MADM-Based Parametric Selection and Ranking of E-Learning Websites Using Fuzzy COPRAS.

Contribution: The main contribution is to provide practitioners and researchers with an insight in efficiently and effectively employing multi-attribute decision making (MADM) methods in e-learning website selection problems. Background: Advances in information systems and the Internet have resulted in e-learning websites becoming an important interface for learners. The selection of a particular website directly affects the end users’ performance, with the objectives and expected outcomes of e-learning being largely dependent on the quality of the teaching processes and the effectiveness of online access. Evaluation and selection of these websites has thus become a decisive issue for learners and developers. Intended Outcomes: This paper is expected to provide decision support to leaders in education and educational organizations in effectively analyzing and managing their e-learning system. A knowledge-based system may be developed to develop and assess e-learning websites in a meaningful way. Application Design: A hybrid MADM method, fuzzy complex proportional assessment (COPRAS) is used to evaluate, rank, and select e-learning websites of “C” programming language. The fuzzy COPRAS method is validated by comparison with the technique for order preference by similarity to ideal solution, on an existing selection problem of 12 websites available in the open literature. Findings: Fuzzy COPRAS provides a comprehensive ranking of e-learning websites based on fitness degree values. The case study results rated tutorialspoint.com as the best of the e-learning websites considered, and howstuffworks.com was rated lowest. This paper shows that fuzzy COPRAS could be useful for e-learning practitioners, developers, and the researchers. [ABSTRACT FROM AUTHOR]