Understanding MOOC continuance: An empirical examination of social support theory

“Generation invisible“. Higher education students’ (non)use of webcams in synchronous online learning

“…Students may perceive less social support in online course settings and be less willing to engage in social relationships. Since some findings underline the importance of social support and social engagement for learning success, further intervention measures could be taken at this point (Hsu et al, 2018).…”

Investigating teachers’ adoption of MOOCs: the perspective of UTAUT2

“…However, many more researchers have focused on the former (e.g. Alraimi et al, 2015;Fang et al, 2019;Hsu et al, 2018;Ma & Lee, 2019a;Ma & Lee, 2019b;Shao, 2018;Wu & Chen, 2017;Zhou, 2016) as compared to the latter; the current study intends to fill this gap.…”

“…Most prior relevant studies have examined MOOC use from the learner's perspective using technology acceptance model (TAM) (Hsu, Chen, & Ting, 2018;Shao, 2018;Wu & Chen, 2017;Yang & Su, 2017;Zhou, 2016), task-technology fit (Huang, Zhang, & Liu, 2017;Jo, 2018;Wu & Chen, 2017), the theory of planned behavior (Yang & Su, 2017;Zhou, 2016), the social support theory (Hsu et al, 2018), the social cognitive theory (Shao, 2018), the self-determination theory (Fang, Tang, Yang, & Peng, 2019;Zhou, 2016), the technology-user-environment perspective (Ma & Lee, 2019a), network externalities (Li, Wang, & Tan, 2018), the regulatory focus theory (Zhang, 2016), the expectationconfirmation paradigm (Alraimi et al, 2015;Zhou, 2017), and the innovation resistance theory (Ma & Lee, 2019b). Relatively few studies have examined this issue from the perspective of teachers (Liyanagunawardena, Adams, & Williams, 2013), even though teachers play a key facilitating role in MOOCs and are instrumental in terms of engaging students in the learning process through course design (e.g.…”

Modeling Collaborative Intentions and Behavior in Digital Environments: The Case of a Massive Open Online Course (MOOC)

“…Additionally, perceived convenience and computer self-efficacy can influence continuance intention for MOOCs, but not for general e-learning (Hsu, Chen, & Ting, 2018). Many of the papers modelling continuance, revisit, and completion intention of MOOCs draw on the Technology Acceptance Model (TAM) proposed by (Davis, 1989).…”

“…Much of technology acceptance research proposes that self-efficacy actually influences intentions only indirectly via attitudes. This has influenced important technology models such as the technology acceptance model (TAM) which has been extensively used in studies of online behavior mediated by technology (Davis, 1989) and recently in MOOC-related research (Hsu et al, 2018). In line with TAM we consider attitude a precursor of intention.…”