Setting up and tutoring the working groups of a virtual learning community

Collaborative work has emerged as a hot research topic in Virtual Learning Communities since it may considerably improve the knowledge quality and experience of students. However, this novel approach makes the assessment process challenging (i.e., interactions between virtual students, their achievements, and their profi les have to be properly addressed). The purpose of this paper is to propose a comprehensive Intelligent Tutoring System for Virtual Learning Communities that relies on artifi cial intelligence techniques which are able to manage the specifi cities of the collaborative working groups that arise in this domain. These specifi cities can be summarized in the following four goals: 1) conduct an individualized tracking of every student upon the collected data from his/her profi le and daily work, 2) confi gure the classroom to maximize the performance of all its members, 3) automatically obtain the teacher's feedback about the class operation and possible anomalies, and 4) monitor the working groups behaviour and achievements automatically to redirect their operation when necessary. The framework of the proposed system is described, a proof of concept is presented, and a new virtual student profi le, named as bystander, is identifi ed in preliminary experimentations.