Abstract
This study tries to propose a unified model integrating the unified theory of acceptance and use of technology (UTAUT) model, task–technology fit (TTF) model, and user satisfaction to investigate the determinants that affect university students’ continued intention of using massive open online courses (MOOCs). Based on the data of a survey on 464 respondents, structural equation modeling is adopted to assess the model. The results reveal that performance expectancy, effort expectancy, social influence, and user satisfaction are the crucial predictors of university students’ continued intention. TTF has an indirect influence on continued intention through user satisfaction. Performance expectancy is affected both by effort expectancy and TTF. Facilitating conditions do not directly influence continued intention; however, they present indirect influences in that they play a mediating role for user satisfaction. The findings help researchers and practitioners to attain a better understanding of university students’ continued usage intention of MOOCs. The implications and limitations of this study are also described.
Highlights
Massive open online course (MOOC) is an innovative educational model that experiences a development in the past 8 years (Huang et al, 2017)
According to the latest statistical data published by the Chinese Ministry of Education, more than 10 MOOC platforms in China were established by universities or associated organizations; more than 3,200 MOOC courses offered by more than 460 universities or colleges were available on the online platforms; the courses were used by 55 million students inside or outside the university and more than 6 million university students have acquired MOOC credits
The results show that facilitating conditions have no direct effect on continued intention, which is opposite to the result of Oh and Yoon (2014) and T
Summary
Massive open online course (MOOC) is an innovative educational model that experiences a development in the past 8 years (Huang et al, 2017). To some extent, it can change the mode of teaching and learning of traditional university classrooms and facilitate the revolution of instruction paradigm, teaching method, learning technology, and so on. Jordan (2014) collected a variety of public data about MOOC enrolment and completion. A case study in China reported that the completion rate of online course was only around 3.7% in the MOOC platform—Icourse (Shao, 2018)
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