Which Psychosocial Characteristics
Make a Difference in the
Engagement of University Freshmen?
M.E.B. Garrison & R.V. Rohli
Louisiana State University
Baton Rouge, LA, US
Abstract
Findings
Implications
The purpose was to investigate the relationship among three
psychosocial characteristics and the engagement of first-year
college students. Statistically significant correlations were found
between engagement and (a) sense of belongingness, (b) selfregulated learning, and (c) academic self-concept. Multiple
linear regression analysis revealed that self-regulated learning
was a better predictor of engagement than belonging and academic self-concept. Findings suggest that first year and precollege programs should emphasize the development selfefficacy over other psychosocial characteristics.
Most of the respondents lived on campus and a plurality were female and white. The mean high school GPA for the survey respondents was 3.48 (SD = 0.39) on a 4.0 scale and the mean ACT
score was a 26 (SD = 3.46). Of the respondents, only 89 (8.2%)
were first-generation college students. The belongingness score
(summed variable) ranged from 12 to 39 with mean of 28.14 and a
standard deviation of 4.02. This result suggests that, in general,
students reported feeling that they fit in well at LSU. The selfregulated learning score (summed variable) ranged from 13 to 55
with a mean of 39.75 and a standard deviation of 8.05, indicating
that students reported perceiving themselves as „well‟ or „mostly
well‟ self-regulated. The range of the academic self-concept score
(summed variable) was from 5 to 25 with mean of 22.08 and a standard deviation of 3.08. This result suggests that students reported
high academic self-concepts. With respect to engagement, the
scale mean was 2.37 and the standard deviation was 1.00, indicating that students were only moderately engaged. The Pearson
correlation analysis revealed that belongingness, self-regulated
learning, and academic self-concept were all significantly (α < 0.01)
related to engagement (r = .33, .38, and .26, respectively). Multiple
linear (ordinary least squares, single block) regression analysis
revealed that self-regulated learning was a better predictor of engagement, as indicated by the standardized regression coefficient,
than belongingness and academic self-concept (Beta = .29, .10,
and .11, respectively), although all three were statistically significant predictors of engagement (t-tests ranged from 3.27 to 9.01).
Living-learning programs that aim to increase the engagement
level of their students must focus on providing quality, positive
interactions with faculty. Identifying specific interests of the
students in the programs and having faculty interact with them
in these areas would be helpful for improving the students‟
sense of self-regulated learning as would teaching them goal
setting. Particularly in resource-constrained programs, efforts
targeted to increase such interactions could be tied to classes
in some manner so that the largest number of students would
be reached. Faculty-led co-curricular programming, such as
through “track coordinators” within subareas of a given livinglearning program, may also represent an effective model for
directing efforts to improve self-regulated learning and sustaining student-faculty communication.
Method
Following IRB approval and as part of a larger study, the target
population was defined as all first-year students at a large,
public, research-extensive university in the South. The entire
population (n=4,583) was surveyed for the study. Students
were invited by the Office of the First Year Experience at the
university to complete an electronic survey via e-mail. Follow-up
e-mails were sent to non-responders after one week and two
weeks. A total of 1,341 (29.26%) of students responded to the
survey. Of these respondents, 221 students did not complete
the entire survey, however; and one student‟s data were unable
to be obtained from the registrar‟s office due to use of an e-mail
address that was not on file. This resulted in a final response
rate of 24.42% or 1,119 usable surveys.
For the survey, sense of belongingness was measured using an
adapted version of Schussler and Fierros‟ (2008) Learning
Community Survey and comprised an 8-item Likert-type scale.
Self-regulated learning, developed by Zimmerman, Bandura
and Martinez-Pons, (1992) comprised an 11-item, 5 point scale
of students‟ perceived capabilities. Academic self-concept was
measured using an abridged version of the Academic SelfConcept Scale (Reynolds et al., 1980) and comprised an 8
item, 5 point Likert-type scale. The Student Academic/Social
Interaction Questionnaire (SA/SIQ), a 14-item Likert-type scale,
was developed for the study to measure student engagement.
All other academic and demographic information was obtained
from the registrar‟s office for each respondent. Students supplied their identification number when completing the survey.
The data from the registrar‟s office were linked to the responses
on the surveys using the students‟ e-mail addresses, and then
all identifiers were destroyed. The data were analyzed using
SPSS.
Several other implications of this research are notable. In the
current study, and in the previous quantitative studies where
engagement was measured in living-learning communities,
engagement is represented by the frequency of students‟
academic and social interactions with faculty and other students. It is usually assumed that all interactions with faculty
and peers are positive. But the mere frequency of interactions
cannot give the total picture when it comes to the engagement
of students.
Qualitative measures, such as focus groups, should be used
in future research to address the nature and effectiveness of
those interactions. Survey questions could include a measure
of the student‟s satisfaction with the interactions and depth of
involvement. Furthermore, the extent to which a student
should be engaged is seldom mentioned. Is there a point at
which students are so engaged that they become enmeshed
and the engagement becomes problematic? Colleges and
universities continue to create programs to increase the academic success of students. Measuring the success of the
program is beneficial, but a helpful first step is considering the
level of engagement and identifying ways to increase it.
For more information visit us at http://lsu.edu or contact:
Robert V. Rohli
[email protected]
Betsy Garrison
[email protected]