Building Psychosocial Engagement:
Measuring the impact of residence hall characteristics of student psychosocial engagement.
Morrie Swerlick and Chris Tarnacki
1
The purpose of this project was to gain a greater understanding of how various
characteristics of undergraduate residence halls have an effect on the psychosocial
engagement of college students. We hypothesize that aspects of residence halls including
occupancy, the student-to-resident advisor ratio, the amount of programs, and the college
hall model would all have a significant effect on psychosocial engagement
Significance of the Problem
This study looks to empirically examine how characteristics of residence halls
influence psychosocial engagement. While theoretical influences were found to exist on
psychosocial engagement(J.M. Braxton, Doyle, Jones, & et al., forthcoming), little research
exists on the actual characteristics of residence life at a particular university and their
influence on this important aspect of social integration. At residential colleges and
universities, the housing system plays a primary role in a student’s life outside the
classroom. For students who choose to live in residence halls, these buildings become their
de facto homes for the time the student is enrolled at the institution. Residence hall life
should be considered an integral part of the college experience. It therefore stands to
reason that a student’s interactions within a residence hall system should have a direct
effect on a student’s decision to persist at the institution(Astin, 1999). Arboleda et
al.(2003) studied some of the aspects that may contribute to student involvement within a
residence hall based on Astin’s research. This study focused more on the traits of the
students to predict their involvement in residence hall activities. The study found certain
demographic characteristics as well as student perceptions of certain aspects of a residence
hall had a significant effect on student involvement(Arboleda, Wang, Shelley, & Whalen,
2003)
2
This study seeks to build on Astin’s theory of student involvement as it is
incorporated into psychosocial engagement as a factor influencing student persistence
(John M Braxton, Hirschy, & McClendon, 2004). For student affairs professionals making
policy decisions about staffing, programming, and construction of residence halls, this
study seeks to answer questions about which characteristics of these halls had a significant
effect on psychosocial engagement. This study could prove to be a valuable tool for
informing decision-makers on what aspects of residence halls are most conducive to
facilitating psychosocial engagement among residents.
The study was conducted at Vanderbilt University, a highly selective, doctoralgranting research university as classified by the Carnegie Foundation for the Advancement
of Teaching. Vanderbilt is known for heavily emphasizing its residential mission.
According to Vanderbilt’s Student Handbook:
“All unmarried undergraduate students, except those who live with their families in
Davidson County, must live in residence halls on campus during the academic year,
May session, and Summer sessions. Authorization to live elsewhere is granted at the
discretion of the Director of Housing Assignments in special situations or when space is
unavailable on campus.”
Broadly, Vanderbilt has three different types of residence halls: upperclassmen residence
halls, the Martha Rivers Ingram Commons for first-year students, and living-learning
communities. The upper-class residence halls contain a wide variety of rooms including
singles, doubles, suites, efficiency apartments, and lodges. Living learning communities
provide students with similar academic interests to live together and offer structured
learning environments located outside the classroom(Office of Housing & Residential
3
Education, n.d.). The Martha Rivers Ingram Commons is a collection of residence halls
exclusively for first year students. These halls have faculty-in-residence, frequent
programs designed to engage students with each other and co-curricular learning, as well
as orientation activities intended to acculturate students with the college experience that
last through the entire first semester.
The Commons system stands in stark contrast to the upper-class residence hall in
many different ways. First off, the Commons consists entirely of students who do not have
pre-existing social networks within the institution. Upper-class students will have had
anywhere from over a year to three years to form relationships and explore extracurricular
offerings. Students in the Commons, at the time of the survey used for this study, are also
not affiliated with Greek organizations, which are an important component of the social life
of many students at Vanderbilt. The Commons also falls under the purview of the Dean of
the Commons whereas all the upper-class residence halls fall under the jurisdiction of the
Dean of Students. Housing assignments, RA selection, and programming are handled
separately.
This study looks at those two fundamentally different types of housing, the
Commons and the upper-class residence halls, and a few measurable characteristics of each
hall. With such a heavy emphasis on residential education at Vanderbilt, the residence
halls should be built to incorporate features that encourage psychosocial engagement, a
critical contributor to social integration on a college campus. The findings of this study will
hopefully inform the decision makers at Vanderbilt and other similar institutions as they
continue to assess new and better ways to encourage students to integrate themselves both
academically and socially into the campus community.
