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A Robust Machine Learning Technique to Predict Low-Performing Students
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Liao, Soohyun Nam; Zingaro, Daniel; Thai, Kevin; Alvarado, Christine; Griswold, William G.; Porter, Leo – ACM Transactions on Computing Education, 2019
As enrollments and class sizes in postsecondary institutions have increased, instructors have sought automated and lightweight means to identify students who are at risk of performing poorly in a course. This identification must be performed early enough in the term to allow instructors to assist those students before they fall irreparably behind.…
Descriptors: Prediction, Low Achievement, Tests, Scores