Vietnamese Students’ Barriers to Online Learning during the COVID-19 Pandemic
The paper used the partial least squares structural equation modeling (PLS-SEM) method, which was applied to analyze the data of this study, based on the snowball sampling method, enabling the validation of the barriers related to students’ academic skills, technical skills, motivation, and feelings toward online learning and their influence on students’ academic achievements in online learning environments. The results show some significant impacts of academic skills and students’ feelings toward online learning on their results in online learning environments. These results can be used by decision-makers, and managers in Vietnam’s HEIs to improve the online courses, and lecturers and students can try to improve their skills to produce better results in the future. Besides, scholars can use this study as a source of reference to expand the research onto other factors like administrative/instructor issues, social interactions, time and support for studies, cost and access to the Internet, technical problems, and attain a wider variety of samples from more regions and both public and private sector. The novelty of the results contributes to the practice of students' barriers to online learning in the context of transitioning from face-to-face learning to online learning.
Keywords: online learning, students’ barriers, COVID-19, Vietnam.
ACUTO, M. (2020). COVID-19: Lessons for an Urban(izing) World. One Earth, 2(4), 317–319. https://doi.org/10.1016/j.oneear.2020.04.004
ALJARAIDEH, Y., & AL BATAINEH, K. (2019). Jordanian Students’ Barriers of Utilizing Online Learning: A Survey Study. International Education Studies, 12(5), 99–108. https://doi.org/10.5539/ies.v12n5p99
ARBAUGH, J.B. (2000). Virtual classroom versus physical classroom: An exploratory study of class discussion patterns and student learning in an asynchronous Internet-based MBA course. Journal of Management Education, 24(2), 213–233. https://doi.org/10.1177/105256290002400206
BATICULON, R.E., SY, J.J., ALBERTO, N.R.I., BARON, M.B.C., MABULAY, R.E.C., RIZADA, L.G.T., TIU, C.J.S., CLARION, C.A., & REYES, J.C.B. (2021). Barriers to online learning in the time of COVID-19: A national survey of medical students in the Philippines. Medical Science Educator, 31(2), 615-626. https://doi.org/10.1007/s40670-021-01231-z
BENAVIDES, L.M.C., ARIAS, J.A.T., SERNA, M.D.A., BEDOYA, J.W.B., & BURGOS, D. (2020). Digital transformation in higher education institutions: A systematic literature review. Sensors, 20(11), 3291. https://doi.org/10.3390/s20113291
BOEKAERTS, M., & PEKRUN, R. (2015). Emotions and emotion regulation in academic settings. In: CORNO, L., & ANDERMAN, E. (eds.) Handbook of educational psychology. New York: Routledge, pp. 90–104.
BUI, T.H., LUONG, D.H., NGUYEN, X.A., NGUYEN, H.L., & NGO, T.T. (2020). Impact of female students’ perceptions on behavioral intention to use video conferencing tools in COVID-19: Data of Vietnam. Data in Brief, 32, 106142. https://doi.org/10.1016/j.dib.2020.106142
CHEN, K.C., & JANG, S.J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741–752. https://doi.org/10.1016/j.chb.2010.01.011
DABAJ, F. (2009). The Role of Gender and Age on Students’ Perceptions towards Online Education. Case Study: Sakarya University, Vocational High School. Turkish Online Journal of Educational Technology, 8(2), 120–123. Retrieved from http://tojet.net/articles/v8i2/8211.pdf
ECCLES, J. (1983). Expectance, values, and academic behaviors. In: SPENCE, J.T. (ed.) Achievement and achievement motives: Psychological and social approaches. San Francisco, California: Freeman, pp. 75–146.
FYANS JR., L.J., & MAEHR, M.L. (1987). Sources of Student Achievement: Student Motivation, School Context and Family Background. Urbana-Chapman, Illinois: Illinois State Board of Education and University of Illinois.
