Browse > Article
http://dx.doi.org/10.6109/jkiice.2016.20.6.1081

Instructor's Smart Learning Acceptance : Focusing on TAM Model  

Kim, Do-Goan (Division of Information and Electronic Commerce, Wonkwang University (Institute of Convergence and Creativity))
Lee, Hyun-Chang (Division of Information and Electronic Commerce, Wonkwang University (Institute of Convergence and Creativity))
Rhee, Yang-Won (Department of Computer Information Engineering, Kunsan National University)
Shin, Seong-Yoon (Department of Computer Information Engineering, Kunsan National University)
Abstract
While smart learning have been introduced for more learning effect, this study is to understand instructor's smart learning acceptance using technology acceptance model(TAM). This study developed the extended TAM model, including external pressure for smart learning and smart self efficacy for smart devices as study variables and attempted to examine the research model through the empirical analysis. The research model has the 7 variables including smart self-efficacy and external pressure. For the empirical study, the survey was conducted for the one month, March, 2016, and the total 143 data among the collected 167 responses were used for the empirical analysis. As the result of the analysis through the structural equation model, the 9 paths among the total 10 paths show the significant relationships between the variables. Through using the result of this study, it is to provide suggestions for the improvement of smart learning environments.
Keywords
TAM; Smart learning; Instructor; Multi media;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 J. H. Kang, "A study on utilizing SNS to vitalize smart learning," Journal of Digital Convergence, vol. 9, no. 5, pp. 265-274, Oct. 2011.
2 F. D. Davis, "Perceived usefulness ease of use, and use acceptance of information technology," MIS Quarterly, vol. 13, no.3, pp. 319-340, Sep. 1989.   DOI
3 S. T. Nam, H. C. Lee, and C. Y. Jin, "Influence of the multimedia function on continue using intention of smartphone based SEM," Journal of the Korea Institute of Information and Communication Engineering, vol. 19, no.6, pp. 1347-1352, Jun. 2015.   DOI
4 V. Venkatesh and F. D. Davis, "A theoretical extention of the technology acceptance model: for longitudinal field studies," Management Science, vol. 46, no. 2, pp. 186-204, Feb. 2000.   DOI
5 E. D. Davis, R. P. Bagozzi, and P. R. Warshaw. "User acceptance of computer technology: a comparison of two theoretical model," Management Science, vol. 35, no. 8, pp. 982-1003, Aug. 1989.   DOI
6 K. Mathieson, "Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior," Information System Research, vol. 2, No. 3, pp. 173-191, Sep. 1991.   DOI
7 S. Tayler and P. A. Todd, "Assessing IT usage: the role of prior experience," MIS Quarterly, vol. 19, no. 4, pp. 561-570, Dec. 1995.   DOI
8 P. Chewlos, I. Bendast and A. S. Dexter, "Research report: empirical test of an EDI adoption mode," Information System Research, vol. 12, pp. 304-321, Sep. 2001.   DOI
9 A. Bandura, "Self-efficay: toward a unifying theory of behavioral change," Psychological Review, vol. 84, no. 2, pp. 191-215, Mar. 1977.   DOI
10 G. D. An, "The reconsideration and prospect of the studies on the learner's affective traits," Journal of Educational Psychology, vol. 11, no. 1, pp. 33-48, Mar. 1997.
11 K. S. Noh and S. W. Park, "Measures for e-learning policy effectiveness improvement through analysis of maturity of korean policy application," The Journal of Digital Policy & Management, vol. 11, no. 12, pp. 11-19, Dec. 2013.