Interpreting Usability Factors Predicting Sustainable Adoption of Cloud-Based E-Learning Environment during COVID-19 Pandemic

Abstract

The COVID-19 pandemic affected educational institutions in an unrivaled way around the globe and forced them to switch from conventional classroom learning mode to e-learning mode within a short time period. Neither instructors nor students had ample time to prepare. The purpose of the current study is to accomplish two objectives: to explore the functional relationship between attitudinal readiness (ATR), subjective well-being (SWB), and cloud-based e-learning adoption intention in Taiwan and examine the constancy of recommended proposed relationships among different students’ groups. The model was then empirically tested using data of 256 university students by structural equation modeling. The current study demonstrates that ATR is completely explained through four dimensions: peer reference, perceived ease of use, perceived usefulness, and perceived ubiquity. SWB is positively interpreted through four dimensions: online course quality, system quality, perceived service quality, and perceived closeness. Self-efficacy has a significant relationship with both attitudinal readiness and adoption intention of a cloud-based e-learning system. Finally, the invariance test explores substantial variance among students who intend to use the system and students who reject it. Therefore, researchers and practitioners regarding educational, technological innovation must consider this empirical evidence to develop and validate a sustainable cloud-based e-learning program in higher education.