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arXiv Machine Learning By Qingchuan Lyu, Yingxin Li, Albert Yang

Study-Strategy Clusters from EdNet Logs Track Engagement, Not Mastery

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The study clusters 5,000 EdNet-KT3 learners into eight study‑strategy groups based on early‑session behaviors such as resource use, revision, video watching, and problem practice. These clusters predict later engagement metrics—like continued practice and session completion—but do not reliably forecast later unassisted accuracy or mastery. The findings suggest that behavioral clustering captures learning styles and engagement patterns rather than knowledge gains.

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