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Journal of Student Affairs Research and Practice
ISSN: 1949-6591 (Print) 1949-6605 (Online) Journal homepage: https://www.tandfonline.com/loi/uarp20
The Benefits of Living on Campus: Do Residence
Halls Provide Distinctive Environments of
Engagement?
Polly A. Graham, Sarah Socorro Hurtado & Robert M. Gonyea
To cite this article: Polly A. Graham, Sarah Socorro Hurtado & Robert M. Gonyea (2018)
The Benefits of Living on Campus: Do Residence Halls Provide Distinctive Environments
of Engagement?, Journal of Student Affairs Research and Practice, 55:3, 255-269, DOI:
10.1080/19496591.2018.1474752
To link to this article: https://doi.org/10.1080/19496591.2018.1474752
Published online: 13 Aug 2018.
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Innovation in Research and Scholarship Feature
The Benefits of Living on Campus: Do
Residence Halls Provide Distinctive
Environments of Engagement?
Polly A. Graham, Indiana University Bloomington
Sarah Socorro Hurtado, Indiana University Bloomington
Robert M. Gonyea, Indiana University Bloomington
The changing landscape of on- and off-campus undergraduate residential
options underline the need to reexamine the impact of on-campus living.
Using multi-institutional survey data from first-year students, this study
investigates the relationship of residential status with engagement and
perceived gains in learning and development. Results indicate, after con-
trolling for student and institution characteristics, that on-campus resi-
dence has small positive effects on some outcomes but not on others
where effects might be expected.
Student affairs theory and practice is rooted in the belief that opportunities for learning
outside of the classroom are abundant (American Council on Education, 1937), and a great many
of these experiences are shaped by the environments and programs provided to those living in
campus residences. In the first volume of their compendium of research, Pascarella and Terenzini
(1991) confirmed that living on campus was “the single most consistent within-college determi-
nant of the impact of college”(p. 611). Along with Blimling (1993), they later explained that the
social-psychological environment of residence halls is “qualitatively different”from off-campus
living, hypothesizing that residence halls lead to social, cultural, and extracurricular involvement
and, in turn, to broader student outcomes. Astin (1985) emphasized the importance of proximity
to campus resources, stating that “simply by virtue of eating, sleeping, and spending their waking
hours in the college campus,”students are more likely to identify with college life (p. 145).
In their second volume, Pascarella and Terenzini (2005) moderated their appraisal of
residence life, summarizing post-1990 research finding the effects to be less prominent and
likely indirect. Among the reasons for restraint is that much of the earlier research was biased
toward traditional, full-time, White undergraduates attending four-year institutions without
consideration for potential differences in the experiences of underrepresented students
(Pascarella & Terenzini, 2005). Recent discourse about living on campus is even more
subdued. Since 2000, studies have found uneven benefits for students of differing identities
(Harwood, Huntt, Mendenhall, & Lewis, 2012; Strayhorn & Mullins, 2012;Turley&
Correspondence concerning this article should be addressed to Polly A. Graham, Indiana University
Bloomington, Center for Post Secondary Research, 1900 East Tenth St., Eigenmann Hall, 419, Bloomington,
IN 47406-7512, USA. E-mail: pagraham@indiana.edu
Graham, P. A., Hurtado, S. S., & Gonyea, R. M. (2018).
The Benefits of Living on Campus: Do Residence Halls Provide Distinctive Environments of Engagement?
Journal of Student Affairs Research and Practice, 55(3), 255–269.
ISSN: 1949-6591 (print)/1949-6605 (online)
JSARP 2018, 55(3) © NASPA 2018 http://journals.naspa.org/jsarp doi:https://doi.org/10.1080/19496591.2018.1474752 255
Wodtke, 2010). For example, while residence halls have the potential to foster positive
interactions with students from diverse backgrounds, they alternatively can encourage group-
think and provide a space for hostile discriminatory practices (Blimling, 1993; Harper et al.,
2011; Pascarella & Terenzini, 2005; Strayhorn & Mullins, 2012). In their review, Mayhew
et al. (2016) concluded that studies of campus residence were generally thin and often do not
support claims of positive impact.
