Presenter: Yun-Ting, Wong Adviser: Ming-Puu,Chen Date: Dec. 09, 2009 Liu, F. I., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. H. (2010). Extending the.

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Presenter: Yun-Ting, Wong Adviser: Ming-Puu,Chen Date: Dec. 09, 2009 Liu, F. I., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. H. (2010). Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education, 54(2),

Introduction Online learning community: When a number of people with a common learning goal form a group, it is called a learning community. Online learning communities are gradually altering traditional learning styles because of the pervasiveness of the Internet. The diverse interactive media play a support role in learning, therefore, it is necessary to consider the needs of learners and the characteristics of each online learning community when designing online learning courses (Dede, 1996). TAM Model:Davis (1986), who proposed the Technology Acceptance Model (TAM), suggested that the ease of use and usefulness of a technology affect users’ intention to use it.

Research Model(1/4) In this study, which build an Intelligent Web-based Interactive Language Learning (IWiLL) community as an online English learning platform for high school students in Taiwan. TAM Model: -Perceived Usefulness -Perceived Ease of Use Venkatesh and Davis (1996) suggested that Perceived Usefulness and Perceived Ease of Use could be affected by external variables. However, TAM only provides general information about whether a technology has been adopted by users. Further information is needed regarding its use in specific fields, so that the development of technology can be guided in the right direction (Mathieson,1991).

Research Model(2/4) In this model,an online learning community is composed of 1.Human elements :the online learning community, including learners and instructors.(how a learner feels? based on pre- experience ) 2.system elements: computers connected to the Internet and used for learning activities, including online courses and online learning system. For students, the design of an online course is the most important determinant of learning effectiveness (Fink, 2003) it is crucial that instructors adopt the proper pedagogical strategy and technology when designing an online learning course. From another perspective, a good interface design helps users resolve technical problems that may arise when using a system (Metros & Hedberg, 2002).

Research Model(3/4) External variables Online Course Design: H1. Online Course Design will positively affect the Perceived Usefulness/ H2.Ease of Useof an online learning program. H3.Interaction with an online learning community. User-interface design (also designed a set of authoring tools for instructors): H4. User-interface Design will positively affect the Perceived Ease of Use Of/H5. Interaction with an online learning community. Previous Online Learning Experience: H6. Previous Online Learning Experience will positively affect the Perceived Usefulness/H7.Ease of Use of an online learning program./H8.the Intention to Use an Online Learning Community.

Research Model(4/4) Perceived variables: one-way human–system interaction to two-way instructor–learner interaction knowledge is created through a series of processes whereby individuals interact with each other to share, recreate, and amplify knowledge (Nonaka & Nishiguchi, 2001). H9. Perceived Ease of Use will positively affect the Perceived Usefulness of an online learning program. H10. Perceived Ease of Use will positively affect the Perceived Interaction with an online learning program. H11. Perceived Usefulness will positively affect the Intention to Use an Online Learning Community. H12. Perceived Ease of Use will positively affect the Intention to Use an Online Learning Community. H13. Perceived Interaction will positively affect the Intention to Use an Online Learning Community.

Methodology(1/2) five-point Likert-type scale was used to answer the questions in the seven constructs of the questionnaire asked 178 high school students listed on the collected from IWill website to complete the preliminary questionnaire of 26 items. By measuring the scale’s reliability based on the value of Cronbach’s alpha,

Methodology(2/2) The study placed the questionnaire on the IWiLL website for 2 weeks.(436 responses were valid, average age:18,gender:m205:f231) Data analysis: Structural equation modeling(SEM),LISREL 8.54

Result(1/3) Model testing criteria: adopted the following indices recommended by Hoyle and Panter (1995) and Kelloway (1998), as the criteria for the model’s evaluation: *the closer the observed data is to the theoretical model, the better the fit of the model

Result(2/3) Model testing result:

Result(3/3) Model testing result: Perceived Usefulness has the strongest effect, followed by Pre-vious Online Learning Experience and then Online Course Design. Moreover, Online Course Design is the strongest indirect effect that influences Intention to Use an Online Learning Community.

Conclusion The implications of the research results as guidelines for developing future online English learning communities. The Intention to Use an Online Learning Community is strongly and directly affected by Perceived Usefulness and indirectly by Online Course Design. Users should be encouraged to gain more online learning experience and to use information technology to learn English. Some advanced teaching aids should be considered when designing the user interface.

Discussion Our findings confirm those of other researchers (e.g., McGiven, 1994; Rovai, 2004) that User-interface Design is the most important determinant that affects Perceived Ease of Use. When the system design is developed in a more user-friendly form, users will feel more comfortable and find the system easier to use. The greater the online learning experiences of users, the stronger their Intention to Use an Online Learning Community. This conclusion is accordance with the research results of Arbaugh and Duray (2002). If learners have Previous Online Learning Experience, even just experience in using related information technologies:  more willing to participate in an online learning community.  easy to operate the system  have more problem-solving ability with the system’s operation.