Using Logistic Regression to Determine Factors Affecting the Completion of an Online Geographic Information Systems Master's Program

• In Event: 63.042 - Graduate Student Experiences and Completion

Abstract

While there are many studies on student persistence in undergraduate programs offered in traditional classroom settings, there is a lack of empirical research investigating the factors affecting the completion of online advanced degree programs. In order to address such research need, this study collected student data from an online GIS Master’s program and employed logistic regression to assess a set of predictors in predicting whether or not a student completed the program. Instead of demographic and entry-level characteristics, students’ academic performance in the present program such as current GPA, credits taken, and stop-out years is found to have significant predictive power of students’ completion of the MGIS program.

Authors

• Jae-Young Park

• Won Ho Kim, The Pennsylvania State University

• Heng Patrick Luo, The Pennsylvania State University

• Jim Detwiler, John A. Dutton e-Education Institute