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Understanding Students' Resistance to Continue Using Online Learning

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Abstract

Previous Online Learning (OL) studies have provided significant insights into why students would adopt or use OL but far less attention has been directed towards understanding why they would reject or resist continuing to use OL. The capability of OL to simulate the learning process to be equivalent to classroom learning remains an unresolved theoretical and pragmatic conundrum. This study is conducted to investigate the factors that affect students’ resistance to continue using OL and proposes a novel model based on the Process Virtualization Theory (PVT). The PVT investigates the amenability or the resistance of a process to be migrated from the physical to the virtual environment and can predict whether a process is conducive to or resistive to being carried out virtually. The study model was validated using structural equation modeling against data obtained from 563 undergraduate students through an online survey. The results revealed that sensory requirements, relationship requirements, synchronism requirements, and monitoring capability significantly increase students’ resistance to continue use OL. A significant negative impact of representation capability on students’ resistance to using OL was found while reach capability impact was insignificant. The significant factors collectively explain 71.6 % of the variance in students’ resistance. The study is among the first that concentrates on students’ resistance, in which it defies the predominant focus on students’ adoption or use in OL literature. The practically application of PVT contributes to enrich both academics and practitioners insights into a novel set of factors that affect students’ resistance that are rarely considered in the context of OL, particularly during the later stages of OL implementation.

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Data availability

The datasets generated during and/or analysed during the current study are available in Google Drive at https://drive.google.com/drive/folders/1DBn_ezonmjw-bUAngPWZX_c37BDOJ0o2z?usp=sharing

References

  • Aboagye, E., Yawson, J. A., & Appiah, K. N. (2021). COVID-19 and E-learning: The challenges of students in tertiary institutions. Social Education Research, 2(1), 1–8.

    Google Scholar 

  • Adnan, M., & Anwar, K. (2020). Online Learning amid the COVID-19 Pandemic: Students’ Perspectives. Online Submission, 2(1), 45–51.

    Google Scholar 

  • Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1, 100011.

    Article  Google Scholar 

  • Aini, Q., Budiarto, M., Putra, P. O. H., & Rahardja, U. (2020). Exploring e-learning challenges during the global COVID-19 pandemic: A review. Jurnal Sistem Informasi, 16(2), 57–65.

    Article  Google Scholar 

  • Al Hosni, B., Naidu, V. R., & Al Mandhari, S. (2023). Support for students with Special needs during and after the COVID-19 pandemic through E-learning: A Case Study. In SHS Web of Conferences (Vol. 156, p. 06004). EDP Sciences.

    Google Scholar 

  • Alarabiat, A., Hujran, O., Soares, D., & Tarhini, A. (2023). Examining students’ continuous use of online learning in the post-COVID-19 era: An application of the process virtualization theory. Information Technology & People, 36(1), 21–47. https://doi.org/10.1108/ITP-02-2021-0142

    Article  Google Scholar 

  • Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2018). Technology Acceptance Model in M-learning context: A systematic review. Computers & Education, 125, 389–412.

    Article  Google Scholar 

  • Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86.

    Article  Google Scholar 

  • Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 1.

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411.

    Article  Google Scholar 

  • Balci, B., Bedué, P., & Franzmann, D. (2013a). Online Or Offline, What Do You Prefer? Pre-Test of Measurement Scales for Empirical Analysis. In Proceedings of the AIS Special Interest Group on Adoption and Diffusion of Information Technology (SIGADIT) Workshop.

    Google Scholar 

  • Balci, B., Grgecic, D., & Rosenkranz, C. (2013b). Why People Reject or Use Virtual Processes: A Test of Process Virtualization Theory. In Proceedings of the Nineteenth Americas Conference on Informations Systems (AMCIS) (pp. 1–8) http://elibrary.aisnet.org/Default.aspx?url=https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1523&context=amcis2013

    Google Scholar 

  • Barrot, J. S., Llenares, I. I., & del Rosario, L. S. (2021). Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines. Education and Information Technologies, 26(6), 7321–7338. https://doi.org/10.1007/s10639-021-10589-x

    Article  Google Scholar 

  • Barth, M., & Veit, D. (2011). Which Processes Do Users Not Want Online? Extending Process Virtualization Theory.

    Google Scholar 

  • Bedenlier, S., Wunder, I., Gläser-Zikuda, M., Kammerl, R., Kopp, B., Ziegler, A., & Händel, M. (2021). Generation invisible? Higher Education Students’ (Non) Use of Webcams in Synchronous Online Learning. International Journal of Educational Research Open, 2, 100068.

    Article  Google Scholar 

  • Bizzo, E. (2021). Acceptance and resistance to e-learning adoption in developing countries: A literature review. Avaliação e Políticas Públicas Em Educação.

    Google Scholar 

  • Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216.

    Article  Google Scholar 

  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.

    Google Scholar 

  • Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online Teaching and Learning in Higher Education during the Coronavirus Pandemic: Students’ Perspective. Sustainability, 12(24). https://doi.org/10.3390/su122410367

  • Day, T., Chang, I.-C. C., Chung, C. K. L., Doolittle, W. E., Housel, J., & McDaniel, P. N. (2021). The immediate impact of COVID-19 on postsecondary teaching and learning. The Professional Geographer, 73(1), 1–13.

