162 citations · 427 across the 14 of their papers we have counts for
14 papers
Raw Produce Quality Detection with Shifted Window Self-Attention
Oh Joon Kwon, Byungsoo Kim, Youngduck Choi
Global food insecurity is expected to worsen in the coming decades with the accelerated rate of climate change and the rapidly increasing population. In this vein, it is important…
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,…
Consistency and Monotonicity Regularization for Neural Knowledge Tracing
Seewoo Lee, Youngduck Choi, Juneyoung Park +2
Knowledge Tracing (KT), tracking a human's knowledge acquisition, is a central component in online learning and AI in Education. In this paper, we present a simple, yet effective s…
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…
Assessment Modeling: Fundamental Pre-training Tasks for Interactive Educational Systems
Youngduck Choi, Youngnam Lee, Junghyun Cho +9
Like many other domains in Artificial Intelligence (AI), there are specific tasks in the field of AI in Education (AIEd) for which labels are scarce and expensive, such as predicti…
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…
Creating A Neural Pedagogical Agent by Jointly Learning to Review and Assess
Youngnam Lee, Youngduck Choi, Junghyun Cho +6
Machine learning plays an increasing role in intelligent tutoring systems as both the amount of data available and specialization among students grow. Nowadays, these systems are f…
A Spectral Regularizer for Unsupervised Disentanglement
Aditya Ramesh, Youngduck Choi, Yann LeCun
A generative model with a disentangled representation allows for independent control over different aspects of the output. Learning disentangled representations has been a recent t…
Auto-Meta: Automated Gradient Based Meta Learner Search
Jaehong Kim, Sangyeul Lee, Sungwan Kim +6
Fully automating machine learning pipelines is one of the key challenges of current artificial intelligence research, since practical machine learning often requires costly and tim…