Bayesian knowledge tracing

Bayesian knowledge tracing is an <a href="/facts/Algorithm/fnl5NmRt">algorithm</a> used in many <a href="/facts/Intelligent_tutoring_systems/DsaIre48">intelligent tutoring systems</a> to model each learner's mastery of the knowledge being tutored.
It models student knowledge in a <a href="/facts/Hidden_Markov_model/ur1zTAhP">hidden Markov model</a> as a latent variable, updated by observing the correctness of each student's interaction in which they apply the skill in question.
BKT assumes that student knowledge is represented as a set of <a href="/facts/Binary_data/PSFa5S2Q">binary variables</a>, one per skill, where the skill is either mastered
by the student or not. Observations in BKT are also binary: a student gets a problem/step either right or wrong.
<a href="/facts/Intelligent_tutoring_systems/DsaIre48">Intelligent tutoring systems</a> often use BKT for mastery learning and problem sequencing. In its most common
implementation, BKT has only skill-specific parameters.

Bayesian knowledge tracing open-in-new

Bayesian knowledge tracing