Researchers suggest that such findings are the result of collegiate and residential experiences
becoming less immersive. In the past, living on campus was associated with pervasive commu-
nication and interactions among peers within the institution. Currently, with ubiquitous mobile
devices, social media, and wifi, it is much easier to interact with family and friends on the outside,
which means on-campus students may not rely as heavily on those within their living environment
for social interaction (Gemmill & Peterson, 2006).
The asserted benefits of on-campus living also include access to a wide variety of educational
and community programming that encourage organic interactions between students and integrate
students’intellectual and social lives (Blimling, Whitt & Associates, 1999; Terenzini & Pascarella,
1984,1997). Scholars pointed out that residential students connect the in- and out-of-classroom
experiences through more frequent interactions with faculty (Kuh, Kinzie, Schuh, Whitt, &
Associates, 2005; Pascarella & Terenzini, 2005), and access to professional staff makes sponta-
neous conversation and emotional support available, benefits that are immeasurable but believed to
add significant contributions to learning and development (MacKinnon & Associates, 2004). As
institutions seek to inspire reflective learning outside of the classroom, residence halls provide
purposeful spaces for student affairs professionals to plan formal and informal educational oppor-
tunities (Davidson, Henderson, Knotts, & Swain, 2011; Moran, 2001).
However, assessing the discrete benefits of such programs can be difficult. Direct comparisons of
students living on campus to their off-campus peers are complex, and there is great variation among types
of residence halls, programming, staffing, and participation among residents. While a good amount of
anecdotal evidence supports the benefits of living on campus, valid measurements are difficult to achieve.
To understand the extant research on the impact of living on campus, it is important to clarify
the different types of living options used in studies. While the terminology often suggests discrete
categories (e.g., on-campus vs. off-campus), the actual living arrangements of students are more
complex. Astin (1993) examined four measures (at home, in a college residence hall, in a private
room or apartment, and distance of home from college) yet found that the effects had more to do
with leaving home to attend college than with the place of residence. Chickering and Reisser (1993),
citing Pace’s(1984) research, referenced three housing categories (residence halls, fraternity and
sorority houses, and off campus) and found developmental benefits for students living in residence
halls and in Greek houses. In addition to residence halls and Greek houses, Pace (1980) added a
dimension of distance for students living off campus, differentiating between walking distance and
driving distance to the institution. Pace’s categories were adopted by the National Survey of Student
Engagement (NSSE) and provide the key independent variable for the current study.
With the additional dimension of commuting distance, readers might revisit Chickering and
Reisser’s(1993) assertion that commuter students are at a disadvantage because they lack access to
the beneficial social-psychological context of on-campus living. The tacit understanding is that
there is something important about living in campus housing rather than just living close to campus.
But is it proximity that matters or, rather, is it engagement with programming, staff, and access to
diverse peers that make a difference?
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Problem Statement
In light of Mayhew et al.’s(2016) conclusion that studies of on-campus living are limited for
most outcomes and often do not find the purported benefits, campus administrators are challenged
to revisit their assumptions about residence life. Many institutions require students to live on
campus for all or some of their undergraduate years and allocate considerable resources for
programming and staffing. Research is needed to clarify the benefits, if any, of the on-campus
experience. Because identity plays a role in how students experience their living environments, it is
imperative to control for background characteristics to better understand the overall impact
(Harper et al., 2011; Harwood et al., 2012; Strayhorn & Mullins, 2012).
Conceptual Framework
Student engagement “refers to college students’exposure to and participation in a constellation of
effective educational practices at colleges and universities”(McCormick, Kinzie, & Gonyea, 2013,p.
47). The concept is indebted to Pace’s(1980) research on the quality of student effort, Tinto’s(1975,
1993) work on social and academic integration, Astin’s(1984) theory of student involvement, and
Chickering and Gamson’s(1987) seven principles for good practice in undergraduate education.
Student engagement takes into account both students’time spent and their quality of effort as well as
institutional factors (Kuh, 2001). Rather than focusing on how students are impacted by a given
intervention, student engagement is a collection of process indicators which research theory has
connected to student success (Kuh et al., 2005). The current study tests the idea that on-campus
residence halls produce distinctive and measurable environments of engagement.
