Predicting Student Performance based on Lecture Materials Data using Neural Network Models. - Sukrit Leelaluk; Tsubasa Minematsu; Yuta Taniguchi; Fumiya Okubo; Atsushi Shimada 001 (LAK (Data Challenge), 2022)

Scaled-Dot Product Attention for Early Detection of At-risk Students. - Sukrit Leelaluk; Tsubasa Minematsu; Yuta Taniguchi; Fumiya Okubo; Takayoshi Yamashita; Atsushi Shimada 001 (TALE, 2022)

Educational Data Analysis using Generative AI. - Abdul Berr; Sukrit Leelaluk; Cheng Tang 001; Li Chen 032; Fumiya Okubo; Atsushi Shimada 001 (LAK Workshops, 2024)

Educational Data Analysis using Generative AI. - Shuaileng Yuan; Sukrit Leelaluk; Cheng Tang 001; Li Chen 032; Fumiya Okubo; Atsushi Shimada 001 (LAK Workshops, 2024)

Attention-Based Artificial Neural Network for Student Performance Prediction Based on Learning Activities. - Sukrit Leelaluk; Cheng Tang 001; Tsubasa Minematsu; Yuta Taniguchi; Fumiya Okubo; Takayoshi Yamashita; Atsushi Shimada 001 (IEEE Access, 2024)

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance. - Sukrit Leelaluk; Cheng Tang 001; Valdemar Svábenský; Atsushi Shimada 001 (SAC, 2025)