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Community College Journal of Research and Practice,00:1–17,2014
Copyright © Taylor & Francis Group, LLC
ISSN: 1066-8926 print/1521-0413 online
DOI: 10.1080/10668926.2012.719481
Student Engagement and Institutional Graduation Rates:
Identifying High-Impact Educational Practices for
Community Colleges
Derek V. Price
DVP-PRAXIS LTD, Indianapolis, Indiana, USA
Esau Tovar
Counseling, Santa Monica College, Santa Monica, California, USA
Philanthropists, researchers, policymakers, and practitioners are increasingly focused on a college
completion crisis in the United States. Collectively and independently, they have called for increasing
the number of adults with postsecondary certificates and degrees as a national imperative. Using
the 2007 administration of the Community College Survey of Student Engagement (CCSSE), this
article explores the statistical relationships between student engagement, as measured by the CCSSE,
and institutional graduation rates reported to the Integrated Postsecondary Education Data System
(IPEDS). Both bivariate correlations and hierarchical multiple regression analyses yielded results
that reinforce the salience of student engagement as an important predictor of college completion.
Specifically, the CCSSE student engagement benchmarks of active and collaborative learning and
support for learners are positive predictors of institutional graduation rates. The article concludes
with suggestions around instructional practices and institutional policies to consider for community
college leaders committed to the completion agenda.
According to the National Center for Higher Education Management Systems (NCHEMS), with-
out a significant increase in degree attainment patterns, the United States will fall 16 million
degrees short of the number necessary to match leading nations and to meet the workforce needs
of 2025 (Jobs for the Future, 2007). More than 22% of the adult population in the United States,
or 37 million Americans, have attended college but not completed a degree (Lumina Foundation
for Education, 2010). Large numbers of students in every state drop out at key transition points
all along the education pipeline that runs from high school through college: on average, for every
100 students who are in the ninth grade, less than half will enroll in college within four years, and
only about 20% will earn a college degree (Davies, 2006). The most recent National Collegiate
Retention and Persistence to Degree Rates report (American College Testing, 2011)notedthat
the national first-to-second year retention rate for public community colleges was 55%. Likewise,
an examination of Integrated Postsecondary Education Data System (IPEDS) data put this figure
Address correspondence to Derek V. Price, President, DVP-PRAXIS LTD, 5034 North Capitol Avenue, Indianapolis,
IN 46208. E-mail: derek@dvp-praxis.org
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2D. V. PRICE AND E. TOVAR
at 60% for full-time students and 40% for part-time students across the nation (Snyder & Dillow,
2011). Moreover, the retention rates for African American, Latino, American Indian/Alaskan
Natives, and East Asian students are reportedly lower than those of White and Asian students
(Swail, Redd, & Perna, 2003). These reports and data point to a college completion crisis in the
United States.
During the past several years, business leaders, philanthropic organizations, researchers, and
policymakers have converged around the idea that more Americans need to enroll and suc-
ceed in college by earning a postsecondary credential. For example, the Lumina Foundation
is calling for the United States to increase higher education attainment rates so that 60% of
adults 25–64 years of age have a college credential by 2025. Similarly, the Bill and Melinda
Gates Foundation wants to double the numbers of low-income youth, 16–26 years of age, who
obtain a college credential. Six leading national higher education organizations have joined in a
completion commitment, setting the goal to produce an additional five million postsecondary
certificates and associate degrees by 2020 (see http://www.cccompletionchallenge.org/). The
organizations include Phi Theta Kappa Honor Society, American Association of Community
Colleges, Association of Community College Trustees, League for Innovation in the Community
College, National Institute for Staff and Organizational Development, and Center for Community
College Student Engagement.
Asignificantmajorityofbusinessleaders(over75%)believethatimprovingpostsecondary
completion will have an extremely or very positive impact on the economy and workforce pro-
ductivity (Bridgeland, Milano, & Rosenblum, 2011). Most notably, President Obama has stated
his goal for the United States to have the highest proportion of students graduating from college in
the world by 2020. These groups have defined a college credential broadly to include short-term
certificates as well as associate and baccalaureate degrees.
This convergence is supported by data regarding returns on a college education for individ-
uals, as well as by data indicating that the jobs of the future increasingly require education and
training beyond high school. Data on employment projections suggest that by 2018, 63% of new
and replacement jobs will require at least some postsecondary education (Carnevale, Rose, &
Cheah, 2011). A survey conducted for Business Roundtable revealed that almost two-thirds of
U.S. employers will require all, most, or some new employees to have earned an associate degree
or higher (Business Roundtable, 2010). The Georgetown University Center on Education and the
Workforce estimates that, since 1999, the premium for a colleg e e d u c a t i o n h a s g r own to 84%: On
average, a bachelor’s degree is worth $2.8 million over a lifetime. There is also a premium for
people with associate degrees who earn, on average, one-third more than those with only a high
school diploma (Carnevale, Rose, & Cheah, 2011). A recently released study also documents that
postsecondary certificate holders earn 20% more than high school graduates without any postsec-
ondary education (Carnevale, Rose, & Hanson, 2012). The bottom line is that employers need
workers with college credentials, and college credentials yield higher earnings for people who
attain them.
