Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute

Journal of Social and Political

Sciences

ISSN 2615-3718 (Online)

ISSN 2621-5675 (Print)

asia insitute of research, journal of social and political sciences, jsp, aior, journal publication, humanities journal, social journa
asia insitute of research, journal of social and political sciences, jsp, aior, journal publication, humanities journal, social journa
asia insitute of research, journal of social and political sciences, jsp, aior, journal publication, humanities journal, social journa
asia insitute of research, journal of social and political sciences, jsp, aior, journal publication, humanities journal, social journa
crossref
doi
open access

Published: 05 August 2022

The Factors Affect the Online Learning Behaviour of Students

Nguyen Thi Van Anh, Hoang Thanh Tung, Tran Pham Chieu Uyen

University of Labour and Social Affairs (Vietnam), Mater Dei High School (Vietnam)

journal of social and political sciences
pdf download

Download Full-Text Pdf

doi

10.31014/aior.1991.05.03.361

Pages: 31-45

Keywords: Determinants, E-Learning, Online Learning, Online Learning Behavior

Abstract

This article aims to analyze the factor affecting online learning (e-learning) of high-school and university students in Vietnam based on such models as the Theory of Reasoned Action (TRA – Fishbein & Ajzen, 1975); Theory of Planned Behavior (TPB - Ajzen, 1991); Technology Acceptance Model (TAM - Davis, 1989); C-TAM-TPB by Taylor and Todd (1995); and Unified Theory of Acceptance and Use of Technology (UTAUT) by Viswanath Venkatesh, Michael G. Moris, Gordon B. Davis, and Fred D (2003), and other related experimental studies. Based on the quantitative analysis results, it can be seen that among six factors that affect the online learning behavior of students, perceived behavioral control has the strongest impact, at 30.5%, the perceived ease of use affecting 28.7%, performance expectancy at 17.3% and facilitating conditions at 14.9%, social influence only at 12.3% and the risk of online learning harms students' behavior at -13.8%. By analyzing the advantages, disadvantages, and the degree of impact of factors affecting online learning behaviors, the research group makes some recommendations on applying a more effective online learning method, even after the Covid-19 pandemic is under control

References

  1. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Springer, New York

  2. Ajzen, I. (1991). The theory of Planned Behavior. Organizational Behavior and human decision processes, 50, 179-211

  3. Baron, R.M, Kenny, D.A (1986), The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of Personality and Social Psychology 51(6):1173-1182

  4. Ministry of Education and Training (2021). Circular regulating Organization of Online Teaching in General Education Institutions and Vocational Education Institutions. March 30, 2021, https://luatvietnam.vn/giao-duc/thong-tu-09-2021-tt-bgddt-quy-dinh-ve-quan-ly-va-to-chuc-day-hoc-truc-tuyen-200817-d1.html

  5. Chen & Lu, (2002), Enticing Online Consumers: An Extended Technology Acceptance Perspective, Information and management 39, pp. 705-719

  6. Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118-143.

  7. David, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-339

  8. Fishbein, M & Ajzen, I (1975), Belief, attitude, intention, and behavior: An introduction to theory and research, Addison- Wesley, Reading, MA

  9. F. D. Davis, R. P.Bagozzi, & P. R.Warshaw (1989). “User acceptance of computer technology: A comparison of two theoretical models, Management Science, (35), 982-1003.

  10. Hartwick, J., & Barki, H. (1994), Explaining the role of user participation in information system use, Management Science, 40(4), 440-465.

  11. Hess, T., Benlian, A., Matt, C., Wiesböck, F., (2016), Options for formulating a digital transformation strategy, Q. MIS Exec. 15 (2), 123–139 (2016)

  12. Hoai, T.T., Nguyen, P.N., (2019), Corporate Social Responsibility: Regulating Internal Control in Enterprises in Vietnam, Journal of Asian Business and Economic Studies, 21-42

  13. Moore G., Benbasat I. (1991), Development of the instrument to measure the perceptions of adopting information technology innovation, Information systems research, 2 (3) 192-222

  14. Pikkarainen (2004), Consumer acceptance of online banking: An extension of the technology acceptance model, Internet research, Vol.14 Issue:3, PP 224- 235.

  15. Tan, M., and Teo, (2000), Factors Influencing the Adoption of Internet Banking, Journal of the Association for Information Systems: Vol. 1: Iss.1, Article 5.

  16. Taylor, S., Todd, P. (1995), Understanding information technology usage: a test of competing models, Inf. Syst. Res. 6(2), 144–176

  17. Taylor, S. &Todd, P. (1995a), Assessing IT usage: the role of prior experience, MIS Quarterly, Vol. 19, pp.561-570.

  18. Taylor, S., and P.A. Todd (1995b), Understanding Information Technology Usage: A Test of Competing Models, Information Systems Research 6(2), pp.145-176

  19. Thompson R., Higgins C., Howell J. (1991), Personal computing: Toward a conceptual model of utilization, MIS quarterly, 15 (1) 125-143

  20. Thuy, H.D.L., Truong, H.T., (2020), Combining Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) to Propose a Model for Online Learning Behavior Analysis in Vietnam during Covid-19 Pandemic, TNU Journal of Science and Technology, 225(07):549-556

  21. Thuy, T. (2022). Online Learning – Future Education Trend. https://alphaacademy.edu.vn/hoc-truc-tuyen-xu-huong-giao-duc-cua-tuong-lai/

  22. Trinh, V. (2012), Some issues related to E-learning, Journal of Science – University of Education,Ho Chi Minh city, vol. 40, no. 86, pp. 86-90.

  23. Shih, Y., Fang, K., (2004), The use of a decomposed theory of planned behavior to study Internet banking in Taiwan, Internet Research, Vol. 14 Issue: 3, pp.213-223,

  24. Shi, H., (2004), Extended technology acceptance model of internet utilization behavior. Inf. Manag. 41(6), 719–729 (2004)

  25. Venkatesh, V., and F.D. Davis (2000), A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, Management Science 46(2), pp. 186-204

  26. Viswanath Venkatesh, Michael G. Moris, Gordon B. Davis, and Fred D (2003), User Acceptance of Information Technology: Toward a Unified View, September 2003, MIS Quarterly 27(3):425-478, DOI:10.2307/30036540