Multi-Criteria Fuzzy AHP Method for Analyzing the Importance of E-Learning Platforms during Covid-19

Abstract

The demand for e-learning has risen to new heights due to uncertainty during the Covid19 pandemic. Every organization try to find better ways of communication with their stakeholders and therefore most of the applications used widely during covid19 pandemic include virtual conferencing tools. However, the effectiveness of virtual conferencing tools, especially those used for teaching and learning purposes, needs to be assessed critically. As a standard practice, it is always useful to consider multiple inputs in decision making especially when there is a need to achieve optimal results. In this regard e-learning platform impacts have been analyzed in this paper with published research articles which are indexed in the Scopus database. The datasets include a lot of information including authors' nativity, journal information, date of publication, abstract of the research article etc. In line with this perspective, this paper considers the application of hybrid multi-criteria decision making for fuzzy logical analysis with analytic hierarchy process (AHP) and the possibility of analytic network process (ANP) to assist decision-making in assessing and choosing priority for high impact e-learning platform. This multi-criteria  model can assist decision-making in assessing and choosing priority for high impact e-learning platforms accurately and effectively by using the Fuzzy AHP method. As per AHP and F-AHP results, its important to aware of the e-learning platforms impact using publication data perspectives, the common things in both analysis is criteria C5 («Abstract») with good impact result. And also other two criterion like C1 («Title of the article») and C7 («Location-Country») have significant impact on this research article publication as per findings of Fuzzy AHP.