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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 the actors. In fact, the analysis process has positive effect on the role of human actors. It helps the tutor in his task of monitoring learners, the teacher (author) in his task of creating educational courses and the learner in his task of viewing his previous actions with more details. It is this context that defines our research work, which is focused on implementing a collaborative learning system based on traces called SYCATA (which is the French acronym of: SYstème pour la Collecte et l'Analyse des Traces d'Apprentissage collaboratif). This system 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 were obtained.

We have assisted the development of a significant number of e-learning systems, which have achieved great success in distance teaching and education, but most of these systems present some limitations and some disadvantages. Most of them are closed where learning resources are fixed and the adaptability, the flexibility, and social relations are ignored and in most cases are not taken into account at all, actors of such systems tend to have a minimal collaborative navigation, awareness features and social relations analysis and they often find themselves isolated without sensing what the rest of learning community is doing. Significantly, new technologies had recently emerged: the social concepts and the social awareness features leading significant change to collaboration and learning. These emerging technologies are increasingly being adopted to improve remote education and providing better enhancement for learning. These improvements are offered to students who, regardless of their computer systems, can collaborate to improve their cognitive and social skills. In this article, we present the concepts of a new learning paradigm: CSSL (Computer Supported Social Learning) and we have implemented a first prototype called SoLearn that groups some of those concepts. SoLearn (A Social Learning Network) aims to provide its users with a new learning experience based on social networks and enhanced with social awareness concepts.