Các yếu tố ảnh hưởng đến hiệu quả đào tạo trực tuyến tại Trường Đại học Nguyễn Tất Thành
Tóm tắt
Research on the effectiveness of online training is an urgent matter for higher education institutions. To provide concrete evidence, the author's team conducted a study and analyzed the factors influencing effectiveness, proposing several solutions to enhance it at Nguyen Tat Thanh University. The results of surveying 393 students, assessed using Smart PLS software to measure their impact, revealed that all four factors - teacher quality, system quality, content quality, and support quality - influence student satisfaction. However, only the system quality factor (online training website) directly affects learning outcomes. The other factors indirectly affect student learning outcomes through student satisfaction. This implies that, in terms of policy, the university should invest in improving the quality of the online training website system and enhancing the quality of teachers and support staff to increase student satisfaction and improve student learning outcomes.
Tài liệu tham khảo
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67-86. http://dx.doi.org/10.1016/j.chb.2019.08.004
Boulding, W., Kalra, A., Staelin, R., & Zeithaml, V. A. (1993). A dynamic process model of service quality: from expectations to behavioral intentions. Journal of Marketing Research, 30(1), 7-27. https://doi.org/10.1177/002224379303000102
Chopra, G., Madan, P., Jaisingh, P., & Bhaskar, P. (2019). Effectiveness of E-learning portal from students’ perspective: A structural equation model (SEM) approach. Interactive Technology and Smart Education, 16(2), 94-116. https://doi.org/10.1108/ITSE-05-2018-0027
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.2307/3150980
Garson, G. D. (2016). Partial least squares: Regression & structural equation models. Statistical Associates Publishing.
Gudigantala, N., Song, J., & Jones, D. (2011). User satisfaction with Web-based DSS: The role of cognitive antecedents. International Journal of Information Management, 31(4), 327-338. https://doi.org/10.1016/j.ijinfomgt.2010.10.009
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications. http://dx.doi.org/10.1007/978-3-030-80519-7
Hock, C., Ringle, C. M., & Sarstedt, M. (2010). Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International Journal of Services Technology and Management, 14(2-3), 188-207. http://dx.doi.org/10.1504/IJSTM.2010.034327
Islam, A. K. M. (2012). The role of perceived system quality as educators’ motivation to continue E-learning system use. AIS Transactions on Human-Computer Interaction, 4(1), 25-43.
Kimathi, F. A., & Zhang, Y. (2019). Exploring the general extended technology acceptance model for E-learning approach on student’s usage intention on E-learning system in University of Dar es Salaam. Creative Education, 10(1), 208-223. http://dx.doi.org/10.4236/ce.2019.101017
Kintu, M. J., Zhu, C., & Kagambe, E. (2017). Blended learning effectiveness: the relationship between student characteristics, design features, and outcomes. International Journal of Educational Technology in Higher Education, 14(1), 1-20. https://doi.org/10.1186/s41239-017-0043-4
Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does E-learning service quality influence E-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1-26. https://doi.org/10.1186/s41239-019-0136-3
Santos, J. (2003). E‐service quality: a model of virtual service quality dimensions. Managing Service Quality: An International Journal, 13(3), 233-246. http://dx.doi.org/10.1108/09604520310476490
Saxena, C., Baber, H., & Kumar, P. (2021). Examining the moderating effect of perceived benefits of maintaining social distance on E-learning quality during COVID-19 pandemic. Journal of Educational Technology Systems, 49(4), 532-554. https://doi.org/10.1177/0047239520977798
Uppal, M. A., Ali, S., & Gulliver, S. R. (2017). Factors determining e‐learning service quality. British Journal of Educational Technology, 49(3), 412-426. https://doi.org/10.1111/bjet.12552
Waight, C. L., & Stewart, B. L. (2005). Valuing the adult learner in e‐learning: Part one–a conceptual model for corporate settings. Journal of Workplace Learning, 17(5/6), 337-345. http://dx.doi.org/10.1108/13665620510606751
Wang, M. (2018). E-Learning in the Workplace (pp. 41-53). Berlin: Springer.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
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