Research Article
Machine Learning and Explainable Artificial Intelligence in Education and Training - Status and Trends
@INPROCEEDINGS{10.1007/978-3-031-58053-6_8, author={Dimitris Pantazatos and Athanasios Trilivas and Kalliopi Meli and Dimitrios Kotsifakos and Christos Douligeris}, title={Machine Learning and Explainable Artificial Intelligence in Education and Training - Status and Trends}, proceedings={Wireless Internet. 16th EAI International Conference, WiCON 2023, Athens, Greece, December 15-16, 2023, Proceedings}, proceedings_a={WICON}, year={2024}, month={5}, keywords={Artificial Intelligence Machine Learning Explainable AI Educational Data Mining VET}, doi={10.1007/978-3-031-58053-6_8} }- Dimitris Pantazatos
Athanasios Trilivas
Kalliopi Meli
Dimitrios Kotsifakos
Christos Douligeris
Year: 2024
Machine Learning and Explainable Artificial Intelligence in Education and Training - Status and Trends
WICON
Springer
DOI: 10.1007/978-3-031-58053-6_8
Abstract
Nowadays, the need to explain the decisions or predictions made by Artificial Intelligence (AI) is emerging more than ever as AI applications are more complex. The research field of eXplainable Artificial Intelligence (XAI) tries to fulfill this need. XAI provides a way to help humans understand how an AI’s predictions and decisions come. The scope of this work is to examine the role of XAI in the field of Education, especially in Educational Data Mining in Vocational Education and Training.
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