Cédric D’Ham

Adaptive test recommendation for mastery learning

By Nassim Bouarour, Idir Benouaret, Cédric D’Ham, Sihem Amer-Yahia

2023-06-12

In Proceedings of the 2nd international workshop on data systems education: Bridging education practice with education research

Abstract We tackle the problem of recommending tests to learners to achieve upskilling. Our work is grounded in two learning theories: mastery learning, an instructional strategy that guides learners by providing them tests of increasing difficulty, reviewing their test results, and iterating until they reach a level of mastery; Flow Theory, which identifies different test zones, frustration, learnable, flow and boredom zones, to determine the best k tests to recommend to a learner.

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