A Neural Approach for Modeling the Inference of Awareness in Computer-Supported Collaboration

Thanasis Daradoumis (1) , Luis A. Casillas (2)

1 DPCS - Distributed Parallel and Collaborative Systems
2 Department of Computer Sciences

Individuals interacting in a computer supported collaborative learning (CSCL) environment produce a variety of information elements during their participation; these information elements usually have a complex structure and semantics, which make it rather difficult to find out the behavioral attitudes and profiles of the users involved. This work provides a model that can be used to discover awareness information lying underneath multi-user interaction. This information is initially captured in log files and then is represented in a specific form in events-databases. By using data mining techniques, it is possible to infer both the users' behavioral profiles and the relationships that occur in a CSCL environment. In this work we combine different data mining strategies and a neural-based approach in order to construct a multi-layer model that provides a mechanism for inferring different types of awareness information from group activity and presenting it to the interested parties. (http://www.springerlink.com/content/r1278368177m14n1/)

Mots clés: learning grids; awareness

Domaines: Environnements Informatiques pour l'Apprentissage Humain

Thanasis Daradoumis, Luis A. Casillas. A Neural Approach for Modeling the Inference of Awareness in Computer-Supported Collaboration. First European Conference on Technology Enhanced Learning, EC-TEL 2006, October 1-4, 2006, 2006, Crete, Greece. pp.464-469, ⟨10.1007/11876663⟩. ⟨hal-00190830⟩