Community college leaders face challenges due to a lack of persistence data concerning 2-year colleges, especially in rural settings, prompting these leaders to turn to national data sets to drive local institutional changes. The purpose of this study was to identify variables associated with student place-frame and academic integration which are predictive of student persistence from the first to the second year in a small, residential community college in a rural frontier setting. Guided by Tinto's institutional departure theory, the theory of social representation, and Bassett's work in ruralism, a nonexperimental, correlational, quantitative research design was used to examine predictive relationships between student place-frame variables (age, sex, and intent to transfer), academic integration variables (student effort, collaborative learning, active learning, and academic challenge), and student persistence. Archival Community College Survey of Student Engagement data collected in 2013–2016 from 332 student participants were used for the study. Regression analysis showed a significant predictive relationship between student age and student intent to transfer with active learning. Additional binary logistical regression showed a significant positive relationship between active learning scores and student persistence. These findings informed development of evidence-based recommendations for programmatic changes to increase active learning practices, which could increase students' academic integration and persistence over time. By improving students' academic integration and persistence, positive social change may result through more students completing their degrees and their 2-year colleges gaining access to more substantial resources that are tied to student performance.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-8292 |
| Date | 01 January 2019 |
| Creators | Hunt, Jeannie |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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