program (t = 1.303; p > .05).

Studyingwith ROSES students:

There was no significant different in academic adjustment scores between
students who studied more with other ROSES students and those who studied less with
other ROSES students (t = -.866; p> .05).

_S_agis_faction with resident agsistant:

There was no significant difference between students who were more satisfied
with the contact with a resident assistant and those who were less satisfied (t = .310;

9 > .05).
Feeling that the ROSES progrim helped socim

There was no significant difference in academic adjustment scores between
students who were more positive that the ROSES program had helped them socially and
those who were less positive (t = .823; p > .05).

Hypothesis 3 is accepted. None of the social components directly related to the
ROSES program were significantly related to academic adjustment.

Hymthesis 4:

There is no difference in academic adjustment scores, as measured by the
academic adjustment subscale of the SACQ, between students with a greater degree
of participation in any of the social components indirectly related to the ROSES
program and those with a lesser degree of participation.

66

Prior knowledge of roomma_t_e_:

Students who knew their roommate before attending MSU scored an average of
149.07 on the academic adjustment subscale which was significantly higher than the
137.42 scored by those who did not know their roommate prior to attendance (t = -2.214;
p < .05).

Satisfaction with roommate relationshg):

There was no significant difference in academic adjustment scores between
students who were more satisfied with their roommate relationship and those who were
less satisfied (t = -.746; p > .05).

Involvement:

There was no significant difference in academic adjustment scores between
students who were involved for three hours per week or more in non-instructional
activities and those who were involved for less than three hour per week (t = -.069;

p > .05).

Hypothesis 4 is rejected. Prior knowledge of one’s roommate was significantly

related to academic adjustment (t = -2.214; p < .05). No other indirect social component

of the ROSES program was related to academic adjustment.

67

Table 20 - T-tests for Participation with Social Components and Academic Adjustment

 

 

 

 

 

 

 

 

 

 

 

ROSES Academic
Component Adjustment
x s.d. t prob.
ROSES roommate Yes 138.28 22.61
No 144.76 25.12 1.303 .20
Proportion study with ROSES 2 .13 138.74 23.39
< .13 141.83 23.30 -.866 .39
Satisfaction with RA 2 4 140.41 23.00
<4 139.15 24.18 .310 .76
ROSES helped socially 2 4 141.45 23.44
<4 138.54 23.10 .823 .41
Prior knowledge of roommate Yes 149.07 26.49
No 137.42 21.97 -2.214 .03"'
Satisfaction with roommate 2 4 139.15 24.23
<4 141.75 21.36 -.716 .48
Hours per week involved 2 3 140.03 23.80
< 3 140.28 22.65 -.O69 .95

 

*p<.05

Social Adjustment

 

The social components unique to the ROSES program included having a ROSES
roommate, studying with other ROSES students, satisfaction with the contact with a
resident assistant, and feeling that the ROSES program had helped socially (i.e. meeting
people, getting involved). The social components indirectly related to the ROSES
program included knowing one’s roommate prior to attending MSU, satisfaction with the
roommate relationship, and the number of hours per week students were involved in non-
instructional activities (i.e. student group, work, community service).

Two-tailed t-tests were conducted to test for differences in social adjustment
scores. For continuous variables, respondents were split into two groups at the median:

those who had a greater degree of participation with the component and those who had a

68

lesser degree of participation with the component. Table 21 presents the means for social
adjustment for the two groups, as well as the results of two-tailed t-tests.

Hymthesis 5:

There is no difference in social adjustment scores, as measured by the
social adjustment su bscale of the SACQ, between students with a greater
degree of participation in the social components directly related to the
ROSES program and those with a lesser degree of participation.

ROSES roommat_e_:

There was no significant difference in social adjustment scores between students
who had roommates who were also participating in the ROSES program and those whose
roommates were not in the ROSES program (t = .402; p_> .05).

Studfimwith ROSES students:

A t-test revealed no significant difference in social adjustment between students
who studied more with other ROSES students, and those who studied less with other
ROSES students (t = .597; p_> .05).

Sat_i§faction with resideflassistaaa

Students who were more satisfied with the contact with a resident assistant scored
an average of 135.59 on the social adj ustment subscale, which was significantly higher
that the average score of 128.16 for students who were less satisfied (t = 2.605;
p_< .05).

Feeling that the ROSES program helped socially:

Students who were more positive that the ROSES program had helped them

socially scored an average of 136.37 on the social adjustment Subscale which was

significantly higher than the average score of 128.88 achieved by the students who were

less positive (t = 2.266; p < .05).

69

Hypothesis 5 is rejected. Feeling that the ROSES program had helped socially
was significantly related to social adjustment (t = 2.266; p_< .05), as was satisfaction with
the contact with a resident assistant (t = 2.605; p < .05). The two remaining social
components of the ROSES program were not significantly related to social adjustment.

Hyp_othesis 6:

There is no difference in social adjustment scores, as measured by the social
adjustment subscale of the SACQ, between students with a greater degree of
participation in the social components indirectly related to the ROSES program and
those with a lesser degree of participation.

Prior knowledge of roommate:

Students who knew their roommate prior to attending MSU had an average
score of 142.31 on the social adjustment subscale, which was significantly higher that
the average score of 131.55 for the students who did not know their roommate prior to
attendance (t = 2.50; p_< .05). ‘

_S_afis_faction with roommate relationship:

Students who were more satisfied with their roommate relationship scored an
average of 135.47 on the social adjustment subscale, which was significantly higher than
the average score of 128.16 for the students who were less satisfied with their roommate
relationship (t = 2.037; p_< .05).

Involvement:

There was no significant difference in the social adjustment scores between

students who reported being involved in non—instructional activities for three hours per

week or more and those who were involved less than three hours per week (t = 1.336;

p_> .05).

70

Hypothesis 6 is rejected. Two of the indirect components of the ROSES program
were significantly related to social adjustment: knowing one’s roommate prior to
attendance (t = 2.50; p_< .05); and satisfaction with one’s roommate relationship (t =
2.037; p_< .05). Involvement in non-curricular activities was not significantly related to

social adjustment.

Table 21 - T-tests for Participation with Social Components and Social Adjustment

 

 

 

 

 

 

 

 

 

 

 

 

ROSES Social
Component Adjustment
x s.d. t prob.

ROSES roommate Yes 132.55 22.30

No 137.43 18.18 1.27 .21
Proportion study with ROSES 2 .13 133.68 19.22

< .13 131.70 24.23 .597 .55
Satisfaction with RA 2 4 135.59 20.83

< 4 125.68 22.76 2.605 .01“
ROSES helped socially 2 4 136.37 20.62

< 4 128.88 22.55 2.266 03*
Prior knowledge of roommate Yes 142.31 20.98

No 131.55 21.39 2.50 .02*
Satisfaction with roommate 2 4 135.47 20.92

< 4 128.16 22.56 2.037 .04“
Hours per week involved 2 3 134.99 20.90

< 3 130.56 22.44 1.336 .18
*p_< .05
Hymthesis 7:

 

There is no difference in social adjustment scores, as measured by the social
adjustment subscale of the SACQ, between students with a greater degree of
participation in any of the academic components directly related to the ROSES
program and those with a lesser degree of participation.

71

Satisfaction with adviser:

There was no significant difference in social adjustment scores between students
who were more positive and those who were less positive about their satisfaction with the
contact with an academic adviser (t = -.679; p > .05).

F eeli_ngknown by the ROSES instructor:

Students who felt known to a greater degree by their ROSES instructor scored an
average of 136.23 on the social adjustment subscale which was significantly higher than
the 128.53 scored by those who felt known to a lesser degree (t = 2.337; p < .05).
Feeling that the ROSES progmn begged academically:

There was no significant difference in adjustment scores between students who
were most positive and those who were less positive in their feeling that the ROSES
program had helped them academically (t = 1.738; p > .05).

Hours per week in class:

There was no significant difference in social adjustment scores between students
who reported being in class 15 hours per week or more and those who were in class for
less than 15 hours per week (t = .850; p_> .05).

Miner week studying;

There was no significant difference in social adjustment scores between students
who reported studying 15 hours per week or more and those who studied less than 15
hours per week (t = .264; p_>.05). .

Hypothesis 7 is rejected. The degree to which students felt known by their

ROSES seminar instructor was significantly related to social adjustment (t = 2.337;

72

p < .05). None of the other academic components of the ROSES program were related to
social adjustment. Table 22 presents the means for social adjustment for the two groups,

as well as the results of t-tests for participation with the academic components and social

adjustment.

Table 22 - T-tests for Participation with Academic Components and Social Adjustment

 

 

ROSES Social
Component Adjustment
x s.d. t prob.
Satisfied with adviser 2 3 132.31 22.22

< 3 134.85 20.28 -.679 .50

 

Known by ROSES instructor 2 3 136.23 19.33
< 3 128.53 24.01 2.337 .02"

 

ROSES helped academically 2 3 134.94 20.67
< 3 128.51 23.54 1.738 .09

 

Hoursperweekinclass 215 133.77 21.78
<15 130.84 21.63 .850 .40

 

 

Hours per week studying _>. 15 133.31 20.16
< 15 132.42 23.65 .264 .79

 

 

 

 

*p < .05

Full Adjustment
To test the relationships between the ROSES components and overall adjustment
to college, t-tests between the academic and social components, and full adjustment
scores were conducted.

Hypgthesis 8:

There is no difference in full adjustment scores, as measured by the SACQ,
between students with a greater degree of participation in any of the academic
components directly related to the ROSES program and those with a lesser degree
of participation.

73

The academic components directly related to the ROSES program are: satisfaction

with an adviser, feeling known by the ROSES seminar instructor, and feeling that the

ROSES program had helped academically.

Satisfaction with adviser:

There was no significant difference in full adjustment scores between those who
were more satisfied and those who were less satisfied with the contact with an academic
adviser (t = -. 1731 p_> .05).

Feeling_kpown by the ROSES instructor:

Students who reported a greater feeling of being known by their ROSES
instructor achieved significantly higher full adjustment scores that students who reported
feeling less well known by the ROSES instructor (t = 2.151; p_< .05).

Feeling that the ROSES progrlim helped academically:

There was no significant difference in full adjustment scores between students
who were most positive and those who were less positive in their feeling that the ROSES
program had helped them academically (t = 1.768; g> .05).

Hypothesis 8 is rejected. Feeling known by the ROSES instructor was
significantly related to full adjustment (t = 2.151; p < .05). The other two direct
academic components were not related to full adjustment.

W

There is no difference in full adjustment scores, as measured by the SACQ,
between students with a greater degree of participation in any of the academic
components indirectly related to the ROSES program and those with a lesser degree

of participation.

74

Academic components that are indirectly related to the ROSES program are the
number of hours per week students report being in class, and the number of hours per
week students report studying.

Hoursy per weekfiin clas_s_:

There was no significant difference in full adjustment scores for students who
reported being in class 15 hours per week or more and those who reported being in class
for less than 15 hours per week (t = 1.536; p_> .05).

