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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Daradoumis, T., & Casillas, L. A. (2006). A neural approach for modeling the inference of awareness in computer-supported collaboration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4227 LNCS, pp. 464–469). Springer Verlag. https://doi.org/10.1007/11876663_37
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