Sukrit Leelaluk, Cheng Tang, Valdemar Švábenský, , Atsushi Shimada Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance
In The 40th ACM/SIGAPP Symposium on Applied Computing (SAC '25), 2025.03 BibTeX, Doi Foundation, Paper Information
Valdemar Švábenský, Conrad Borchers, Elizabeth B. Cloude, , Atsushi Shimada Evaluating the Impact of Data Augmentation on Predictive Model Performance
The 15th International Learning Analytics and Knowledge Conference (LAK 2025), 2025.03 BibTeX, Doi Foundation, Paper Information
Jan Vykopal, Valdemar Švábenský, Michael Tuscano Lopez II, Pavel Čeleda Cybersecurity Study Programs: What's in a Name?
Proceedings of the 56th ACM Technical Symposium on Computer Science Education (Association for Computing Machinery), Vol.25, p.7, 2025.02 BibTeX
Ivo Lodovico Molina, Valdemar Svabensky, Tsubasa Minematsu, Li Chen, Fumiya Okubo, Atsushi Shimada Comparison of Large Language Models for Generating Contextually Relevant Questions
Technology Enhanced Learning for Inclusive and Equitable Quality Education (EC-TEL 2024), Vol.15160, No.2, pp.137–143, 2024.09 BibTeX
Svabensky Valdemar, Melina Verger, Maria Mercedes T. Rodrigo, Clarence James G. Monterozo, Ryan S. Baker, Miguel Zenon Nicanor Lerias Saavedra, Sebastien Lalle, Atsushi Shimada Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students
The 17th International Conference on Educational Data Mining (EDM2024), 2024.07 BibTeX
Yuma Miyazaki, Svabensky Valdemar, Yuta Taniguchi, Fumiya Okubo, Tsubasa Minematsu, Atsushi Shimada E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems
The 17th International Conference on Educational Data Mining (EDM2024), 2024.07 BibTeX