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- W3208441762 abstract "With more deep learning techniques being introduced into the knowledge tracing domain, the interpretability issue of the knowledge tracing models has aroused researchers' attention. Our previous study(Lu et al. 2020) on building and interpreting the KT model mainly adopts the ASSISTment dataset(Feng, Heffernan, and Koedinger 2009),, whose size is relatively small. In this work, we perform the similar tasks but on a large and newly available dataset, called EdNet(Choi et al. 2020). The preliminary experiment results show the effectiveness of the interpreting techniques, while more questions and tasks are worthy to be further explored and accomplished." @default.
- W3208441762 created "2021-11-08" @default.
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- W3208441762 date "2021-10-31" @default.
- W3208441762 modified "2023-09-24" @default.
- W3208441762 title "Interpreting Deep Knowledge Tracing Model on EdNet Dataset" @default.
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- W3208441762 doi "https://doi.org/10.48550/arxiv.2111.00419" @default.
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