Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Verger, Mélina"'
Predictive student models are increasingly used in learning environments. However, due to the rising social impact of their usage, it is now all the more important for these models to be both sufficiently accurate and fair in their predictions. To ev
Externí odkaz:
http://arxiv.org/abs/2407.05398
Autor:
Švábenský, Valdemar, Verger, Mélina, Rodrigo, Maria Mercedes T., Monterozo, Clarence James G., Baker, Ryan S., Saavedra, Miguel Zenon Nicanor Lerias, Lallé, Sébastien, Shimada, Atsushi
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 work has considered algorithmic bias based on regional (sub-national) b
Externí odkaz:
http://arxiv.org/abs/2405.09821
Publikováno v:
Proceedings of the 16th International Conference on Educational Data Mining (EDM 2023)
Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes,
Externí odkaz:
http://arxiv.org/abs/2305.15342
Autor:
Verger, Mélina, Escalante, Hugo Jair
Data-driven decision making is serving and transforming education. We approached the problem of predicting students' performance by using multiple data sources which came from online courses, including one we created. Experimental results show prelim
Externí odkaz:
http://arxiv.org/abs/2109.07903
Publikováno v:
Journal of Educational Data Mining; 2024, Vol. 16 Issue 1, p365-409, 45p
