Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

A Study of Factors Affecting on m-learning Satisfaction based on UTAUT

UTAUT에 기반한 m-learning 만족도에 미치는 요인에 관한 연구

  • 송형철 (동원대학교 사회경영학부 e-비즈니스전공)
  • Received : 2018.05.02
  • Accepted : 2018.07.20
  • Published : 2018.07.28
Download PDF
⟨ Previous Next ⟩

Abstract

This study aims m-learning based on UTAUT and learners' satisfaction For empirical analysis, a survey was conducted on 289 university students and SPSS 22.0, AMOS 21.0 were used. The result of structual equation modeling analysis are as follows: First, performance expectancy was influenced by security, diversity, economics. Second, performance expectancy, effort expectancy affect learners' satisfaction. This research provide practical guidance in m-learning based on UTAUT amd the limltation of this research and future study are discussed. In the future, variables of m-learning based on UTAUT including the general public besides university students will be complement to analyze.

본 연구의 목적은 대학에서 UTAUT에 기반한 m-learning 학습자의 만족도에 미치는 영향을 실증적으로 검증하고자 하였다. 각 요인의 관계를 살펴보기 위하여 289부의 설문지를 SPSS 22.0, AMOS 21.0을 이용하여 분석하였다. 분석결과는 보안성이 성과기대와 노력기대에 정(+)의 영향을 미칠 것이라는 가설은 채택되었다. 다양성과 경제성도 성과기대에 영향을 미치는 것으로 나타났다. 매개변수인 성과기대와 노력기대는 학습자의 만족도에 정의 영향을 미친다는 가설은 채택되었다. 이런 결과는 UTAUT에 기반한 m-learning 운영에 필요한 기초자료를 제공하였다는 시사점이 있다. 이와 같은 시사점에도 불구하고 UTAUT에서 제시된 요인 중 일부만을 분석하였다는 한계점이 있다. 향후에는 대학생 외에 일반인에 대한 분석도 포함하여 UTAUT에 기반한 m-learning에 미치는 다양한 영향 변수에 대한 분석을 통하여 계속적으로 보완하고자 한다.

Keywords

References

  1. V. Venkatesh, M. G. Morris, G. B. Davis & F. D. Davis. (2003). User Acceptance of Information Technology: Toward a Unified View, Management Information Systems Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
  2. J. Leh. (2014). Social Learning - How Social is Your LMS?. DOI:http://talentedlearning.com/social-learning-social-lms/
  3. I. J. Jang. (2011). Smart Education Strategy Implementation Plan, ministry of education(2011). DOI:http://www.keris.or.kr/upload/board05/131485411995 7_429894927.pdf
  4. V. Venkatesh, J. Y. L. Thong & X. Xu. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead, Journal of the Association for Information Systems, 17(5), 328-376. https://doi.org/10.17705/1jais.00428
  5. https://ko.wikipedia.org/wiki
  6. T. Grossman, D. Pierre & R. Balakrishnan. (2007). Strategies for accelerating on-line learning of hotkeys. Proceedings of CHI 2007 - the ACM Conference on Human Factors in Computing Systems, 1591-1600.
  7. P. C. Sun, R. J. Tasi, G. Finger, Y. Y. Chem & D. Yeh. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202. https://doi.org/10.1016/j.compedu.2006.11.007
  8. K. Hassanein, M. Head & F. Wang. (2010). Understanging Student Satisfaction in Mobile Learning environment: the Role of Internal and External Facilitators, In Mobile business and 2010 Ninth Global Mobility Roundtable, 289-296.
  9. R. A. Westbrook. (1981). Source of Consumer Satisfaction with Retail Outlets, Journal of Retailing, 57(fall), 68-85.
  10. X. Luo, A. Gurung & J. P. Shim. (2010). Understanging the determinants of user acceptance of enterprise instant messaging: an empirical study, Journal of Organizational Computing and Electronic commerce, 20(20), 155-181. https://doi.org/10.1080/10919391003709179
  11. W. H. DeLone & E. R. Mclean. (2003). The DeLone and Mclean model of Information System Success: a ten year update, Journal of Management Information System, 19(4), 9-30. https://doi.org/10.1080/07421222.2003.11045748
  12. M. Reid & Y. Levy. (2008). Integrating trust and computer self-efficacy with TAM: An empirical assessment of customers' acceptance of banking information system in Jamaica, Journal of Internet Banking and Commerce, 13(3), 1-18.
  13. R. Martins, T. Oliveria & M. A.Thomas. (2016), An empirical analysis to assess the determinants of SaaS diffusion in firms, Computers in Human Behavior, 62, 19-33. https://doi.org/10.1016/j.chb.2016.03.049
  14. G. Baptista & T. Oliveria. (2015), Understanging Mobile Banking: The unified theory of acceptance and use of technology combined with cultural moderators, Computers in Human Behavior, 50, 418-430. https://doi.org/10.1016/j.chb.2015.04.024
  15. M. Alshehri, S. Drew, T. Alhussain & R. Alghamdi. (2012). The impact of trust on e-government services acceptance: A study of users'' perceptions by applying UTAUT model. International Journal of Technology Diffusion, 3(2), 1-5. https://doi.org/10.4018/jtd.2012040101
  16. M. Alshehri & S. K. Sharma. (2017). Computational Model for the Generalised Dispersion of Synovial Fluid, (IJACSA) International Journal of Advanced Computer Science and Applications, 8(2), 134-138
  17. S. R. Yee. (2015). A Study of Team satisfaction and associated Factors of engineering College Freshmen, Journal of Digital Convergence, 13( 2), 315-324. https://doi.org/10.14400/JDC.2015.13.2.315
  18. A. J. Tomarken & N. G. Waller. (2003). Potential problems with "well fitting" models, Journal of Abnormal Psychology, 112(4), 578-598. https://doi.org/10.1037/0021-843X.112.4.578