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Top1. Introduction
Technology has played a critical role in carrying out daily operations during the pandemic around the world. The advancement of technology has resulted in significant changes in a variety of disciplines (Nadikattu, 2020). E-learning, particularly in the education sector, has proven to be advantageous for quickly maintaining the teaching-learning process during the lockdown via apps like as Voov, Zoom, Google meet, Google classroom, and others. It is evident that developing creative learning domains that give students with an effective and simple learning experience is critical. In terms of the technological and flexibility qualities of these platforms, each institution may have distinct prospects. In this situation, a successful online learning tool can be selected by first determining the needs of both learners and educators. Hence, selecting the best E–learning platform to meet the requirements is a process in which several criterions must be examined. Several studies have been conducted to examine the learner's perspective on the relative importance of characteristics while selecting an E-learning platform. Shee and Wang (2008) proposed a “Multi-criteria methodology for the evaluation of web-based e-learning system from the perspective of learner satisfaction”. This study empirically investigated learners’ perceptions of the relative importance of decision criteria with 13 criteria under 4 dimensions. The investigation was analyzed by Analytic Hierarchy Process (AHP) and found that learners regarded the “learner interface” as being the most important dimension of decision criteria. Karasan and Erdogan (2021) used extended cognitive mapping with intuitionistic fuzzy sets for prioritizing the E–learning platform selection factors. Based on the multi–expert judgments, infrastructure and ease of use are determined as the most effective factors. Begicevic et al. (2007) evaluated the problem of prioritization of E-learning forms by using multi-criteria modelling. The problem is solved using a group decision model with AHP method. In order to form a decision problem, different criteria for evaluating E-learning tools must be established. Various sources on E-learning were studied, and a set of criteria as features required in an E-learning tool for quality and innovative teaching were identified. It is revealed that the key features that should be evaluated are “f1: User-friendliness, f2: Integration with Learning Management System, f3: Operational stability, and f4: Price.” Because most decision problems are described as complicated processes for which complete information is not always available, Fuzzy Multi Criteria Decision Making (FMCDM) is an effective tool to assess them (Das & Granados, 2022; Gergin et al., 2022; Liu & Li, 2017).
Zadeh (1975) introduced Type-2 fuzzy sets (T2FS) in 1975 to handle the incomplete information available in the data. Later, the concept of Intuitionistic Fuzzy Set (IFS) was familiarized by Atanassov (1986). By considering the degree of membership, non-membership, a generalization of T2FS and IFS was introduced and named as Type-2 Intuitionistic Fuzzy Set (T2IFS) (Nadikattu, 2020). T2IFS models inaccurate information perfectly in real-world applications providing an additional degree of freedom to indicate the ambiguity in information for DMs. As a result, the current study is being conducted to investigate Optimal E-learning Tool selection with T2IFS settings.