4
Conceptual Framework
Much has been written on the subject of college student departure. Vincent Tinto’s
landmark study on departure theory developed the interactionalist model of student
persistence. According to Tinto, the greater the degree of social integration, the greater
the level of subsequent commitment to the institution. A greater level of subsequent
commitment to the institution then leads to a greater likelihood of college student
persistence(Tinto, 1975). Social integration can be defined as “the student’s perception of
his or her degree of congruence with the attitudes, values, beliefs, and norms of the social
communities of a college or university(Braxton, Hirschy, & McClendon, 2004, pg. 9). The
positive relationship between social integration and subsequent commitment to the
institution as well as the positive relationship between subsequent commitment to the
institution and student persistence were found to have strong empirical support in
residential colleges and universities.(J.M. Braxton, Sullivan, & Johnson, 1999)
Furthermore, several influences on social integration were identified and found to
have an empirically strong effect. In a revision of Tinto’s interactionalist theory, the
following are posited to have a positive effect on social integration at residential colleges
and universities: commitment of the institution to student welfare, institutional integrity,
communal potential, proactive social adjustment, and psychosocial engagement (Braxton,
Hirschy, & McClendon, 2004). In a subsequent study testing these posited effects on social
integration, three of the six stated influences on social integration are found to have a
positive influence: commitment of the institution to student welfare, institutional integrity,
and psychosocial engagement. These three antecedents were found to explain 41% of the
variance in social integration (J.M. Braxton et al., forthcoming)
5
Psychosocial engagement is a term used to describe the amount of psychological
energy a student puts forth to integrate into the social life of a college or university
(Braxton, Hirschy and McClendon, 2004). Putting forth the effort to interact with peers and
participating in experiences outside the classroom grant students the opportunities
necessary to judge their level of social integration. Without these experiences, students are
unlikely to perceive that they are social integrated into the campus community(Braxton,
Hirschy, and McClendon, 2004).
This study aimed to explore the relationships between factors students are exposed
to in residence halls and their psychosocial engagement. The following were predicted: 1.
being in a Commons hall will be associated with an increase in psychosocial engagement, 2.
everything else held equal, an increase in occupancy levels or RA Ratio will be associated
with a drop in psychosocial engagement, and 3. everything else being equal, an increase in
number of programs will be associated with an increase in psychosocial engagement.
Methods
Subjects
For the present study, data from the 2011 Vanderbilt Quality of Life Survey (QLS)
was used. The QLS is an annual survey that is administered in December of the fall
semester to all Vanderbilt students. It is important to note the date the survey was
administered, especially for students within the Commons, as they would have had
approximately three months to participate in activities offered by their residence halls as
well as begin to form friendships at Vanderbilt. If the survey had been issued earlier in the
semester, there may not have been sufficient time for this to have occurred. The survey is
made up of 193 questions, ranging from questions about student involvement to student
6
perceptions of their academic workload and religious life. For the 2011 survey, a total of
1610 undergraduate students responded. The data sample was narrowed to include only
respondents living in the 10 Martha Rivers Ingram Commons Residence Halls and 10
randomly selected upper-class residence halls. These 10 halls were selected using a
random number generator, with each upper-class hall being assigned a number based on a
list on the Residential Education Web Site. Living Learning Communities(LLCs) were
excluded from this process. LLCs were excluded because they represent a different living
experience then traditional upperclass residence halls. For the study, 6 variables relating
to psychosocial engagement were identified from the QLS, and any student who did not
respond to all 6 of these was excluded from the sample as well. After all these exclusion
criteria were applied, 688 respondents remained in the sample.
