This study aims to explore the importance of efficient management of event information generated from group activity in collaborative learning practices for its further use in extracting and providing knowledge on interaction behavior. The essential issue here is how to design a platform that can be used for real, long-term, complex collaborative problem-solving situations and which enables the instructor to both analyze group interaction effectively and provide an adequate support when needed. The achievement of this task first involves the design of a conceptual model that structures and classifies the information generated in a collaborative learning application at several levels of description. This conceptual model is then translated into a computational model that not only allows the efficient management of the knowledge produced by the individual and group activity but also the possibility of exploiting this knowledge further as a meta-cognitive tool for real-time coaching and regulating the collaborative learning process. The computational model becomes the central issue in this contribution while the conceptual model is briefly introduced.