Kaili Lu, Feng Pang and Shadiev Rustam 

Education and Information Technologies  

2023   Volume 28   Issue 8

https://doi.org/10.1007/s10639-023-11591-1

Abstract🤸🏽‍♀️：

Asynchronous online learning has gained great popularity in higher education, especially due to the recent COVID-19 pandemic. However, few studies have investigated how to maintain students’ continuous usage intention of asynchronous online courses in the context of higher education. This study incorporated four key factors (intrinsic motivation, extrinsic motivation, perception of multiple sources, and cognitive engagement) associated with students’ continuous usage intention of asynchronous online courses into technology acceptance model (TAM) to identify the influencing factors on students’ continuous usage intention. A survey with 325 college students was conducted to explore their continuous usage intention of asynchronous online courses and structural equation modeling analysis was carried out to analyze the relationships between the key influencing factors and students’ continuous usage intention. The results showed that cognitive engagement was the only factor that directly related to continuous usage intention. Intrinsic motivation, extrinsic motivation, and perception of multiple sources indirectly correlated with students’ continuous usage intention through different pathways. The results of the study have several theoretical and practical implications. Theoretically, the study verified what key learning factors incorporated into TAM and in what way they relate to the continuous usage intention of asynchronous online courses. Practically, the present study indicated that it is required to take intrinsic motivation, extrinsic motivation, perception of multiple sources, cognitive engagement and TAM into consideration when designing and conducting asynchronous online learning courses to ensure college students’ continuous usage intention of asynchronous online courses.

Keywords: Asynchronous online learning; Continuous usage intention; Technology acceptance model; Intrinsic motivation; Extrinsic motivation; Perception of multiple sources; Cognitive engagement