Hour; per week studying:

There was no significant difference in full adjustment scores for students who
reported studying 15 hours per week or more and those who reported studying less than
15 hours per week (t = 1.622; p_> .05).

Hypothesis 9 is accepted. Neither the number of hours per week in class nor the
hours per week spent studying was significantly related to full adjustment. Table 23
presents the means for full adjustment for the two groups, as well as the results of t-tests

for participation with the academic components and full adjustment.

75

Table 23 - T-tests for Participation with Academic Components and Full Adjustment

 

 

ROSES Full
Component Adj ustment
x s.d. t prob.
Satisfied with adviser 2 3 417.82 61.36

< 3 419.73 60.87 -.173 .86

 

Known by ROSES instructor 2 3 426.94 59.76
< 3 406.92 61.32 2.151 03*

 

ROSES helped academically Z 3 424.03 58.64
< 3 405.87 64.84 1.768 .08

 

Hours per week in class 215 423.59 62.42
<15 408.92 58.54 1.536 .13

 

 

Hours per week studying _>_ 15 425.47 58.13
< 15 410.28 63.96 1.622 .11

 

 

 

 

*g< .05

Hymthesis 10:

There is no difference in full adjustment scores, as measured by the
SACQ, between students with a greater degree of participation in any of the
social components directly related to the ROSES program and those with a
lesser degree of participation.

The social components unique to the ROSES program were having a
ROSES roommate, studying with other ROSES students, being satisfied with the
contact with a resident assistant, and feeling that the ROSES program had helped
socially (i.e. meeting people, getting involved).

ROSES roommate:
There was no significant difference in full adjustment scores between

students who had roommates who were also participating in the ROSES program

and those whose roommates were not in the ROSES program (t = 1.272; p_> .05).

76

Studw'ngth ROSES students:

There was no significant difference in full adjustment scores between
students who spent a greater proportion of their total study time studying with
other ROSES students and those who studied less with other ROSES students
(t = -.562; p_> .05).

_Sat_r§f_‘action with resident aLssisaLnL;

There was no significant difference in full adjustment scores between
students who were more satisfied with the contact with a resident assistant and
those who were less satisfied (t = 1.721; p_> .05).

Feeling that the ROSES progr_am helped sociaflyy

There was no significant difference in full adjustment scores between
students who were more positive and those who were less positive in their feeling
that the ROSES program had helped them socially (t = 1.333; p_> .05).

Hypothesis 10 is accepted. None of the social components directly related
to the ROSES program were significantly related to full adjustment.

Hymthesis 11:

There is no difference in full adjustment scores, as measured by the
SACQ, between students with a greater degree of participation in any of the
social components indirectly related to the ROSES program and those with a
lesser degree of participation.

The social components indirectly related to the ROSES program included
knowing one’s roommate prior to attending MSU, satisfaction with the roommate
relationship, satisfaction with the contact with a resident assistant, and the number of
hours per week students were involved in non-instructional activities (i.e. student groups,

work, community service).

77

Prior knowledge of roommat_e_:

Students who knew their roommate prior to attending MSU scored an
average of 449.93 on the full adjustment scale which was significantly higher than
the 410.89 achieved by the students who did not know their roommate prior to
attending MSU (t = -3. 102; p_< .05).
§a11§faction with roommate relafionsLig

There was no significant difference in full adjustment scores between
students who were more satisfied with their roommate relationship and those who
were less satisfied with their roommate relationship (t = .777; p> .05).

Involvement:

There was no significant difference in full adjustment scores between students
who reported being involved in non-instructional activities for three hours per week or
more and those who were involved less than three hours per week (t = .341; p_> .05).

Hypothesis 11 is rejected. Knowing one’s roommate prior to attending
MSU was significantly related to full adjustment (t = -3.102; p_< .05). None of
the other indirect social components were related to full adjustment. Table 24
presents the means for full adj ustment for the two groups, as well as the results of
t-tests for participation with the social components of the ROSES program and

full adjustment.

78

Table 24 - T-tests for Participation with Social Components and Full Adjustment

 

 

ROSES Full
Component Adjustment
x s.d. t prob.
ROSES roommate Yes 430.43 60.31

No 414.90 61.38 1.272 .21

 

Proportion study with ROSES .>_ .13 415.87 59.32
<.13 421.16 63.67 -.562 .58

 

 

Satisfaction with RA 2 4 423.24 59.76
< 4 404.91 63.20 1.721 .09
ROSES helped socially 2 4 424.12 60.96

< 4 411.76 60.92 1.333 .18

 

Prior knowledge of roommate Yes 449.93 59.14
No 410.89 62.07 -3.102 .00"

 

Satisfaction with roommate 2 4 420.89 60.58
<4 413.04 62.83 .777 .44

 

 

Hours per week involved .2 3 419.96 59.91
< 3 416.78 62.55 .341 .73

 

 

 

 

** p_< .01

Fall Semester Grade Point Average
To test for differences in fall semester grade point average, medians were used to
divide respondents into two groups: those who had a greater degree of participation with
the ROSES components and those who had a lesser degree of participation.

Hypgthesis 12:

There is no difference in fall grade point average between students with a
greater degree of participation in any of the academic components directly related
to the ROSES program and those with a lesser degree of participation.

The academic components directly related to the ROSES program are: satisfaction

with an adviser, feeling known by the ROSES seminar instructor, and feeling that the

ROSES program had helped academically.

79

Swamion with adviser:

There was no significant difference in fall semester grade point averages between
students who were more satisfied with their contact with an academic adviser and those
who were less satisfied (t = 1.687; p_> .05).

Feelirygflown by ROSES instructor:

There was no significant difference in fall semester grade point average for
students who felt known to a greater degree by their ROSES instructor and those who felt
known to a lesser degree (t = 1.425; p_> .05).

Feeling ROSES helped academically:

Students who were more positive in their feeling that the ROSES program had
helped them socially earned an average fall semester grade point average of 2.95, which
was significantly higher than the 2.67 earned by students who were less positive
(t = 2.060; p_< .05).

Hypothesis 12 is rejected. Feeling that the ROSES program helped academically
was significantly related to fall semester grade point average (t = 2.060; p_< .05).
However, the other two ROSES indicators were unrelated to grade point average.

Hymthesis 13:

There is no difference in fall grade point average between students with a
greater degree of participation in any of the academic components indirectly related
to the ROSES program and those with a lesser degree of participation.

Academic components that are indirectly related to the ROSES program are the
number of hours per week students report being in class, and the number of hours per

week students report studying.

80

Hours in class:

There was no significant difference in fall semester grade point average between
students who spent 15 or more hours per week in class and those who spent less than 15
hours per week in class (t = 1.439; p_> .05).

Hours studying:

Students who spent 15 or more hours per week studying earned a fall semester
grade point average of 3.01, which was significantly higher than the 2.70 grade point
average earned by students who studied fewer than 15 hours per week (t = 2.705;
p_< .05).

Hypothesis 13 is rejected. Fall semester grade point average was significantly
related to the number of hours per week students reported studying (t = 2.705; p_< .05).
Table 25 presents the mean grade point averages for the two groups, as well as the results

of t-tests for participation with the academic components of the ROSES program and fall

semester grade point average.

Table 25 - T-tests for Participation with Academic Components and Fall Semester GPA

 

 

 

 

 

 

 

 

ROSES Fall GPA
Component
x s.d. t prob.

Satisfied with adviser 2 3 2.92 .722

< 3 2.66 .893 1.687 .10
Known by ROSES instructor 2 3 2.93 .755

< 3 2.77 .784 1.425 .16
ROSES helped academically z 3 2.94 .701

< 3 2.67 .878 2.060 .04*
Hours per week in class 2 15 2.95 .703

< 15 2.75 .868 1.439 .15
Hours per week studying 2 15 3.01 .745

< 15 2.70 .762 2.705 .01*

 

 

 

*p_< .05

81

Hymthesis 14:

There is no difference in fall grade point average between students with a
greater degree of participation in any of the social components directly related to
the ROSES program and those with a lesser degree of participation.

The social components that were unique to the ROSES program were
having a ROSES roommate, studying with other ROSES students, satisfaction
with the contact with a resident assistant, and feeling that the ROSES program
had helped socially (i.e. meeting people, getting involved).

ROSES roommate:

There was no significant difference in the fall semester grade point average for
students who had a ROSES roommate and those who did not (t = -.666; p_> .05).
Studyingwith ROSES students:

There was no significant difference in the fall semester grade point average
between students who spent 13 percent or more of their total study time studying with
other ROSES students and those who studied with other ROSES students less than 13
percent ofthe time (t = -1.522; p_> .05).

Satisfaction with resident assistant:

There was no significant difference in the fall semester grade point average
between students who were more satisfied with their contact with a resident assistant and
those who were less satisfied (t = .325; p_> .05).

Feeling that ROSES helped socially:
There was no significance difference in the fall semester grade point average

between students who were more positive in their feeling that the ROSES program had

helped them socially and those who were less positive (t = .660; p_> .05).

82

Hypothesis 14 is accepted. There were no significant differences in fall semester
grade point average between students who participated more in the social components of
the ROSES program and those who participated less.

Hymtbesis 15:

There is no difference in fall grade point average between students with a
greater degree of participation in any of the social components indirectly related to
the ROSES program and those with a lesser degree of participation.

The social components indirectly related to the ROSES program included
knowing one’s roommate prior to attending MSU, satisfaction with the roommate
relationship, and the number of hours per week students were involved in non-
instructional activities (i.e. student groups, work, community service).

Prior knowledge of roommjag

There was no significant difference in the fall semester grade point average
between students who knew their roommate prior to attending MSU and those who did
not (t = 1.296; p_> .05).

Satisfaction with roommafl

There was no significant difference in the fall semester grade point average
between students who were more satisfied with their roommate relationship and those
who were less satisfied (t = -.059; p_> .05).

Involvement:

There was no significant difference in the fall semester grade point average

between students who spent three or more hours per week involved in non-instructional

activities and those who were involved fewer than three hours per week (t = .606;

p_> .05).

83

Hypothesis 15 is accepted. There were no significant differences in fall semester
grade point average between students who participated more in the social components
indirectly related to the ROSES program and those who participated less. Table 26
presents the mean grade point averages for the two groups, as well as the results of t-tests

for participation in the social components of the ROSES program and fall semester grade

point average.

Table 26 - T-tests for Participation with Social Components and Fall Semester GPA

 

 

ROSES Fall GPA
Component
x s.d. t prob.
ROSES roommate Yes 2.84 .811
No 2.92 .591 -.666 .51

 

Proportion study with ROSES 2.13 2.79 .685
<.13 2.96 .844 -1.522 .13

 

 

 

 

 

 

Satisfaction with RA 2 4 2.87 .752
< 4 2.83 .824 .325 .75

ROSES helped socially 2 4 2.91 .725
< 4 2.84 .777 .660 .51

Prior knowledge of roommate Yes 2.30 .606
No 2.82 .805 1.296 .20

Satisfaction with roommate 2 4 2.85 .793
< 4 2.86 .724 -.059 .95

Hours per week involved 2 3 2.88 .747

 

 

 

< 3 2.80 .833 .606 .55

 

Summary of Bivariate Analyses
A summary of the results of bivariate tests of significance between the individual
ROSES components and the outcomes of academic adjustment, social adjustment, full
adjustment, and fall semester grade point average are presented in Table 27. An “*”

indicates a significant relationship between the individual variable and outcome.

