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Download full textAzhar, Aqil Zainal; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2022
This paper studies the use of Reinforcement Learning (RL) policies for optimizing the sequencing of online learning materials to students. Our approach provides an end to end pipeline for automatically deriving and evaluating robust representations of students' interactions and policies for content sequencing in online educational settings. We…
Descriptors: Reinforcement, Instructional Materials, Learning Analytics, Policy Analysis
