Explainable AI Tools for Educational Data

The use of machine learning (ML) and artificial intelligence (AI) techniques has become increasingly pervasive in the world of education. Indeed, in this context, a great amount of data is continuously being produced by the management systems of training and educational entities such as universities and schools. In recent years, there have been many applications in which educational data have been considered and analyzed through ML/AI models in different contexts, such as teaching-learning workflow personalization and evaluation, detection of early drop-out, predicting the students’ outcomes, and, in general, optimization of the educational processes. In this abstract, we provide a snapshot of some of the most used general-purpose tools and libraries that may be used for generating and evaluating XAI models in the educational context. Particularly, we have identified five factors that could be useful to choose the most suitable solution for a specific stakeholder.