Quality Assurance for Reusable Learning Objects on a Peer-To-Peer Network

Authors

  • Rajendra G. Singh The University of the West Indies
  • Margaret A. Bernard The University of the West Indies

DOI:

https://doi.org/10.3991/ijet.v11i10.5881

Keywords:

eLearning, Learning Object, Peer-To-Peer

Abstract


In this research, improving on the quality of Reusable Learning Objects (RLOs) on a Peer-To-Peer (P2P) network is considered. The RLO was first redesigned to have a fundamentally inherent pedagogical structure, which gave it an immediate foundational level of quality in terms of opportunities related to reusability. Applying the Learning Object Review Instrument 1.5 (LORI 1.5) demonstrated that some of the elements are inherent in this new RLO design, so there was no need to constantly have such features evaluated with LORI. A modified LORI was therefore developed in order to evaluate the remaining features of the RLO. The research identified these remaining elements to produce a Review Rubric for scoring the RLO’s quality. In addition, an algorithm is given which considers one or more subject-matter experts as part of a review process. Utilizing the subject-matter experts in a P2P network involved the creation of special nodes to ensure data integrity and post-availability of the review scores for RLOs. The research concludes that the redesigned RLOs along with the corresponding Review Rubric and scoring algorithm produces a system suitable for a P2P network, where for the first time, RLOs can be shared of assured quality to promote eLearning within P2P networks.

Author Biographies

Rajendra G. Singh, The University of the West Indies

Systems Engineer - Network Security

Margaret A. Bernard, The University of the West Indies

Senior Lecturer, Department of Computing and Information Technology, Faculty of Science and Technology

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Published

2016-10-27

How to Cite

Singh, R. G., & Bernard, M. A. (2016). Quality Assurance for Reusable Learning Objects on a Peer-To-Peer Network. International Journal of Emerging Technologies in Learning (iJET), 11(10), pp. 4–10. https://doi.org/10.3991/ijet.v11i10.5881

Issue

Vol. 11 No. 10 (2016)

Section

Papers

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