Compară metode

	Bayesian Knowledge Tracing	Cognitive Diagnostic Modeling
Domeniu	Education	Education
Familie	Machine learning	Latent structure
Anul apariției	1994	2010
Autorul original	Albert Corbett & John Anderson	Tatsuoka; DiBello, Roussos & Stout; Junker & Sijtsma; de la Torre
Tip	Two-state hidden Markov model of latent skill mastery from response sequences	Restricted latent class models for diagnosing mastery of discrete skills
Sursa seminală	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.	Rupp, A. A., Templin, J., & Henson, R. A. (2010). Diagnostic Measurement: Theory, Methods, and Applications. Guilford Press. ISBN: 9781606235270
Denumiri alternative	BKT, Knowledge Tracing (Corbett-Anderson), Hidden Markov Knowledge Tracing, Skill Mastery Tracing	CDM, Diagnostic Classification Models, DCM, DINA / G-DINA Models
Înrudite	3	4
Rezumat	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.	Cognitive diagnostic models (CDMs), also called diagnostic classification models, are restricted latent class models that report not a single ability score but a profile of which discrete skills or attributes a student has mastered. Each item is linked to the attributes it requires through a Q-matrix, and the model classifies every examinee into one of the possible binary mastery patterns. CDMs answer 'which specific skills does this student lack' rather than 'how much overall ability does this student have,' making them central to fine-grained diagnostic and formative assessment.