8 citations · 14 across the 3 of their papers we have counts for
3 papers · 1 filter
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…
Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students
Valdemar Švábenský, Mélina Verger, Maria Mercedes T. Rodrigo +5
Algorithmic bias is a major issue in machine learning models in educational contexts. However, it has not yet been studied thoroughly in Asian learning contexts, and only limited w…