The challenge with this completion agenda is that no single solution is a panacea. Several
strategies will likely be needed to address this challenge including increasing the academic prepa-
ration of students who graduate high school; aligning high school and adult education curriculum
to college and career readiness standards; facilitating stronger connections between workforce
education and training and postsecondary education system; leveraging student financial aid more
effectively; and improving educational practices by colleges so more students already enrolled
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STUDENT ENGAGEMENT AND GRADUATION RATES 3
actually earn a postsecondary credential. None of these—or other—strategies can meet this
challenge alone; rather, all of them must be addressed if the United States is to successfully
meet this challenge.
Community colleges will play a critical role in the national agenda to improve the number and
percentages of adults with postsecondary credentials. Recent developments in the area of stu-
dent engagement and learning outcomes can help facilitate this ambitious goal. This article will
present research findings that highlight the impact of student engagement, and the correspond-
ing educational practices and policies, on graduation rates at community colleges throughout the
country. The analysis utilizes data from the Community College Survey of Student Engagement
(CCSSE), a widely accepted instrument that colleges use to meet varying institutional needs
including benchmarking, monitoring the effectiveness of institutional practices, identifying areas
where institutions can improve students’ educational experiences, accreditation, professional
development, and institutional research. Given the widespread use of CCSSE by community
colleges—between 2009 and 2011, 669 colleges in 48 states and the District of Columbia, five
Canadian provinces, Bermuda, and Northern Marianas administered the survey to more than
440,000 students (data retrieved from the CCSSE website: http://www.ccsse.org/survey/national.
cfm)—an analysis of the relationship between student engagement as measured by CCSSE and
institutional graduation rates would seem a useful contribution to the community college field.
(Both the NSSE and CCSSE have recently come under scrutiny by some researchers [see Nora,
2011, and the response from McCormick and McClenney, 2012]. Addressing these critiques is
beyond the scope of this article.)
Our study examines the relationship between CCSSE benchmarks on student engagement
and institutional graduation rates. Put simply, is there a statistical relationship between student
engagement benchmarks as measured by CCSSE and institutional graduation rates? And if this
relationship is statistically significant, what are the implications for educational practices and
policies at community colleges? Prior to delving into our methodology, findings, and conclu-
sions, we briefly discuss the research literature on community college student persistence and
student engagement.
REVIEW OF LITERATURE
According to the 2010 issue of the Digest of Education Statistics,communitycollegestudents
accounted for more than one-third of the 19.1 million students attending degree-granting institu-
tions in fall 2008; during the fall 2009, 7.1 million students attended a public community college
in the United States (Snyder & Dillow, 2011). Community colleges serve as the entry point
into higher education for many impacted groups including traditionally underrepresented ethnic
minorities like Black and Hispanic students, low-income, and first-generation college students.
Unlike four-year college students, the vast majority of students at public community colleges
attend on a part-time basis (about 60% in 2009) and on a more varied daytime/evening basis,
work a significant number of hours per week, commute, and have family responsibilities such as
child care, and are often financially strained (Cohen & Brawer, 2008;Gonzalez,2000;Grimes,
1997).
Additionally, community college students are often unprepared for college-level course-
work as evidenced by their reading, writing, and mathematics skills. A recent study conducted
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4D. V. PRICE AND E. TOVAR
by the National Center for Education Statistics found that just over 40% of students in the
2007–2008 National Postsecondary Student Aid Study reported taking remedial courses while
at these institutions (Snyder & Dillow, 2011). A nationally representative study utilizing the
National Education Longitudinal Study of 1988 dataset found that 58% of community col-
lege students took at least one remedial course (Attewell, Lavin, Domina, & Levey, 2006).
Similarly, a study comprising institutions participating in the Achieving the Dream initiative
found that 59% of students enrolled in at least one developmental course (Bailey, Jeong, & Cho,
2010).
Take n t ogether, t h e a b ove characteristics p l a c e p u b l i c c o m m u n i t y c o l l e g e s t u d e n t s a t r i s k o f n o t
succeeding academically (Tovar & Simon, 2006)ordroppingoutofcollegebeforecompletinga
certificate or degree. Consequently, these students require intentional assistance from community
colleges to support their success. The Digest of Education Statistics reported that one in five
of the 2005 first-time, full-time degree-seeking students attending public community colleges
obtained an associate degree or certificate within 150% of the expected normal time, or three
years (Snyder & Dillow, 2011). This percentage differed markedly by race/ethnicity: about 30%
for nonresident aliens, 26% for Asian/Pacific Islanders, 23% for Whites, 18% for American
Indian/Alaskan Natives, 16% for Hispanics, and 12% for Blacks. With respect to gender, men
graduated at a slightly lower rate than women (20% versus 21%, respectively). Thus, meeting
the credential attainment challenge is especially critical for community colleges, whose students
traditionally experience a variety of barriers to degree attainment (Cohen & Brawer, 2008;Kim,
Sax, Lee, & Hagedorn, 2010).
