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Knowledge Tracing/Evidence
Method evidence record

Knowledge Tracing

Knowledge Tracing (KT) is a student-modeling technique that estimates, at each moment in time, the probability that a learner has mastered a target knowledge component. Introduced by Corbett and Anderson in 1994, the classical Bayesian Knowledge Tracing (BKT) model treats skill acquisition as a two-state Hidden Markov Model driven by four interpretable parameters: prior knowledge, learning rate, slip, and guess. Deep variants (DKT, DKVMN, AKT) later replaced HMMs with recurrent and transformer architectures.

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Knowledge Tracing (Bayesian / Deep)
Taxonomic method record · ml-model / education-analytics
  • 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 10.1007/BF01099821
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Related methods

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See alsoBayesian Networkmachine-suggested · Relational suggestion, not evidence.Same method familyLSTMmachine-suggested · Relational suggestion, not evidence.See alsoRasch Modelmachine-suggested · Relational suggestion, not evidence.

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Sources

1 recorded citation, copied from the method source record.

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