Method
We investigated the association between undergraduate living arrangements and several
measures of student engagement and perceived gains. Acknowledging that course-based engage-
ments are largely unrelated to where a student lives, this study examined the impact of residential
status on measures that are relevant to residence. We not only compared students who live on
campus to those who live off but also differentiated two off-campus categories—students who live
within walking distance and farther than walking distance. Thus, we examined the relationship
between engagement and residence, making it possible to test specifically for the effects of
proximity to campus.
Data Source
Data for the study came from NSSE, a large-scale, multi-institutional survey administered
annually to first-year and senior bachelor’s degree-seeking students. NSSE asks students about
their engagement in educationally purposeful activities, which have been categorized into 10 valid
and reliable Engagement Indicators (Miller, Sarraf, Dumford, & Rocconi, 2016). NSSE also asks
students to estimate the extent to which their institution contributed to their knowledge, skills,
and personal development in several curricular and cocurricular areas.
Sample
We started with student responses from 1,238 U.S. institutions that participated in NSSE
between 2013 and 2016. For institutions that participated in multipleyears,onlythemost
recent year of data were used. Because of our focus on residential status, we examined first-
year students to emphasize the important role of student affairs in supporting new students in
transition and to help them succeed in college. We decided not to examine seniors because
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only a relatively small and selective group of them live on campus (13% in 2016), and those
who do are disproportionately student leaders, athletes, non-transfer, international, and White
(National Survey of Student Engagement (NSSE), 2016). Next, we limited our sample to full-
time students because only a slim portion of part-time students (2.7% in 2016) lived in
campus housing. This removed any unbalanced effects from off-campus, part-time students
who by definition take fewer classes, interact with fewer faculty, work more, and spend less
time on campus.
Next, we excluded institutions that were mainly residential (more than 80% of first-year
students living on campus) or mainly commuter (fewer than 20% of first-year students living on
campus) to reduce effects associated with the differences between primarily residential campuses
and those that serve mostly commuter student populations. This reduced the sample to 576
institutions. A summary of institutional characteristics shows a diverse mix of Carnegie types,
public and private, and enrollment sizes (Table 1).
Finally, we removed 759 students who lived in Greek houses because of the relatively low
number and because it is atypical for first-year students to live in fraternity and sorority housing.
We also removed 3,470 students who selected “none of the above”to the residential question,
presumably because they were distance education students.
The resulting data contained 94,577 first-year students with 60.3% living on campus, 9.3%
living in a residence within walking distance, and 30.4% living in a residence farther than walking
Table 1
Characteristics of Institutions in the Sample
n%
Basic 2015 Carnegie Classification R1: Doctoral Universities - Highest research activity 31 5%
R2: Doctoral Universities - Higher research activity 49 9%
R3: Doctoral Universities - Moderate research activity 43 7%
M1: Master’s Colleges and Universities - Larger programs 168 29%
M2: Master’s Colleges and Universities - Medium programs 84 15%
M3: Master’s Colleges and Universities - Smaller programs 48 8%
Baccalaureate Colleges: Arts & Sciences Focus 27 5%
Baccalaureate Colleges: Diverse Fields 88 15%
Other Carnegie Categories 38 7%
Control Public 281 49%
Private, not-for-profit 290 50%
Private, for-profit 5 1%
Enrollment size Fewer than 1,000 66 11%
1,000–2,499 173 30%
2,500–4,999 115 20%
5,000–9,999 107 19%
10,000–19,999 72 13%
20,000 or more 42 7%
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distance. A few differences among student characteristics are notable (Table 2), such as a higher
proportion of White students living on campus, whereas Latino and first-generation students were
more likely to commute from farther than walking distance. Traditional-age students were more
likely to live on campus, as were those working fewer than 10 hours per week, but transfer students
were more likely to live off campus. Such differences support the need for controlling for
individual differences in the models to isolate the net effects of the residential status.
Variables
Our primary independent variable of interest was the student’s living arrangement, derived
from the question:
Which of the following best describes where you are living while attending college?
a. Dormitory or other campus housing (not fraternity or sorority house)
b. Fraternity or sorority house
c. Residence (house, apartment, etc.) within walking distance to the institution
d. Residence (house, apartment, etc.) farther than walking distance to the institution
e. None of the above
As mentioned, we excluded students living in fraternity or sorority houses and those reporting
“None of the above.”