Numerous theoretical frameworks have been proposed and advanced over the course of the
past four decades to explicate why attrition occurs at two-year colleges and universities (e.g.,
Bean, 1982;Bean&Eaton,2000;Nora,Barlow,&Crisp,2005;Spady,1970,1971;Swailetal.,
2003;Tinto,1975,1993),butlesssoforhowtoeffectivelyaddressit(Tinto,2006). Vincent
Tinto’s model of student departure (1993) has received the most attention. This model empha-
sizes the need for students to separate from their former communities to successfully transition
to college, thus enabling them to partake of the programs and services available at the college.
Furthermore, the model promotes the central role of academic and social integration experiences,
inside and outside the classroom, as cornerstones to student retention and persistence. Tinto’s
model has been criticized for placing significant onus on the student while deemphasizing the role
of the institution and institutional agents—faculty, staff, administrators—in promoting or imped-
ing student success and retention (Bensimon, 2007). Additionally, it has been noted that Tinto’s
model does not sufficiently explain the experiences of historically underrepresented groups such
as ethnic minorities, first-generation to college, and low-income students, or students attending
community colleges (Bensimon, 2007;Cejda&Hoover,2010;Rendón,Jalomo,&Nora,2000;
Tierney, 1992).
In recent years, Tinto himself has come to acknowledge the limitations of his model: that
the process of retaining students differs by institutional type, and that breaking connections to
student’s former communities (e.g., home) is not necessary to successfully transition and succeed
in college (Tinto, 2006). Most recently, Tinto (2012) has also emphasized the need to refocus
institutional action (intervention) around four key conditions that foster student success: setting
high expectations; providing academic, social, and financial support; engaging in frequent and
timely assessment and feedback; and creating opportunities for student involvement. Each of
these conditions is under direct institutional control.
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STUDENT ENGAGEMENT AND GRADUATION RATES 5
Recent research substantiates the key role that institutional faculty, staff, and administra-
tors play in facilitating or impeding student success, both in and out-of-the classroom (Barnett,
2010;Braxton&McClendon,2001;Cejda&Hoover,2010;Deil-Amen,2011;Karp,Hughes,
&O’Gara,2010;Lundberg&Schreiner,2004;Stanton-Salazar,1997;Tinto,2012). Both
Deil-Amen and Cejda and Hoover found that for community college students, student-faculty
interactions of an academic and social nature served as vehicles for imparting important infor-
mation to students, increased their comfort in college, and were precursors to student retention.
The importance of these interactions as perceived by students is that they occur simultaneously.
These socioacademic integrative moments transpire during events or activities when students
interact with institutional agents and other students (Deil-Amen, 2011).
The study of student engagement has gained considerable attention over the last decade, pri-
marily in response to demands from the public, legislators, and accreditors that colleges and
universities demonstrate the link between college attendance and student outcomes. Engagement,
as described by Kuh (2009),ischaracterizedastheamountoftimeandeffortthatstudents
place in their involvement in educationally beneficial practices that promote their learning and
development. Engagement also refers to the intentional efforts institutions place in investing
and in promoting these activities to affect student success and academic attainment (Kuh, 2009;
McClenney, 2004;McClenney,Marti,&Adkins,2006).
Student engagement as is now conceptualized is rooted in the works of Pace (1980, 1984)on
quality of effort, and Astin’s (1984) theory of student involvement; and it also largely reflects
Chickering and Gamson’s (1987) seven principles of effective educational practice in undergrad-
uate education. Given its prominence in educational circles, the construct of engagement has been
promulgated significantly via the development of a few student engagement surveys administered
nationally (and in select countries) including the National Survey of Student Engagement (NSSE)
and the CCSSE. These instruments are composed of dozens of items ingrained in the higher edu-
cation literature that correlate highly with educational outcomes (e.g., learning, retention, grades),
are reflective of institutional practices and student and faculty behaviors, and provide colleges and
universities with actionable data to improve the college student experience.
In the case of the CCSSE, which is the basis for the present study, the following are the
five student engagement benchmarks: active and collaborative learning; student effort; academic
challenge; student-faculty interaction; and support for learners. Research on the CCSSE has been
conducted using single-institution datasets (e.g., Akin, 2009;Balog&Search,2006;Reynolds,
2007;Schuetz,2008), as well as multiple-institution, multistate, or national datasets (e.g., Lynch
Ervin, 2010;McClenney,2007;McClenney&Marti,2006;Roman,Taylor,&Hans-Vaughn,
2010). Furthermore, the Center for Community College Student Engagement (CCCSE) at the
University of Texas-Austin regularly analyzes and disseminates findings on student engagement
to the public at-large.
Take n a l together, r e s e a r c h s t u d i e s u s i n g C C S S E g e n e r a l l y find that student engagement
in educationally effective practices has a positive effect on outcomes such as retention, per-
sistence, grade point average, and in some instances, on degree completion. For example, a
multiyear study encompassing CCSSE benchmark scores for students enrolled across the Florida
Community College System (reported in McClenney & Marti, 2006)foundamoderateeffectof
student engagement as measured by the five benchmarks on grade point average (GPA): Student
engagement accounted for well over 30% of the variance after controlling for a variety of back-
ground variables. Likewise, small effects were found for the active and collaborative learning
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6D. V. PRICE AND E. TOVAR
benchmark on course completion ratio. With respect to associate degree attainment, the study
also found small effects for the active and collaborative learning, student effort, and the sup-
port for learners’ benchmarks. The active and collaborative learning benchmark also significantly
predicted persistence to the following term and the second year. What is particularly notable
in this study is a set of conditional effects found showing that increased levels of engagement
significantly improved GPA for academically underprepared students, but not for college-ready
students, and for African American students. Similarly, conditional effects on course completion
ratios were found for both African-Americans and Hispanics: That is, increased levels of engage-
ment improved course completion ratios for these two groups of students. A second national
study comprising 24 community colleges participating in the Achieving the Dream Initiative
(2002–2004) found that three of the CCSSE’s five benchmarks (active and collaborative learn-
ing, academic challenge, and student-faculty interaction) positively correlated with degree or
certificate attainment.