84

The analyses revealed that background variables were related to academic
adjustment and fall semester grade point average. Gender was significantly related to
academic adjustment and to fall gpa; ethnicity was significantly related to fall gpa; and
predicted gpa was significantly related to academic adjustment and fall gpa.

The only academic components of the ROSES program significantly related to
academic adjustment were the number of hours per week spent in class and studying,
both of which are not directly related to the ROSES program. The degree to which
students felt known by their ROSES seminar instructor was significantly related to social
adjustment and full adjustment. The degree to which students felt the ROSES program
had helped them academically and the number of hours students reported studying were
both significantly related to fall gpa.

The social components of the ROSES program that were significantly. related to
social adjustment were satisfaction with the contact with a resident assistant, feeling that
ROSES had helped socially, knowing one’s roommate prior to attending MSU, and being
satisfied with the roommate relationship. Knowing one’s roommate prior to attending

MSU was also significantly related to academic adjustment and fiill adjustment.

85

Table 27 - Summary of Relationships between Components and Outcomes

 

Academic Social Full Fall
GPA

 

BACKGROUND
Gender *
Ethnicity
College
Predicted GPA * *

ACADEMIC
Satisfied with

Adviser
Known by ROSES

Instructor * *
ROSES helped

Academically
Class (hours)
Study (hours) * *

SOCIAL
ROSES roommate
Study with ROSES
Knew roommate *
Satisfied with RA
ROSES helped

Socially
Satisfied with
Roommate
Involvement (hours)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Multiple Regression Analysis
Multiple regression was utilized to test the full model, with all variables entered,
for the outcomes of academic adjustment, social adjustment, and fall grade point average.
Collinearity was assessed for all regression models by examining the tolerance statistics.
All regression models had low tolerance statistics (close to 0); thus, multi-collinearity
was not deemed problematic (George and Mallery, 1995).
The same predictor variables were entered for each regression to determine the

relative importance of each predictor for each of the four outcomes (academic

86

adjustment, social adjustment, full adjustment, and fall grade point average).

Background variables in each regression included gender, race/ethnicity, college of
enrollment, and predicted grade point average. The predicted grade point average is
based upon high school grade point average, test scores (ACT or SAT), and quality of the
high school attended.

A second category of variables measured the academic components of the ROSES
program and consisted of satisfaction with contact with an academic adviser; feeling
known by the ROSES seminar instructor; the degree to which students felt the ROSES
program had helped them academically; the number of hours per week respondents
reported being in class; and the number of hours per week respondents reported studying.

A third category of variables entered into the regression incorporated the social
components of the ROSES program: having a ROSES student as a roommate; the
proportion of study time students spent studying with other ROSES students; satisfaction
with the contact with a resident assistant, the degree to which students felt the ROSES
program had helped them socially; prior knowledge of their roommate; satisfaction with
the roommate relationship; and the number of hours per week the student was engaged in
non-instructional activities such as work, student organizations and community service.

Finally, the ROSES seminar grade was entered into each regression equation.
The seminar grade is based on the number of points earned by students for attendance
and completion of assignments. Thus, the grade reflected the degree to which students
attended and participated in the weekly ROSES seminar class and evening programs

facilitated by the residence life staff.

87

Dummy variables were created for some of the variables. For gender, female was
coded 1 and male was coded 0. A dummy variable was created for college of enrollment;
with a code of 1 if the respondent had a major in the College of Engineering and a code
of 0 if they were in the College of Natural Science or in the College of Agriculture and
Natural Resources. Race/ethnicity was coded as a l to indicate non-minority students
and 0 to indicate students in all other racial categories. Having a ROSES roommate was
coded 1, while having a roommate who was not a ROSES student was coded 0. Knowing
one’s roommate prior to attending MSU was coded 1, and not knowing one’s roommate
prior to attendance was coded O. Satisfaction scores (satisfaction with the roommate,
satisfaction with the Resident Assistant and satisfaction with the academic adviser) were
coded 0 through 5, with 0 being “does not apply” and 5 indicating “very satisfied”. How
well the respondent felt the ROSES seminar instructor knew them was coded 1 for “not at
all” through 5 for “very well”. The degree to which students believed the ROSES
program had helped them socially and academically was coded from 1 for “helped not at
all” to 5 for “helped to a great extent”. The number of hours each week that respondents
reported studying with other ROSES students was expressed as a proportion of the total
number of hours each respondent reported studying.

Multiple regression analyses were conducted for three different outcomes:
academic adjustment, social adjustment, and fall semester grade point average. The same
variables were entered into each of the regressions. Of particular interest was the amount
of variance in the outcome variable explained by the predictor variables. The
unstandardized regression coefficients (B) indicate the effect of each individual variable

on the outcome variable. Additionally, by examining the relationships between

88

individual predictor variables and the outcome, insight was gained with regard to the
relative importance of various predictors to that outcome. Because the independent
variables had different units of measurement, the Beta coefficients were used for
comparative purposes. All regression results were interpreted at the .05 level of
significance, but .05 - .10 was also examined for marginally significant results.
Academic Adjustment

As shown in Table 28, background variables, social component variables,
academic component variables, and the ROSES seminar grade, taken together; accounted
for 20% of the variance in academic adjustment scores. This relationship was statistically
significant (F17343 = 2.08, p_< .05). In this regression model, the ROSES seminar grade
was significantly positively related to academic adjustment (t 17,143 = 2.00, p < .05).
Knowing one’s roommate prior to attending MSU was marginally significant (67,143 =
1.93; p < .10). For each point increase in the seminar grade, the academic adjustment
score increased by 5.35 points. Knowing one’s roommate prior to attendance added

10.01 points to the academic adjustment score.

89

 

Table 29 - Regression Coefficients for Model Predicting Academic Adjustment

 

Predictor Variables
B Beta t Sig._

 

 

 

 

 

(Constant) 82.31 4. 12 .00
Engineering (dummyy 8.071 .146 1.485 .14
Ethnicity (dummy) .501 .008 .093 .93
Gender (dummy) 7.231 .149 1.567 . 12
Predicted GPA 4.159 .054 .627 .53

 

Know roommate (dummy) 10.006 .165 1.933 .06+
ROSES roommate (dummy) -2.516 -.042 -.492 .62
Involvement (hours per week) -.301 -.O98 -1.223 .22

 

 

 

 

 

 

 

 

Study with ROSES 4.974 .037 .449 .65
Satisfied with RA -.983 -.055 -.682 .50
Satisfied with roommate .606 .030 .373 .71
ROSES helped socially .594 .033 .336 .74
Study (hours per week) .354 .128 1.517 .13
Satisfied with adviser .587 .038 .457 .65

 

Known by ROSES instructor 1.059 .046 .542 .59
ROSES helped academically 1.175 .061 .630 .53
Class (hours pg week) .299 .052 .649 .52
Seminar grade 5.349 .184 2.004 .05*
F17,143 = 2.08; p < .05; R2 = .20

*p_< .05; ’p_< .10

 

 

 

 

 

 

 

 

 

Social Adjustment

All variables in the model accounted for 21% of the variance in social adjustment
scores, and were significantly associated with social adjustment (F1734; = 2.24; g< .05).
The degree of satisfaction with one’s roommate (Q7343 = 2.05; p< .05) and the number of
hours spent in class 017,143 = 2.54; p_< .05) were both significantly positively related to
social adjustment. The regression model is presented in Table 30. Each incremental
increase in satisfaction with one’s roommate added 3.07 points to the social adjustment
score. For each additional hour spent in class, social adjustment scores increased 1.08

points.

90

Table 30 - Regression Coefficients for Model Predicting Social Adjustment

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Predictor variables
B Beta t Sig._
(Constant) 108.437 5.904 .00
Egineering (dummy) 5.189 .101 1.038 .30
Ethnicity (dummy) -1.076 -.018 -.218 .83
Gender (dummy) 6.746 .150 1.590 .1 1
Predicted GPA -8.961 -.125 -1.469 .14
Know roommate (dummy) 7.1 18 .127 1.496 .14
ROSES roommate (dummy) -3.463 -.062 -.737 .46
Involvement (hours per week) .292 .103 1.292 .20
Study with ROSES 13.553 .108 1.330 .19
Satisfied with RA 1.501 .091 1.132 .26
Satisfied with roommate 3.070 .164 2.053 .04"
ROSES helped socially 2.620 .157 1.612 .11
Study (hours per week) -.073 -.028 -.341 .73
Satisfied with adviser —1.023 -.O72 -.868 .39
Known by ROSES instructor 2.573 .121 1.433 . 15
ROSES helped academically -.658 -.O37 -.383 .70
Class (hours per week) 1.077 .203 2.542 .01“
Seminar grade -.583 -.022 -.238 .81
Fm” = 2.24; p_< .05; R2 = .21
*p < .05
Full Adjustment

The regression model including background variables, social component
variables, academic component variables, and the ROSES seminar grade explained 17%
of the variance in full adjustment scores, and the overall relationship was significant
(F17343 = 1.78; p_< .05). Hours spent in class (67,143 = 2.10; p_< .05) and knowing one’s
roommate (67,143 = 2.27; p_< .05) were significantly positively related to full adjustment.
For each hour spent in class, full adjustment score increased 2.61 points. Knowing one’s
roommate added 31.58 points to the full adjustment score. The final regression model is

presented in Table 31.

91

 

Table 31 - Regression Coefficients for Model Predicting Full Adjustment

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Predictor Variables

B Beta t 8L
(Constant) 289.343 5.376 .00
Engineering (dummy) 15.886 .108 1.085 .28
Ethnicity (dummy) 3.649 .021 .253 .80
Gender (dummy) 21.109 .164 1.698 .09
Predicted GPA -5.422 -.026 -.303 .76
Know roommate gummy) 31.578 .196 2.265 .03*
ROSES roommate (dummy) -5.805 -.037 -.422 .67
Involvement (hours per week -.093 -.011 -. 141 .89
Study with ROSES 19.006 .053 .637 .53
Satisfied with RA 1.193 .025 .307 .76
Satisfied with roommate 5.618 .105 1.282 .20
ROSES helped socially 5.274 .110 1.108 .27
Study (hours per week) .315 .043 .502 .62
Satisfied with adviser -1.673 -.O41 -.484 .63
Known byROSES instructor 4.388 .072 .834 .41
ROSES helped academically -.650 -.013 -. 129 .90
Class (houraper weeky 2.605 .171 2.098 .04“
Seminar grade 6.675 .086 .928 .36
F1734; = 1.78; p_< .05; RI: .17
*p < .05

Fall Semester Grade Point Average

Fall semester grade point average was the final outcome assessed by multiple
regression. Because the seminar grade was included in the calculation of the fall
semester grade point average, in this analysis, fall gpa was recalculated to exclude the
seminar grade. Background variables, social component variables, academic component
variables, and the ROSES seminar grade, taken together, accounted for 42% of the
variation in fall semester grade point average. The model was also statistically
significant (R7343 = 5.973; p_< .01). Predicted grade point average was significantly
positively related to fall semester grade point average (tum = 4.21; p_< .01), with each

point increase in predicted grade point average adding an additional .31 point to the fall

92

semester grade point average. The other significant individual variable in this model was
the ROSES seminar grade (67,143 = 4.273; p<.01), with each point increase in the ROSES
seminar grade increasing the fall semester grade point average by .33 point. The

coefficients for the final regression model are presented in Table 32.