Research Design
As mentioned above, 6 variables were selected from the QLS which related to
psychosocial engagement. All items had a 1-5 Likert response scale, unless otherwise noted
These items were as follows: 1. “How many programs sponsored by your residence hall
have you attended this past semester? (1-4 response scale)”, 2.” I am satisfied with the
quality of life on my floor”, 3. “I know most of the people on the floor”, 4. “I am satisfied
with my social experience at Vanderbilt”, 5. “I attend programs or events (in addition to
regular meetings) sponsored by student organizations?,” 6. “I have developed a close
working relationship with at least one faculty member at Vanderbilt.” Since these items did
not all use the same response scale, the responses for all 6 variables were transformed into
standardized z-scores. A constant of 10 was added to each standardized score. A reliability
analysis was them run on the 6 new standardized variables, which produced a Cronbach’s
7
Alpha of .639. Analyses showed that if the faculty relationship variable was removed, this
value would increase to .683. Since this variable was the weakest in terms of face validity in
regards to psychosocial engagement, it was taken out of the scale. A final composite score
of psychosocial engagement, which served as the dependent variable in the study, was
calculated by adding the remaining 5 standardize variables together. Values for this
composite variable ranged from 38.44 to 55.30 and had a mean of 50.03 and a standard
deviation of 3.30.
While the Cronbach’s Alpha for the psychosocial engagement scale described above
falls within the “questionable” range, the items themselves appear to be face valid. As
discussed in the conceptual framework above, psychosocial engagement refers to the
amount of psychological energy a student puts forth to integrate into the social life of a
college or university. The variables that ask respondents if there are sufficient programs
on campus and how many residence hall programs they attended give an idea of whether
students are attending events on campus. Attending events represent an expenditure of
psychological energy aimed at participating in the campus community. For the two
satisfaction items, the level of satisfaction a student expresses is somewhat indicative of
whether they have been able to integrate into both their residence hall community and the
Vanderbilt community as a whole. Lastly, the question which asks students if they know
most of the people on their floor indicates how much psychological energy a student has
put forth to meet peers and make friends.
Beyond information from the QLS, residence hall level data were collected from the
Office of Housing and Residential Education. This included information on building
occupancy, the number of Resident Advisors (RA) in a building, and the number of
8
programs that occurred in each of the halls. Occupancy numbers were determined by
looking at a 10th day occupancy report from the fall of 2011. This document contains an
accurate count of how many students were living in a building 10 days after the start of fall
classes. Additionally, a list of RAs was used to determine the number of RAs per building.
Using this information and the occupancy data, a ratio of the number of students per RA
was calculated. Lastly, a list of programs and the RAs who sponsored the event was
obtained. Cross referencing the RA name with the building he or she was assigned to, a
total number of programs per residence hall was calculated. Each of these three variables
about the conditions in a specific residence hall was added to the data set by assigning
them to respondents living in corresponding halls. These three variables served as
independent variables in the study. While these variables represent building level data,
they also represent conditions which each student living in that building would have been
exposed to. Additionally, in order to make comparisons across Commons halls and upperclass dorms, a binary variable was created (1=Commons hall, 0=upper-class). On top of the
independent variables discussed above, control variables were created for gender (male=1
female=0), ethnicity/race (white=1, non-white=0), and estimated family income (Above
$100,000=1 below $100,000=0).
Analyses and Results
In order to test the hypotheses outline above, independent t-tests and multiple
regression analyses were utilized. Before constructing regression models, tests for
multicolinearity were performed. For all the independent variables, these tests produced
tolerance and VIF levels within an acceptable range based on guidelines laid out by
Ethrington, Thomas and Pike (2002).
9
Independent Sample t-tests were performed to detect differences in the
independent variables between Commons halls and upper class residences halls. The
results of these tests indicate that Commons halls have significantly smaller occupancy
levels, significantly lower RA to student ratios, and significantly higher numbers of
programs (Appendix A). Additionally, residents of Commons halls had significantly higher
scores on the psychosocial engagement scale (Appendix A).These results fall in line with
the first hypothesis listed above.
In order to test the final two hypotheses, multiple regression analyses were used.
The dependent variable for the regression model was scores on the psychosocial
engagement index. Binary control variables for gender, ethnicity, and family income were
added along with the independent variables. The results from the model are below.