In summarizing findings from three independent studies sponsored by CCSSE, McClenney
and Marti (2006) observed that the benchmarks most closely associated with degree/certificate
attainment were active and collaborative learning, academic challenge, and student-faculty inter-
action (with bivariate correlations ranging from .07 to .11). All except the support for learners’
benchmarks significantly correlated with cumulative GPA. In addition, active and collaborative
learning, followed by faculty-student interaction and support for learners, were most closely
related to persistence to second term and to second year of college.
METHODOLOGY
Data Sources
Community College Survey of Student Engagement
Data for this study were provided by the Center for Community College Student Engagement
at The University of Texas-Austin; they encompassed 166,031 student-level records from the
2007 administration of the CCSSE. A total of 279 institutions participated in this administration;
however, only 261 community colleges met criteria for inclusion in this study by reporting grad-
uation rates for 2009 via their annual IPEDS (Integrated Postsecondary Education Data System)
submission. The missing 18 institutions either (a) did not report a 2009 graduation rate; (b) were
part of a university system that reported combined graduation rates for its four-year and two-
year programs; or (c) was not a U.S. based-institution. The 261 colleges accounted for 162,394
(97.8%) students taking the 2007 CCSSE.
According to the Center for Community College Student Engagement, CCSSE provides infor-
mation on students’ engagement in educationally effective practices and student behaviors that
are closely associated with student learning and student retention at community colleges (CCCSE,
2011). This includes the frequency with which students engage in classroom discussions; interact
with faculty members in and out of class; participate in learning opportunities (e.g., internships,
developmental education, learning communities); extracurricular activities; academic and student
support services, etc. Students also report on the level of academic challenge they experience in
college, assignments, and examinations, as well as on the mental activities in which they engage
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STUDENT ENGAGEMENT AND GRADUATION RATES 7
(e.g., memorizing, synthesizing information). CCSSE is administered annually at participating
institutions during the spring semester to randomly selected credit-bearing classes.
Subsequent to its administration, results are summarized in five standardized benchmarks
reflective of the content noted above. According to Marti (2008),thefivebenchmarks,which
together constitute a model of effective educational practice, were derived via confirmatory fac-
tor analysis based on psychometric and expert feedback. Marti further notes that CCSSE has
demonstrated reasonable internal reliability across these measures: active and collaborative learn-
ing (α=.66), student effort (α=.56), academic challenge (α=.80), student–faculty interaction
(α=.67), and support for learners (α=.76). Consistent with its goal, Marti goes on to state that
CCSSE is a “reliable instrument that can be used to inform institutional decision making with
regard to teaching practices, campus design, and institutional culture. ...and can be used for
research with community college students” (p. 2).
Integrated Postsecondary Education Data System
AcustomdatafilewasdownloadedfromtheNationalCenterforEducationStatisticsIPEDS
Data Center with graduation rates and institutional characteristics. The file contained multiple
institutional characteristics, student enrollment statistics, and 2009 graduation rates variables for
1,769 Title IV, degree granting, two-year institutions in the United States. The IPEDS graduation
rate measures the percentage of first-time, full-time students who earned a college credential at
the same institution within three years of initial enrollment.
These two data sources (CCSSE and IPEDS) were merged to create an analytic file with col-
leges as the unit of analysis. We derived institutional-level variables by averaging responses for
each student’s CCSSE benchmark and variable composing each benchmark. We first analyzed the
degree of missing data for each variable and determined that missing data was a relatively minor
issue. We then conducted multiple imputation in SPSS (five imputed sets) to replace missing val-
ues on the benchmarks, based on their pooled values (Marti, 2008). The pooled means were very
close to the original means without imputation. Lastly, these data were subsequently merged with
the IPEDS data above, thus forming our analytic working file for this research project.
Data Analysis
Two s e t s o f a nalyses were conducted to address our research quest i o n s . I n t h e fi r s t s e t , w e a d j u s t e d
our analyses using an institutional weight variable computed by CCSSE that is based on the ratio
of part-time to full-time students at the college. This set was comprised of full- and part-time
students. We did not adjust outcomes in the second set, which was based on CCSSE benchmark
scores for only full-time students.
