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This study aims at managing activity carried out in Computer-Supported Collaborative Learning (CSCL) environments. We apply an approach that gathers and manages the knowledge underlying huge data structures, resulting from collaborative interaction among participants and stored as activity logs. Our method comprises a variety of important issues and aspects, such as: deep understanding of collaboration among participants in workgroups, definition of an ontology for providing meaning to isolated data manifestations, discovering of knowledge structures built in huge amounts of data stored in log files, and development of high-semantic indicators to describe diverse primitive collaborative acts, and binding these indicators to formal descriptions defined in the collaboration ontology; besides our method includes gathering collaboration indicators from web forums using natural language processing (NLP) techniques. [ABSTRACT FROM AUTHOR]

In this work we investigate the importance of emotion awareness in e-learning environments, with emphasis to Computer Supported Collaborative Learning (CSCL) activities. Our presented solution involves a new conceptual model of emotions of interest in e-learning context. In the basis of this model, a computational model has been implemented employing self-report of emotions, affective feedback and effective emotion visualisations. Both models have been tested in real education settings, contributing to the research agenda. [ABSTRACT FROM AUTHOR]