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http://dx.doi.org/10.5573/ieie.2015.52.3.221

A Study of Factors Influencing Intention to use Technology in Teaching Activities  

Joo, YoungJu (Dept. of Educational Technology, Ewha Womans University)
Chung, AeKyung (Dept. of Early Childhood Education, JEI University)
Choi, Miran (Dept. of Educational Technology, Ewha Womans University)
Yi, SangHoi (Dept. of Digital Electronics, Dong Seoul University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.3, 2015 , pp. 221-229 More about this Journal
Abstract
The purpose of this study is to verify factors influencing attitude to use of technology in teaching activities. For this study, a hypothetical technology acceptance model(TAM) was composed of TPACK, technostress, innovation, perceived ease of use, perceived usefulness, and behavioral intention to use technology in teaching activities. The survey was administered to 254 pre-service teachers. The result of this study through structural equation modeling analysis is as follows: First, TPACK significantly affects technostress. second, perceived ease of use affects perceived usefulness. Third, TPACK, technostress, perceived usefulness affects behavioral intention to use, but innovation and perceived ease of use did not affect behavioral intention to use. These results imply that TPACK, technostress, perceived usefulness are important to enhance behavioral intention to use technology in teaching activities. This study propose the constructive foundation for providing strategies raising the behavioral intention to use of technology in teaching activities.
Keywords
TPACK; Technostress; Technology; Pre-service teachers; Technology Acceptance Model;
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1 Cuban, Kirkpatrick, and Peck, High Access and Low Use of Technologies in High School Classroom: Explaining an Apparent Paradox, American Educational Research Journal, Vol. 38, no. 4, pp. 813-834, 2001.   DOI
2 Pamuk, Understanding preservice teachers' technology use through TPACK framework, Compute Assisted Learning, Vol. 28, pp. 425-439, 2012.   DOI   ScienceOn
3 M. R. Eom, W, S, Shin, and I, S, Han, A Survey on the Differences of Pre-service Teachers' Perception of the Technology, Pedagogy, and Content Knowledge (TPACK), Korean Teacher ducation, Vol. 28, no. 4, pp. 141-165, 2011.
4 Al-Fudail, and Mellar, Investigating teacher stress when using technology, Computers & education, Vol. 51, no. 3, pp. 1103-1110, 2008.   DOI   ScienceOn
5 Brod, C, Technostress: The human cost of the computer revolution, MA: Addison-Wesley, Vol. 13, p. 242, 1984.
6 D'Ignazio, F., and Goth-Tew, S, Teacher explorers, pioneers, and settlers, The computing teacher, Vol. 19, no. 4, pp. 38-40, 1991.
7 J. Y. Kim, Y. S. Kim, and N. R. Kim, The Effects of an Educational Computing Course on Preservice Teacher's Teaching Efficacy, Attitude and Anxiety Toward Computer, Asian Journal of ducation, Vol. 4, no. 3, pp. 101-119, 2003.
8 Hohmann, C, Staff development practices for integrating technology in early childhood education programs. Young children: Active learners in a technological age, pp. 104, 1994.
9 Koehler and Mishra, What is technological pedagogical content knowledge, Contemporary Issues in Technology and Teacher Education, Vol. 9, o. 1, pp. 60-70, 2009.
10 Agarwal, R. and Prasad, J, A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, Vol. 9 no. 2, pp. 204-215, 1998.   DOI   ScienceOn
11 Rogers, E. M. Diffusion of Innovation, New York: The Free Press, 1995.
12 Davis, F. D., A User acceptance of computer technology: a comparison of two theoretical models, Management science, Vol. 35, no. 8, pp. 982-1003, 1989.   DOI   ScienceOn
13 K. J. Yoo and M. K. Kim, The development and application of a task based information, communication and technology literacy educational program for pre-service early childhood teachers, Vol. 32, no. 4, pp. 365-401, 2012.
14 M. J. Kim and H. S. Cheon, The Comparative Study of Attitude toward E-learning Adoption between Korean and Vietnamese College Students, The e-business studies, Vol. 15 , no. 1 , pp. 25-51, 2014.
15 liu, I. F., Chen, M. C., Sun, Y., Wible, D., and Kuo, C, Extending the TAM model to explore the factors that affect Interation to use an Online Learning Community, Computers & Education, 54, pp. 600-610, 2010.   DOI   ScienceOn
16 Molebash, P, Preservice teacher perceptions of a technology-enriched methods course. Contemporary Issues in Technology and Teacher Education, Vol. 3, no. 4, pp. 412-432, 2004.
17 Franklin, C. A., and Molebash, P. E, Technology in the elementary social studies classroom: Teacher preparation does matter. Theory & Research in Social Education, Vol. 35, no. 2, pp. 153-173, 2007.   DOI
18 Aghamohammadi, A., Mohammadi, J., Parvaneh, N., Rezaei, N., Moin, M., Espanol, T., and Hammarstrom, L. , Progression of selective IgA deficiency to common variable immunodeficiency, International archives of allergy and immunology, Vol. 147, no. 2, pp. 87-92, 2008.   DOI   ScienceOn
19 liu, Y., Li, H., and Carlsson, C, Factors driving the adoption of m-learning: An empirical study, Computers & Education, pp. 1211-1219, 2010.
20 S. H. Park and Y. J. Choi, The Study of Educational Mobile Application Usage Based on Technology Acceptance Model, Vol. -, no. 82, pp. 9-35, 2013.
21 Fagan, M., Kilmon, C., and Pandey, V. (2012). Exploring the adoption of a virtual reality simulation: The role of perceived ease of use, perceived usefulness and personal innovativeness. Campus-Wide Information Systems, Vol. 29, no. 2, pp. 117-127, 2012.   DOI   ScienceOn
22 Y. Joo, A. Chung, S. Yi, Y. Lee, "Prediction of academic self-efficacy, perceived usefulness and ease of use on flow and academic achievement in D college education." Journal of the Institute of Electronics and Information Engineers of Korea, Vol. 47, no. 12, pp. 59-67, 2010.
23 M. S. Kang, C. H. Jung, and Y. S. Chung, An Empirical Study on the Factors Influencing the Acceptance of SmartWork, Daehan Academy of Management Information Systems, Vol. 32, no.1, pp. 19-41, 2013.
24 K. S. Chung, M. J. Noh, and W. B. Lee, Factors Affecting the Continuous Use Intention of E-learning Site, Journal of Employment and Skills Development, Vol.11, No.3, pp. 237-261, 2008.
25 Brown, S. A., Massey, A. P., Montoya-Weiss, M. M., and Burkman, J. R, Do I really have to? User acceptance of mandated technology, European journal of information systems, Vol. 11 no. 4, pp. 283-295, 2002.   DOI   ScienceOn
26 Mathieson, K, Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior, Information systems research, Vol.2, no.3, pp. 173-191, 1991.   DOI