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Prediction of In-Class Performance Based on MFO-ATTENTION-LSTM

Abstract In this paper, we present a novel approach to predicting in-class performance using log data from course learning, which is important in the field of personalized education and classroom management. Specifically, a set of fine-grained features is extracted from unit learning log data to tra...

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Autors principals: Xue Qin, Cang Wang, YouShu Yuan, Rui Qi
Format: Artigo
Idioma:Inglês
Publicat: Springer 2024-01-01
Col·lecció:International Journal of Computational Intelligence Systems
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Accés en línia:https://doi.org/10.1007/s44196-023-00395-3
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