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arXiv Machine Learning By Samuel Girard, Juan D. Pinto, Jill-J\^enn Vie, Amel Bouzeghoub

RegKT: Interpretable and Robust Deep Knowledge Tracing With IRT-Regularizer

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RegKT introduces an IRT‑regularizer to deep knowledge tracing models, aiming to improve both interpretability and robustness. The paper argues that while deep learning has boosted accuracy, it has reduced explainability and increased overfitting, especially on small educational datasets. By adding this regularization, RegKT seeks to make deep knowledge tracing more suitable for real‑world educational applications.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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