The model accounts for 15.3% of the variance in the scores on the psychosocial
engagement scale (Appendix B). Number of programs, Race (white=1), and Residence Hall
type (Commons=1) are all significant in the model . Gender, family income, student-to-RA
Ratio, and occupancy are non-significant. Compared to the upper-class residence halls,
living in a Commons hall is associated with a 2.158 point increase on the psychosocial
engagement scale. In regards to race and ethnicity, being white is associated with a 1.044
point increase on the psychosocial engagement scale. While the number of programs is
significant in the model, an increase in 1 program is associated with a .025 decrease in
psychosocial engagement scores, which is the opposite direction than predicted. However,
this decrease is so small that it does not represent a meaningful finding.
With the finding that being a Commons Hall effects scores on the psychosocial
engagement scale, the data file was divided into upper-class dorms and Commons halls and
10
regressions were run on each pool of data (Appendix B). Since there seems to be a
difference between the environments in the two types of residence halls, the variables in
question could potentially have different effects in each type. Both of the spilt models
explained very little of the variance, with the commons model accounting for 2.4% of the
variance in the dependent variable and the upper class model accounting for 5.2%. In the
upper-class model, race, family income, and the number of programs were statistically
significant. Once again, being white is associated with an increase in psychosocial
engagement scores (a 1.356 point increase). Having a self-reported family income of over
$100,000 is associated with a .810 decrease in psychosocial enragement. Just like in the
composite model, an increased number of programs is associated with a drop in
psychosocial engagement (in the model, an increase of one program lead to a .138 point
decrease in psychosocial enragement). The only variable that is significant in the Commons
model was the Race variable, with being white associated with a .774 point increase in
psychosocial engagement.
With the lack of significant findings using continuous variables in mind, categorical
variables were made for the three independent variables. Categories of high, medium, and
low were used, with the 33.33 and 66.66 percentiles acting as the dividing points. The same
multiple regressions used with the continuous variables were performed (Appendix C). In
the composite model, including both types of residence halls, 16.1% of the variance in the
dependent variable is explained. Once again race and residence hall type are significant
factors. Additionally, medium occupancy was a significant predictor. When compared to
low occupancy, medium occupancy is associated with a .626 point increase on the
psychosocial enragement scale. This does not match the second hypothesis from earlier.
11
Lastly, a medium RA ratio is significant and associated with a 1.075 decrease in
psychosocial engagement when compared to a low RA ratio. This is in line with the second
hypothesis, but within the model high RA ratio was not associated with a significant
decrease, which is not in line with the second hypothesis. The split models using
categorical independent variables explained very little variance (8% for upper class halls
and 1.9% for Commons halls) (Appendix C). These models had some issues with
multicollinearity, which resulted in the low number of programs variable being excluded
from the upper-class model. Additionally, none of the Commons halls had a high RA ratio,
which resulted in this variable being excluded. The only significant factor in each is race,
with being white having a predicated jump in psychosocial engagement of 0.793 points in
upper-class residence halls and 0.802 points in the Commons.
The results discussed above are inconsistent and do not contain very many
statistically significant findings. Two factors were found to be significant across all the
models, residence hall type and race. Being a Commons hall is significant in both composite
regression models, and is associated with the largest changes in psychosocial engagement
scores. When results from the t-tests are looked at as well, it appears that the Commons
halls have a different environment from upper-class halls and that living in a Commons hall
leads to more psychosocial engagement. While the factors that t-tests showed differed in
the Commons compared to upper-class halls did not show consistent effects, there is a
possibility that the Commons experience is made up of more than the variables included in
the study. One interesting result was medium occupancy being associated with increases in
psychosocial engagement when compared to low occupancy. This was not consistent with
the second hypothesis. One possibility is that medium sized residence halls give students
12
the best of both worlds, with small enough numbers of people to make meaningful
relationships, but large enough numbers where students do not feel isolated. Also
interesting was that all significant findings in regards to programs were associations of
more programing leading to lower psychosocial engagement. As mentioned before, these
effects were small and do not seem to be particularly meaningful. Despite this, the direction
of these effects is interesting. This could hint at the idea of “over-programming,” where too
many programs undermine the intended effect of the programming.
Limitations
While there were some significant and/or interesting findings that came out of this
study, there are a number of limitations. First, the regression models discussed above
explain very little of the variance in psychosocial engagement as measured in the study.
