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Educational Data Mining×Bayesian Knowledge Tracing×
分野EducationEducation
系統Machine learningMachine learning
提唱年20091994
提唱者Educational data mining community (Baker, Yacef, Romero, Ventura)Albert Corbett & John Anderson
種類Application of data-mining and machine-learning methods to educational dataTwo-state hidden Markov model of latent skill mastery from response sequences
原典Baker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3–17. link ↗Corbett, A. T., & Anderson, J. R. (1994). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4(4), 253–278. DOI ↗
別名EDM, Mining Education Data, Data Mining in Education, Learner Data MiningBKT, Knowledge Tracing (Corbett-Anderson), Hidden Markov Knowledge Tracing, Skill Mastery Tracing
関連43
概要Educational data mining (EDM) is the field that develops and applies data-mining and machine-learning methods to data generated by educational settings — clickstreams from online courses, intelligent tutoring system logs, assessment records, and student information systems. Its goal is to discover patterns that explain and predict learning: who is at risk of failing, how students work through material, which content sequences help, and what hidden skill structures underlie performance. EDM treats fine-grained learner data as a source of actionable scientific and practical insight.Bayesian knowledge tracing (BKT) is a model that estimates, after each problem a student attempts, the probability that the student has mastered the underlying skill. Introduced by Corbett and Anderson for intelligent tutoring systems, it is a two-state hidden Markov model: the latent variable is whether the skill is learned or not, and observed correct/incorrect responses update that latent state through Bayesian inference. With just four parameters — initial knowledge, learning, slip, and guess — BKT drives the mastery decisions that tell a tutor when a student can move on.
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ScholarGate手法を比較: Educational Data Mining · Bayesian Knowledge Tracing. 2026-06-24に以下より取得 https://scholargate.app/ja/compare