Presentation information

General Session

General Session » [GS] J-12 Human interface, education aid

[1O3-J-12] Human interface, education aid: education and evaluation

Tue. Jun 4, 2019 3:20 PM - 4:20 PM Room O (Front-left room of 1F Exhibition hall)

Chair:Masato Soga Reviewer:Megumi Kurayama

3:20 PM - 3:40 PM

[1O3-J-12-01] Hidden Markov IRT model as a generalization of Bayesian Knowledge Tracing

〇Emiko Tsutsumi1, Shuhei Shionoya1, Masaki Uto1, Maomi Ueno1 (1. The University of Electro-Communications)

Keywords:Bayesian Knowledge Tracing, Item response theory, Hidden Markov model

To develop learner's ability, a teacher should grasp the learner's knowledge state accurately in a learning process.For this purpose, Bayesian Knowledge Tracing (BKT) has been proposed to infer learner's knowledge state.Although conventional BKT models learner's knowledge state as a discrete value, the learner's knowledge state must be contentious. Based on this idea, we propose a Hidden Markov IRT model as a generalization of Bayesian Knowledge Tracing. In the proposed model, learner's knowledge state takes a continuous value and change according to a Hidden Markov process in a learning process. The proposed model estimates the optimal value of the degree of learner's mastering knowledge from learning data.From some numerical experiments, we demonstrate that the proposed model improves the estimation accuracy of the learner's knowledge state.