@inproceedings{adfc3e29229140cb90daf01f416dfda2,
title = "Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students",
keywords = "distance education, educational data mining, fairness, learning analytics, online learning, performance prediction",
author = "Valdemar {\v S}v{\'a}bensk{\'y} and M{\'e}lina Verger and Rodrigo, \{Maria Mercedes T.\} and Monterozo, \{Clarence James G.\} and Baker, \{Ryan S.\} and Saavedra, \{Miguel Zenon Nicanor Lerias\} and S{\'e}bastien Lall{\'e} and Atsushi Shimada",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright is held by the author(s).; 17th International Conference on Educational Data Mining, EDM 2024 ; Conference date: 14-07-2024 Through 17-07-2024",
year = "2024",
doi = "10.5281/zenodo.12729936",
language = "English",
isbn = "9781733673655",
series = "Proceedings of the International Conference on Educational Data Mining",
publisher = "International Educational Data Mining Society",
pages = "744--751",
editor = "\{Demmans Epp\}, Carrie and Benjamin Paa{\ss}en and David Joyner",
booktitle = "Proceedings of the 17th International Conference on Educational Data Mining, EDM 2024",
address = "United States",
}