For each of the analyses, we first ran bivariate correlation statistics to determine if the CCSSE
benchmark and individual items comprising it were statistically associated with 2009 gradua-
tion rates for the institution and for specific groups of students (i.e., males, females, and for
several race and ethnic groups). Given statistically significant correlations, we pursued hier-
archical ordinary least squares (OLS) regression analysis. The dependent variable was the
2009 institutional graduation rate. Independent variables were entered in two blocks. The first
block controlled for the effects of several institutional-level student demographic variables
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8D. V. PRICE AND E. TOVAR
obtained from IPEDS: variables were percentage of students that were female; Black (non-
Hispanic); Hispanic; Asian/Pacific Islander; and attending full-time. Also included in Block
1wereinstitutional-levelvariablesincludedintheCCSSEdatafile:variableswerecollegesize
(small to extra-large, dummy coded); urbanicity (urban to rural, dummy coded); and percentage
of survey respondents who had taken developmental English or math courses. Block 2 consisted
exclusively of the CCSSE standardized benchmark scores: active and collaborative learning;
student effort; academic challenge; student-faculty interaction; and support for learners.
The CCSSE benchmarks together reflect a “model of effective educational practices” (compare
to Marti, 2008,p.2);thus,itseemedplausiblethataninstitutionscoringfavorablyononebench-
mark could also score favorably on other benchmarks. From a statistical perspective, that means
CCSSE benchmarks could be multicollinear. We examined this possibility in two ways. First, we
reviewed multicollinearity statistics and standardized residuals. This review resulted in two cases
with excessive residual values (>±3.29) (Tabachnick & Fidell, 2006), so we removed them from
the analytic file. The result from this decision is that tolerance and variance inflation factor (VIF)
values are well-within acceptable levels of >.2 and <4.0, respectively (Garson, 2012). Second,
we examined multicollinearity diagnostics and inter-variable correlation. This review indicated
eight of 14 dimensions with condition indices greater than 15; however, among these dimensions,
no two variables within a dimension had correlations greater than .50 (Garson, 2012;Tabachnick
&Fidell,2006).Giventheresultsofthesetwoapproaches,weconcludedthatmulticollinearity
is not an issue for our analysis, and thus our regression coefficients are not biased.
Limitations
AlimitationofthisstudyisthatIPEDSgraduationratedatameasureonlyfirst-time,full-time
students at a college who graduate at the same institution within three years, while CCSSE is
administered in the spring term to all college students. Thus, the student responses used to create
institutional-level student engagement benchmarks are not necessarily from the same students
who would be counted in the IPEDS graduation rate data. This limitation resulting from access to
aggregate data only on a national basis is widely applicable to most educational studies because
the nation’s postsecondary institutions lack a student unit record data system that could be used
by researchers to explore patterns of student progress and completion in college more precisely.
The consequence of this limitation is that researchers have to develop and use proxy measures to
indirectly assess student progress (Ewell & Jones, 1993). Accordingly, the results from this anal-
ysis should be considered a proximate estimate of the relationship between student engagement
and graduation rates.
RESULTS
Table 1 presents a summary of institutional characteristics for the community colleges composing
our study, and it shows how these compare to public two-year degree-granting institutions in the
United States. This table excludes all private colleges because the vast majority (96%) of CCSSE
participants were public two-year institutions. With respect to student characteristics, CCSSE
colleges tended to be much larger in total enrollment, full-time, and part-time enrollment; and
they have a slightly higher percentage of Hispanic and nonresident alien students but a lower
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STUDENT ENGAGEMENT AND GRADUATION RATES 9
TA B L E 1
2007 Institutional Characteristics for Public Associate Degree-Granting Colleges: CCSSE Participants
Ver s us No n pa r t ic i pa n ts
Institutional Characteristic
CCSSE Student
Par t i cip a n ts
(N=162,394)a
CCSSE
Institutions
(N=249)b
Mean
Non-CCSSE
Institutions
(N=805)b
Mean
All Public
Institutions
(N=1,053)
Mean
Institutional student enrollment
Tot a l e nro l l men t ∗∗∗ 8131.31 5737.47 6304.08
Full-time equivalent enrollment: Fall 2007∗∗∗ 4816.40 3414.86 3746.59
Full-time enrollment∗∗∗ 3090.76 2230.38 2434.02
Part-time enrollment∗∗∗ 5040.55 3507.09 3870.05
Percent of total enrollment that are:
White, non-Hispanic 62.3 65.88 64.03 64.47
Black, non-Hispanic∗11.3 12.05 15.00 14.30
Hispanic∗14.0 11.43 9.38 9.86
Asian or Pacific Islander 5.7 3.43 4.00 3.87
American Indian or Alaskan Native 1.5 .96 1.58 1.43
Race/ethnicity unknown 4.3 4.98 5.17 5.13
Nonresident alien∗∗∗ −1.19 .74 .85
Women 59.2 58.54 58.89 58.81
Under 18 −9.07 8.96 8.98
18–24∗68.0 52.92 50.86 51.35
25–64∗∗ 31.6 37.31 39.30 38.83
Over 65 .4 .59 .83 .77
Receiving any grant aid∗44.85 48.28 47.45
Receiving Pell grant 28.57 29.60 29.35
Current year GRS cohort as a percent of entering class∗∗∗ 39.89 39.94 39.93
Attending full-time 69.7
Attending first semester 11.0
Completed 1–29 credits 53.8
Completed 30+credits 35.2
Too k D eve l opm e n tal M a t h or En g l ish 47.7
English is first language 85.7
aSource: CCSSE 2007.
bIPEDS Data Center: Fall 2007.
