Evaluation of Intelligent Grouping Based on Learners’ Collaboration Competence Level in Online Collaborative Learning Environment


  • Maina Elizaphan Muuro Kenyatta University
  • Robert Obwocha Oboko University of Nairobi
  • Peter Waiganjo Wagacha University of Nairobi




online collaborative learning, intelligent grouping, Learning Management Systems, true experiment design, learner’s collaboration competence level


In this paper we explore the impact of an intelligent grouping algorithm based on learners’ collaborative competency when compared with (a) instructor based Grade Point Average (GPA) method level and (b) random method, on group outcomes and group collaboration problems in an online collaborative learning environment.  An intelligent grouping algorithm has been added in a Learning Management System (LMS) which is capable of forming heterogeneous groups based on learners’ collaborative competency level. True experiment design methodology was deployed to examine whether there is any association between group formation method and group scores, learning experiences and group problems.  From the findings, all groups had almost similar mean scores in all group tests, and shared many similar group collaboration problems and learning experiences. However, with the understanding that GPA group formation method involves the instructor, may not be dynamic, and the random method does not guarantee heterogeneity based on learner’s collaboration competence level, instructors are more likely to adopt our intelligent grouping method as the findings show that it has similar results. Furthermore, it provides an added advantage in supporting group formation due to its guarantee on heterogeneity, dynamism, and less instructor involvement.

Author Biography

Maina Elizaphan Muuro, Kenyatta University

Elizaphan M. Maina is a Lecturer in the Department of Computing and Information Technology at Kenyatta University, Kenya. He has taught computer Science for ten years in Universities and Tertiary colleges. Currently He is the chairman Computing and Information Technology Department and a member of ICT Board in Kenyatta University. He has published journals in the field of artificial intelligence and collaborative learning. He lecturers in the field of artificial intelligence, programming, database systems and use of ICT in Education. His primary research focus is on integration of artificial intelligence techniques in e-learning in order to create new e-pedagogies which can support personalized e-learning and also provide computer supported collaborative learning.



How to Cite

Muuro, M. E., Oboko, R. O., & Wagacha, P. W. (2016). Evaluation of Intelligent Grouping Based on Learners’ Collaboration Competence Level in Online Collaborative Learning Environment. The International Review of Research in Open and Distributed Learning, 17(2). https://doi.org/10.19173/irrodl.v17i2.2066



Research Articles