Trace-based Collaborative Learning System

Yacine Lafifi, Noureddine Gouasmi, Khaled Halimi, Wassila Herkas, Nassima Salhi, Assia Ghodbani


The users of any educational software may leave traces which concern all their activities. In collaborative learning context, these traces are very voluminous and very heterogeneous. They are the results of various interactions between the actors themselves, and between the actors and the system. Hence, first, they must be collected and filtered. Then, these traces must be analyzed to help or support these actors (the tutor in his task of monitoring learners and the teacher-author in his task of creating educational courses). It is this context that defines our research work, which is focused on implementing a collaborative learning system based on traces called SYCATA (SYstème pour la Collecte et l’Analyse des Traces d’Apprentissage collaboratif). SYCATA collects all traces of actors’ activities (especially learners) and groups them into five categories. It offers a multitude of forms (graphical, numerical or mixed) to show these traces to the tutors and the authors. Some traces may be viewed by learners to promote their pedagogical activities and raise their awareness. SYCATA was implemented and experimented with a sample of university students where good results have been obtained.

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