4 citations · 4 across the 2 of their papers we have counts for
6 papers
Knowledge Transfer by Discriminative Pre-training for Academic Performance Prediction
Byungsoo Kim, Hangyeol Yu, Dongmin Shin +1
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However,…
SAINT+: Integrating Temporal Features for EdNet Correctness Prediction
Dongmin Shin, Yugeun Shim, Hangyeol Yu +3
We propose SAINT+, a successor of SAINT which is a Transformer based knowledge tracing model that separately processes exercise information and student response information. Follow…
Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement
Youngnam Lee, Byungsoo Kim, Dongmin Shin +4
Intelligent Tutoring Systems (ITSs) have been developed to provide students with personalized learning experiences by adaptively generating learning paths optimized for each indivi…
Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment
Youngnam Lee, Dongmin Shin, HyunBin Loh +8
Student dropout prediction provides an opportunity to improve student engagement, which maximizes the overall effectiveness of learning experiences. However, researches on student…
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
Youngduck Choi, Youngnam Lee, Junghyun Cho +6
Knowledge tracing, the act of modeling a student's knowledge through learning activities, is an extensively studied problem in the field of computer-aided education. Although model…
EdNet: A Large-Scale Hierarchical Dataset in Education
Youngduck Choi, Youngnam Lee, Dongmin Shin +7
With advances in Artificial Intelligence in Education (AIEd) and the ever-growing scale of Interactive Educational Systems (IESs), data-driven approach has become a common recipe f…