Overview

Educational Data Mining uses data from learning management systems, intelligent tutors, assessments, classroom interactions, and learner-produced work to study how people learn and where they need support. Common approaches include predicting performance or disengagement from activity logs, knowledge tracing and cognitive diagnosis, graph-based recommendation, clustering learner behaviors, and language or multimodal analysis of dialogue and classroom activity. These methods can inform personalized practice, early warnings, tutoring, and instructional redesign, while large language models are increasingly used to analyze educational content and interactions. A central challenge is ensuring that models generalize across courses and learner groups, distinguish engagement from mastery, avoid data leakage, and support privacy and fair decisions rather than treating predictive accuracy as evidence of learning gains.

Latest papers

CardsList

74 papers7 papers in the last four weeks, down 22% on the four weeks before. 0.0% of all new papers.

  1. Toward Scalable Co-located Practical Learning: Assisting with Computer Vision and Multimodal Analytics

    Mar 14, 2026Xinyu Li, Linxuan Zhao, Yueqiao Jin +5Human Activity RecognitionVideo Object Detection

  2. Prediction of Grade, Gender, and Academic Performance of Children and Teenagers from Handwriting Using the Sigma-Lognormal Model

    Mar 12, 2026Adrian Iste, Kazuki Nishizawa, Chisa Tanaka +4Educational AssessmentEducational Data Mining

  3. Sandpiper: Orchestrated AI-Annotation for Educational Discourse at Scale

    Mar 9, 2026Daryl Hedley, Doug Pietrzak, Jorge Dias +9LLM-Assisted AnnotationHuman-in-the-Loop Annotation

  4. Personalized AI Practice Replicates Learning Rate Regularity at Scale

    Mar 9, 2026Jocelyn Beauchesne, Christine Maroti, Jeshua Bratman +6EducationPersonalized Learning

  5. Data-Driven Hints in Intelligent Tutoring Systems

    Mar 7, 2026Sutapa Dey Tithi, Kimia Fazeli, Dmitri Droujkov +3Intelligent Tutoring SystemsGenerative AI in Education

  6. Multi-view Attention Fusion of Heterogeneous Hypergraph with Dynamic Behavioral Profiling for Personalized Learning Resource Recommendation

    Mar 4, 2026Tao Xie, Yan Li, Yongpan Sheng +1Hypergraph LearningEducational Data Mining

  7. UniSkill: A Dataset for Matching University Curricula to Professional Competencies

    Mar 3, 2026Nurlan Musazade, Joszef Mezei, Mike ZhangEducational Data Mining

  8. Machine Learning Grade Prediction Using Students' Grades and Demographics

    Feb 28, 2026Mwayi Sonkhanani, Symon Chibaya, Clement N. NyirendaEducational Data MiningEducational Assessment

  9. Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

    Feb 26, 2026Xingcheng Fu, Shengpeng Wang, Yisen Gao +4Knowledge TracingEducational Data Mining

  10. Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

    Feb 19, 2026Valdemar Švábenský, Brendan Flanagan, Erwin Daniel López Zapata +1Educational Data Mining

  11. Instructor-Aligned Knowledge Graphs for Personalized Learning

    Feb 19, 2026Abdulrahman AlRabah, Priyanka Kargupta, Jiawei Han +1Personalized LearningKG Construction

  12. When AI Agents Teach Each Other: Discourse Patterns Resembling Peer Learning in the Moltbook Community

    Feb 16, 2026Eason Chen, Ce Guan, A Elshafiey +4LLM AgentsAI in Education