Table 32 - Regression Coefficients for Model Predicting Fall Semester GPA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Predictor Variables

B Beta t Sig._
(Consan -2.007 -3.291 .00
Engineering (dummy) .221 .112 1.347 .18
Ethnicity (dummy) .181 .078 1.121 .26
Gender @ummy) .177 . 103 1.275 .20
Predicted GPA .859 .312 4.211 00*
Know roommate (dummy) -.024 -.011 -. 152 .88
ROSES roommate (dummy) -.073 -.034 -.471 .64
Involvement (hours per week) .007 .033 .477 .63
Study with ROSES .264 .055 .785 .43
Satisfied with RA .017 .027 .396 .69
Satisfied with roommate .066 .092 1.341 .18
ROSES helped socially -.058 -.O91 -1.089 .28
Study (hours per wecfi .004 .039 .546 .59
Satisfied with adviser .043 .078 1.099 .27
Known by ROSES instructor .041 .050 .695 .49
ROSES helped academically .059 .087 1.053 .29
Class (hours per week) .009 .045 .658 .51
Seminar grade .344 .334 4.273 .00“
F1114, = 5.973; p< .01; R2 = .42
*p < .05

Summary

Bivariate analyses identified significant relationships between individual variables
and outcomes. Regression analyses tested each hypothesis using the full set of predictor

variables.

93

Academic Adjustment

For academic adjustment, the seminar grade (Beta = .184) was a stronger
predictor than knowing one’s roommate prior to attendance (Beta = . 165) though they
were both significant in the regression. Neither of these variables were academic
components of the ROSES program. With all variables included in the model, no other
variables were significant predictors of academic adjustment.

Social Adjustment

The hours spent in class (Beta = .203) was a stronger predictor of social
adjustment than the degree of satisfaction with the roommate relationship (Beta = .164).
With all variables included in the regression, these two variables were the only ones
which significantly predicted social adjustment. Both of these variables were considered
components of the ROSES program, albeit indirect; that is, they are not exclusive
components of the ROSES program. Only the degree of satisfaction with the roommate

relationship was a direct social component.

Full Adjustment

With all variables entered in the regression, only knowing one’s roommate prior
to attendance at MSU and the number of hours per week spent in class were significant
predictors of full adjustment. Prior knowledge of one’s roommate (Beta = .196) was a
stronger predictor than the number of hours per week in class (Beta = .171). Neither of
these variables are uniquely related to the ROSES program.

Fall Semester Grade Point Average
With all variables entered in the regression, only the predicted grade point

average and seminar grade were significant predictors of fall semester grade point

94

average. The seminar grade (Beta = .427) was a stronger predictor than the predicted
grade point average (Beta = .323). None of the academic components or social
components of the ROSES program were significant predictors of fall semester grade
point average.

Table 32 presents a summary of the relationships between the predictor variables
and the outcomes of academic adjustment, social adjustment, full adjustment, and fall
semester grade point average. The bivariate relationships revealed that individual
academic components of the ROSES program were related to academic adjustment, full
adjustment, and to fall semester grade point average; but not to social adjustment. Some
of the individual social components of the ROSES program were related to social
adjustment and fiill adjustment; but not to academic adjustment or to fall semester grade
point average. The results of the regression analyses revealed that with background
variables, academic components, social components, and seminar grade entered into the
model, the significant predictors of academic adjustment were the seminar grade and
knowing one’s roommate prior to attendance at MSU. The significant predictors of
social adjustment, with all variables entered into the regression, were the hours per week
spent in class and satisfaction with one’s roommate relationship. The significant
predictors of fiill adjustment were the number of hours per week in class and knowing
one’s roommate prior to attendance at MSU. With all variables entered into the
regression, the significant predictors of fall semester grade point average were the

seminar grade and the predicted grade point average.

95

Table 32 - Summary of Relationships between Predictors and Outcomes

 

Academic

Social

Full

Fall
GPA

 

BACKGROUND

 

Gender

*

 

Ethnicity

 

College

 

Predicted GPA

*X

 

ACADEMIC

 

Satisfied with
Adviser

 

Known by ROSES
Instructor

 

ROSES helped
Academically

 

Class (hours)

 

Study (hours)

 

SOCIAL

 

ROSES roommate

 

Study with ROSES

 

Satisfied with RA

 

ROSES helped
Socially

 

Knew roommate

*X

*X

 

Satisfied with
Roommate

*X

 

Involvement (hours)

 

ROSES Seminar

 

 

X

 

 

 

 

Note. * = significant bivariate relationship
X = significant predictor of outcome

96

 

Chapter 5
SUMMARY, DISCUSSION, AND RECOMMENDATIONS
Summary and Discussion

The purpose of this study was to examine the contribution of a residential
program for first year science and engineering students on their adjustment to college.
Specifically, social and academic aspects of the program were examined to determine
their relationship with academic adj ustment, social adjustment, full adjustment, and fall
semester grade point average. All first year students (221 total) enrolled in the
Residential Option for Science and Engineering Students (ROSES) were included in this
study.

All respondents received an introductory letter and two surveys near the end of
fall semester, 1997. This time was selected in order to give students nearly a full
semester of experiences in college and the ROSES program, yet not conflict with the end
of the semester and finals week. A total of 199 surveys were returned, representing a
90% return rate. Of the returned surveys, 174 were complete and used for statistical
analyses, yielding a 79% usable return rate. Data were analyzed using the SPSS for
Windows Statistical Package for the Social Sciences.

Two primary research questions guided the study: 1) Do components of the
ROSES program contribute differentially to academic adjustment, social adjustment, full
adjustment, and fall semester grade point average; and 2) Which individual components
of the ROSES program make the most significant contributions to predicting adjustment
to college and fall semester grade point average? Bivariate relationships between

individual components of the ROSES program and outcomes were examined. Multiple

97

regression was utilized to identify significant predictors of academic adjustment, social
adjustment, full adjustment and fall semester grade point average. Data were analyzed at
the .05 level of significance, with .05 - .10 also examined in the multiple regression
analyses for marginally significant results.
Relationships between Individual Variables and Outcomes
Background Variables

Background variables consisted of gender, ethnicity, college of enrollment, and
predicted grade point average. Females achieved significantly higher academic
adjustment than males. Females also had significantly higher fall semester grade point
averages than males, even though there was no significant difference in the predicted
grade point averages between females and males. This finding is interesting because
females are often thought to achieve lower grades in math and science. The first semester
curriculum for all students consists of general education course requirements. Included
in the typical first semester course schedule for entering science and engineering students
are introductory math and science courses. Further research should explore whether
females who participated in the ROSES program as first-year students continue to earn
higher grades in math, science, and engineering courses during subsequent academic
years. Nonetheless, this finding for female students in the ROSES program should not be
overlooked in the male-dominated fields of science and engineering.

Ethnicity was significantly related to fall semester grade point average. Minority
students in the ROSES program had significantly lower grade point averages than non-
minority students, despite entering college with predicted grade point averages that were

not significantly different. This finding is troubling, not only for the success of minority

98

students, but also as it relates to the under-representation of minority group members in
science and engineering fields.

Predicted grade point average was significantly related to academic adj ustment
and to fall semester grade point average. There were no significant relationships between
the college of enrollment and academic adjustment, social adjustment, full adjustment, or
fall semester grade point average.

Academic Variables

Not surprisingly, the number of hours students reported being in class and the
number of hours students reported studying were significantly related to academic
adjustment. Additionally, the number of hours students reported studying was
significantly related to fall semester grade point average. These relationships are
reasonable to understand. Faculty and staff should certainly use this information to
promote class attendance and studying, especially among new students.

Satisfaction with the contact with an academic adviser was not related to any form
of adjustment or to fall semester grade point average. This finding is unexpected, given
the intentional efforts to connect students with academic advisers. The advisers often
meet the ROSES students during the summer orientation program. Once school starts,
academic advisers for the ROSES students attempt various strategies to maintain on-
going contact with students throughout the first semester. Some students are required to
meet with their academic adviser as part of the ROSES seminar, and some advisers serve
as instructors for the ROSES seminar.

Feeling known by the ROSES seminar instructor was not related to academic

adjustment or fall semester grade point average, but was significantly related to social

99

adj ustment and full adjustment. It is possible that, for those advisers who are ROSES
seminar instructors, students relate to them more as instructors than as advisers. In any
case, the quality of the relationship between students and the instructors for the seminar
appears to be important to social adjustment and full adjustment.

Students’ feelings that the ROSES program helped them academically (i.e.
classes, studying) was positively related to fall semester grade point average. This
finding could also be explained by other factors (such as motivation or general attitude
toward academic work) which could contribute to both.

Social Variables

Knowing one’s roommate prior to attending MSU was significantly related to
academic, social, and full adjustment. Further, being satisfied with one’s roommate
relationship was significantly related to social adjustment. These findings suggest that
comfort, or at least the lack of uncertainty about one’s roommate, may be beneficial, not
only to social adjustment, but also to academic and full adjustment. It is reasonable that
the quality of the roommate relationship may provide elements of the social validation
that Terenzini et a1. (1992) identified as crucial to the transition to college. However,
neither of these variables (prior knowledge of roommate or the satisfaction with the
roommate relationship) are directly related to the ROSES program, and there is nothing
to suggest that the importance of roommate relationships is unique to the ROSES
program.

An unexpected finding was that having a roommate who was also a ROSES
student was not related to social adjustment or to fall semester grade point average. It

was hypothesized, and implied in the design of the ROSES program, that students would

100

benefit from having roommates who were in the same program and going through similar
experiences. It may be that any effects of having a ROSES roommate are evident later in
one’s academic experience.

The proportion of time students spent studying with other ROSES students was
not related to academic adjustment, social adjustment, full adjustment, or to grade point
average. One of the underlying premises of the ROSES program was that students would
find academic support and assistance from one another that might assist them
academically and socially. For the group of students in this study, only about 17% of
their total study time was spent with other ROSES students. It was anticipated that
students in the ROSES program would spend a greater proportion of their total study time
with one another because they have several of the same courses. This finding is difficult
to interpret due to the lack of a comparison group (students in the same classes but who
do not live in the same residence hall). It could be that studying together 17% of the time
is more than other groups of first-year students study together. In any case, studying with
other ROSES students was not significantly related to adjustment or to fall semester
grade point average.

