New MCEQLS TFN method for evaluating quality and reusability of learning objects

Abstract

The aim of the paper is to present a new simple to use and efficient MCEQLS (Multiple Criteria Evaluation of the Quality of Learning Software) TFN (Trapezoidal Fuzzy Numbers) method for the expert evaluation of the quality and reusability of learning objects (LOs). MCEQLS and TFN methods are analysed, improved, and practically applied to present the decision analysis process for selecting LOs suitable to reuse in different pedagogical situations and in different education systems. The research results are implemented in eQNet – a three-year strategic pan-European project focused on reusability of LOs. A novel method of consecutive application of Fuzzy Numbers theory to establish the weights of LOs quality criteria and MCEQLS approach to establish final evaluation results are explored in more detail. A number of multiple criteria decision analysis principles are applied to create a comprehensive quality model (criteria system) for evaluating the quality and reusability of LOs. Several practical examples of LOs evaluated against the proposed MCEQLS TFN method are presented in the paper. The research results have shown that the proposed method is quite objective, exact, simple to use, and efficient for selecting qualitative reusable LOs alternatives in the market.

Keywords:

• alternatives
• criteria
• decision making
• e-learning

JEL Classification:

• C02
• C69
• D83
• I29

Additional information

Notes on contributors

Eugenijus Kurilovas

Eugenijus KURILOVAS is an Associate Professor in Vilnius Gediminas Technical University and Research Scientist in Vilnius University Institute of Mathematics and Informatics. He is a member of over 20 committees of international scientific journals and conferences, published over 80 scientific papers and 6 books, and participated in about 30 EU-funded large scale R&D projects and studies. He is also guest editor in “Journal of Universal Computer Science” and “Computers in Human Behavior”, and reviewer in “Behaviour & Information Technology”, “Computers in Human Behavior”, “Journal of Web Engineering”, and “IET Software”, all abstracted / indexed in Thomson ISI Web of Science. He is the author of over 10 best paper awards in the largest international e-Learning conferences during last years.

Silvija Serikoviene

Silvija SERIKOVIENE is a Lecturer in Panevezys Institute of Kaunas University of Technology. She has published a number of scientific papers in international journals and participated in a number of large scale R&D projects.