This may be due to the limited number of building level variables that were looked at (due
to time constraints and difficulty obtaining data). Future research should use a larger set of
building and potentially floor attributes. Another of these limitations has to do with the fact
that upper-class housing and the Commons represent different models of on-campus living.
Also, first year students and upper-class students have different opportunities on campus
which may influence the findings. For example, first year students were not allowed to be
part of Greek organization at the time of the survey, while a large portion of upperclassmen were members in these organization. As a result, the factors which are at play in
regards to psychosocial engagement may interact differently across type of housing. Future
studies could address this issue by obtaining large enough sample sizes to look at one
specific model of on-campus living. Additionally, while we found that the Commons model
13
appears to be working in increasing first year student psychosocial engagement, students
change and thus the model used in the Commons may not have the same effects with older
students.
The location of this study acts as a limitation as well. Vanderbilt University is an
exception rather than the norm when it comes to institutions of higher education.
Vanderbilt is very selective and very residential, and as a result caution needs to be used
when extrapolating what works at Vanderbilt to other institutions. Lastly, this study is a
secondary analysis of existing data. The scale which was used to measure psychosocial
engagement was built using items that were originally developed for other purposes.
Future studies should look to use similar methods, but collect original data tailored
towards more accurate measurements of psychosocial engagement.
Conclusions
This study showed that the Commons model does have a clear, statistically
significant effect on psychosocial engagement. The study was less clear about some of the
other variables tested, including the student-to-RA ratio, the number of students in each
hall, and the amount of programming that occurs in each hall during a given year. It is
important not to draw too many conclusions on the difference between upperclass halls
and Commons halls as they are an apples-to-oranges comparison. Rather it is vital that we
just understand that the Commons does have a positive effect and it is a model that works.
Many aspects of the Commons seem to be intentionally geared towards encouraging
psychosocial engagement among students. The programming is geared towards
incentivizing students to put forth the effort to build the social relationships so crucial to
social integration. Vanderbilt seems eager to expand the Commons model to the College
14
Hall project scheduled to begin construction in May of 2012. While it was impossible to
study the effect of the Commons model on first year students and upperclassmen, it would
not be surprising if the College Hall model was shown to have the same effect on
psychosocial engagement among upperclassmen.
From a policy perspective, although Vanderbilt does not have a retention problem
due in great part to its high selectivity and excellent academic and social support systems,
implementing a Commons model at a residential school with persistence issues may be a
worthwhile endeavor. Although models such as the Commons may be prohibitively
expensive, finding unique ways to encourage psychosocial engagement among students
should be an institutional priority and a good way to address persistence issues outside the
classroom.
Finally, this study did find some potentially interesting effects that hall size had on
psychosocial engagement, namely that medium sized residence halls had a positive
contribution on psychosocial engagement when compared to small residence halls. Hall
size is a major component of any residence hall design and its effects should be fully
studied before any decision is made. We also believe there are probably other aspects of
residence halls that encourage or discourage psychosocial engagement that could be the
focus of future inquiry.
15
Appendix A
Independent means t-tests
Independent t-tests: Commons vs Upper-Class residents
Std.
Variables
Deviation
Mean
N
Number of
Programs
Pyschosocial
Engagement
Scale
RA Ratio
Occupancy
Upper-class
Residents
Commons
Residents
Upper-class
Residents
Commons
Residents
Upper-class
Residents
Commons
Residents
Upper-class
Residents
Commons
403
10.85
3.072
533
19.01
12.902
276
48.5805
3.11868
412
50.9978
3.06550
403
49.6890
6.50922
533
35.2646
7.18695
403
255.9380
90.42285
533
187.9756
63.53793
Residents
Variables
Std. Error
Mean
Sig. (2Difference Difference
tailed)
.579
-8.161
.000
-14.085
df
610.246
-10.033
582.825
.000
-2.41725
RA Ratio
32.090
904.157
.000
Occupancy
12.875
685.941
.000
t
Number of
Programs
Psychosocial
Engament
95% Confidence
Interval of the
Difference
Upper
Lower
-9.299
-7.023
.24093
-2.89045
-1.94405
14.42445
.44949
13.54228
15.30663
67.96236
5.27852
57.59835
78.32636
16
Appendix B
Continuous independent variable regression models
Pyschosocial Engagement Regression Model
R
R Square
.403a
Independent Variables
R Square
.270
a
Independent Variables
(Constant)
.073
.052
Unstandardized
Coefficients
B
Std. Error
49.982
1.970
Occupancy
-.001
.002
-.379
.705
RA Ratio
-.037
.019
-1.883
.060
Programs
-.025
.012
-1.971
.049
.277
.239
1.162
.246
Over $100,000
-.172
.243
-.708
.479
White
1.044
.257
4.058
.000
Commons
2.158
.333
6.488
.000
Pyschosocial Regression Model:
Commons residence halls
R
3.03634
Sig.