Satisfaction with the contact with a resident assistant was related to social
adjustment. As returning students, resident assistants are in positions to be viewed by
students as institutional agents who are also students. Resident assistants interpret the
rules and procedures of the institution, assist individual students with personal issues, and
plan activities. In the ROSES program, the resident assistants are involved with the new
student orientation program and the evening programs which supplement the ROSES

seminar class. Thus, students have opportunities to see resident assistants often and in a

101

variety of roles. The resident assistants may act as peer socialization agents in the living
environment.

Involvement in non-instructional activities did not relate to any form of
adjustment or grade point average. It may be that students need a longer period of time
than what was afforded in this study in order to establish meaningful involvement
opportunities. Further investigation of the role of involvement in non-instructional
activities and adjustment over a longer period of time may be valuable.

The feeling that the ROSES program helped students socially (i.e. meeting
people, getting involved) was significantly related to social adjustment. This finding, in
combination with the significance of the relationships with the roommate and resident
assistant, suggests at least an initial importance of the social and interpersonal
experiences for new students.

Predictors of Adjustment and Fall Semester Grade Point Average

The second research question of interest in this study was to identify the
components of the ROSES program which predicted academic adjustment, social
adjustment, full adjustment, and fall semester grade point average. Multiple regression
was used to identify the significant predictors for each outcome.

Academic Adjustment

Only one of the variables found to be significantly related to academic adjustment
in the bivariate analyses was identified by multiple regression as a significant predictor of
academic adjustment. Knowing one’s roommate prior to attending MSU was considered

a social component; yet, it was a significant predictor of academic adjustment. This

102

finding was surprising and suggests the importance of the social environment, not only
for social adjustment, but also for academic adjustment.

The ROSES seminar grade was also a significant predictor of academic
adjustment. This finding seems congruent with the topics that are covered in the seminar
class and evening sessions. Topics include academic skills such as test taking and time
management, as well as issues such as learning styles and career exploration. Students
are also exposed to a variety of academic resources on campus.

Perhaps most interesting is the finding that none of the variables identified in this
study as academic components of the ROSES program were significant predictors of
academic adjustment. Despite the efforts of advisers and ROSES seminar instructors to
develop connections with new students, the two measures in this study (satisfaction with
the contact with an adviser and feeling known by a ROSES instructor) were not
significant predictors of academic adjustment. Even though the number of hours spent in
class and the number of hours spent studying were significantly related to academic
adjustment in the bivariate analyses, neither were identified as significant predictors in
the regression analysis.

Overall, the results of the regression analysis do not suggest that greater
involvement with the academic components of the ROSES program results in higher
academic adjustment. Prior knowledge of one’s roommate (identified in this study as a
social component) is indirectly related to the ROSES program in that knowing one’s
roommate is not a design element of the ROSES program. The only significant predictor
of academic adjustment that is specifically related to the ROSES program is the ROSES

seminar class.

103

Social Adjustment

The number of hours students reported being in class was a significant predictor
of social adjustment. This finding was surprising in that the number of hours per week
spent in class was considered to be an academic component. One possible explanation
for this finding is that being in class may increase one’s interactions with others (peers
and faculty), which may contribute to social adjustment.

Satisfaction with the relationship with one’s roommate was significantly related to
social adjustment and was also a significant predictor of social adjustment. Satisfaction
with the roommate relationship is not directly related to the ROSES program, but in this
study, it was considered a social component. This finding seems to highlight the
importance of the immediate environment (one’s room) for the successful social
adj ustment of new students.

None of the other individual variables of the ROSES program were significant
predictors of social adjustment. Relationships with peers in the enviromnent, specifically
with other ROSES students and with resident assistants, were not predictors of social
adjustment. Thus, the hypothesis that greater involvement in the social components of
the ROSES program results in higher social adjustment is only minimally supported,
since the only significant predictors of social adjustment were indirectly related to the
ROSES program.

Full Adjustment

Knowing one’s roommate prior to attendance at MSU and the number of hours

per week students reported spending in class were significant predictors of full

adjustment. Again, the importance of the roommate relationship is crucial. The positive

104

relationship between the number of hours spent in class and full adjustment may suggest
that the structure of attending class and the contact with others are important to overall
adjustment. Neither of the significant predictors of full adjustment are features directly
related to the ROSES program.

Fall Semester Grade Point Average

Regression analysis identified the predicted grade point average as the only
background variable that was a significant predictor of fall grade point average, despite
the significant relationships between gender and fall grade point average and between
ethnicity and fall grade point average. Thus, with all other components of the ROSES
program considered, gender and ethnicity are not significant predictors of fall grade point
average.

The ROSES seminar grade was also a significant predictor of fall semester grade
point average. Because the grade is based upon class attendance, evening session
attendance, and completion of assignments, it could be that the student habits required for
successful seminar performance are also practiced in other classes, which contributes to
successful academic performance in other courses.

It was hypothesized that the social components would not be significantly related
to fall semester grade point average. In the bivariate analyses, the number of hours of
studying and feeling that the ROSES program had helped academically were both
significantly related to fall semester grade point average. However, none of the academic
components or social components of the ROSES program were identified by multiple

regression as significant predictors of fall semester grade point average.

105

Summag

Even though there were some significant relationships between some individual
variables and outcomes, multivariate analyses did not identify the significant predictors
that had been hypothesized. Academic components did not significantly predict
academic adj ustment or fall semester grade point average. The only social component
that significantly predicted social adjustment was the degree of satisfaction with the
roommate relationship, which is not a directly related component of the ROSES program.

Implications for Practice

The findings of this study, both the expected and the unexpected, provide
implications for staff and institutional leaders.
Implications for Staff

One striking implication of this study is the importance of the roommate
relationship on adjustment to college. This may be true for students not only in a
residential program such as the ROSES program, but for students in other programs or in
no special program. Thus, it seems wise for administrators of living-learning programs
and housing systems to allow students to choose their roommates; and for residence hall
staff to focus on the development of satisfactory roommate relationships. Certainly,
many students enter college without the opportunity or inclination to live with someone
they already know. Residence life staff should consider implementing strategies which
would more quickly assist roommates in establishing roommate relationships that are
comfortable.

It also seems that living-learning programs, such as the ROSES program, are

designed based upon knowledge or beliefs that may not be fully understood or tested.

106

For example, there appears to be support for the idea of housing students together who
have classes or majors in common. Presumably, this arrangement should make it easier
for students to study with one another. Yet, in this study, the proportion of time students
spent studying with other ROSES students did not significantly relate to adjustment or to
fall semester grade point average, nor did it significantly predict academic or social
adjustment or fall grade point average. Perhaps additional or different interventions are
necessary to achieve the maximum benefit from housing students together who have
classes or majors in common. It may be that students do not know how to productively
study with others. Instructors should consider designing assignments that will assist
students in developing the skills necessary for working with others to complete a task.
Another benefit would be that such group work may reduce the degree of competiveness
among students that can be detrimental to student success.
Implications for Institutional Leaders

For leaders of institutions, especially of the size and complexity of Michigan State
University, the importance of the student transition experience should not be overlooked.
This study suggests that for students in their first semester of college, the immediate and
interpersonal environment is important. In a very general sense, it appears that those
students who form satisfactory relationships with those nearest to them in their
environment experience greater social adjustment.

The small classroom experience of the ROSES seminar allows students to have
contact with an adult who acts as an agent of the institution. Yet the relationships with
advisers and ROSES instructors, as measured in this study, do not significantly contribute

to adjustment or fall semester grade point average. The allocation of resources so that

107

first-year students in the ROSES program have a small classroom experience is well—
intentioned, but should be examined further to determine the relative costs in terms of
resources and benefits to students. It may also be important to note that the academic
advisers for the ROSES program are professional advisers and not faculty. Faculty
advisers may be perceived differently by students and their impact on students may be
different than that of professional advisers. Assigning faculty advisers to first-year
students is a significant institutional resource, but one that may be worth exploring.

Leaders should continue to encourage and support the collaborative efforts
between academic affairs and student affairs which are necessary to implement living-
leaming programs. New programs should be designed to address issues or deficiencies
identified through careful study, with the goals of the programs clearly articulated.
Additionally, systematic assessment must be conducted to determine the contributions of
living-learning programs and to guide the innovations made to existing programs.
Assessment and evaluation data should be used to determine the appropriate roles and
responsibilities of academic and student affairs staff members.

Finally, many living-learning programs focus on experiences for first-year
students. Without diminishing the attention to first-year students, institutional leaders
ought to encourage faculty and staff to consider what happens to students beyond their
first year, with special attention to the sophomore year. Do living-learning programs for
first-year students create a set of expectations about college that lead to disillusionment
once the first year program has ended? Are students who enter the institution through a
smaller, more comfortable living-learning program ready and able to negotiate the larger

university, or do they experience another transition?

108

Limitations of the Study

A limitation of this study is the reliance on self-reported information about
participation and involvement with components of the ROSES program, as well as self-
reported responses to the items on the adjustment surveys. Adjustment scores from this
group of respondents were similar to scores obtained in other research studies (see Baker
& Siryk, 1989), so there is some assurance of the use of this survey for this purpose.
Additionally, the elements that compose the ROSES program are difficult to isolate and
measure as individual components.

The respondents in this study were not a randomly drawn sample from the general
student population; thus, the results can not be generalized to other groups of first-year
students. There is a self-selection factor among these respondents in that students
interested in science and engineering majors request to participate in the ROSES
program; thus, they may exhibit a higher level of motivation, readiness, and interest in
college experiences than peers who do not express interest in this program. Additionally,
due to space limitations in the program, two of the participating colleges establish
selection criteria for students interested in the ROSES program. It may be interesting to
examine the effects of a living-learning program on the adjustment and academic success
of students who are less academically prepared.

Finally, participation in an academic, residential program is only one set of a
multitude of experiences which influence and shape the lives of college students. This
study did not attempt to measure or to control for the myriad of academic and social

experiences which are potentially related to adjustment to college or to fall semester

109

grade point average. This study also did not control for personal or psychological factors
within individual students which may be related to adj ustment.
Recommendations for Further Research

This study was primarily interested in outcomes of adjustment to college and the
contribution of a residential program on those outcomes. Other research about college
students suggests that the first six weeks are crucial in the transition to college. However, ‘
Baker and Siryk (1989) report some significant effects on at least some of the adjustment I
scales depending on whether the survey was administered during the first semester or the
second semester. Therefore, it would be beneficial to examine the contributions of the
ROSES program to adjustment over a longer period of time. For example, it may be that
the relationships formed with peers in the first year of college will lead to less
competition among students when they are engaged in upper level science or engineering
courses. Controlled, longitudinal studies should be undertaken to explore whether
students who participate in the ROSES program as first-year students progress differently
through their majors and ultimately to graduation.

