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