∗p<.05, ∗∗p<.01, ∗∗∗p<.001 (Differences examined for IPEDS derived data only).
percentage of Black students. Students 18–24 years of age tended to also be overrepresented at
CCSSE colleges, but those 25–64 years of age were somewhat underrepresented. Lastly, fewer of
the students attending CCSSE colleges received any type of grant aid financial assistance.
Correlations: The Relationship Between Student Engagement and IPEDS Graduation
Rates
As shown in Tab l e 2 ,bivariatecorrelationanalysisindicatedthatthreeofthefivestudentengage-
ment benchmarks were correlated to a statistically significant degree with IPEDS graduation rates
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10 D. V. PRICE AND E. TOVAR
TA B L E 2
Correlations Between 2009 IPEDS Graduation Rates With Weighted and Unweighted CCSSE Benchmark
Scores
CCSSE Benchmark (and Number of Benchmark Variables Significantly Correlated
With Re sp ec tive Grad ua ti on R ate)
Active &
Collaborative
Learning
(7 Variables)
Student
Effort
(8 Variables)
Academic
Challenge
(10 Variables)
Student–Faculty
Interaction
(6 Variables)
Support for
Learners
(7 Variables)
Wei g h ted g r a dua t i on ra t e : All s t u den t s
Total cohort .25∗∗∗ (6) .05 (5) .01 (2) .22∗∗∗ (2) .19∗∗ (5)
Men .29∗∗∗ (6) .06 (3) .05 (3) .23∗∗∗ (3) .17∗∗ (6)
Wom e n . 23∗∗∗ (6) .08 (4) .09 (2) .16∗∗ (2) .18∗∗ (4)
White, non-Hispanic .21∗∗∗ (5) −.03 (3) .07 (1) .23∗∗∗ (2) .12∗(3)
Black, non-Hispanic .03 (0) .04 (1) .04 (1) .09 (2) .12‡(2)
Hispanic .15∗(3) −.06 (0) −.02 (0) .18∗∗ (3) −.01 (1)
Asian/Pacific Islander .06 (1) −.03 (1) −.04 (0) .06 (0) .05 (0)
American Indian or Alaskan
Native
.15∗(3) .09 (1) .12 (3) .21∗∗∗ (2) .17∗∗ (3)
Unweighted graduation rate: Full-time students only
Total cohort .22∗∗∗ (4) −.04 (3) .08 (3) .17∗∗ (3) .20∗∗∗ (5)
Men .26∗∗∗ (5) .00 (2) .02 (2) .20∗∗∗ (2) .18∗∗ (4)
Wom e n . 20∗∗ (4) −.03 (2) .06 (1) .11‡(2) .18∗∗ (5)
White, non-Hispanic .18∗∗ (4) −.12∗(2) .05 (2) .19∗∗ (3) .15∗(3)
Black, non-Hispanic .05 (0) .06 (1) .08 (2) .06 (2) .08 (0)
Hispanic .16∗∗ (3) −.08 (0) .05 (1) .16∗∗ (3) .02 (2)
Asian/Pacific Islander .10 (1) .02 (1) .04 (0) .09 (1) .08 (2)
American Indian or Alaskan
Native
.14∗(2) .11 (1) .09 (0) .18∗∗ (3) .18∗∗ (4)
∗∗∗p<.001, ∗∗p<.01, ∗p<.05, ‡p<.10.
for the institutions participating in this study: benchmarks were active and collaborative learn-
ing, student-faculty interaction, and support for learners. Additionally, we examined correlations
between student engagement benchmarks and institutional graduation rates for specific groups of
students. Bivariate correlations were statistically significant for both men’s and women’s gradu-
ation rates and for graduation rates of Whites, non-Hispanics, Hispanics, and American Indian/
Alaskan Natives. However, these bivariate correlations did not hold for graduation rates of Black,
non-Hispanics, or Asian/Pacific Islanders. While none of the benchmarks correlated significantly
with graduation rates for Black and Asian/Pacific Islander students, an analysis of the individual
variables composing each benchmark revealed that a few items did correlate with their respective
graduation rates. (These data are not reported in this article.)
The pattern of correlations was also consistent across the weighted and unweighted CCSSE
benchmark scores. However, the magnitude of the correlations was marginally higher (.01–.05)
for the active and collaborative learning and student–faculty interaction benchmarks for the
weighted scores, but it was lower (.0–.03) for the support for learners benchmark in comparison
to the correlations for the unweighted scores. The strongest correlation was between the men’s
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STUDENT ENGAGEMENT AND GRADUATION RATES 11
graduation rate and the active and collaborative benchmark for all students (weighted) and for
full-time students only (unweighted), r=.29 and r=.26 respectively. This was closely followed
for the total cohort. Correlations ranged from .14 to .29.
Regression Analyses: The Role of Student Engagement in Predicting IPEDS
Graduation Rates
The first regression analysis assessed the impact of student engagement (Block 2) on IPEDS
graduation rates for all students while controlling for institutional characteristics (Block 1).
