Estimation of Students’ Learning States using Bayesian Networks and Log Data of Learning Management System

Nobuhiko Kondo; Toshiharu Hatanaka

doi:10.52731/ijirm.v3.i2.460

Nobuhiko Kondo Tokyo Metropolitan University http://orcid.org/0000-0003-1507-8196
Toshiharu Hatanaka Osaka University

DOI: https://doi.org/10.52731/ijirm.v3.i2.460

Keywords: Learning analytics, Institutional research, Bayesian networks, Learning management system, Learning states

Abstract

Over the last decade, learning analytics (LA) and its related fields have rapidly developed. LA has become a robust concept of Institutional Research (IR) or student support. In this study, building a model of learning process by a Bayesian network from a large amount of educational data has been studied. Moreover, we propose the Bayesian network model for the learning process based on the log data accumulated from the learning management system (LMS). From the numerical simulation results, the proposed approach can be used to predict certain learning states of students.

Author Biographies

Nobuhiko Kondo, Tokyo Metropolitan University

Nobuhiko Kondo is an associate professor at the University Education Center, Tokyo Metropolitan University, Japan.

Toshiharu Hatanaka, Osaka University

Toshiharu Hatanaka is an assistant professor at the Graduate School of Information Science and Technology, Osaka University, Japan.

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