Interpreting Deep Knowledge Tracing Model on EdNet Dataset
  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.