    Article  Google Scholar 

  • Distel, B. (2020). Assessing citizens’ non-adoption of public e-services in Germany. Information Polity, 25(3), 339–360.

    Article  Google Scholar 

  • Dung, D. T. H. (2020). The advantages and disadvantages of virtual learning. IOSR Journal of Research & Method in Education, 10(3), 45–48.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  • Franque, F. B., Oliveira, T., Tam, C., & de Oliveira Santini, F. (2020). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 1–36. https://doi.org/10.1108/INTR-03-2019-0103

    Article  Google Scholar 

  • Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 5.

    Google Scholar 

  • Graupner, E., & Maedche, A. (2015). Process digitisation in retail banking: An empirical examination of process virtualization theory. International Journal of Electronic Business, 12(4), 364–379.

    Article  Google Scholar 

  • 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).

  • 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.

    Article  Google Scholar 

  • Jaoua, F., Almurad, H. M., Elshaer, I. A., & Mohamed, E. S. (2022). E-learning success model in the context of COVID-19 pandemic in higher educational institutions. International Journal of Environmental Research and Public Health, 19(5), 2865.

    Article  Google Scholar 

  • Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64, 611–630.

    Article  Google Scholar 

  • Kaufmann, R., & Vallade, J. I. (2020). Exploring connections in the online learning environment: Student perceptions of rapport, climate, and loneliness. Interactive Learning Environments, 1–15.

  • Kosinski, M., Matz, S. C., Gosling, S. D., Popov, V., & Stillwell, D. (2015). Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines. American Psychologist, 70(6), 543.

    Article  Google Scholar 

  • Laumer, S., & Eckhardt, A. (2012). Why do people reject technologies: A review of user resistance theories. Information Systems Theory, 1, 63–86.

    Google Scholar 

  • Luu, T. M. V. (2022). Readiness for Online Learning: Learners’ Comfort and Self-Directed Learning Ability. International Journal of TESOL & Education, 2(1), 213–224.

    Article  MathSciNet  Google Scholar 

  • Malik, S., & Rana, A. (2020). E-Learning: Role, advantages, and disadvantages of its implementation in higher education. JIMS8I-International Journal of Information Communication and Computing Technology, 8(1), 403–408.

    Article  Google Scholar 

  • Means, B., & Neisler, J. (2021). Teaching and learning in the time of COVID: The student perspective. Online Learning, 25(1).

  • Muqtadiroh, F. A., Nisafani, A. S., Saraswati, R. M., & Herdiyanti, A. (2019). Analysis of user resistance towards adopting e-learning. Procedia Computer Science, 161, 123–132.

    Article  Google Scholar 

  • Muthuprasad, T., Aiswarya, S., Aditya, K. S., & Jha, G. K. (2021). Students’ perception and preference for online education in India during COVID -19 pandemic. Social Sciences & Humanities Open, 3(1), 100101. https://doi.org/10.1016/j.ssaho.2020.100101

    Article  Google Scholar 

  • Nassr, R. M., Aborujilah, A., Aldossary, D. A., & Aldossary, A. A. A. (2020). Understanding Education Difficulty During COVID-19 Lockdown: Reports on Malaysian University Students’ Experience. IEEE Access, 8, 186939–186950.

    Article  Google Scholar 

  • Ofoeda, J., Boateng, R., & Asmah, A. (2018). Virtualization of government-to-citizen engagement process: Enablers and constraints. Electronic Journal of Information Systems in Developing Countries, 84(5), 1–16. https://doi.org/10.1002/isd2.12037

    Article  Google Scholar 

  • Overby, E. (2008). Process virtualization theory and the impact of information technology. Organization Science, 19(2), 277–291.

    Article  Google Scholar 

  • Overby, E. (2012). Migrating processes from physical to virtual environments: Process virtualization theory. In Information systems theory (pp. 107–124). Springer.

    Chapter  Google Scholar 

  • Overby, E., Slaughter, S. A., & Konsynski, B. (2010). Research commentary—The design, use, and consequences of virtual processes. Information Systems Research, 21(4), 700–710.

    Article  Google Scholar 

  • Rajab, M. H., & Soheib, M. (2021). Privacy concerns over the use of webcams in online medical education during the COVID-19 pandemic. Cureus, 13(2).

  • Sarker, M. F. H., Al Mahmud, R., Islam, M. S., & Islam, M. K. (2019). Use of e-learning at higher educational institutions in Bangladesh: Opportunities and challenges. Journal of Applied Research in Higher Education, 11(2), 210–223.

    Article  Google Scholar 

  • Sarwar, H., Akhtar, H., Naeem, M. M., Khan, J. A., Waraich, K., Shabbir, S., Hasan, A., & Khurshid, Z. (2020). Self-reported effectiveness of e-Learning classes during COVID-19 pandemic: A nation-wide survey of Pakistani undergraduate dentistry students. European. Journal of Dentistry, 14(S 01), S34–S43.