We selected dependent variables based on literature that connects living on campus to positive
interactions with others, personal development, and a supportive environment (Chickering &
Reisser, 1993). Dependent variables included five Engagement Indicators: Collaborative Learning,
Discussions with Diverse Others, Student–Faculty Interaction, Quality of Interactions, and
Supportive Environment. Each Engagement Indicator is expressed on a 60-point scale and
provides valuable information about a distinct aspect of student engagement by summarizing
students’responses to a set of related survey questions. Scale reliabilities (Cronbach’s alpha) ranged
from 0.80 to 0.88. We also analyzed the amount of time students spent studying and on academic
work using the item:
About how many hours do you spend in a typical 7-day week preparing for class (studying, reading, writing,
doing homework or lab work, analyzing data, rehearsing, and other academic activities)?
Finally, we created a Perceived Cocurricular Gains scale by combining results from five items, by (as
with the Engagement Indicators) computing it on a 60-point scale:
How much has your experience at this institution contributed to your knowledge, skills, and personal
development in the following areas?
●Working effectively with others;
●Developing or clarifying a personal code of values and ethics;
●Understanding people of other backgrounds (economic, racial/ethnic, political, religious, nationality,
etc.);
●Solving complex real-world problems;
●Being an informed and active citizen
The scale reliability coefficient (Cronbach’s alpha) was 0.88.
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Table 2
Demographics of Study Participants
Residence status
a
Student characteristics On
campus
Within walking
distance
Farther than walking
distance
Sex Female 68% 59% 67%
Male 32% 41% 33%
Race or ethnicity American Indian or Alaska
Native
1% 1% 1%
Asian 5% 8% 10%
Black or African American 11% 10% 7%
Hispanic or Latino 11% 13% 19%
Native Hawaiian or other
Pacific Islander
0% 0% 1%
White 62% 50% 53%
Other 3% 3% 4%
Foreign or nonresident alien 4% 12% 4%
Two or more races/
ethnicities
4% 3% 4%
Grades
b
Mostly A grades 49% 45% 48%
Mostly B grades 42% 46% 44%
Mostly C grades or lower 8% 10% 8%
Major or expected major
b
Arts & Humanities 10% 10% 9%
Biological Sciences, Agric., &
Nat. Res.
11% 11% 11%
Physical Sci., Math., &
Computer Sci.
5% 6% 6%
Social Sciences 10% 9% 10%
Business 14% 16% 15%
Communications, Media, &
Public Rel.
4% 4% 3%
Education 8% 6% 8%
Engineering 8% 9% 8%
Health Professions 18% 16% 19%
Social Service Professions 5% 5% 6%
All other 4% 5% 4%
Undecided, undeclared 3% 3% 3%
First-generation
c
41% 45% 57%
Traditional age (20 or younger) 98% 87% 86%
Transfer 6% 13% 13%
(continued )
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We standardized all dependent variables and the one continuous independent variable (time spent
working) before running the models so that the unstandardized beta coefficients can be interpreted as
effect sizes. See Table 3 for means, counts, and standard deviations of the dependent variables.
Analysis
To control for salient institutional and student characteristics and to isolate the net relation-
ship of the residential variable, we analyzed the data in two models as a block hierarchical
regression for each dependent variable. The first block for each dependent variable included the
background characteristics (see Appendix): sex, race (dummy-coded with White as the reference
group), major (dummy-coded with business as the reference group), first-generation, transfer,
traditional age (20 years and under), and grades (dummy-coded with “mostly A’s”as the
reference group). The first block also included dummy-codes for each of the 576 institutions,
with one institution left out of the models. Institutions were entered into the model as individual
dummy codes; therefore, we left one institution out to serve as the reference category in order to
avoid redundancy (although no attempt is made to interpret individual school coefficients). This
Table 2
(Continued)
Residence status
a
Student characteristics On
campus
Within walking
distance
Farther than walking
distance
Time spent working (on and/or
off campus)
0 hrs/wk 62% 51% 37%
1–10 hrs/wk 16% 14% 14%
11–20 hrs/wk 15% 18% 22%
More than 20 hrs/wk 8% 17% 27%
a. Student-reported. Response options included: Dormitory or other campus housing (not fraternity or sorority house);
Residence (house, apartment, etc.) WITHIN walking distance to the institution; Residence (house, apartment, etc.)
