How to identify at-risk students in open online courses has received increasing attention, since the dropout rate is unexpectedly high. Most prior studies have focused on using machine learning techniques to predict student dropout based on features extracted from students' learning activity logs. However, little work has viewed the dropout…

A study described the nontraditional adult students attending full-time, occupationally specific vocational training programs in Ohio. It also developed a dropout prediction model of enrolled students using sets of independent variables adapted from the Conceptual Model of Nontraditional Student Attrition and Persistence in Postsecondary…