Abstract
Predictive modeling can help identify students who may be “at-risk” to drop out from an online course. An early detection of academically at-risk students will allow instructors and advisors to proactively use appropriate retention strategies. The purpose of this paper is to perform a study to analyze variables and construct a predictive model uniquely suited to identify students who may be more likely to drop out from an online course.
Recommended Citation
Bukralia, Rajeev, "Predictive Modeling to Improve Retention of Online Students" (2009). MWAIS 2009 Proceedings. 12.
https://aisel.aisnet.org/mwais2009/12
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