2.2 Technology acceptance model
2.2.1 Specification of TAM model
Technology acceptance model was developed in 1986 to improve the understanding of user acceptance processes in new systems before implementation (Davis, 1986). TAM is short for technology acceptance model, and the framework of TAM model is shown in the Figure 2.1. Davis (1989) held external variables affected perceived usefulness and perceived ease of use. Perceived Usefulness (PU) is the degree to which the user assesses that using a technology would help perform the work better. While Perceived ease of use (PEOU) is the degree to which a user considers that using a technology would be free of effort. Moreover, Davis (1989) considered perceived ease of use as an antecedent to perceived usefulness. Meanwhile, perceived usefulness is strongly linked to behavioral intention to use technology. Perceived usefulness and perceived ease of use affect learners’ attitudes towards use. Perceived usefulness and attitude determine the behavioral intention to use the system; Ultimately, the behavioral intention to use the system determines the actual behavior of using the system.
Chapter Three Theoretical Model and Hypothesis.............................16
3.1 The definitions of variables and research hypothesis………………………..16
3.2 Research model……………………………………20
Chapter Four Research Design.......................22
4.1 Research questions……….………….....22
4.2 Participants……......................22
Chapter Five Results and Discussion...........................30
5.1 Descriptive statistics of mobile English learning.........................30
5.2 Factors affecting students’ intention to use mobile English learning………..32
Chapter Five Results and Discussion
5.1 Descriptive statistics of mobile English learning
To address the first study question, what is the current state of college students’ mobile English learning, descriptive statistics were used with the software application Statistical Product and Service Solutions version 25 (SPSS 25.0), and the results are shown in Table 5.1.
Table 5.1 lists mobile devices of college students’ English learning. 71.2 % students use smartphones as the device of mobile English learning. 11.3% students use Laptops as the device for mobile English learning. 6.8 % students IPAD as the device of mobile English learning. 0.5% students use MP3s as the devices of mobile English learning. 0.5% students use e-dictionary as the devices of mobile English learning. 9.7 % students use other devices of mobile English learning. Over two third students use smart phones as the devices of mobile English learning. Smartphones are widely applied and accepted in mobile English learning.
Chapter Six Conclusion
6.1 Main findings
Three new findings are generated from the study. First, mobile English learning is uncommon among college students. English e-reading, English learning data recording and storage, English e-material searching, real-time assessment and online English courses for English learning, the sharing of English learning materials, and English conversation all demonstrate their low frequency of mobile learning.
Second, except for perceived usefulness, perceived ease of use and behavioral intention to use, the results demonstrate the new factors has a positive and significant influence on intention to use. There are seven important predictors of influencing users’ intention to use mobile devices in English learning. That is self-management, flow experience, mobile learning resource and social influence.
Third, the results of the research depict the strong relationship of some influencing factors. It shows up in perceived usefulness, perceived ease of use, and behavioral intention, all of which are fundamental components of intention. The perceived utility, ease of use, and behaviora
