Factors that Predict Persistence in College at the University of Wisconsin-Parkside

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The presentation will explore whether
participation in service-learning is
related to persistence in college with a
focus on the University of Wisconsin-
Parkside.
Helen Rosenberg
Professor
University of Wisconsin-Parkside

Published in: Education
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  • Success is the dependent variable and is defined as re-enrollment or graduation.
  • Some of these contribute to retention, while others do not. For example, academic integration and social integration contribute to retention. Academic integration=learning communities; CBL; Social integration=clubs;
    CBL contributes to students’ feelings of integration in that students report that they feel part of a larger whole and that faculty and administrators care about them.

    Engagement as measure of academic integration: National Survey of Student Engagement (NSSE) finds that students involved in “high impact practices” more likely to re-enroll (Kuh, 2012)
  • What remains stable over time: age, first generation status, race and the number of freshmen enrolled in each year.
    Slight increases in gender
    Increases in part-time status – full time students tend to graduate earlier so greater percentages of part time students are left
    GPA increases over time.
    Service learning was defined as any student taking a service learning course. As the number of students in service learning increase, the total increases with time.
    Enrollment: 65% of freshmen enrolled in 2009 are enrolled in 2010
    51% are enrolled in 2011 and 41% are enrolled in 2012
    Our statistics show that after six years, only about 37% of our entering students have graduated.
  • Our dependent measure was success, defined as re-enrollment or graduation.
  • What matters
    Overall, students who take service learning classes are almost twice as likely to re-enroll and graduate as those who do not
  • What matters
    Race seems to make the most difference the first year of school, but then its effects on persistence decline
  • What matters
    Transfer: This effect is significant only in the last year, 2012 with transfer students more likely to persist
    It becomes statistically insignificant when full time status and GPA are entered in the analysis
  • Not enough classes at 200 level
  • Factors that Predict Persistence in College at the University of Wisconsin-Parkside

    1. 1. Factors that Predict Persistence in College at the University of Wisconsin-Parkside Following a Student Cohort from 2009 through 2012
    2. 2. Research  Why focus on non-traditional students?  UWP has greatest percentage of students receiving Pell grants in UW- System  Over 2/3rds of students work in addition to going to school full time  UWP has the highest percentage of students of color in the UW-System  UWP has the lowest retention rate in the UW-System, 30%  20% of students do not return after the freshman year
    3. 3. Research  Predictors of successful outcomes for UW-Parkside students  What is success?  The dependent measure is persistence over time  Persistence refers to long-term outcomes, while retention is most often used to talk about re-enrollment from freshman to sophomore year
    4. 4. Factors contributing to re-enrollment Tinto (1975, 1997, 2005) identified four factors: academic integration social integration financial pressures psychological differences, i.e., family background, past educational experiences
    5. 5. Identifying Non-traditional Students 24+ or 25 + years old Employed Full-time Married/Caregiving Part time enrollment First Generation Students of Color (sometimes referred to as “under represented students”) The term "nontraditional student" is not a precise one (NCES, 2002)
    6. 6. Independent Variables Measures of Non-traditionality Age (24+) Enrolled Part Time First Generation College Student Race (students of color) Service Learning Took service learning class or not Demographics Gender Freshman/Transfer Students GPA
    7. 7. Demographic Distribution of Students entering UWP N=1155 Measures of Non- traditionality Age (24+) Enrolled Part Time First Generation College Student Race (students of color) Service Learning Took service learning class or not Demographics Gender Freshmen/Transfer Students GPA Persistence to Graduation Measure Fall, 2010 Fall, 2011 Fall, 2012 24+ 11.7% 12.0% 11.6% Part-time 40.3% 56.9% 65.7% First Gen 60.1% 60.4% 60.5% Students of Color 29.4% 27.4% 29.4% Took SL 13.3% 24.2% 34.0% Female 56.8% 56.5% 60.1% Freshmen 71.7% 69.5% 68.1% GPA 2.59 2.73 2.85 Re- Enrolled/G raduated 65% 51% 41%
    8. 8. Correlations Among Independent Measures  Strongest relationship  Full-time enrollment and GPA  Positive relationships  Students who enroll in CBL classes tend to be full-time  Students who enroll in CBL classes tend to have higher GPAs than students who do not take a class with CBL  Conclusion:  There is a strong relationship among full-time enrollment, CBL course enrollment and GPA
    9. 9. Correlations Among Independent Measures Demographic relationships to GPA  Men and students of color tend to have lower GPAs than women and Whites.  There is no relationship between being a first generation student and GPA  Transfer students tend to be older and earn higher GPAs than incoming Freshmen  Older (24+) students are more likely to be part-time and earn lower GPAs than younger students
    10. 10. Methodology Logistic Regression Analysis predicts reenrollment or graduation (coded 1) or non- enrollment as a dichotomous dependent variable Used backwards, stepwise technique for exploratory analysis Allows entry of sets of variables in stepwise manner to assess the relative effect explained by each variable in model First step entered measures of non-traditionality and demographics Second step entered if student enrolled in a CBL course Third step entered GPA Followed sample across 2010, 2011 and 2012 © 1998 G. Meixner
    11. 11. Significance of Service-Learning Students who take service-learning courses are more likely to persist.  Service Learning has a consistently strong impact on reenrollment and graduation.  When full-time enrollment and GPA are added into the model, the effects of service learning decline because of its strong relationship to these variables
    12. 12. Significance of Demographics Race Race is an inconsistent predictor of persistence with white students more likely to reenroll.  Students of color are about 75% as likely to re-enroll and graduate as are white students Age The effects of age are slight and insignificant over time First Generation Status The effect of being a first generation college student is slight and becomes insignificant over time
    13. 13. Significance of Transfer Students and Full-Time Status Transfer Students Entry status is an inconsistent predictor of re-enrollment with transfer students more likely to persist. Full-time Status Full time status is a powerful predictor of reenrollment throughout all years of the analysis  The effects of full-time enrollment are very strong, but decline when GPA is added to the model
    14. 14. Service-Learning has a positive effect on all students (traditional and non-traditional) Part-time enrollment seems to pose the greatest challenges for non-traditional students in relation to re-enrollment Service learning was significant for freshmen and juniors, but not for second year Implications for UW-Parkside

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