As previously noted, this analysis was based on weighted CCSSE benchmark scores for all stu-
dents participating in CCSSE including full- and part-time students. As shown in Tab l e 3 ,the
regression model accounted for 32% of the variance in graduation rate, F(13, 248) =8.39,
p<.001, R2=.32, adjusted R2=.28. Results indicated that among Block 1 variables,
the percentage of Black (β=−.30), Hispanic (β=−.30), and of developmental students
(β=−.20) attending the institution negatively predicted graduation rate; whereas the percentage
of Asian/Pacific Islander students (β=.21) positively predicted graduation (p<.01). Block 1
accounted for 24% of the total variance. The single statistically significant predictor in Block 2
(student engagement) was the support for learners benchmark (β=.22); however, the active and
collaborative learning benchmark approached statistical significance. This block accounted for
8%ofthetotalvariance(p<.01).
The second regression analysis assessed the relationship of student engagement (Block 2) and
graduation rates for full-time students only while controlling for institutional characteristics
(Block 1). The analysis was based on the unweighted benchmark scores of full-time students
participating in CCSSE. As shown in Tab l e 3 ,thefinalregressionmodelaccountedfor40%of
the total variance in graduation rate, F(13, 244) =12.06, p<.001, R2=.40, adjusted R2=.37.
Similar to Block 1 in the regression model above, the percentage of Hispanic (β=−.31), Black
(β=−.27), and of developmental students (β=−.18) attending the institution negatively pre-
dicted graduation rate; whereas the percentage of Asian/Pacific Islander students attending the
college (β=.23) positively predicted graduation (p<.01). Neither college size nor the degree of
urbanicity had an effect on graduation rate. With respect to variables in Block 2, which accounted
for 8% of the variance (p<.01), two of the five student engagement benchmarks significantly
predicted IPEDS graduation rates: active and collaborative learning (β=.30) and support for
learners (β=.22). In sum, the CCSSE benchmarks contributed eight percentage points of the
overall explanatory power in this model (R2=.40); and both the active and collaborative learn-
ing and the support for learners benchmarks were significant and positive predictor of graduation
rates. Put another way, 20% of the explanatory power of the regression model is attributed to the
CCSSE benchmarks of institutional student engagement.
DISCUSSION AND IMPLICATIONS FOR COMMUNITY COLLEGE PRACTICES AND
POLICIES
The results above provide support for the salience of student engagement as an important pre-
dictor of college completion. Student engagement is statistically associated with institutional
graduation rates; in particular, the CCSSE benchmarks of active and collaborative learning and
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12 D. V. PRICE AND E. TOVAR
TA B L E 3
The Impact of Institutional Characteristics and Student Engagement on 2009 Community Colleges IPEDS
Graduation Rates
Model 1 Model 2
Variable B SE βtBSEBt
Wei g h ted g r a dua t i on ra t e : All s t u den t s
Constant 37.31 10.94 3.41∗∗∗ −18.14 16 −1.14
Block 1: Institutional characteristics
Percentage full-time, 2009 8.4 6.65 .08 1.26 1.74 6.66 .02 .26
Percentage developmental −23.4 10.87 −.10 −2.15∗−36.86 11.5 −.20 −3.2∗∗
Percentage women −.05 .12 −.03 −.45 −.02 .13 −.01 −.17
Percentage Asian/Hawaiian/Pacific
Islander
.51 .11 .29 4.65∗∗∗ .38 .12 .21 3.05∗∗
Percentage Black/African
American
−.25 .07 −.20 −3.42∗∗ −.28 .07 −.30 −3.90∗∗∗
Percentage Hispanic/Latino(a) −.17 .06 −.20 −2.69∗∗ −.24 .07 −.30 −3.58∗∗∗
College size −1.03 .97 −.10 −1.06 .72 1.01 .05 .72
Urbanicity 1.18 .98 .08 1.21 .88 .96 .06 .91
Block 2: Student engagement
benchmark
Active and collaborative learning .46 .28 .15 1.67
Student effort −.21 .30 −.10 −.68
Academic challenge .22 .32 .06 .70
Student–faculty interaction .06 .33 .02 .17
Support for learners .68 .26 .22 2.62∗∗
R2=.24 R2change =.08 R2=.32
Unweighted graduation rate: Full-time
students only
Constant 42.79 9.40 42.79 7.18 14.45 .50
Block 1: Institutional characteristics
Percentage full-time, 2009 9.85 5.74 .11 9.85 7.49 5.63 .08 1.33
Percentage developmental −16.70 8.98 −.12 −16.70 −26.52 9.65 −.18 −2.75∗∗
Percentage women −.26 .10 −.14 −.26 −.14 .11 −.08 −1.27
Percentage Asian/Hawaiian/Pacific
Islander
.50 .09 .32 .50 .36 .10 .23 3.44∗∗∗
Percentage Black/African
American
−.26 .06 −.26 −.26 −.27 .06 −.27 −4.60∗∗∗
Percentage Hispanic/Latino(a) −.17 .05 −.21 −.17 −.25 .06 −.31 −4.48∗∗∗
College size −.56 .84 −.05 −.56 .78 .84 .06 .93
Urbanicity 1.68 .85 .13 1.68 .81 .83 .06 .98
Block 2: Student engagement
benchmark
Active and collaborative learning .83 .23 .30 3.57∗∗∗
Student effort −.34 .26 −.11 −1.33
Academic challenge −.19 .27 −.05 −.70
Student–faculty interaction −.24 .26 −.08 −.94
Support for learners .60 .20 .22 3.00∗∗
R2=.33 R2change =.08 R2=.40
∗∗∗p<.001, ∗∗p<.01, ∗p<.05.
