E-learning Quality and the Learners’ Choice Using Spherical Fuzzy Analytic Hierarchy Process Decision-making Approach

Abstract

E-learning in the context of Industry 4.0 and the outbreak of the COVID-19 pandemic has transformed traditional education. However, the smooth transition from face-to-face education to e-learning remains a challenging task, given concerns about e-learning quality. This study aims to explore the quality criteria and the adoption of e-learning via the spherical fuzzy analytic hierarchy process (SF-AHP). The extended technical acceptance model is used as a theoretical framework for constructing quality in an adoption hierarchical model. The input data derived from in-depth interviews of 20 experts in the field and the SF-AHP calculator have generated the priority weights of quality criteria in the model of e-learning adoption. The findings confirm the role of three major criteria, in order of importance, as follows: system, resources and core factors. The results highlight system factors as most crucial, including aspects such as governmental policies and institutional leadership, which are essential for setting a conducive environment for e-learning. Resource factors are ranked second, emphasizing the importance of IT applications, human capital and facilities to support e-learning infrastructure. Core factors, though ranked lower, are vital in ensuring the effectiveness of e-learning through course materials, instruction, and learner support. The weights of 14 sub-criteria have further shed light on policies to promote e-learning quality and its adoption. The implied priority of each weight a valuable guideline for the stakeholders’ actions to reach the targeted goals under the constraint resources.