Exploring University Students’ Online Learning Readiness: A Mixed Methods Study of Forced Online Learning
Abstract
Background: Despite the advancement achieved in previous research into online learning, few studies have used both quantitative and qualitative data to examine how students’ readiness to learn online is affected by three different external factors, comprising (i) the degrees to which technology is available to students, (ii) the support provided by the institutions of learning, and (iii) the social influence affecting the students engaged in forced online learning in a pandemic situation.
Purpose: To fill this research gap, this study explored university students’ forced online learning readiness in relation to technological accessibility, institutional support and social influence during a pandemic, in an attempt to furnish insights into how educators can maximize the benefits of adopting online learning methods.
Method: A mixed methods research design was employed in this study. Quantitative data, elicited via self-administered questionnaires completed by 211 participants, was analyzed using the frequencies, means, standard deviations and Pearson correlation analysis involving the Statistical Package for the Social Sciences (SPSS) software version 27. Qualitative data, elicited via 11 open-ended questions posed to 41 students through in-depth interviews, was then studied using a thematic analysis of the participants’ feedback concerning the three constructs in online learning.
Results: Our quantitative analysis showed that institutional support had the strongest positive correlation with online learning readiness, and this was followed by technology accessibility and social influence in relation to students’ readiness to learn online. Qualitative findings further indicated that students were largely concerned about Internet accessibility and the setting where their roles were restricted to being mere listeners in online sessions. Apart from being apprehensive about excessive online assignments, students also acknowledged that their online interactions were influenced by their friends and family members, and they would prefer practical work that could inspire them to reflect and engage actively with the course material given during the pandemic.
Conclusion: While lecturers can make online classes more interactive and discussion-generative, university administrators need to aptly facilitate their institution’s transition to the forced online learning mode, moderate social influence, improve the learning management system, and provide training to teachers and students on the use of emerging technology.
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References
Adnan, M., & Anwar, K. (2020). Online learning amid the COVID-19 pandemic: Students' perspectives. Journal of Pedagogical Sociology and Psychology, 2(1), 45-51,
Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Education Research Open, 1, 1-8.
Ahmad, N., Umar, N., & Kadar, R., & Othman, J. (2020). Factors affecting students' acceptance of e-learning system in higher education. Journal of Computing Research and Innovation (JCRINN), 5(2), 54-65.
Al-Ammary, J. H., Al-Sherooqi, A. K., & Al-Sherooqi, H. K. (2014). The acceptance of social networking as a learning tool at University of Bahrain. International Journal of Information and Education Technology, 4(2), 208-214.
Albrecht, J. R., & Karabenick, S.A. (2018). Relevance for learning and motivation in education. The Journal of Experimental Education, 86(1), 1-10.
Alkis, N., Coskunçay, D. F., & Yildirim, S. Ö. (2014). A systematic review of technology acceptance model in e-Learning context. In Proceedings of the XV International Conference on Human Computer Interaction, article no. 55, 1-5. ACM.
Allen, I., & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States, 2002-2003. Needham, MA: Sloan.
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, 25, 5261-5280.
Al-Shehri A. M. (2010). E-learning in Saudi Arabia: “To E or not to E, that is the question”. Journal of Family and Community Medicine, 17(3), 147–150.
Azlan, C. A., Wong, J.H.D., Tan, L.K., Nizam, M. S., Huri, D.,Ung, N.M., Pallath, V., Tan, C.P.L., Yeong, C. H., & Ng, K. H.(2020).Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic – A case study from Malaysia. Physica Medica, 80, 10–16.
Baber, H. (2021). Modelling the acceptance of e-learning during the pandemic of COVID-19-A study of South Korea. The International Journal of Management Education, 19(2), 100503.
Betlej, P. (2013). E-examinations from student's perspective – The future of knowledge evaluation. Studia Ekonomiczne,152, 9–22.
Bowen, J. A. (2012). Teaching naked: How moving technology out of your college classroom will improve student learning. Jossey-Bass.
Britt, R. (2006). Online education: A survey of faculty and students. Radiologic Technology, 77(3), 183-190.
Buzzetto-More, N. (2013). Models to inform capstone program development. Issues in Informing Science and Information Technology, 10(1), 81-93.
