Collaborative technologies have drawn much attention from educational scholars, as they can provide students with a platform on which they can discuss, exchange, and share their opinions and ideas, as well as construct their own knowledge collaboratively.
In sum, the main proposition of the TTF model is that a user with greater support from a given technology with regard to a focal task will have better perception of the task-technology fit, as well as of the use of this technology (Lee & Lehto, 2013).
The TTF model consists of four major constructs, namely task characteristics, technology characteristics, task-technology fit, and technology utilization (Lin & Huang, 2008).
Goodhue and Thompson (1995) proposed the task-technology theory (TTF) to fill in the gap between user acceptance towards IT systems and the ability of the system to support a focal task, in order to provide a more precise explanation of the links between work-related factors and IT support.
Gagne and Deci (2005) stated that “intrinsic motivation involves people doing an activity because they find it interesting and derive spontaneous satisfaction from the activity itself; in contrast, extrinsic motivation requires an instrumentality between activity and some separable consequences such as tangible or verbal rewards, so satisfaction comes not from the activity itself but r
As proposed by Deci and Ryan (1985), the Self Determination Theory (SDT) posits that intrinsic and extrinsic motivation are the core elements which can explain why people carry out an activity.
The ECM posits that the user’s level of satisfaction, the extent of their confirmed expectation, and their post-adoption expectations (perceived usefulness) have direct or indirect effects on their intention to continue IT usage.
Based on the congruence between users’ continued usage intention towards IT and consumers’ repeat purchase decision making behavior, Bhattacherjee (2001a, 2001b) proposed expectation-confirmation model (ECM) to explain IT users’ intention to continue or discontinue to use an IS.
Ito et al. (2008) indicated that learners are greatly influenced by social interactions in multimedia learning environments. When learners perceive that their important referents think they should use GBL, they are likely to incorporate this idea into their own beliefs, simply because their friends are users of GBL.
Social influence profoundly affects user behavior (Ajzen, 1991; Lee, 2006), and thus users’ decision to adopt a specific IT may often be influenced by the suggestions of group members. I
TAM proposes that two particular beliefs, perceived usefulness and perceived ease of use, are the primary drivers of technology acceptance. Perceived ease of use is defined as “the degree to which a person believes that using a particular system would be free of physical and mental effort”, while perceived usefulness is defined as “the degree to which a person believes that
The technology acceptance model (TAM) (Davis, 1989) is the most frequently cited and influential model for explaining technology acceptance and adoption. Davis (1989) first introduced the TAM as a theoretical extension of the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975).
The ECM posits that users’ perceived usefulness of IT has a positive effect on their intentions to continue IT usage. The confirmation of expectations suggests that users obtained the expected benefits through their usage of the focal IT, and this has a positive effect on their satisfaction.
Educational digital games, which typically require the use of logic, memory, problem-solving, and critical thinking skills, generate higher levels of student interest in the focal subject matters (Annetta, 2008).
Game-based learning (GBL) is as a system in which learners are immersed in a set of interactive components and challenging activities based on a series of clear goals, agreed rules and constraints, and such issues are often discussed in the context of educational technology (Salen & Zimmerman, 2004).
The expectation confirmation model (ECM) was developed by Bhattacherjee (2001) based on expectation confirmation theory (Oliver, 1980), and includes three dimensions of user intention to continue using certain technologies: perceived usefulness, confirmation of expectations and satisfaction.