FARTHER THAN walking distance to the institution
b. Student-reported, collapsed into related-major categories
c. Neither parent/guardian holds a bachelor’s degree
Table 3
Dependent Variable Descriptive Statistics
Dependent variables NMean SD
Collaborative Learning* 92,380 32.9 13.9
Discussions with Diverse Others* 93,186 41.4 15.7
Student-Faculty Interaction* 92,702 20.7 14.6
Quality of Interactions* 90,749 41.5 12.3
Supportive Environment* 93,261 37.6 13.7
Time spent preparing for class (in hours) 93,760 14.1 8.3
Perceived co-curricular gains* 93,720 34.5 15.6
* All variables except “time spent preparing for class”were computed on a scale of 0 to 60.
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method controlled for all types of variation and nuance between institutions (size, control,
mission, selectivity, etc.) because each institution’s effects are included as a separate variable.
The second block added the residence variable, which was dummy-coded for those living on
campus, within walking distance, and farther than walking distance. Living on campus was left
out of the models as the reference group.
Results
In general, results show that living on campus had statistically significant and positive effects
on all seven dependent variables, especially when compared to living farther than walking distance
from campus (Table 4). However, because p-values are highly sensitive to sample size, the
regression coefficient is a better effect size for interpreting the practical significance, or magnitude,
of the relationships. The most popular frame of reference is a set of benchmarks offered by Cohen
(1988,1992). Cohen described small effects as those that are hardly visible, medium effects as
observable and noticeable to the eye of the beholder, and large effects as plainly evident or obvious.
He suggested that rvalues of about 0.1, 0.3, and 0.5 would represent small, medium, and large
effects, respectively. Using this standard, we can identify which are the more meaningful effects in
our results and which are perhaps too small to be of any consequence.
Using Cohen’s references, results show that three of the models had at least a small effect.
First, although living on campus had a small positive effect (0.07) on engagement in Collaborative
Learning compared to living within walking distance, it had a medium positive effect (0.26)
compared to living farther than walking distance. Second, living on campus had small effects
(0.13 and 0.15) on engagement in discussions with diverse others relative to all students living off
campus, no matter their proximity to campus. This affirms claims that residence halls play an
important role in fostering diversity awareness and understanding (Pike, 2002). Third, living on
campus had a small to medium positive effect (0.20) on student–faculty interaction compared to
Table 4
Results for Residence Status for All Regression Models
Dependent variables
Walking
distance
(relative
to living
on
campus)
Farther than
walking
distance
(relative to
living on
campus)
R
2
(explained
variance) Change in R
2
Change in R
2
portion of
explained
variance
Collaborative Learning −0.07 *** −0.26 *** 0.07 0.010 *** 14.8%
Discussions with Diverse Others −0.13 *** −0.15 *** 0.05 0.004 *** 8.8%
Student-Faculty Interaction 0.04 ** −0.20 *** 0.06 0.007 *** 10.7%
Quality of Interactions −0.05 *** −0.04 *** 0.05 0.000 *** 0.6%
Supportive Environment −0.06 *** −0.06 *** 0.05 0.001 *** 1.5%
Time spent preparing for class −0.02 −0.06 *** 0.09 0.001 *** 0.7%
Perceived co-curricular gains 0.04 *** −0.04 *** 0.05 0.001 *** 1.3%
Notes: Coefficients are unstandardized betas. Dependent variables were standardized before analysis. R
2
is amount of
variance explained in the dependent variable; R-squared change is the amount of increase after the residence
variable was entered in the model. Living on campus is the reference group.
*p< 0.05, ** p< 0.01, *** p< 0.001
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living farther than walking distance. Most of the remaining results for the residence variable were
statistically significant, but were trivial in size.
R-squared values estimate that the models explained 5% to 9% of the variance in the
dependent variables. Yet, the change in R-squared statistics reveal very small effects for the
residence variable in general, ranging from 0 to 1% of additional explanatory power. However,
our purpose was not to create predictive models that attempt to explain the total variance in the
dependent variables but was to isolate the effects of residence status after controlling for as many of
the fixed institutional and background characteristics as possible. Another way one might interpret
the R-squared change statistic is to consider the portion of explained variance that resulted from
the residence variable. For example, in the Collaborative Learning model, the additional variance
accounted for by the residence variable was 0.01, or 15% of the total variance explained (0.07). So,
among all the student and institution characteristics that explained variance in collaborative
learning, one variable, residential status, accounted for 15% of that variance. Likewise, residence
represented 9% of the explained variance for Discussions with Diverse Others and 11% of the
explained variance in Student–Faculty Interaction. Residence represented less than only 1% or 2%
of explained variance in the other four dependent variables.