Given the factors which contribute to students switching out of science and
engineering majors (Seymour, 1992), it would be insightful to investigate major-
switching among students who enter the university as ROSES students. While retention
within science and engineering majors is a desired outcome of the ROSES program, there
will undoubtedly be students who switch to non-science and non-engineering majors. It
would be interesting to know if ROSES students who ultimately switch into other majors

cite different reasons for switching than those identified by Seymour’s research.

110

This study raises questions about the impacts of clustering students with similar
academic interests in one residence hall. While this study did not compare students in
this hall-based program to similar students not participating in a similar program, the
added residential features of this program did not seem to have powerful predictability
relative to adjustment. Further research which compares participants of living-learning
programs to non-participants is needed to further investigate the added value of the
residential experience. It is also possible that living-learning programs associated with
different academic disciplines would yield a different array of relationships between the
program components, adjustment, and grade point average.

Certainly, multi-faceted adjustment to college and fall semester grade point
average are only a few of the potentially valuable outcomes of a living-learning program.
Additional research ought to examine relationships between participating in these sorts of
programs and other outcomes associated with higher education, including cognitive and
intellectual development, psychosocial development, and educational attainment. It
would also be valuable to conduct qualitative research with students in living-learning
programs in order to describe the kinds of experiences that students identify as
meaningful to their adjustment and success.

Current conversations about undergraduate education are laced with suggestions
for programs similar to the ROSES program. Living-learning programs, learning
communities, and freshman interest groups are intended to add integration and coherence
to the undergraduate experience. These programs are designed to increase the
connections between curricular and co-curricular aspects of the collegiate experience.

Program developers must be explicit about the program goals and implement strategies

111

consistent with the goals and mission of the program. Even when conceptually sound,
these programs require resources of time, effort, and money. Evaluation reseach should
be conducted to determine the effectiveness and efficiency of these various innovations,
and the degree to which the desired goals are met. Additionally, program developers
must be cognizant of the effects of such programs on students from diverse backgrounds

and in different academic disciplines.

112

APPENDIX A

APPENDIX A

SCIENCE AND ENGINEERING
BACCALAUREATE DEGREE PROGRAMS
MICHIGAN STATE UNIVERSITY

College of Agriculture and Natural Resources
Agribusiness Management
Agriculture and Natural Resources Communications
Agriscience
Animal Science
Biosystems Engineering
Building Construction Management
Crop and Soil Science
Environmental and Natural Resource Policy Issues
Fisheries and Wildlife
Food Industry Management
Food Science
Forestry
Horticulture
Packaging
Park, Recreation, and Tourism Resources
Public Resource Management

College of Engineering
Biosystems Engineering
Chemical Engineering
Civil Engineering
Computer Science
Computer Engineering
Electrical Engineering
Engineering Arts
Material Science and Engineering
Manufacturing Engineering
Mechanical Engineering
Mechanics

113.

College of Natural Science
Astrophysics
Biochemistry
Biochemistry/Biotechnology
Botany and Plant Pathology
Chemical Physics
Chemistry
Clinical Laboratory Science
Computational Mathematics
Entomology
Environmental Geoscience
Geological Sciences
Mathematics
Medical Technology
Microbiology
Physics
Physiology
Statistics and Probability
Zoology

114

 

APPENDIX B

APPENDIX B

SURVEY ITEM CLUSTERS

Survey items on the Student Adaptation to College Questionnaire (SACQ) are organized
into 12 critical clusters, which comprise four subscales.

ACADEMIC ADJUSTMENT SUBSCALE

 

 

Cluster Item Description
ls definite about reasons for being in
college.
Has well-defined academic goals.
Motivation Considers college degree important.

Doubts value of college degree.
Enjoys academic work.

Most interests are not related to course
work.

 

Keeps up-to-date with academic work.
Application Does not work as hard as he or she should.
Is not motivated to study.

Attends classes regularly.

 

Finds academic work difficulty.

Does not function well during exams.

Is satisfied with academic performance.
Performance Does not feel smart enough for course
work.

Does not use study time efficiently.
Enjoys writing papers for courses.

Has trouble concentrating when studying.
Does not do well academically, considering
effort.

Has trouble getting started on homework.

 

 

Is satisfied with variety of courses.
Is satisfied with quality of courses.
Academic Environment ls satisfied with program of courses.
Is satisfied with professors.

Is satisfied with academic situation.

 

 

115

 

APPENDIX B (cont’d).

SOCIAL ADJUSTMENT SUBSCALE

 

Cluster Item Description

 

Fits in well with college environment.
Is very involved with college social
activities.

General Is adjusting well to college.

Has several close social ties.

Is satisfied with social participation.
Is satisfied with social life.

 

Is meeting people and making friends.

Has informal contact with professors.

Gets along well with roommates.

Has difficulty feeling at ease with others at
Other PeOple college.

Does not mix well with opposite sex.

Feels different from others in undesirable
ways.

Has good friends to talk about problems
with.

 

Is lonesome for home.
Nostalgia Feels lonely a lot.
Would rather be home.

 

Is pleased about decision to attend this
Social Environment college.

Enjoys living in a dormitory.

Is satisfied with extracurricular activities.

 

 

 

116

 

 

APPENDIX B (cont’d).

PERSONAL-EMOTIONAL SUBSCALE

 

Cluster Item Description

 

Feels tense or nervous.

Feels blue and moody.

Being independent has not been easy.

Is not able to control emotions well lately.
Psychological Has thought about seeking psychological
help recently.

Gets aneg too easily lately.

Sometimes things gets muddled too easily.
Worries a lot about college expenses.

Has trouble coping with college stress.

 

 

Feels tired a lot lately.

Appetite is good.

Has a lot of headaches.

Physical Gained or lost a lot of weight lately.
Is not sleeping well.

Feels in good health.

 

 

ATTACHMENT SUBSCALE

 

Cluster Item Description

 

Is pleased with decision to go to college.
Thinks a lot about dropping of college
General permanently.

Is thinking about taking time off from
college.

 

 

Is pleased about attending this college.
Would prefer to be at another college.
This College Expects to finish bachelor’s degree.

Is thinking about transferring to another
college.

 

 

117

 

 

 

APPENDIX C

APPENDIX C

ROSES EXPERIENCES SURVEY

Please answer the following questions based on your experiences this semester. There
are no correct or incorrect answers.

By providing your PID, you authorize the researcher to use selected institutional data (fall
semester course enrollment, ROSES seminar attendance, ACT/SAT score, high school F,
GPA, enrollment status for spring semester, expected fall semester GPA, fall semester '
GPA, academic status at the beginning of spring semester) for research purposes only.

Information from this survey will be used for research purposes only. Research findings
will not associate individual students with specific responses.

:.—-.II.'-§. nl'T‘l'l" :- v .'

 

Your PID:

 

1. How many roommates do you have (or for a majority of the semester)?
zero one two (if zero, skip to item 2)
a. Do you have a roommate(s) in the ROSES program?
yes no
b. Did you know your roommate(s) before coming to MSU?
yes no
2. For the following activities, indicate the approximate numbers of hours per week you
have been involved in each activity this semester. You can round your answers to the
nearest whole hour. If you have had no involvement, place a zero in the space
provided.

Hours per week Activity

Hall groups (caucus, government, floor council, other groups)
Campus organizations (i.e. academic or social organizations)
Part-time work

Off-campus organizations (i.e. religious or community groups)
Community service (volunteer work)

Floor activities (i.e. IM sports, social activities)

Class

Study (i.e. homework, reading for class, other academic work)

:qcrhor-Log‘e

118

3. Of the total hours you study, how many hours per week do you study:

a. in your own room

b. in another student room in your residence hall

c. in a consulting room in Bailey Hall (B108, B208, B308)
d. in a lounge in your residence hall

e. in a location other than any residence hall

4. Of the total hours you study, how many hours per week do you study:

a. by yourself

b. with other ROSES student(s)

c. with non-ROSES student(s)

d. with a consultant in Bailey Hall

For the following items, please indicate the number of times you have interacted with the
individuals listed. If you have had no contact, please write a zero in the space provided.

5. How many times this semester have you:

__ a. met with a consultant for ROSES students in Bailey Hall

_ b. talked with your academic adviser

__ c. talked with an instructor (professor, TA, ROSES seminar instructor)
outside of class

6. How many times this semester have you talked about academics (i.e. classes,
grades, professors, major, studying) with:

a. your academic adviser

b. an instructor (professor, TA)
c. a peer leader

(1. a resident assistant

e. the hall director

7. How many times this semester have you talked about career information with:

a. your academic adviser

b. an instructor (professor, TA)
c. a peer leader

d. a resident assistant

e. the hall director

119

 

8. How many times this semester have you talked about the ROSES seminar or
program with:

your academic adviser

an instructor (professor, TA)
a peer leader

a resident assistant

the hall director

9. How many times this semester have you talked about social concerns (i.e.
roommate, friends, extracurricular activities) with:

your academic adviser

an instructor (professor, TA)
a peer leader

a resident assistant

the hall director

10. How many time this semester have you talked about personal concerns (i.e. health,
stresses) with:

your academic adviser

an instructor (professor, TA)
a peer leader

a resident assistant

the hall director

1 1. How many times this semester have you talked about general concerns (your
decision to come to MSU, campus resources) with:

your academic adviser

an instructor (professor, TA)
a peer leader

a resident assistant

the hall director

120

‘9'

w
. -'l' . i '\

12. For each of the following items, please indicate your degree of satisfaction by
placing the number from the scale in the space provided to the left of each item.

 

Does not Very Very
Apply Satisfied Satisfied Dissatisfied Dissatisfied
O 1 2 3 4 5
a. your roommate relationship
b. contact with an academic adviser
c. contact with a peer leader 1”
(1. contact with a resident assistant ‘
e. contact with an instructor I.
13. Please respond to the following items by placing the number from the scale in the
space provided to the left of the item. "
Not at all Somewhat Moderately well Fairly well Very well
1 2 3 4 5
a. How well do you feel your academic adviser knows you?
b. How well do you feel your ROSES seminar instructor knows you?
c. How well do you feel any of your instructors for other courses
knows you?
d. How well do you feel your resident assistant knows you?
e. How well do you feel any of the ROSES peer leaders knows you?

14. How well do you believe the ROSES program has helped you in the following areas?
Place your response from the scale in the space provided.

