Computers in Human Behavior Reports (May 2024)
Investigating the behavioral differences in the acceptance of MOOCs and E-learning technology
Abstract
This study aims to investigate the behavioral differences in the acceptance of MOOCs and E-learning. The study employs combining models TAM and ECM to reveal user's behavior in using MOOCs and E-learning. In accessing these learning systems, e-learning users are more mandatory in accessing the learning contents than MOOCs. The eight latent variables derived from reviewing previous related literatures including information quality, self-efficacy, perceived ease of use, perceived usefulness, attitude, confirmation, satisfaction, and behavioral intention are employed to reveal the behavioral differences in using these systems. This study also employs type of learning systems (MOOCs and E-learning) as difference variable. The respondents of this study are MOOCs and e-learning users in Indonesia. The online questionnaires are delivered to e-learning and MOOCs users in high school and university and the supplemental questionnaires are delivered to employers and entrepreneurs as MOOC users. There are 706 questionnaire data collected and examined in statistically manner using smart-PLS to prove the hypotheses in proposed model. Several analyses including the structural model and hypotheses, MGA, and IPMA are employed in this study. This study has findings on the accepted of all hypotheses on the model in adoption of MOOCs technology. For the adoption of e-learning technology all hypotheses on the model are accepted excluding the hypothesis of information quality which has positive direct effect on the perceived usefulness. The difference values on the MGA result reveals that there is difference on the correlation of between information quality and perceived usefulness, perceived usefulness and attitude, confirmation and satisfaction, and attitude and behavioral intention. IPMA analysis reveals the difference on importance and performance among indicators of construct of the model and serves interesting insights into the role of indicators of construct and their relevance for managerial implications.