Limitations
We identified two limitations that affect the interpretation of our results. First, the on-
campus experience can vary greatly between campuses and even within the same campus, making
living “on campus”a blunt measure in many respects. Some institutions have residential programs
that are well resourced and highly professional, while others are less developed. More granular
information, such as residence style, number of roommates, residential amenities such as computer
labs and quiet study areas, on-site advising, and programming could explain more of the variation
within the broad residence categories.
The second limitation is a consequence of our choice to exclude the primarily residential and
primarily commuter campuses. Institutions that require first-year students to live on campus are
likely to have more professional, developmental programs and services that target the needs of
students in transition. Removing these institutions had the potential to lower the overall average
engagements of students living on campus, reducing the comparative strength of on-campus living
relative to the off-campus options. At the same time, removing primarily commuter institutions
could have affected the overall strength of the off-campus options in unknown ways. Yet, after
sampling only institutions with a good mix of both on- and off-campus residents, we still had a
large, diverse, and representative set of institutions for the analysis.
Discussion and Implications
Consistent with contemporary studies of on-campus living (Harwood et al., 2012; Mayhew
et al., 2016; Strayhorn & Mullins, 2012; Turley & Wodtke, 2010), our findings offer mixed support
for the claims in earlier research that living on campus has an advantage over other living situations
(Astin, 1977,1993; Pascarella et al., 1994; Pascarella & Terenzini, 1991). Students living on campus
had a small advantage in three ways over their peers who commuted from farther than walking
distance to the campus: more engagement in collaborative learning, discussions with diverse others,
and student–faculty interaction. Taken together, these suggest a more positive social integration for
the residential students. However, when compared to peers who lived within walking distance to the
campus, the advantages of on-campus living were less evident. On-campus students engaged in
interactive diversity a bit more, and perhaps were more involved in collaborative learning activities.
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In other words, living on campus has an advantage over commuting from a distance in areas related
to social integration, but by living close to campus, students may mitigate some of the disadvantages.
The Not So Good News
While living on campus was found to have positive effects in three areas of social integration,
there were no meaningful effects for supportive environment, quality of interactions, time spent
preparing for class, or perceived cocurricular gains. Residence halls are presumably hospitable and
supportive spaces, seeking to foster quality interactions among residents. If residence halls are no
more supportive than other living environments, it is incumbent upon student affairs practitioners
to better understand why this is the case to ensure they enact the missions they embrace.
Our study did not specifically investigate the types of programs offered or the extent to which
students participated in these programs; however, we still contend practitioners should thoroughly
assess the effectiveness of their models. This examination should consider the following questions:
Do your programs meet diverse students’needs? Do you connect students to learning support
services, advisors, faculty, and other campus resources? Do you ensure students are engaged in
collaborative learning as well as positive social interactions? Evidence-based assessment of these
questions will clarify the distinctiveness of living on campus for individual campuses. Institutions
should identify the services, amenities, and programs off-campus students receive from their living
environments to inform comparisons with their residential conditions.
Along with more recent research that calls into question the wholesale advantages of living on
campus (Harwood et al., 2012; Mayhew et al., 2016; Strayhorn & Mullins, 2012; Turley &
Wodtke, 2010), our findings should prompt housing professionals to reexamine their assumptions
and practices. Indeed, convinced of the benefits, many institutions across the country require first-
year and sophomore students to live on campus (e.g., Braxton & McClendon, 2001). Given that
on-campus housing demands an enormous investment in resources, it is important to consider
how the findings from this study should impact practice.
What about Building Style and Amenities?