Helped to a Helped to a Helped to a Helped Helped
great extent good extent fair extent somewhat not at all

1 2 3 4 5

a Academically (i.e. classes, studying)

b. Personally (i.e. support, assistance)

c. Gain information about your major

(I Gain information about MSU

e Socially (i.e. meeting people, getting involved)

15. Would you recommend the ROSES program to another freshman in your major?

Yes No

121

16. At this time, what is your intent regarding your major? (indicate the most likely
choice by placing an “X” in the blank)

__ stay in my current major

__ change to a different major in science, engineering, or agriculture and
natural resources

__ change to a major outside of science, engineering, or agriculture and
natural resources

__ I have no idea

122

v

__. x— A“_ _
‘u .

 

APPENDIX D

 

APPENDIX D

H0. VIP; h.m0. VIP.“

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

00A 500 N00- v00- 00.0 m00 *40N0 **0N.0 2.3.0 420 .I.NN.0 ..sz0 ...L-m0 .10—.0 m00 :0N0 EEEom
50.0 00; 0~0- S0 :0 no.0 00.0 0.0- —0.0 M00 N00 2.0 m00- _00- 00.0 00.0- .2925
N00- 050- 00._ M00 N50 N50 00.0 50.0 _0.0 ELNO .420 N00 N00 500 :0 N00- <M\>>.Hmm
.Eoou
V0.0- 000 m00 00._ 0~0 S0 v0.0- 00.0- :0 000- V00 V00 V00 w00 1mN0 v00- \>> dam
00.0 :0 2.0 0—0 00; 20 **NNO 00.0- :0m0 1:0 :0 N00 500 ".3050 :VNO :0 .00m 30:
mmmom
m00 no.0 S0 00 N~ .0 00; 00.0- 0~ .0- 00.0 00.0 000- *0_ 0- 00.0- 0.0 2 .0 000- :5 amuam
1.0N0 00.0 00.0 v00- :NNO 000- 00.0 sum—.0 LNO v_0 *:.0 .420 ”INN. 2.0 00.0 .050 huam
:0N0 S0- 500 000- 00.0- 0—0- .320 004 00.0 000 2.0 20 {-50 «*0N0 2.0 2.0 mmflU
*20 0.0 _00 :0 :0m0 00.0 *shN0 00.0 00A .30 :VNO _0.0 :0N. 00.0 00.0 .4000 0&2“ 903
26911
42.0 m00 **_N.0 000- ::0 00.0 :0 00.0 “.30 004 2.0 2.3.0 20 4:0 .050 2.0 mMmOM
:NNO N00 .420 #00 3.0 M00. ...:0 2.0 *svm0 2.0 00._ 20 ..2..mN.0 50.0 00.0 {L0 .>vd\3.umm
_.:Lm0 20 N00 #00 N00 .40—.0- ...E0 20 0.0 *0~.0 2.0 00._ :0v0 0_ .0 @00- e0~0 #50 00.5
1590 m00- N00 V0.0 500 00.0- ......NNO *:.0 :0N0 2.0 ..imN0 .I.0v0 00A *smN0 m00- £4340 «aw—Eh
1.050 _0.0- 50.0 00.0 3.000 50.0 0~.0 **0N0 00.0 ...:0 50.0 0—0 $3.10 00.0 :50 ..imw0 =sm
M00 00.0 2.0 **MNO :vm0 2.0 00.0 2.0 00.0 s0~0 00.0 V0.0- m00- .2100 00; 3.94.0 360m
*e0N0 000- N00- v00- :0 000- .4050 2.0 *20 20 42.0 3,050 .3340 5300 334.0 00; owEovmodx
mflmom
é .Eoom .oom \3 fina< Bog .>0< <00 <AO
HEP—ow, .202: \3 Adm \3 4mm 30: >035 swvam mafia—U 30$ mmmom \3 0mm .020 =mm =3“— EEom fidu<

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

350830 98 85253 5.0 thE cone—250 -mm 2an

123

APPENDIX E

 

\Q

....J

 

 

OFFICE OF
RESEARCH
AND
GRADUATE
STUDIES

University Commlttee on
Research lnvolvln
Human Subjects
(UCRIHS)

Michigan State University
246 Administration Building
East Lansing, Michigan
48824-1046

517/355-2180
FAX: 517/432-1171

The M..:ntgan State University
mashmmmmDme
HMMWMAMM

MSU 15 an ailments-action.
coral-omortuntnr Institution

APPENDIX E

MICHIGAN STATE

 

U N l V E R S l T Y
October 24, 1997
TO: Kathryn M. Moore
418 Erickson Hall
RE: IRB#: 97-513
TITLE: ADJUSTMENT TO COLLEGE: THE CONTRIBUTION OF A

LIVING-LEARING PROGRAM FOR SCIENCE AND
ENGINEERING STUDENTS

REVISION REQUESTED: N/A
CATEGORY: 1 - C
APPROVAL DATE: 10/22/97

The University Committee on Research Involving Human Subjects'(UCRIHS)

review of this project is complete._ I am pleased to adVise that the

rights and welfare of the human subjects appear to be adequately
rotected and methods to obtain informed consent are appropriate.

herefore,
above.

RENEWAL :

REVISIONS:

PROBLEMS/
CHANGES:

the UCRIHS approved this project and any reVisions listed

UCRIHS approval is valid for one calendar year, beginning with
the approval date shown above. Investigators planning to
continue a project beyond one year must use the green renewal
form (enclosed with t e original approval letter or when a
project is renewed) to seek u date certification. There is a
maXimum of four such expedite renewals possible. Investigators
wishing to continue a preject beyond that time need to submit it
again or complete reView.

UCRIHS must review any changes in procedures involving human
subjects, rior to initiation of t e change. If this is done at
the time o renewal, please use the green renewal form. To
revise an approved protocol at any 0 her time during the year,
send your written request to the CRIHS Chair, requesting reVised
approval and referencing the project's IRB # and title. Include
in your request a description of the change and any revised
instruments, consent forms or advertisements that are applicable.

Should either of the following arise during the course of the
work, investigators must noti y UCRIHS promptly: (l) roblems
(unexpected Side effects, comp aints, etc.) involving uman
subjects or (2) changes in the research environment or new
information indicating greater risk to the human sub'ects than
eXisted when the protocol was previously reviewed an approved.

If we can be of any future help, please do not hesitate to contact us
2-

at (517)355-2180 or FAX (517)4

Sincerely,

   
 
  
  

DEW : bed

vid E. Wright,
CRIHS Chair

1171.

 
  

cc: Cynthia K. Helman /

...—J
I‘d
Jo.

 

APPENDIX F

APPENDIX F

October 6, 1997

Western Psychological Services
Publishers and Distributors
12031 Wilshire Boulevard

Los Angeles, CA 90025

A‘l 1N: Ms. Susan Weinberg

I am a doctoral student in the Higher, Adult and Lifelong Education program at Michigan
State University. The topic of my dissertation research is college student adjustment,
and I would like to use the Student Adaptation to College Questionnaire.

My research specifically examines the contribution of a living-learning program on the
adjustment of first year science and engineering students. Several hundred first year
students will receive the survey near the end of Fall Semester (December, 1997).

In previous telephone communication with Western Psychological Services, I understand
that there is a discount for purchasing instruments to be used in student research projects.
Thus, I am requesting the discount for the Student Adaptation to College Questionnaire
(hand-scored version). I will need the discount through May, 1998.

This dissertation research is a requirement for the completion of my doctoral degree. In
accordance with policies at Michigan State University, I am an enrolled student and will
be enrolled during the time of data collection. All research procedures conform to APA
standards as well as to the policies at Michigan State University governing research
pr0jects.

Sincerely,

Cynthia K. Helman

Doctoral Student

Michigan State University
(517)339-3632

email: helman@pilot.msu.edu

125

 

APPENDIX G

APPENDIX C

December ‘I, 1997

Dear ROSES student:

I am a doctoral student in the Higher, Adult and Lifelong Education program here at MSU. I am
conducting research for my dissertation and am requesting your assistance.

The transition from high school and home to college and living in a residence hall is a period of
adjustment for most students. My dissertation research focuses on the transition made by first
semester students. In particular, I am interested in learning about the experiencesof students in
the ROSES program and their transition to college. I am asking all students in the ROSES
program this Fall to complete the enclosed two surveys.

I know this is a busy time of the semester; however, I would appreciate it very much if you would
take a few minutes to share your experiences with me by completing the surveys. The two
surveys should take only about 25 minutes to complete.

You may be assured of complete confidentiality. I will use your PlD only to match the two
surveys, and to access selected institutional data (SAT/ACT score, high school GPA, predicted
GPA, fall class schedule, and ROSES seminar attendance, fall semester GPA, and spring
semester enrollment status). Once matched, all data will be assigned a random four digit
number; date will be stored and analyzed only by that code. The code sheet linking Ple and
the random numbers will be securely stored apart from all other data and records pertaining to
this research project.

Please return the completed surveys in a sealed envelope (enclosed) to the Bailey Hall Resident
Director’s office (A101 Bailey) by December 8, 1997.

You have had a variety of opportunities (i.e. attending an extra success seminar, attending a
workshop, and other experiences announced by seminar instructors) to earn bonus points in the
ROSES seminar. The ROSES seminar instructors have agreed that returning the survey by
December 8, 1997 is also an opportunity to gain a bonus point toward your total ln-Class
Activity Points for the ROSES seminar. When you turn in your surveys to the Resident Director,
you will be asked to sign a slip of paper which will be fonuarded to your ROSES seminar
instructor so you receive credit for returning the surveys.

You indicate your voluntary agreement to participate by completing and returning the surveys.
Participation in this study is voluntary and there is no penalty for not responding. You may
choose to omit any question on the surveys. By providing your PID, you authorize me to access
the institutional data indicated above. All results and information will be treated with strict
confidence and all respondents will remain anonymous in all reports of the research findings.
Copies of the results of this research will be available in Bailey Hall during the spring semester,
1998.

I would be happy to answer any questions you may have about this study. I can be reached at 2-
2493 or helman@pilot.msu.edu.

Thank you very much for your thoughtful responses and your assistance with this study.

Cindy Helman
Graduate Student

126

BIBLIOGRAPHY

Van's-... ' Arr—1e.“

 

BIBLIOGRAPHY

Astin, A. W. (1977). Preventing students from dropping out. San Francisco:
Jossey-Bass, 1nc., Publishers.

Atkinson, R. C. (1990). Supply and demand for scientists and engineers: A
national crisis in the making. Science, 248, 425-432.

Baker, R. W. (1986). The student adaptation to college questionnaire and its use
ipan intervention study with freshmen. Paper presented at the Annual Meeting of the
American College Personnel Association, New Orleans, LA.

Baker, R. W., & Siryk, B. (1980). Alienation and freshman transition into
college. Journal of College Student Personnelg19, 437-442.

Baker, R. W., & Siryk, B. (1983). Social propensity and college adjustment.
Journal of College Student Personnel, 24(4), 331-336.

Baker, R. W., & Siryk, B. (1986). Exploratory intervention with a scale
measuring adjustment to college. Journal of CougselinLPsychologL 33(1), 31-3 8.

Baker, R. W., & Siryk, B. (1989). Student Adaptation to CollggaQaestionngirp
(SACQ). Los Angeles, CA: Western Psychological Services.

Baker, R. W., Siryk, B., & McNeil, O. V. (1985). Expectation and reality in
freshman adjustment to college. Jouml of Counseling Psychology, 32(1), 94-103.

