Ascertaining the More Knowledgeable Other among peers in Collaborative E-Learning Environment

Collaborative E-Learning is an environment where in learners learn through interaction among peer group mates using computers. Evaluating learners in terms of collaboration capabilities in a collaborative e-learning session can be quantified based on several parameters. These parameters include learner's contribution in the collaborative e-learning sessions; collaboration history of a learner in collaborative e-learning sessions and the level of knowledge of the learner in the group in which he participates. In respect to this finding the More Knowledgeable Other (MKO) person refers to someone who has a better understanding and higher ability level than other learners, with respect to a particular task, process, or concept. He can make others learn effectively. By finding out the MKO it is possible to form effective and efficient group where in learner's learning capabilities in a group can be enhanced so that the peers in the group participate to maximum extent and there is an increase in knowledge level. In this paper, a fuzzy model is introduced to find out an MKO using an intelligent inference system to improve learner's learning capabilities in terms of a proposed metric called fuzzy associative matrix. This matrix can be utilized to guide the collaborative e-learning system for finding out the MKO as the best choice for very effective collaborative e-learning. Simulation study using NetLogo has been carried out to evaluate the performance of the proposed strategy. Simulation results show that the proposed strategy provides an optimal solution in ascertaining an MKO among peers in collaborative E-learning environments.