What Drives Rural Students' Online Learning Continuance Intention: An SEM Approach

Liang, L.; Zhong, Q.; Zuo, M.; Luo, H.; Wang, Z.

Affected by the COVID-19, almost everywhere, including rural areas, had to learn online at home. However, the experience during this period would directly affect the interest and willingness to learn online in the future, especially for rural students. This study examined the factors influencing online learning continuance intention in rural areas by empirical investigations on large-scale online teaching in rural schools from four provinces. About 18000 questionnaires were collected and the structural equation model (SEM) about the proposed expanded Technology Acceptance Model (TAM) in this study showed a high degree of fit, accounting for 64 % of the variance in the continuance intention. It also revealed that perceived usefulness, perceived ease of use, behavioral and emotional engagement all have a positive impact on students' online learning continuance intention. However, cognitive engagement was not found to affect continuance intention. Finally, it offered some recommendations for educators to optimize the design of large-scale online instructions for rural students in the future and research new external factors of TAM. © 2021 IEEE.