A meta-analysis of learners' continuance intention toward online education platforms

Jian Dai, Xing Zhang, Chengliang Wang

Abstract: The extant research on the factors influencing online education platform learners’ continuance intention has yielded inconsistent results, which necessitates a thorough review and reanalysis of relevant literature. Therefore, this study combines different theoretical models and conducts a meta-analysis on 219 articles obtained from Web of Science, Scopus, and Engineer Village. The results show that variables from the expectation-confirmation model of continued IT usage, information system success model, theory of planned behavior, and flow theory are highly significant in driving learners’ continuance intention. Among them, attitude (r = 0.603), perceived usefulness (r = 0.526), and satisfaction (r = 0.606) are strongly correlated with continuance intention. This study provides valuable insights for understanding the determinants of learners’ continuance intention toward online education platforms. We also expected that the disclosure of effect sizes of influencing factors can provide scientific and convincing guidelines for platform developers, educators, and policymakers.