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- W2952529418 abstract "In Intelligent Tutoring System (ITS), tracing the student's knowledge state during learning has been studied for several decades in order to provide more supportive learning instructions. In this paper, we propose a novel model for knowledge tracing that i) captures students' learning ability and dynamically assigns students into distinct groups with similar ability at regular time intervals, and ii) combines this information with a Recurrent Neural Network architecture known as Deep Knowledge Tracing. Experimental results confirm that the proposed model is significantly better at predicting student performance than well known state-of-the-art techniques for student modelling." @default.
- W2952529418 created "2019-06-27" @default.
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- W2952529418 date "2018-09-24" @default.
- W2952529418 modified "2023-09-26" @default.
- W2952529418 title "Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing" @default.
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