ORCID ID
0000-0002-8892-8465
Date Awarded
2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.)
Department
Education
Advisor
Pamela L Eddy
Committee Member
James H Stronge
Committee Member
Thomas J Ward
Abstract
Vertical transfer is a centennial symbol of access that also provides inputs for operational funding and produces outcomes for performance-based funding (PBF). Thus, this mission-critical community college function may be leveraged to decisively impact the higher education completion agenda. Yet, deeper insights into student level data are needed to understand what powers vertical transfer efficiency. Previous research used administrative data, analyzed access, and tracked transfer outcomes, but few studies have used vertical transfer as a single analysis framework to reconcile access and efficiency goals while examining tensions between access, accountability, and resource allocation. The body of research tends to isolate and individually analyze student and institutional variables related to the input, process, and output factors of institutional performance. to connect access and efficiency, this study linked student course-taking variables to institutional performance outcomes. The conceptual framework fused resource dependence and choice overload theories to examine institutional resource allocation and student course selection. Predictive models replicated the Community College Transfer Calculator and cohesively linked access, efficiency, institutional accountability, and funding. For a largely part-time cohort, this study found that course-taking variables, including average credits per semester significantly predicted the likelihood of vertical transfer and bachelor's degree completion within six years. PBF points were highly sensitive to vertical transfer, and USP outcomes intensified PBF point gains.
DOI
http://dx.doi.org/10.25774/w4-zrpq-5x45
Rights
© The Author
Recommended Citation
Ellerbe, LaVerne Wingate, "Connecting Access and Efficiency: Community College Course-Taking Patterns That Predict Vertical Transfer" (2019). Dissertations, Theses, and Masters Projects. William & Mary. Paper 1550153974.
http://dx.doi.org/10.25774/w4-zrpq-5x45