Date of Award
2024-12-01
Degree Name
Ed.D.
Department
Educational Leadership and Administration
Advisor(s)
Penelope Espinoza
Abstract
Each year, approximately 64% of admitted students do not enroll at the University of Texas at El Paso (UTEP). This is particularly concerning given the projected decline in regional high school graduates beginning in the 2025-2026 academic year. The El Paso region is also predominantly composed of groups who have been historically underrepresented in higher education, including Hispanic or Latino students, individuals from low socio-economic backgrounds, and first-generation college students. Using logistic regression analysis, this quantitative study investigates how seven key factors impact the likelihood of enrollment among admitted UTEP applicants. The study utilized admissions data provided by UTEP’s Texas Public Information Act office. The predictive model developed by two different statistical software packages (SPSS and R) demonstrates improvements in accuracy of 9.7% and 8.4% over the null model. Results revealed that college readiness, as defined by the Texas Administrative Code, had the strongest impact on the likelihood of enrollment. Increases in High school quartile and prior college credits both positively influence the likelihood of enrollment while first-generation status and increases in unmet financial need and applicant distance from UTEP negatively impact the likelihood of enrollment. Notably, students selected for financial aid verification are more likely to enroll, challenging initial assumptions. A potential scale of measurement error in the unmet financial need variable was also identified. The model explains a modest proportion of variance in enrollment and has moderate predictive power (25.4% Nagelkerke R2 and .765 AUC ROC score). However, the results of the study provide actionable insights to support UTEP’s enrollment strategies. The study recommends utilizing machine learning for any future predictive modeling. The study illustrates the potential of predictive modeling to inform campus leaders and advance UTEP’s mission of expanding educational opportunities.
Language
en
Provenance
Recieved from ProQuest
Copyright Date
2024-12-01
File Size
113 p.
File Format
application/pdf
Rights Holder
Marcus Gay
Recommended Citation
Gay, Marcus, "Examining Key Predictors Of Enrollment At A Regional, Open-Access Research University On The U.S. - Mexico Border" (2024). Open Access Theses & Dissertations. 4243.
https://scholarworks.utep.edu/open_etd/4243