Learning Analytics
This work aims to use techniques from the analysis of social networks and machine learning to produce Learning Analytics (LA) that will support learners and teachers in changing their practices.
We are particularly interested in how the analysis of social interactions allows us to obtain insights into the dynamics of learning strategies.
This work is supported in particular by the post-doctoral work of Raphaël Charbey and the ongoing thesis work of Michael Kamau Wahiu.
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.
Publications
(2021).
Analysing Peer Assessment Interactions and Their Temporal Dynamics Using a Graphlet-Based Method.
EC-TEL.
(2021).
Analysing Student Engagement in an Online Course in the Context of Hybrid Learning Environment. An Empirical Study.
CSEDU.
(2019).
Roles in social interactions: graphlets in temporal networks applied to learning analytics .
In Complex Networks 2019, The 8th International Conference on Complex Networks and their Applications, Lisbonne, Portugal.
(2018).
Understanding Learner's Drop-out in MOOCs.
19th International Conference on Intelligent Data Engineering and Automated Learning, Madrid.