Student-at-risk detection by current learning performance indicators using Bayesian networks

2020/04/21 by Tatiana A. Kustitskaya, Kustitskaya, T. A., А. А. Кытманов +3
Computer Science · #62P25 #62P99 #Applications (stat.AP) #Educational Technology and Assessment #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics

paper · pdf · doi:10.48550/arxiv.2004.09774

openalex publication_date 2020/04/21 · openalex created_date 2020/05/01 · openalex updated_date 2026/07/28

Abstract

The present article is focused on the problem of prediction of student failures with the purpose of their possible prevention by timely introducing supportive measures. We propose a concept for building a predictive model based on Bayesian networks for an academic course or module taught in a blended learning format. Our empirical studies confirm that the proposed approach is perspective for the development of an early warning system for various stakeholders of the educational process.

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