Pagerank algorithm to improve the Peer-Led team learning pedagogical approach

Abstract

Peer-Led Team Learning model has been introduced into several undergraduate courses and it showed improvement in students’ learning performance. Despite its success, little attention has been given to further enhance the model for academic benefits particularly in terms of suitable peer leaders selection, homogenous groups forming and the process of disseminating the educational knowledge. In this paper, we utilized PageRank Algorithm to improve the PLTL pedagogical approach. Unlike the traditional way, we introduced social interaction analysis as a way to create natural groups of students, and select the best peer leaders in classrooms who can disseminate the educational knowledge in an efficient and smooth fashion. The new proposed approach was tested on a dataset of 16 students in an Operating System course offered at the College of Information Technology (CIT), United Arab Emirates University. The improvement in students’ performance achieved is encouraging evidence in favor of the proposed method.