RESEARCH
Shifting the paradigm through AIOur AI lab creates new and better ways of assessing knowledge. Find out how we make assessments more adaptive, accessible, and reliable.
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What you know vs. what you don’t know
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Publications
Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach
Soonwoo Kwon, Sojung Kim, Seunghyun Lee, Jin-Young Kim, Suyeong An, Kyuseok Kim
UPDATED: 23 AUG, 2023
No Task Left Behind: Holistic Student Assessment Framework based on Multi-task Learning
Suyeong An, Junghoon Kim, Minsam Kim, Juneyoung Park
UPDATED: 8 APR, 2022
GRAM: Fast Fine-tuning of Pre-trained Language Models for Content-based Collaborative Filtering
Yoonseok Yang, Kyu Seok Kim, Minsam Kim, Juneyoung Park
UPDATED: 6 MAY, 2022
Behavioral Testing of deep neural knowledge tracing models
Minsam Kim, Yugeun Shim, Seewoo Lee, Hyunbin Loh, Juneyoung Park
Proceedings of The 14th International Conference on Educational Data Mining
Tracing knowledge for tracing dropouts: multi-task training for study session dropout prediction
Seewoo Lee, Kyu Seok Kim, Jamin Shin, Juneyoung Park
Condensed Discriminative Question Set Generation for Accurate and Reliable Exam Score Prediction
Jung Hoon Kim, Jineon Baek, Chanyou Hwang, Chan Bae & Juneyoung Park
UPDATED: 1 FEB, 2021
SAINT+: Integrating Temporal Features for EdNet Correctness Prediction
Dongmin Shin, Yugeun Shim, Hangyeol Yu, Seewoo Lee, Byungsoo Kim, Youngduck Choi
Knowledge transfer by discriminative pre-training for academic performance prediction
Byungsoo Kim, Hangyeol Yu, Dongmin Shin, Youngduck Choi
UPDATED: 12 JUL, 2021
Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement
Youngnam Lee, Byungsoo Kim, Dongmin Shin, JungHoon Kim, Jineon Baek, Jinhwan Lee, Youngduck Choi
UPDATED: 1 JUL, 2020
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
Youngduck Choi, Youngnam Lee, Junghyun Cho, Jineon Baek, Byungsoo Kim, Yeongmin Cha, Dongmin Shin, Chan Bae, Jaewe Heo
UPDATED: 1 FEB, 2021