The Predictive Power of Nontraditional Student Characteristics on Online Degree Completion: A Regression Analysis

Abstract

Non-traditional students (NTS) represent the majority of students who are enrolling in online learning. However, NTS experience retention rates of 7 – 30% lower than their traditional counterparts. This quantitative study examined the characteristics of NTS as predictors of bachelor’s degree completion in a 100% online learning environment with four-year universities in the United States. Rovai’s Composite Persistence Model (CPM), which formed the underpinnings for the study, suggested that the characteristics of NTS and environmental factors create risk factors, which impede academic success, especially in online learning environments (Rovai, 2003). Data were collected from anonymous online questionnaires completed by 270 eligible participants. The data were collected for the following variables: bachelor’s degree completion status, minority status, first-generation status, secondary school completion status, marital status with or without dependents, and unemployed status. The data for the variables of marital status with or without dependents, unemployed status, and secondary school completion status were removed from the study as the data violated the assumptions of multicollinearity and linearity of logistic regression tests. Predictor variables included in the study were participants who were first-generation students whose parents did not attend college, part-time and full-time employed at the time of starting their degrees, and minority status. The results of the binomial logistic regression analyses showed that minority status was significant in predicting degree completion. First-generation status and part-time and full-time employment status were not significantly predictive of degree completion. The results of the study may help administrators in the online modality develop strategies to help NTS succeed. Developing and implementing automated tracking systems and reporting of student characteristics such as gender and age, internal and external environmental factors may benefit scholars and higher education administrators in taking proactive steps to improve student retention and success.