96 citations · 549 across the 34 of their papers we have counts for
7 papers · 1 filter
Ranking-Based At-Risk Student Prediction Using Federated Learning and Differential Features
Shunsuke Yoneda, Valdemar Švábenský, Gen Li +2
Digital textbooks are widely used in various educational contexts, such as university courses and online lectures. Such textbooks yield learning log data that have been used in num…
Single-Agent vs. Multi-Agent LLM Strategies for Automated Student Reflection Assessment
Gen Li, Li Chen, Cheng Tang +4
We explore the use of Large Language Models (LLMs) for automated assessment of open-text student reflections and prediction of academic performance. Traditional methods for evaluat…
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…
Detecting Unsuccessful Students in Cybersecurity Exercises in Two Different Learning Environments
Valdemar Švábenský, Kristián Tkáčik, Aubrey Birdwell +6
This full paper in the research track evaluates the usage of data logged from cybersecurity exercises in order to predict students who are potentially at risk of performing poorly.…
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…
Towards Generalizable Detection of Urgency of Discussion Forum Posts
Valdemar Švábenský, Ryan S. Baker, Andrés Zambrano +2
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and…