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Top1. Introduction
Massive open online course (MOOCs) was first put forward by David Cormier in 2008. Scholars contend that the main goal of MOOCs is to engage people in a social–technical learning system in which the teacher is no longer the central figure in the classroom but a node in a larger learning network (Pilli & Admiraal, 2016). With their rapid development, academic research on MOOCs has proceeded apace. John L. Hennessy, president of Stanford University, called this phenomenon a “MOOCs Tsunami” (Wohlfeil, 2013). The essence of MOOCs is a knowledge dissemination path based on information technology innovation and development and people's willingness to adopt novel technologies. To date, “MOOCs” is still a hot educational topic in the world (e.g., García-Peñalvo, Fidalgo-Blanco, & Sein-Echaluce, 2018; Reich, & Ruipérez-Valiente, 2019).
MOOCs have already undergone rapid development and widespread deployment, however, further improvements to the platform and wider dissemination is possible. This is because contemporary students are generations with a high degree of acceptance of personal information technology (Taipale, 2016). The theory of personal information technology acceptance and related research stems from the technology acceptance model (TAM; Davis, 1985). Scholars continued to expand the scope of research in this area and proposed the theory of planned behavior (TPB; Ajzen, 1991), the model of PC utilization (MPCU; Thompson, Higgins, & Howell, 1991), the motivation model (MM; Davis, Bagozzi, & Warshaw, 1992), the social cognitive theory (SCT; Compeau & Higgins, 1995), the extension of the technology acceptance model (Venkatesh & Davis, 2000), the innovation diffusion theory (Rogers, 2003), the unified theories of acceptance and usage of technology model (UTAUT; Venkatesh, Morris, Davis, & Davis, 2003), the technology acceptance model 3 (Venkatesh & Bela, 2008), and others.
Among these theories, the UTAUT model is a typical and widely used one (Chu, 2013). UTAUT integrates several technology acceptance models and identifies several potential variables: performance expectancy, effort expectancy, social influence, facilitating conditions, age, sex, experience, and four moderating variables. Therefore, the interpret ability of UTAUT model is as high as 70%, which considerably exceeds the 17% to 42% interpretation ability of the previous model (Venkatesh, Thong, & Xu, 2016).
In China, college students’ acceptance of MOOCs is not only an individual behavior of information technology acceptance, but also a social trend. Under the current education system in China, it is difficult for college students to study MOOC because of their heavy loading. But it is a reality that college education in China requires teachers to adopt MOOC as one of the teaching approaches. That’s why many students are forced to be involved in it if they have free time. Thus, the conflict between leisure and learning is evident. This study investigated some factors that influence the MOOC learning intention and behavior of university students from the perspective of technical acceptance.