Although proximity explains some differences in engagement, further understanding is
needed to clarify how distinctions of living environment contribute to engagement. With the
shifting landscape of housing options (Baumann, 2016; Palmer, Broido, & Campbell, 2008), it is
important to assess the affect of changes in facilities on student interactions and subsequently the
benefits associated with on-campus housing. As institutions consider building new facilities,
careful attention should be paid to the impact of design details such as the balance between
private and public space, equity factors, and the optimization of educational experiences (Heasley,
Lengowski, Haapala, & Dunkel, 2015). In short, the relationship of hall design and student
success indicators must be considered in residence hall construction decisions along with market-
able features (Association of College and University Housing Officers—International (ACUHO-
I), 2015).
Are Commuter Students Better Off?
Conversely, could the lack of substantial effects on engagement be the result of exerted efforts
to engage off-campus students? Perhaps institutions have answered Jacoby’s(2000) charge to
“deepen commuter students’involvement in learning (p. 81). If institutions have made headway
in integrating off-campus students into the academic and social community, then the benefits of
living on campus have not declined; rather, the ill effects of living off campus have been
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attenuated. In the last few decades alone, there has been an explosion in scholarship, programs,
policies, and positions to support all students in transition (Keup & Barefoot, 2005; Tinto &
Goodsell, 1994; Upcraft, Gardner, & Barefoot, 2004). Arguably, the engagement of off-campus
students may be inflated for first-year students because of the substantial attention and resources
committed to first-year success.
Effects on Diverse Students
Although not discussed specifically in our results, our study illuminated insights into student
demographics for on- and off-campus students. Hispanic or Latino students were more likely to
live farther than walking distance from campus, while White students were much more likely to
live on-campus. There were also higher proportions of first-generation students living off-campus
compared to their peers. These breakdowns are important to consider given historically margin-
alized groups face various forms of discrimination and harassment living on-campus (Harper et al.,
2011; Harwood et al., 2012; Strayhorn & Mullins, 2012). It seems reasonable to assume that
experiencing discrimination has a negative impact on student engagement, which may play a factor
in our findings. Institutions should think critically about the environments they create on campus
for marginalized populations and seek to address their specific needs. Institutions should assess the
factors influencing students’decisions to live on- or off-campus, perceptions of the climate in their
living environment, and their interactions with diverse peers.
Does Technology Play a Role?
Lastly, researchers should further investigate the role of technology as it impacts students’
living situations (Mayhew et al., 2016). The nature of relationships between students is changing
with the mass use of social media and technology, including increased access to academic resources
and file sharing with peers (Jones, 2002). Wang, Tchernev, and Solloway (2012) summarized the
research on social media (SM) and claimed that SM offers
unprecedented convenience and efficiency for creating, maintaining, and strengthening social relation-
ships. Many features of SM facilitate self-disclosure and social interactions, such as the removal of
geographic boundaries and the rich interaction opportunities afforded by networks of ‘friends’and
information. (p. 1829)
SM (e.g., Facebook) can increase college student involvement (Heiberger & Harper, 2008)as
well as increase social integration to campus and persistence (Gray, Vitak, Easton, & Ellison,
2013). Changing technology usage may also mediate benefits to living on campus, and should be a
focus of future research.
Conclusion
Like much of the recent research on the topic, our findings suggest that the benefits of living
on-campus are not extensive. While there are positive effects for some measures of engagement
(i.e., collaborative learning, discussions with diverse others, and student-faculty interaction)
particularly when comparing on-campus students to those living farther than walking distance,
this was not the case for other forms of engagement, nor for students’perceived gains in learning
and growth in cocurricular areas. Although it is clear that proximity boosts engagement, we
encourage housing professionals not to rely on assertions that on-campus living is inherently
good. Rather, further research is necessary to parse out the sources of positive impact, further
investigating the environment, programming, and peer interactions to improve practice.
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Additionally, researchers should seek to better understand how differing populations experience
on-campus living, with the intention to address inequity. As housing options for students continue
to develop and change, it is incumbent upon residence life professionals to live up to their calling
as educators and consider the changing, complex landscape, responding accordingly.
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Appendix
Regression Results: Relationship of Living Arrangements with Engagement and Perceived
Gains for First-Year Students
Dependent Variables
Collaborative
Learning
Discussion with
Diverse Others
Student-Faculty
Interaction
Quality of
Interactions
Model
1
Model
2
Model
1
Model
2
Model
1
Model
2
Model
1
Model
2
Independent Variables Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Sex (constant) −0.16* −0.02 0.18 ** 0.27 *** −0.10 −0.01 0.32 *** 0.34 ***
0 = Female,
1 = Male
−0.04*** −0.04*** −0.03*** −0.03*** 0.07*** 0.07*** 0.12*** 0.12***
Self-reported
grades (ref.
