Improved computation of individual ZPD in a distance learning system

This paper builds upon theoretical studies in the field of social constructivism. Lev Vygotsky is considered one of the greatest representatives of this research line, with his theory of the Zone of Proximal Development (ZPD). Our work aims at integrating this concept in the practice of a computer-assisted learning system. For each learner, the system stores a model summarizing the current Student Knowledge (SK). Each educational activity is specified through the deployed content, the skills required to tackle it, and those acquired, and is further annotated by the effort estimated for the task. The latter may change from one student to another, given the already achieved competence. A suitable weighting of the robustness (certainty) of student’s skills, stored in SK, and their combination are used to verify the inclusion of a learning activity in the student’s ZPD. With respect to our previous work, the algorithm for the calculation of the ZPD of the individual student has been optimized, by enhancing the certainty weighting policy, and a graphical display of the ZPD has been added. Thanks to the latter, the student can get a clear vision of the learning paths that he/she can presently tackle. This both facilitates the educational process, and helps developing the metacognitive ability self-assessment

The definition of a tunneling strategy between adaptive learning and reputation-based group activities

We investigate the integration of LECOMPS, a webbased e-learning environment for the automated construction and adaptive delivery of learning paths, and SOCIALX, a webbased 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. © 2011 IEEE