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Download full textWang, Feng; Chen, Li – International Educational Data Mining Society, 2016
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…
Descriptors: Identification, At Risk Students, Online Courses, Large Group Instruction
