Stephen T. Njenga

Work place: Murang’a University of Technology, School of Computing & Information Technology, Kenya

E-mail: snjenga@mut.ac.ke

Website:

Research Interests: Computer systems and computational processes, Artificial Intelligence, Computer Architecture and Organization, Data Structures and Algorithms

Biography

Stephen T. Njenga is currently pursuing a Phd. in Computer Science in the University of Nairobi, Kenya. Njenga received Msc. in Computer Science from the University of Nairobi, Kenya in 2011 and a Bsc. in Computer Science from Egerton University, Kenya in 1998.  

He is currently a Lecturer in the School of Computing and Information Technology in Murang’a University of Technology. He has taught in the field of Computer Science in universities and tertiary colleges for more than eighteen years. His research interest is in the field of Artificial Intelligence, Mobile Learning and Intelligent Mobile Applications.

Mr. Njenga is a member of the Institute of Electronic and Electrical Engineer (IEEE).

Author Articles
Use of Intelligent Agents in Collaborative M-Learning: Case of Facilitating Group Learner Interactions

By Stephen T. Njenga Robert O. Oboko Elijah I. Omwenga Elizaphan M. Maina

DOI: https://doi.org/10.5815/ijmecs.2017.10.03, Pub. Date: 8 Oct. 2017

Intelligent agents have been used in collaborative learning. However, they are rarely used to facilitate group interactions in collaborative m-learning environments. In view of this, the paper discusses the use of intelligent agents in facilitating collaborative learning in mobile learning environments. The paper demonstrates how to design intelligent agents and integrate them in collaborative mobile learning environments to allow group learners to improve their levels of group knowledge construction. The design was implemented in a collaborative mobile learning system running on Modular Object-Oriented Dynamic Learning Environment (Moodle) platform. The application was used in some experiments to investigate the effects of those facilitated interactions on the level of group knowledge construction. The results showed improved levels of group knowledge construction in instances where the facilitations were enabled compared to where they were disabled. The paper concludes that the use of intelligent agents in facilitating learner group interactions in collaborative mobile learning environments improves the levels of group knowledge construction. For future work, the use of intelligent agents can be tested in other areas of group interactions to enhance group learning.

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