Mostly A’s)
Mostly Bs −0.03*** −0.03*** −0.07*** −0.07*** −0.09*** −0.10*** −0.15*** −0.15***
Mostly Cs or
lower
−0.22*** −0.22*** −0.12*** −0.12*** −0.17*** −0.18*** −0.36*** −0.36***
Race/
ethnicity
(ref. White)
American
Indian/AK
Native
−0.01 −0.02 0.02 0.02 0.22*** 0.21*** −0.03 −0.03
Asian 0.05*** 0.08*** −0.13*** −0.11*** 0.06*** 0.08*** −0.07*** −0.06***
Black/African
American
0.07*** 0.03** −0.03* −0.04*** 0.21*** 0.19*** −0.04*** −0.04***
Hispanic/Latino −0.01 0.01 −0.02* −0.01 0.09*** 0.11*** −0.04** −0.03**
Pacific Islander 0.14* 0.17** −0.02 0.00 0.10 0.13* −0.08 −0.08
Other Race/
Ethnicity
0.01 0.00 −0.06*** −0.05*** 0.13*** 0.12*** −0.05*** −0.05***
Major
category
(ref. Business)
Arts and
Humanities
−0.17*** −0.17*** 0.12*** 0.12*** 0.10*** 0.10*** 0.03* 0.03*
Biological
Sciences
0.16*** 0.17*** 0.09*** 0.09*** 0.05*** 0.06*** 0.02 0.02
Physical
Sciences
−0.07*** −0.06*** 0.01 0.02 −0.12*** −0.11*** 0.04* 0.04*
Social Sciences −0.14*** −0.14*** 0.15*** 0.15*** 0.00 0.00 −0.01 −0.02
Communication −0.04* −0.05** 0.10*** 0.09*** 0.10*** 0.10*** 0.03 0.02
Education 0.01 0.02 0.07*** 0.07*** 0.15*** 0.15*** 0.08*** 0.08***
Engineering 0.24*** 0.24*** 0.04** 0.05*** −0.06*** −0.06*** 0.00 0.00
Health
Professions
0.16*** 0.16*** 0.02 0.02 0.05*** 0.05*** 0.00 0.00
Social Service
Professions
−0.08*** −0.08*** 0.08*** 0.08*** 0.01 0.02 0.04* 0.04*
Other Majors −0.07*** −0.07*** 0.03 0.03 0.04* 0.04* 0.07*** 0.07***
Undecided −0.24*** −0.23*** −0.11*** −0.10*** −0.16*** −0.15*** −0.13*** −0.13***
(continued )
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(Continued)
Dependent Variables
Collaborative
Learning
Discussion with
Diverse Others
Student-Faculty
Interaction
Quality of
Interactions
Model
1
Model
2
Model
1
Model
2
Model
1
Model
2
Model
1
Model
2
Independent Variables Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
Unstd.
B
First-
generation
−0.04*** −0.03*** −0.05*** −0.04*** 0.03*** 0.04*** −0.01 0.00
Traditional age (16–20 years
old)
0.33*** 0.24*** 0.08*** 0.02 0.16*** 0.10*** −0.13*** −0.15***
Transfer
status
−0.01 0.00 0.02 0.03* −0.03* −0.02 −0.04*** −0.04**
Time Spent Working (Hrs/Wk) 0.05*** 0.07*** 0.03*** 0.05*** 0.10*** 0.12*** −0.01*** −0.01**
Individual Institutions (546
dummy variables)
a
Residential
Status
Within walking
distance
−0.07*** −0.13*** 0.04** −0.05***
Farther than
walking
distance
−0.26*** −0.15*** −0.20*** −0.04***
R
2
0.06 0.07 0.04 0.05 0.06 0.06 0.05 0.05
Change in R
2
0.010*** .004*** .007*** .000***
Note: Unstd. B is the unstandardized beta coefficient.
a. Dummy-codes for each of the 576 institutions were included in the models, with one institution left out as a
reference group.
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