Abstract
The purpose of study is to propose and verify that the extended technology acceptance model can be applied to explain and predict the acceptance of mobile learning in museum. In the study, we try to review and establish the relationship between the external variables and user’s attitude and behavior in museum mobile learning system. According the relationship between the external variables and user’s attitude and behavior, we will do the investigation in our museum for the m-learning system exhibition. We have finished the detail investigation and find the constructs relationship between the external variables and user’s attitude and behavior in museum.
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References
Adams, D.A., Nelson, R.R., Todd, P.A.: Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Q. 16, 227–247 (1992)
Agarwal, R., Prasad, J.: Are individual differences germane to the acceptance of new information technologies? Decis. Sci. 30(2), 361–391 (1999)
Bagozzi, R.P., Davis, F.D., Warshaw, P.R.: Development and test of a theory of technological learning and usage. Hum. Relat. 45(7), 660–686 (1992)
Brown, I., Licker, P.: Exploring differences in internet adoption and usage between historically advantaged and disadvantaged groups in South Africa. J. Glob. Inf. Technol. Manage. 6(4), 6–22 (2003)
Bruner II, G.C., Kumar, A.: Applying T.A.M.: to consumer usage of handheld Internet devices. J. Bus. Res. 58, 553–558 (2005)
Childers, T., Carr, C., Peck, J., Carson, S.: Hedonic and utilitarian motivations foronline retail shopping behaviour. J. Retail. 77(4), 511–535 (2001)
Chin, W., Todd, P.: On the use, usefulness, and ease of use of structural equationmodelling in MIS research: a note of caution. MIS Q. 19, 237–246 (1995)
Compeau, D.R., Higgins, C.A.: Computer self-efficacy: development of a measure and initial test. MIS Q. 19(2), 189–211 (1995)
Coursaris, C., Hassanein, K., Head, M.: M-Commerce in Canada: an interaction framework for wireless privacy. Can. J. Adm. Sci. 20(1), 54–73 (2003)
Dabholkar, P., Bagozzi, R.: An attitudinal model of technology-based self-service:moderating effects of consumer traits and situational factors. J. Acad. Mark. Sci. 30(3), 184–201 (2002)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)
Doll, W.J., Hendrickson, A., Deng, X.: Using Davis’s perceived usefulness andease-of-use instrument for decision making: a confirmatory and multigroup invarianceanalysis. Decis. Sci. 29(4), 839–869 (1998)
Eason, K.: Changing perspectives on the organizational consequences of information technology. Behav. Inf. Technol. 20(5), 323–328 (2001). https://doi.org/10.1080/01449290110083585
Falk, J.H., Dierking, L.D.: School field trips: assessing their long-term impact. Curator 40(3), 211–218 (1997)
Gefen, D., Straub, D.W.: Gender differences in the perception and use of e-mail:an extension to the TAM. MIS Q. 21(4), 389–400 (1997)
Hannafin, M., Peck, K. : The Design Development and Evaluation of Instructional Software. MacMillian Publishing, New York (1988)
Heijden, H.: Factors influencing the usage of websites: the case of a generic portal in the Netherlands. Inf. Manage. 40(6), 541–549 (2003)
Hendrickson, A.R., Massey, P.D., Cronan, T.P.: On the test-retest reliability of perceived usefulness and perceived ease of use scales. MIS Q. 17, 227–230 (1993)
Hill, T.R., Roldan, M.: Toward third generation threaded discussions for mobile learning: opportunities and challenges for ubiquitous collaborative environments. Inf. Syst. Front. 7, 55–70 (2005). https://doi.org/10.1007/s10796-005-5338-7
Hu, P.J., Chau, P.K., Liu Sheng, O.R., Tam, K.Y.: Examining the TAM using physicianacceptance of technology. J. MIS. 16(2), 91–112 (1999)
Igbaria, M., Iivari, J.: The effects of self-efficacy on computer usage. Omega Int. J. Manag. Sci. 23(6), 587–605 (1995)
Jyri, N.: Reflections on technology acceptance in higher education (2004). http://is2.lse.ac.uk/asp/aspecis/20040115.pdf. Accessed 5 Dec 2006
Mathieson, K.: Predicting user intentions: comparing the TAM with the theory of planned behaviour. Inf. Syst. Res. 2(3), 173–91 (1991)
McDermott, K.J., Nafalski, A., Gol, O.: Active learning in the University of South Australia. Front. Educ. Conf. 1(18–21), 18–21 (2000)
Moon, J.W., Kim, Y.G.: Extending the TAM for a world-wide-web context. Inf. Manage. 38(4), 217–230 (2001)
O’Cass, A., Fenech, T.: Web retailing adoption: exploring the nature of internet users’ web retailing behavior. J. Retail. Consum. Serv. 10, 81–94 (2003)
Quin, C.: Mlearning: mobile, wireless, in – your-pocket learning. LiNE Zine (2001)
Revans, R.: The Origins and Growth of Action Learning. Chartwell Bratt, Sweden (1982)
Segars, A.H., Grover, V.: Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. MIS Q. 17, 517–525 (1993)
Subramanian, G.H.: A replication of perceived usefulness and perceived ease of use measurement. Decis. Sci. 25(5/6), 863–873 (1994)
Szajna, B.: Software evaluation and choice: predictive evaluation of the technology acceptance instrument. MIS Q. 18(3), 319–324 (1994)
Ting, R.Y.L.: Mobile learning: current trend and future challenges. In: Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies (ICALT 2005)
Tornatzky, L.G., Klein, R.J.: Innovation characteristics and innovation adoption-implementation: a meta-analysis of findings. IEEE Trans. Eng. Manag. EM 29, 28–45 (1982)
Traxler, J.: Mobile Learning: It’s Here but Where Is It? (2005). http://www2.warwick.ac.uk/services/cap/resources/ineractions/archive/issue25/traxler/. Accessed 5 Dec 2006
Venkatesh, V.: Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)
Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996)
Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)
Wang, Y., Wang, Y., Lin, H., Tang, T.: Determinants of user acceptance of Internet banking: an empirical study. Int. J. Serv. Ind. Manage. 14(5), 501–519 (2003)
Yi, M.Y., Hwang, Y.: Predicting the use of web-based information systems:self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. Int. J. H-C Stud. 59(4), 431–449 (2003)
Young, S.C., Chung, C.H., Liu, I.F.: An overview of integration of mobile technologies into teaching and learning settings. Instr. Technol. Media 73, 62–76 (2005). (in Chinese)
Yu, J., Ha, I., Choi, M., Rho, J.: Extending the TAM for a t-commerce. J. Inf. Manage. 42(7), 965–976 (2005)
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Fan, Cw. (2020). Applied the Technology Acceptance Model to Survey the Mobile-Learning Adoption Behavior in Science Museum. In: Rau, PL. (eds) Cross-Cultural Design. Applications in Health, Learning, Communication, and Creativity. HCII 2020. Lecture Notes in Computer Science(), vol 12193. Springer, Cham. https://doi.org/10.1007/978-3-030-49913-6_23
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