a
Independent Variables
Adjusted
R Square
.038
.024
Unstandardized
Coefficients
B
Std. Error
Std. Error
of the
Estimate
3.02873
t
Sig.
25.368
.000 (Constant)
52.202
1.047
49.849
.000
.000
.002
-.165
.869
-.043
.023
-1.904
.058
-.024
.013
-1.886
.060
.001 White
.031 Over $100,000
.774
.332
2.335
.020
.269
.323
.830
.407
.901 Male
.475
.313
1.519
.130
.004
-.332
RA Ratio
-.003
.049
-.054
.957 RA Ratio
.039 Programs
-2.078
White
1.356
.414
3.272
Over $100,000
-.810
.374
-2.165
.047
.376
.125
Male
R Square
.195
-.001
.067
Sig.
.000
Occupancy
-.138
t
52.791
.740 Occupancy
Programs
Std. Error
.948
Std. Error
of the
Estimate
t
B
3.04056
50.029
Psychosocial Engagement Regression Model:
Upperclass Residence Halls
R
.162
.153
Unstandardized
Coefficients
(Constant)
Male
Adjusted
R Square
Adjusted Std. Error of
R Square the Estimate
17
Appendix C
.327 a
Independent Variables
(Constant)
Adjusted
R Square
.107
.080
Unstandardized
Coefficients
B
Std. Error
Std. Error
of the
Estimate
R
R Square
.195 a
2.99064
Independent Variables
t
Sig.
.000
.435
-.781
3.909
.257
.242
-.189
1.006
Over $100,000
White
.227
1.208
.288
Male
.238
.129
.445
.358
.556
.000
.018
.004 Over $100,000
.072 Male
.206
.325
.634
.526
.520
.314
1.656
.099
.314
.474
.662
.508
.425
.521
.816
.415
2.935
Over $100,000
-.668
.370
-1.803
.029
.399
.073
Medium Number of
Programs
-.244
.494
-.494
.942 Low Num ber of
.622 Program s
Medium Occupancy
1.022
.593
1.723
.086
High Occupancy
-.918
.704
-1.305
.193
White
Medium Num ber of
Program s
Medium Occupancy
.482
1.049
.460
Sig.
2.377
.410
High RA Ratio
t
.334
1.203
-.345
Std. Error
.793
White
.956
B
3.03623
105.516
51.577
-.330
.038
.019
Uns tandardized
Coefficients
Std. Error
of the
Es tim ate
.476
.933
Medium RA Ratio
Adjus ted
R Square
50.196
.000
(Cons tant)
48.101
Male
.543
.426
Commons Halls
Upperclass Residence Halls
R Square
1.518
.765
.287
-1.065
.401
Psychosocial Engagement Regression Model:
Psychosocial Engagement Regression Model:
R
Low Occupancy
Low RA Ratio
-.396
-.427
High Numbers of
Programs
.240
-1.176
3.321
.358
1.188
Medium
Occupancy
Medium Number
of Programs
.336
.001
.176
-1.355
-.660
Medium RA Ratio
.487
.000
5.357
2.344
Commons
.438
t
131.239
.363
Std. Error
B
47.682
Independent
Variables
R
.417
a
(Constant)
3.02629
.174
.161
Unstandardized
Coefficients
Std. Error
of the
Estimate
Adjusted
R Square R Square
Psychosocial Regression Model
Sig.
.000
Regression models using categorical variables
.730
High Occupancy
.646 Medium RA Ratio
.381
.387
.984
.326
-.039
.511
-.076
.940
-.759
.490
-1.548
.122
18
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