A K-complementarity Technique for Forming Groups of Tutors in Intelligent Learning Environments

Abstract

In e-learning environments, tutors perform the main function of tutoring. They follow up learners and answer their assistance requests which require different skills. These requests may not belong to the tutors’ skills and competencies, so collaboration among other tutors is expected. In fact, this collaboration can improve tutors’ skills and provide learners with effective monitoring. It can be permanent and adaptive, according to learners’ needs and requests. Grouping tutors with different skills is the aim of this research. In this paper, a new technique for grouping tutors is presented. The proposed technique is called K-complementarity. It is based on the complementarity of roles that are assigned to tutors. K-complementarity is based on tutor model and aims at obtaining K groups of tutors who have the most of the roles and skills. The proposed technique has been used by a Computer-Supported Collaborative Tutoring (CSCTT) system. This system had been tested in an Algerian University. The obtained results showed that the groups’ members are heterogeneous and the groups are homogeneous. Furthermore, each group had more than 80% of the roles by combining those of its members. So, these results can be considered as acceptable and very encouraging.