UPDATED: 1 FEB, 2022

SAINT+: Integrating Temporal Features for EdNet Correctness Prediction

by Dongmin Shin, Yugeun Shim, Hangyeol Yu, Seewoo Lee, Byungsoo Kim, Youngduck Choi

We introduce an addition to SAINT in SAINT+, where temporal features are added to the list of inputs used to train our model.


SAINT(Separated Self-AttentIve Neural Knowledge Tracing) is one of our knowledge tracing model that captures complex relations between educational exercises and student responses to assess a student’s knowledge state. Learn more about it here
Empirical evaluations show a 1.25% increase in AUC compared to SAINT, and a maximum 3.61% increase in AUC compared to other deep learning-based knowledge tracing models such as DKT, DKVMN, and SAKT.


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