The Definition of a Tunneling Strategy between Adaptive Learning and Reputation-based Group Activities

We investigate the integration of LECOMPS, a web-based e-learning environment for the automated construction and adaptive delivery of learning paths, and SOCIALX, a web-based system for shared e-learning activities, which exploits a reputation system to provide feedback to its participants. Our overall goal is the integration of personalized and collaborative learning to support the Vygotskij's educational theory of proximal development. Therefore we propose a two-way tunneling strategy: the LECOMPS student model is used to select the set of social activities (met in SOCIALX) according to the present individual learner state of knowledge, on the other hand, the solution of exercises, and the associated reputation derived in SOCIALX, is used to update the LECOMPS student model. In particular, we present a mapping between the student model and the definition of Vygotskij's concepts of Autonomous Problem Solving and Proximal Development regions, with the aim to provide the learner with better guidance during the taking of the course.