11 citations · 23 across the 3 of their papers we have counts for
3 papers
Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance
Sukrit Leelaluk, Cheng Tang, Valdemar Švábenský +1
Educational data mining (EDM) is a part of applied computing that focuses on automatically analyzing data from learning contexts. Early prediction for identifying at-risk students…
Evaluating the Impact of Data Augmentation on Predictive Model Performance
Valdemar Švábenský, Conrad Borchers, Elizabeth B. Cloude +1
In supervised machine learning (SML) research, large training datasets are essential for valid results. However, obtaining primary data in learning analytics (LA) is challenging. D…
Comparison of Large Language Models for Generating Contextually Relevant Questions
Ivo Lodovico Molina, Valdemar Švábenský, Tsubasa Minematsu +3
This study explores the effectiveness of Large Language Models (LLMs) for Automatic Question Generation in educational settings. Three LLMs are compared in their ability to create…