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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationSmart Education and e-Learning 2016
EditorsVladimir L. Uskov, Robert J. Howlett, Lakhmi C. Jain, Lakhmi C. Jain, Lakhmi C. Jain
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783319396897
Publication statusPublished - 2016
Event2nd International KES conference on Smart Education and e-Learning, 2015 - Sorrento, Italy
Duration: Jun 17 2015Jun 19 2015

Publication series

NameSmart Innovation, Systems and Technologies
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026


Other2nd International KES conference on Smart Education and e-Learning, 2015


  • Cooperative learning
  • Google PageRank algorithm
  • Group learning
  • Learning improvement
  • Peer leader
  • Peer-Led team learning
  • Social network analysis

ASJC Scopus subject areas

  • General Decision Sciences
  • General Computer Science


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