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.
@article{arxiv.2004.09774,
title = {Student-at-risk detection by current learning performance indicators using Bayesian networks},
author = {T. A. Kustitskaya and A. A. Kytmanov and M. V. Noskov},
journal= {arXiv preprint arXiv:2004.09774},
year = {2020}
}