College completion is an issue of great concern in the United States, where only 50% of students who start college as freshmen complete a bachelor's degree at that institution within six years. Researchers have studied a variety of factors to understand their relationship to student persistence. Not surprisingly, student characteristics, particularly their academic background prior to entering college, have a tremendous influence on college success. Colleges and universities have little control over student characteristics unless they screen out lesser qualified students during the admissions process, but selectivity is contrary to the push for increased accessibility for under-served groups. As a result, institutions need to better understand the factors that they can control. High-impact educational practices have been shown to improve retention and persistence through increased student engagement. Service-learning, a pedagogical approach that blends meaningful community service and reflection with course content, is a practice that is increasing in popularity, and it has proven beneficial at increasing student learning and engagement. The purpose of this study was to investigate whether participation in service-learning has any influence in the likelihood of degree completion or time to degree and, secondarily, to compare different methods of analysis to determine whether use of more complex models provides better information or more accurate prediction. The population for this study was a large public urban research institution in the mid-Atlantic region, and the sample was the cohort of students who started as first-time, full-time, bachelor's degree-seeking undergraduates in the fall of 2005. Data included demographic and academic characteristics upon matriculation, as well as financial need and aid, academic major, and progress indicators for each of the first six years of enrollment. Cumulative data were analyzed using logistic regression, and year-to-year data were analyzed using discrete-time survival analysis in a structural equation modeling (SEM) framework. Parameter estimates and odds ratios for the predictors in each model were compared. Some similarities were found in the variables that predict degree completion, but there were also some striking differences. The strongest predictors for degree completion were pre-college academic characteristics and strength of academic progress while in college (credits earned and GPA). When analyzed using logistic regression and cross-sectional data, service-learning participation was not a significant predictor for completion, but it did have an effect on completion time for those students who earned a degree within six years. When analyzed longitudinally using discrete-time survival analysis, however, service-learning participation is strongly predictive of degree completion, particularly when credits are earned in the third, fourth, and sixth years of enrollment. In the survival analysis model, service-learning credits earned were also more significant for predicting degree completion than other credits earned. In terms of data analysis, logistic regression was effective at predicting completion, but survival analysis seems to provide a more robust method for studying specific variables that may vary by time.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-3909 |
| Date | 01 January 2012 |
| Creators | Lockeman, Kelly |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © The Author |
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