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STUDENT ENGAGEMENT AND GRADUATION RATES 13
support for learners have impact. Additionally, several items that together represent these two
benchmarks are also statistically associated with institutional graduation rates: four of seven
items representing active and collaborative learning, and five of seven items representing sup-
port for learners. Exploring this finding further reveals both institution-wide and classroom-based
behaviors to consider as potential high-impact educational practices.
With regard to active and collaborative learning, faculty should consider incorporating or
expanding the effective instructional and pedagogical practices listed below. These practices
reflect the four underlying items in the active and collaborative learning benchmark that were
statistically correlated with institutional graduation rates:
•Requiringstudentstoworktogetheronprojectsduringclass.
•Encouragingstudenttoworkwithclassmatesoutsideofclasstoprepareclassassignments.
•Creatingopportunitiesforstudentstotutoreachother,eithervoluntaryorpaid.
•Committingfacultytimeforstudentstodiscussideasfromreadingsorclasseswith
instructors outside of class.
There are many ways to incorporate these practices in the classroom and beyond. For exam-
ple, assignments could require groups to complete rather than individual students, and time in
class and outside class could be set aside for this collaborative approach to learning. Learning
communities are a popular way for faculty to collaborate with each other and establish classroom
collaborative practices for students. Emergent evidence from a randomized control trial of learn-
ing community participants at an urban community college in the mid-Atlantic region suggests
that learning communities enable students to complete developmental education courses more
successfully, earn more college credits, and earn a college credential (Sommo, Mayer, Rudd, &
Cullinan, in press). Supplemental instruction represents another widely used strategy for peer-to-
peer teaching and learning; and faculty can bring their office hours to their students by spending
time in academic support centers or by joining students during lunch or dinner breaks in the
cafeteria or food courts. There remains a need for additional research on these and other specific
instructional practices and their impact on student success and college completion. However, the
evidence from this analysis suggests that effective instructional practices will need to incorporate
principles of active and collaborative learning.
With regard to support for learners, community colleges need to reconsider how they structure
and deliver student supports, both academic and nonacademic, and including financial aid. This
analysis suggests the following policy and practice areas for institutional leaders to consider that
can support the college completion agenda:
•Whatarethespecificsupportsstudentsneedtohelpthemsucceedatcommunitycollege,
and how can we better provide these supports?
•Howcancommunitycollegesbetterhelpstudentscopewithnonacademicresponsibilities
such as work and family?
•Whatkindsofsupportsshouldcommunitycollegesprovidetoenablestudentstothrive
socially?
•Howcancommunitycollegesprovidemoreeffectivelythefinancialsupportstudentsneed
to afford college?
•Howcancollegesincreasethefrequencybywhichstudentsreceiveadvisingservicesfor
academic and career planning?
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14 D. V. PRICE AND E. TOVAR
These questions speak directly to institutional leadership and institution-wide commitment to
creating an environment where support for learners is part of the college-culture, and the sup-
port is infused in the behavior and attitudes of faculty, staff, and administrators. This analysis
suggests that students who attend community colleges that provide a supportive environment
through academic advising; nonacademic supports (e.g., counseling); and financial supports are
more engaged–and more engagement around the support for learners’ benchmark is predictive of
higher institutional graduation rates.
The challenge for community colleges is identifying and enacting policies and practices
around academic and nonacademic support services that are proactive rather than waiting for stu-
dents to seek them. For example, recent research from the Community College Research Center
suggests that students who enroll in structured programs of study early on are more likely to earn
credentials (Jenkins & Cho, 2012); thus, one way for community colleges to revamp their aca-
demic support structure is to have an advising process that is more prescriptive for students. More
prescriptive advising could also include career planning and requiring regular advisor-student
engagement throughout a student’s academic career. Community colleges may also need to find
innovative ways to support students financially. This can be done through work-study or other
on-campus work opportunities so that external work responsibilities are less likely to distract stu-
dents from their academic coursework. Several research studies have shown a significant negative
relationship between the numbers of hours worked and GPA for students who worked more than
15 hours a week (e.g., Bozick, 2007;Dundes&Marx,2006). Researchers have also found that
students who worked 20 or fewer hours on campus had higher grades than students who did not
work or who worked more than 20 hours per week (Pike, Kuh, & Massa-McKinley, 2008).
CONCLUSION
This analysis provides empirical support that student engagement—specifically as it is experi-
enced through active and collaborative learning and in a supportive institutional environment for
learners—can result in higher graduation rates. While additional research can be useful in doc-
umenting more precisely what high-impact educational practices look like, community college
leaders committed to the completion agenda need not wait for such evidence to act. Enabling and
encouraging faculty to incorporate effective active and collaborative learning practices in their
classroom and beyond, and addressing institution-wide policies and practices that provide more
support for learners, can yield better student engagement, and thereby improve student success.
FUNDING
This research was supported by the Center for Community College Student Engagement at The
University of Texas-Austin. The authors are solely responsible for the analysis and conclusions.
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