Barthelemy, K. J ., & Fine, M. A. (1995). The relations between residence hall
climate and adjustment in college students. College Student Jomgk 29(4), 465-475.

Blimling, G. S. (1993). The influence of college residence balls on students. In
J. C. Smart (Ed), Higher education: Handbook of theory and research (Vol. D(, pp. 248-
307). New York: Agathon Press.

Borg, W. R., & Gall, M. D. (1979). Edugagional research: An introduction. New
York: Longrnan, Inc.

Bragg, T. A. (1994). A study of the relationship between adiustrnent to college
and freshman retention. Unpublished doctoral dissertation, University of Oklahoma,
Norman, Oklahoma.

Brooks 11, J. H., & DuBois, D. L. (1995). Individual and environmental
predictors of adjustment during the first year of college. Journal of College Student
Development, 36(4), 347-360.

127

Buchanan, S. R. (1991). A longitudinal study of the effects of concurrently
taking a modified university 10] course during the high school senior year on students’
anticipated adjustment to college and actual adjustment to college as compared to the
adjustment to college of students who concurrently took a traditional lecture course or
took no course during the high school senior year (Doctoral dissertation, University of
South Carolina, 1991). Dissertation Abstracts IntemationLSZ-WA, 2386.

Chickering, A. W. (1975). Commuting versus resident students. San Francisco:
J ossey-Bass Publishers, Inc.

Christie, N. G., & Dinham, S. M. (1991). Institutional and external influences on
social integration in the freshman year. J ourn_aal of Higher Edugation. 62(4), 412-436.

Cooper, S. E., & Robinson, D. A. G. (1988). Psychometric properties of the
student adaptation to college questionnaire with engineering and science students.
Measuremergaynd Evaluation in Counselingand Development, 21, 124-129.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests.
Psychometrika, 16(3), 297-334.

Dahmus, S., Bemardin, H. J ., & Bemardin, K. (1992). Student adaptation to
college questionnaire. Maasurement and Evaluation in Cougelingand Develgrment, 25,
139-142.

Draper, R. W. (1991). On your own: The freshman experience at an American
university (Doctoral dissertation, University of Oregon, 1991). Dissertation Abstra_g_t§
International 52-04A 1221.

 

Feldman, K. A., & Newcomb, T. M. (1969). The impact of college on students.
San Francisco: Jossey-Bass, Inc., Publishers.

Fisher, S., & Hood, B. (1987). The stress of the transition to university: A
longitudinal study of psychological disturbance, absent-mindedness and vulnerability to
homesickness. British Journal of Psychology/J8, 425-441.

George, D. & Mallery, P. (1995). SPSS/PC+ step by step: A simple guide gig
reference. Belmont, CA: Wadsworth Publishing Company.

Harris, B. C. (1991). The college student experience: How social support and
loneliness relate to adaptation and attrition (Doctoral dissertation, The George
Washington University, 1991). Dissertation Abstgrcts International 52-08B 4520.

 

Jewler, A. J. (1989). Elements of an effective seminar: The university 101
program. In M. L. Upcrafi & J. N. Gardner (Eds), The freshman year experience:
Helpinggtudents survive in collega . San Francisco: J ossey-Bass Publishers, Inc.

128

 

Johnson, G. M., Staton, A. Q., & Jorgensen-Earp, C. R. (1995). An ecological
perspective on the transition of new university freshmen. Communication Education. 44,

336-352.

Krotseng, M. V. (1992). Predicting persistence from the student adaptation to
college questionnaire: Early warning or siren song? Reseaazh in Higher Education,
33(1), 99-111.

Lapsley, D. K., Rice, K. G., & F itzGerald, D. P. (1990). Adolescent attachment,
identity, and adj ustment to college: Implications for the continuity of adaptation
hypothesis. Journal of Counseling and Development, 68, 561-565.

Lapsley, D. K., Rice, K. G., & Shadid, G. E. (1989). Psychological separation
and adjustment to college. Journal of Counseligg Psychology, 36(3), 286-294.

 

Levine, A. (1989). Shaping higher education's future: Demographic glides anal
opportunities, 1990-2000. San Francisco: Jossey-Bass Inc., Publishers.

Lopez, F. G. (1991). Patterns of family conflict adn their relation to college
student adjustment. Jourpal of Counselingand Develmgmerg69(3), 257-260.

Lopez, F. 6., Campbell, V. L., & Watkins, C. E., Jr. (1988). Family structure,
phsychological separation, and college adjustment: A canonical analysis and cross-
validation. Journal of Counselinngchology, 35(4), 402-409.

Lopez, F. G., Campbell, V. L., & Watkins, C. E., Jr. (1986). Depression,
psychological separation, and college adjustment: An investigation of sex differences.
Journal of Counaeling Psychology, 33, 53-56.

Martin, N. K., & Dixon, P. N. (1989). The effects of freshman orientation and
locus of control on adjustment to college. Journal of Coflgge Student Development,
3_0(4), 362-367.

Mooney, S. P., Sherman, M. F., & LoPresto, C. T. (1991). Academic locus of
control, self-esteem, and perceived distance from home as predictors of college
adjustment. Journal of Counseling and Development, 69(5), 445-448.

Murguia, E., Padilla, R. V., & Pavel, M. (1991). Ethnicity and the concept of
social integration in Tinto's model of institutional departure. Journal of College Student
Development, 32(5), 433-439.

Nelson, R. B., Scott, T. B., & Bryan, W. A. (1984). Precollege characteristics
and early college experiences as predictors of freshman year persistence. Journal of
College Student Personnel, 25(1), 50-54.

129

Noel, L. (1985). Increasing student retention: new challenges and potential. In L.
Noel, R. Levitz, D. Saluri, & Associates (Eds), Increasiag student retention: Effective
progzams and prrgices for reducingghe dropout r_a_ta (pp. 1-27). San Francisco:
Jossey-Bass, Inc., Publishers.

Nosow, S. (1975). An attitudinal comparison of residential college seniors with
other seniors. Journal of College Student Personnel, 16(1), 17-23.

Panos, R. J ., & Astin, A. W. (1968). Attrition among college students. American
Educatirml Research Journal, 5(1), 57-72.

Pascarella, E. T., & Terenzini, P. T. (1980). Predicting freshman persistence and
voluntary dropout decisions from a theoretical model. Journal of Higher Edugtion.
51 (1), 60-75.

Pascarella, E. T., & Terenzini, P. T. (1991). How college affects students. San
Francisco: Jossey-Bass Inc., Publishers.

Pascarella, E. T., Terenzini, P. T., & Wolfle, L. M. (1986). Orientation to college
and freshman year persistence/withdrawal decisions. Journal of Higher Education. 57(2),
15 5-1 75.

Pemberton, C. ( 1969). An Evaluation of a Living-Learning Residence Ha1_l
Progzam (ERIC Document Reproduction Service No. ED 077 082)

Pool, R. (1990). Who will do science in the 19903? Science, 248, 433-435.

Rice, K. G. (1992). Separation-individuation and adjustment to college: A
longitudinal study. Journal of Cou_aspling Psychology. 39(2), 203-213.

Seymour E. (1992). Undergraduate problems with teaching and advising in SME
majors—Explaining gender differences in attrition rates. Journal of College Science
Teaching, 21(5), 284-292.

Schwitzer, A. M., McGovern, T. V., & Robbins, S. B. (1991). Adjustment
outcomes of a freshman seminar: A utilization-focused approach. Journal of Collega
Student Development, 32(6), 484-489.

Smith, M. A., & Baker, R. W. (1987). Freshman decidedness regarding
academic major and adjustment to college. Psychological Reports. 61. 847-853.

Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary
review and synthesis. Interchange, 1(1), 64-85.

Spady, W. G. (1971). Dropouts from higher education: Toward an empirical
model. Interchange, 2(3), 38-62.

130

Stoecker, J ., Pascarella, E. T., & Wolfle, L. M. (1988). Persistence in higher
education: A 9-year test of a theoretical model. Journal of College Student
Development, 29(3), 196-209.

Terenzini, P. T., Allison, K. W., Millar, S. B., Rendon, L. 1., Upcraft, M. L.,
Gregg, P., & Jalomo, R. (1992). The transition to college project: Final report .
University Park, PA: The Pennsylvania State University.

Terenzini, P. T., & Pascarella, E. T. (1976). The relation of freshman students'
social and academic integration munition (ERIC Document Reproduction Service No.
ED 126 843 )

Terenzini, P. T., & Pascarella, E. T. (1977). Voluntary freshman attrition and
patterns of social and academic integration in a university: A test of a conceptual model.
Researph in Higher Education, 6, 25-43.

Terenzini, P. T., & Pascarella, E. T. (1978). The relation of students' precollege
characteristics and freshman year experience to voluntary attrition. Research in Higher
Education, 9, 347-366.

Terenzini, P. T., Rendon, L. I., Upcraft, M. L., Millar, S. B., Allison, K. W.,
Gregg, P. L., & Jalomo, R. (1996). The transition to college: Diverse students, diverse
stories. In F. K. Stage, G. L. Anaya, J. P. Bean, D. Hossler, & G. D. Kuh (Eds), College
students: The evolving nature of research (pp. 54-65). Needham Heights, MA: Simon
and Schuster Custom Publishing.

Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of
recent research. Review of Educational Research, 45(1), 89-125.

Tinto, V. (1985). Dropping out and other forms of withdrawal from college. In
L. Noel, R. Levitz, D. Saluri, & and Associates (Eds), Increasing student retention:
Effective pr_ogams and praatices for reducingahe dropout rata (pp. 28—43). San Francisco:
Jossey-Bass, Inc., Publishers.

Tinto, V. (1988). Stages of student departure: Reflections on the longitudinal
character of student leaving. Jourpal of Higgr Education, 59(4), 438-455.

Tinto, V. (1993). Leaving college: rethinking the causes and cures of student
attrition. Chicago: The University of Chicago Press.

 

Upcraft, M. L., & Gardner, J. N. (1989). The freshman year experience: Helping
student survive in collega. San Francisco: Jossey-Bass Publishers, Inc.

Van Gennep, A. (1960). The rites of passage (M. B. Vizedom & G. L. Caffee,
Trans). Chicago: The University of Chicago Press.

131

 

 

Wallace, W. L. (1966). Student culture: Sociaj structure and continuity in a
liberal arts college. Chicago: Aldine Publishing Co.

Wilson, R. J ., Anderson, S. A., & Fleming, W. M. (1987). Commuter and
resident students' personal and family adjustment. Journal of Collage Student Personnel,
_2_§(3), 229-233.

Zeller, W. J ., & Mosier, R. (1993). Culture shock and the first year experience.
The Journal of College and University Student Housing. 23(2), 19-23.

Zmich, R., Lux, P., DeRosa, S., & Gordon, T. (1997). Student guide to the
ROSES experience (5th Anniversary) [Brochure]. East Lansing, MI: Michigan State
University.

 

132

I'IICHIGRN STATE UNIV. LIBRARIES
lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll
31293018342067