2014/07/26 by Tanmay Sinha, Patrick Jermann, Sinha, Tanmay +5 · 2 citations
Computer Science · Psychology · Social Sciences · #Educational Games and Gamification #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Innovative Teaching Methods #Machine Learning (cs.LG) #Online Learning and Analytics
paper · pdf · doi:10.48550/arxiv.1407.7131
openalex publication_date 2014/07/26 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28
In this work, we explore video lecture interaction in Massive Open Online\nCourses (MOOCs), which is central to student learning experience on these\neducational platforms. As a research contribution, we operationalize video\nlecture clickstreams of students into cognitively plausible higher level\nbehaviors, and construct a quantitative information processing index, which can\naid instructors to better understand MOOC hurdles and reason about\nunsatisfactory learning outcomes. Our results illustrate how such a metric\ninspired by cognitive psychology can help answer critical questions regarding\nstudents' engagement, their future click interactions and participation\ntrajectories that lead to in-video & course dropouts. Implications for research\nand practice are discussed\n