A Logistic Regression Study of How Pre-Enrollment Factors Predict Graduation at a Christian Historically Black University
School of Education
Doctor of Education in Curriculum & Instruction (EdD)
Higher Education, Graduation Rates, HBCU, Pre-admission Factors
Education | Higher Education
Young, Tara Laron, "A Logistic Regression Study of How Pre-Enrollment Factors Predict Graduation at a Christian Historically Black University" (2018). Doctoral Dissertations and Projects. 1916.
The purpose of this logistic regression study is to review the pre-admission factors through the lenses of multiple retention constructs and graduation rates at a Christian, Historically Black College or University (HBCU). A binary logistic regression is used to analyze the odds of graduation based on a set of pre-admission factors of first-time freshmen, as predictor variables. In particular, the predictor variables of interest are eligibility of academic support based on academic scholarships, gender, international status, and type of high school attended. The outcome variable of interest is graduation. This study is important because it contributes to the scholarship in the study of Christian HBCUs and the understanding of how preadmission factors may affect graduation. This study addresses the problem by using regression relationships to guide supportive programs that reinforce retention, persistence, and completion of students based on pre-admission factors, as reflected in the work of Tinto, Astin and other theorists. The number of participants used for this regression analysis supports adequate statistical power for a medium effect size. This study took place at a Christian HBCU in north Alabama with data collected from the admissions office for the freshmen class of 2011, where N=364. The results of this study suggest that students that attend a private high school have high odds of completing a post-secondary degree at a Christian HBCU and makes recommendations to support the retention and recruitment of the targeted population. The implications for further research could include a variety of replication studies with additional preadmission factors, longitudinal, mixed methods, or qualitative studies reviewing persistence, completion, and yearly graduation rates as they relate to the preadmission factors.