Mining Associations Between Collaborative Skills and Group Roles in Collaborative E-Learning Environments

Abstract

Nowadays it is quite common for universities to use computer-supported collaborative learning (CSCL) systems to favor group learning and teaching processes. CSCL systems provide communication, coordination and collaboration tools that ease group dynamic regardless space-time location of group members. However, forming a group and having the technology to support group tasks is not enough to guarantee students collaboration. Effective collaboration supposes the manifestation of specific roles by group members. Considering that group roles are conditioned (among other factors) by collaborative skills that students manifest, this article explores relations between collaborative skills and group roles by means of the application of association rules over a dataset of university students' interactions during CSCL sessions. The discovered knowledge might be used for automatic recognition of student roles based on collaborative skills that students manifest in their groups. Furthermore, the discovered association rules could be used for forming groups with a balanced combination of roles.