Comparative Analysis of the Essential Factors for the Adoption of Massive Open Online Courses in Higher Education of a Developing Country

Pre and Post COVID-19

Abstract

Although massive open online courses (MOOCs) offer numerous benefits to students, developing countries are still in the early stages of promoting their implementation. This study aims to investigate how the factors influencing MOOC adoption have evolved in response to the increased usage of online courses during the pandemic. The proposed model is based on the Technology Acceptance Model, and research hypotheses are presented based on six different factors: Perceived Usefulness, Perceived Ease of Use, Openness, Self-Efficacy, Quality of Service, and Reputation of the MOOC Provider. To test these hypotheses two surveys were conducted, one before and one after the COVID-19 period. Analyzing the data from these two time periods provides insight into the level of influence each of these factors has had on increased MOOC usage. Survey data was tested using the novel Partial Least Squares-Artificial Neural Network approach, which can effectively analyze complex human decisions. The findings indicate that Perceived Usefulness was the most influential factor in the adoption of MOOCs both before and after the COVID-19 pandemic. Interestingly, changes have been observed in the impact of Openness between the pre-pandemic and post-pandemic periods.