12 citations · 18 across the 5 of their papers we have counts for
7 papers · 1 filter
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…
AI-Driven Interface Design for Intelligent Tutoring System Improves Student Engagement
Byungsoo Kim, Hongseok Suh, Jaewe Heo +1
An Intelligent Tutoring System (ITS) has been shown to improve students' learning outcomes by providing a personalized curriculum that addresses individual needs of every student.…
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…
Choose Your Own Question: Encouraging Self-Personalization in Learning Path Construction
Youngduck Choi, Yoonho Na, Youngjik Yoon +5
Learning Path Recommendation is the heart of adaptive learning, the educational paradigm of an Interactive Educational System (IES) providing a personalized learning experience bas…
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…