[Carnot TSN 2019] eXplainable AnalytIcs for EDUcation

The XAI-EDU project aims to use Artificial Intelligence (AI) techniques to produce Learning Analytics (LA) that will support learners and teachers in changing their practices based on in particular on a dimension that is currently little exploited: the influence of social interactions.

To address this issue, we propose a mixed numerical and symbolic approach (based on business knowledge) to make decision-making tools explainable and actionable.

Laurent Brisson
Associate Professor

Laurent BRISSON received a Ph.D degree in Computer Science from Université Nice Sophia-Antipolis (France) in 2006. His work focuses on the analysis of social networks along two axes: information dissemination and the detection of temporal communities.