Platform for Creating Collaborative E-Learning Communities Based on Automated Composition of Learning Groups

The current paper presents a platform for self-built e-learning communities, in which a trainee enrolls into the educational process, gains points through achievements and ultimately becomes a trainer, based on those points. When creating a new account, an intelligent profile is attached to the newly created trainee. This profile is composed by the information received from several sources: the form filled by the trainee and the data obtained from querying the social graph of the student. Currently, the social graph is fed with the data extracted from the Facebook profile of the student, through a Facebook connector, which exports RDF data. The intelligent profile of the student is used to build optimal learning groups, by applying a Particle Swarm Optimization algorithm. The authors claim that quantifying various indicators, such as similarity between the type of interest of the participants and background diversity, within a group and between groups could influence the efficiency of learning groups. The paper also offers preliminary results regarding the effectiveness of this kind of approach in creating collaborative e-learning environments.