    Google Scholar 

  • Schnee, D., Ward, T., Philips, E., Torkos, S., Mullakary, J., Tataronis, G., & Felix-Getzik, E. (2019). Effect of live attendance and video capture viewing on student examination performance. American Journal of Pharmaceutical Education, 83(6).

  • Schwenck, C. M., & Pryor, J. D. (2021). Student perspectives on camera usage to engage and connect in foundational education classes: It’s time to turn your cameras on. International Journal of Educational Research Open, 2, 100079. https://doi.org/10.1016/j.ijedro.2021.100079

    Article  Google Scholar 

  • Sekaran, U., & Bougie, R. (2010). Research Methods for Business: A Skill Building Approach. John Wiley & Sons.

    Google Scholar 

  • Sharma, M. (2021). SOCMS: Smart online class monitoring system. Journal of Statistics and Management Systems, 24(2), 251–261.

    Article  Google Scholar 

  • Singh, V., & Thurman, A. (2019). How Many Ways Can We Define Online Learning? A Systematic Literature Review of Definitions of Online Learning (1988-2018). American Journal of Distance Education, 33(4), 289–306. https://doi.org/10.1080/08923647.2019.1663082

    Article  Google Scholar 

  • Stevens, J. P. (2012). Applied multivariate statistics for the social sciences (Fifth). Routledge.

    Book  Google Scholar 

  • Stewart, W. H., & Lowenthal, P. R. (2022). Distance education under duress: A case study of exchange students’ experience with online learning during the COVID-19 pandemic in the Republic of Korea. Journal of Research on Technology in Education, 54(sup1), S273–S287.

    Article  Google Scholar 

  • Suryaman, M., Cahyono, Y., Muliansyah, D., Bustani, O., Suryani, P., Fahlevi, M., & Munthe, A. (2020). COVID-19 pandemic and home online learning system: Does it affect the quality of pharmacy school learning. Systematic Reviews in Pharmacy, 11(8), 524–530.

    Google Scholar 

  • Thomas, M., Costa, D., & Oliveira, T. (2016). Assessing the role of IT-enabled process virtualization on green IT adoption. Information Systems Frontiers, 18(4), 693–710.

    Article  Google Scholar 

  • Valverde-Berrocoso, J., Garrido-Arroyo, M. D. C., Burgos-Videla, C., & Morales-Cevallos, M. B. (2020). Trends in Educational Research about e-Learning: A Systematic Literature Review (2009–2018). Sustainability, 12(12), 5153.

    Article  Google Scholar 

  • Venkatesh, V., Thong, J. Y., Chan, F. K., Hu, P. J., & Brown, S. A. (2011). Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527–555. https://doi.org/10.1111/j.1365-2575.2011.00373.x

    Article  Google Scholar 

  • Williams, C., & Pica-Smith, C. (2022). Camera Use in the Online Classroom: Students’ and Educators’ Perspectives. European Journal of Teaching and Education, 4(2), 28–51.

    Article  Google Scholar 

  • Yan, M., Filieri, R., & Gorton, M. (2021). Continuance intention of online technologies: A systematic literature review. International Journal of Information Management, 58, 102315. https://doi.org/10.1016/j.ijinfomgt.2021.102315

    Article  Google Scholar 

  • Zikmund, W., Babin, B., Carr, J., & Griffin, M. (2013). Business research methods. Cengage Learning.

    Google Scholar 

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Funding

The authors did not receive support from any organization for the submitted work.

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Authors and Affiliations

  1. Department of Management Information Systems, Amman College for Financial and Managerial Science, Al-Balqa’ Applied University, P.O. Box 206, Al-, Salt, 19117, Jordan

    Ayman Alarabiat

  2. Department of Statistics and Business Analytics, College of Business and Economics, United Arab Emirates University, Al Ain, 15551, United Arab Emirates

    Omar Hujran

  3. Department of Software Engineering, Faculty of Information Technology, Isra University, Amman, Jordan

    Dimah Al-Fraihat

  4. Department of Management Information Systems, School of Business, Mutah University, Al-Karak, Jordan

    Ali Aljaafreh

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  1. Ayman Alarabiat
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  2. Omar Hujran
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  3. Dimah Al-Fraihat
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  4. Ali Aljaafreh
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Contributions

Ayman Alarabiat: Conceptualization, Methodology, Writing – original draft, Writing – review & editing, Supervision. Omar Hujran: Concep-tualization, Methodology, Writing – review & editing. Dimah Al-Fraihat: Formal analysis, Visualization, Validation, Writing – review & editing. Ali Aljaafreh: Formal analysis, Validation, Data curation. All authors read and approved the final manuscript.

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Correspondence to Ayman Alarabiat.

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Table 7 Cross loadings for latent constructs
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Alarabiat, A., Hujran, O., Al-Fraihat, D. et al. Understanding Students' Resistance to Continue Using Online Learning. Educ Inf Technol 29, 5421–5446 (2024). https://doi.org/10.1007/s10639-023-12030-x

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