Determining The Drivers Of Student Performance In Online Business Courses

Abstract

An emerging question in business education is whether all students would benefit from distance learning and if student performance can be predicted prior to enrollment in an online course based on student characteristics. In this paper, the role of student characteristics on academic performance is examined in the context two different online courses. Empirical test of a self-assessment tool on 272 students across 9 course sections, using a logistic regression framework demonstrates that end-of-semester student grades can be predicted by students' own self-reports of their learning preferences at the onset of the course. However systematic differences are found between the two courses in terms of the drivers of student performance, demonstrating the importance of a customized approach to the predictive framework presented.