GARCÍA-HERMOSO, A., SAAVEDRA, J.M., OLLOQUEQUI, J., & RAMÍREZ-VÉLEZ, R. (2017). Associations between the duration of active commuting to school and academic achievement in rural Chilean adolescents. Environmental Health and Preventive Medicine, 22(1), 31. https://doi.org/10.1186/s12199-017-0628-5
HAIR, J.F., RISHER, J.J., SARSTEDT, M., & RINGLE, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
HAYASHI, A., CHEN, C., RYAN, T., & WU, J. (2004). The role of social presence and moderating role of computer self efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139–154. Retrieved from https://aisel.aisnet.org/jise/vol15/iss2/5
HO, L.-A., KUO, T.-H., & LIN, B. (2010). Influence of online learning skills in cyberspace. Internet Research, 20(1), 55-71. https://doi.org/10.1108/10662241011020833
HOWLETT, D., VINCENT, T., GAINSBOROUGH, N., FAIRCLOUGH, J., TAYLOR, N., COHEN, J., & VINCENT, R. (2009). Integration of a case-based online module into an undergraduate curriculum: What is involved and is it effective? E-Learning, 6(4), 372–384. https://doi.org/10.2304/elea.2009.6.4.372
JONES, I.S., & BLANKENSHIP, D. (2018). Learning styles, online courses, gender, and academic achievement of Hispanic students in higher education. Research in Higher Education Journal, 35, 1-14. https://www.aabri.com/manuscripts/182830.pdf
KIM, K.-J., & FRICK, T.W. (2011). Changes in student motivation during online learning. Journal of Educational Computing Research, 44(1), 1–23. https://doi.org/10.2190/EC.44.1.a
LAMB, M. (2017). The motivational dimension of language teaching. Language Teaching, 50(3), 301–346. https://doi.org/10.1017/S0261444817000088
LAN, H.T.Q., LONG, N.T., & VAN HANH, N. (2020). Validation of depression, anxiety and stress scales (Dass-21): Immediate psychological responses of students in the e-learning environment. International Journal of Higher Education, 9(5), 125–133. https://doi.org/10.5430/ijhe.v9n5p125
LEPPER, M.R., & CORDOVA, D.I. (1992). A desire to be taught: Instructional consequences of intrinsic motivation. Motivation and Emotion, 16(3), 187–208. http://dx.doi.org/10.1007/BF00991651
MAHESHWARI, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies, 26, 6629–6649. https://doi.org/10.1007/s10639-021-10465-8
MUILENBURG, L.Y., & BERGE, Z.L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26(1), 29–48. http://dx.doi.org/10.1080/01587910500081269
NADLER, R. (2020). Understanding “Zoom fatigue”: Theorizing spatial dynamics as third skins in computer-mediated communication. Computers and Composition, 58, 102613. https://doi.org/10.1016/j.compcom.2020.102613
NURDIN. (2021). Students’ Readiness for E-Learning: A Case Study of Students in Higher Education. Journal of Southwest Jiaotong University, 56(5), 327-339. https://doi.org/10.35741/issn.0258-2718.104.22.168
PANDA, S., & MISHRA, S. (2007). E-Learning in a Mega Open University: Faculty Attitude, Barriers and Motivators. Educational Media International, 44(4), 323–338. http://dx.doi.org/10.1080/09523980701680854
PHAM, H.H., & HO, T.T.H. (2020). Toward a ‘new normal’ with e-learning in Vietnamese higher education during the post COVID-19 pandemic. Higher Education Research & Development, 39(7), 1327–1331. https://doi.org/10.1080/07294360.2020.1823945
RASHEED, R.A., KAMSIN, A., & ABDULLAH, N.A. (2020). Challenges in the online component of blended learning: A systematic review. Computers and Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701
REN, Y., ZHANG, F., JIANG, Y., & HUANG, S. (2020). Family Socioeconomic Status, Educational Expectations, and Academic Achievement among Chinese Rural-to-Urban Migrant Adolescents: The Protective Role of Subjective Socioeconomic Status. The Journal of Early Adolescence, 41(8), 1129–1150. https://doi.org/10.1177/0272431620983459
THI THU DAO, H., & THI KIM LE, T. (2020). Transitioning from Traditional Learning to Blended Learning at Some Public Universities in Vietnam after the Covid-19 Pandemic. Proceedings of the 4th International Conference on Advances in Artificial Intelligence, London, 9-11 October 2020, pp. 85–91. https://doi.org/10.1145/3441417.3441429
TRUNG, T., HOANG, A.D., NGUYEN, T.T., DINH, V.H., NGUYEN, Y.C., & PHAM, H.H. (2020). Dataset of Vietnamese student’s learning habits during COVID-19. Data in Brief, 30, 105682. https://doi.org/10.1016/j.dib.2020.105682
VALLERAND, R.J., & REID, G. (1984). On the causal effects of perceived competence on intrinsic motivation: A test of cognitive evaluation theory. Journal of Sport and Exercise Psychology, 6(1), 94–102. https://doi.org/10.1123/JSP.6.1.94
VIETNAM MINISTRY OF EDUCATION AND TRAINING. (2020). Official Letter No. 795/BGDĐT-GDĐH dated 13/3/2020 about the implementation of distance learning in response to Covid-19. Retrieved from https://moet.gov.vn/van-ban/vbdh/Pages/chi-tiet-van-ban.aspx?ItemID=2668
WORTHA, F., AZEVEDO, R., TAUB, M., & NARCISS, S. (2019). Multiple negative emotions during learning with digital learning environments – Evidence on their detrimental effect on learning from two methodological approaches. Frontiers in Psychology, 10, 2678. https://doi.org/10.3389/fpsyg.2019.02678
YASSINE, F.L.Y.A., MAAITAH, T.A., MAAITAH, D.A., & AL-GASAWNEH, J.A. (2022). Impact of Covid-19 on the University Education System in Jordan. Journal of Southwest Jiaotong University, 57(1), 649-663. https://doi.org/10.35741/issn.0258-2722.214.171.124
ZEELENBERG, M., NELISSEN, R.M., BREUGELMANS, S.M., & PIETERS, R. (2008). On emotion specificity in decision making: Why feeling is for doing. Judgment and Decision Making, 3(1), 18-27. Retrieved from http://www.decisionsciencenews.com/sjdm/journal.sjdm.org/bb2.pdf
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