E-learning Satisfaction during the Covid -19 Epidemic: Evidence from a Vietnam-based Law School
Keywords:Technology Acceptance Model (TAM), Delone and Mclean IS Success (D&M ISS), Learner Satisfaction
The purpose of this research is to investigate the association between system, information, service quality, perceived ease of use, perceived usefulness, and learner satisfaction with e-learning in Vietnam during the Covid-19 era. The research collected 612 answers from current law students at Ho Chi Minh University of Law using a questionnaire-based survey and sampling by convenience. To validate the hypotheses, structural equation modeling was used. Except for the association between system quality and learner satisfaction, all quality factors were shown to positively impact learner satisfaction. In addition, the present research demonstrated that perceived usability and value moderate the link between quality and students' partial and complete satisfaction. This is the first research to examine the relationship between perceived ease of use, perceived usefulness, and student happiness in a platform-based setting. In addition, this research has major implications for education administrators who want to successfully retain students by bolstering the elements that contribute to student satisfaction with online learning.
Akyol, Z., & Garrison, D. R. (2011). Assessing metacognition in an online community of inquiry. The Internet and Higher Education, 14(3), 183-190. https://doi.org/10.1016/j.iheduc.2011.01.005
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. https://doi.org/10.1037/0033-2909.103.3.411
Baber, H. (2020). Determinants of students’ perceived learning outcome and satisfaction in online learning during the pandemic of COVID-19. Journal of Education and e-Learning Research, 7(3), 285-292. DOI: 10.20448/journal.509.2020.73.285.292
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: personal computer adoption ans use as an Illustration. DOI: 10.4236/ti.2011.21002
Burke, S. C., Snyder, S., & Rager, R. C. (2009). An assessment of faculty usage of YouTube as a teaching resource. Internet Journal of Allied Health Sciences and Practice, 7(1), 8. DOI: 10.46743/1540-580X/2009.1227
Chen, H.-R., & Tseng, H.-F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398-406. https://doi.org/10.1016/j.evalprogplan.2011.11.007
Chow, M., Herold, D. K., Choo, T.-M., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use Second Life for enhancing healthcare education. Computers & Education, 59(4), 1136-1144. https://doi.org/10.1063/1.5005405
Chow, W. S., & Shi, S. (2014). Investigating students’ satisfaction and continuance intention toward e-learning: An Extension of the expectation–confirmation model. Procedia-Social and Behavioral Sciences, 141, 1145-1149. https://doi.org/10.1177/21582440211059181
Cidral, W. A., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273-290. https://doi.org/10.1016/j.compedu.2017.12.001
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340. https://doi.org/10.2307/249008
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95. DOI:10.1080/07421222.2003.11045748
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30. https://doi.org/10.1080/07421222.2003.11045748
DeLone, W. H., & McLean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International journal of electronic commerce, 9(1), 31-47. https://doi.org/10.1080/10864415.2004.11044317
DeLone, W. H., & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 1-116. DOI: 10.12691/ajis-7-1-2
Dixson, M. D. (2010). Creating Effective Student Engagement in Online Courses: What Do Students Find Engaging? Journal of the Scholarship of Teaching and Learning, 10(2), 1-13. DOI: 10.4236/ojbm.2019.74115
Estriegana, R., Medina-Merodio, J.-A., & Barchino, R. (2019). Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Computers & Education, 135, 1-14. https://doi.org/10.1016/j.compedu.2019.02.010
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.2307/3151312
Gable, G. G., Sedera, D., & Chan, T. (2008). Re-conceptualizing information system success: The IS-impact measurement model. Journal of the association for information systems, 9(7), 18. DOI:10.17705/1JAIS.00164
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of management information systems, 18(1), 185-214. DOI:10.1080/07421222.2001.11045669
Hair, J. F., Black, W. C., Babin, B. J., & Tatham, R. L. (2010). Multivariate Data Analysis. Seventh Edition. In: Pearson Education, Inc.
Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling: saGe publications.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Islam, A. N. (2013). Investigating e-learning system usage outcomes in the university context. Computers & Education, 69, 387-399. https://doi.org/10.1016/j.compedu.2013.07.037
Kannan, V. R., & Tan, K. C. (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33(2), 153-162. https://doi.org/10.1016/j.omega.2004.03.012
Kline, R. B. (2015). Principles and practice of structural equation modeling: Guilford publications.
Lewnard, J. A., & Lo, N. C. (2020). Scientific and ethical basis for social-distancing interventions against COVID-19. The Lancet infectious diseases, 20(6), 631-633. DOI: 10.1016/S1473-3099(20)30190-0
Liaw, S.-S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864-873. https://doi.org/10.1016/j.compedu.2007.09.005
Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374. https://doi.org/10.1016/j.chb.2014.07.044
Moorhouse, B. L. (2020). Adaptations to a face-to-face initial teacher education course ‘forced’online due to the COVID-19 pandemic. Journal of Education for Teaching, 46(4), 609-611. https://doi.org/10.1080/02607476.2020.1755205
Nguyen, T. K., & Nguyen, T. H. T. (2021). The Acceptance and Use of Video Conferencing for Teaching in Covid-19 Pandemic: An Empirical Study in Vietnam. AsiaCALL Online Journal, 12(5), 1-16. https://asiacall.info/acoj/index.php/journal/article/view/77
Ozkan, S., & Koseler, R. (2009). Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53(4), 1285-1296. https://doi.org/10.1016/j.compedu.2009.06.011
Pham, M. T., Luu, T. T. U., Mai, T. H. U., Thai, T. T. T., & Ngo, T. C. T. (2022). EFL Students’ Challenges of Online Courses at Van Lang University during the COVID-19 Pandemic. International Journal of TESOL & Education, 2(2), 1-26. https://doi.org/10.54855/ijte.22221
Pham, N. T., & Van Nghiem, H. (2022). Online Teaching Satisfaction amid the Covid-19 Pandemic: Evidence from a Vietnamese Higher Education Context. International Journal of TESOL & Education, 2(1), 310-326. https://doi.org/10.54855/ijte.222119
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet research. http://dx.doi.org/10.1108/10662240410542652
Preacher, K. J., & Hayes, A. F. (2008). Assessing mediation in communication research: The Sage sourcebook of advanced data analysis methods for Communication Research (pp. 13-54). Thousand Oaks, CA: Sage. https://doi.org/10.4135/9781452272054.n2
Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information systems research, 13(1), 50-69. http://dx.doi.org/10.1287/isre.126.96.36.199
Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling: psychology press.
Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information systems research, 8(3), 240-253. https://doi.org/10.1287/isre.8.3.240
Sedera, D., Gable, G., & Chan, T. (2004). A factor and structural equation analysis of the enterprise systems success measurement model. Paper presented at the Proceedings of the 10th Americas Conference on Information Systems. https://aisel.aisnet.org/amcis2004/94
Sullivan, G. M., & Feinn, R. (2012). Using effect size—or why the P-value is not enough. Journal of graduate medical education, 4(3), 279-282. DOI: 10.4300/JGME-D-12-00156.1
Šumak, B., Heričko, M., & Pušnik, M. (2011). A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types. Computers in Human Behavior, 27(6), 2067-2077. https://doi.org/10.1016/j.chb.2011.08.005
Sun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (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
Tran, Q. H., & Nguyen, T. M. (2022). Determinants in Student Satisfaction with Online Learning: A Survey Study of Second-Year Students at Private Universities in HCMC. International Journal of TESOL & Education, 2(1), 63-80. https://doi.org/10.54855/ijte22215
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478. https://doi.org/10.2307/30036540
Zhang, Q., & Zhu, W. (2008). Exploring emotion in teaching: Emotional labor, burnout, and satisfaction in Chinese higher education. Communication Education, 57(1), 105-122. https://doi.org/10.1080/03634520701586310
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