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J. & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative and mixed methods approaches (5th ed.). Sage.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
De Luca, K., McDonald, M., Montgomery, L., Sharp, S., Young, A. ,Vella,S., Holmes, M. M., Aspinall, S., Brousseau,D., Burrell1,C., Byfield, D., Dane, D., Dewhurst,P., Downie, A., Engel, R., Gleberzon, B., Hollandsworth, D., Nielsen, A. M., O’Connor,L., Starmer,D., Tunning, M., Wanlass, P., & French, S. D. (2021). COVID-19: How has a global pandemic changed manual therapy technique education in chiropractic programs around the world? Chiropractic & Manual Therapies, 29(7), 1-11.
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology, 49(1), 5-22.
Dogruera , N., Eyyamb, R., & Menevis, I. (2011). The use of the Internet for educational purposes. Procedia - Social and Behavioral Sciences. 28, 606 – 611.
Elkaseh, A. M., Wong, K. W., & Fung, C. C. (2015). The acceptance of e-learning as a tool for teaching and learning in Libyan higher education. IPASJ International Journal of Information Technology (IIJIT), 3(4), 1–11.
Farahat, T. (2012). Applying the technology acceptance model to online learning in the Egyptian universities. Procedia-Social and Behavioral Sciences, 64, 95–104.
Favale, T., Soro, F., Trevisan, M., Drago, I., & Mellia, M. (2020). Campus traffic and e learning during COVID-19 pandemic. Computer Networks, 176, 107290.
Ferri, F., Grifoni,P., & Guzzo, T. (2020). Online learning and emergency remote teaching: Opportunities and challenges in emergency situations. Societies, 10 (4), 1-18.
Fitzpatrick, T. (2012). Key success factors of e-learning in education: A professional development model to evaluate and support e-learning. US-China Education Review A, 9, 789-795.
Gherghel, C., Yasuda, S., & Kita, Y. (2023). Interaction during online classes fosters engagement with learning and self-directed study both in the first and second years of the COVID-19 pandemic. Computers & Education, 200, Article 104795.
Golladay, R., Prybutok, V., & Huff, R. (2000). Critical success factors for the online learner. Journal of Computer Information Systems, 40(4), 69-71.
Graham, C. R., & Dziuban, C. (2008). Blended learning environments. In M. J. Bishop (Ed.), Handbook of research on educational communications and technology (pp. 269-276). Lawrence Erlbaum Associates.
Greenhow, C. (2011). Online social networking and learning. International Journal of Cyber Behavior, Psychology and Learning, 1(1), 36–50.
Hai, L. C., & Kazmi, S. H. A. (2015). Dynamic support of government in online shopping. Asian Social Science, 11(22), 1-9.
Hara, N. & Kling, R. (2000). Students’ distress with a web-based distance education course: An ethnographic study of participants’ experiences. Information, Communication and Society, 3(4), 557-579.
Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Retrieved from . Accessed May 1, 2020.
Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343–367.
Hoss, T., Ancina, A., & Kaspar, K. (2021). Forced remote learning during the COVID-19 pandemic in Germany: A mixed-methods study on students’ positive and negative expectations. Frontiers in Psychology, 12, 1-9.
Jaffar, M. N., Mahmud, N. H., Amran, M. F. Abdul Rahman, M. H., Abd Aziz, N. H. & Moh, M. A. C. (2022). Online learning and teaching technology services: USIM’s experience during COVID-19 pandemic. Frontiers in Education, 7, 1-7.
Khan, S. & Khan, R. A. (2019). Online assessments: Exploring perspectives of university students. Education and Information Technologies, 24, 661-677.
Kuriakose, R. B., & Luwes, N. (2016). Student perceptions to the use of paperless technology in assessments– a case study using clickers. Procedia - Social and Behavioral Sciences, 228, 78–85.
Laugasson, E., Quaicoe, J. S., Jeladze, E., & Jesmin, T. (2016). Bridging digital divide in schools in developing countries: Perceptions of teachers of free software opportunities. In International Conference on Learning and Collaboration Technologies (pp. 695-706). Springer.
Lee, J., & Jung, I. (2021). Instructional changes instigated by university faculty during the COVID19 pandemic: The effect of individual, course and institutional factors. International Journal of Educational Technology in Higher Education, 18, 1–19.
Lee, S. J., Srinivasan, S., Trail, T., Lewis, D., & Lopez, S. (2011). Examining the relationship among studentperception of support, course satisfaction, and learning outcomes in online learning. The Internet and Higher Education, 14(3), 158–163.
Lim, J. (2022). Impact of instructors’ online teaching readiness on satisfaction in the emergency online teaching context. Education and Information Technologies, 28(2), 1-18.
Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors influencing online shopping behavior: The mediating role of purchase intention. Procedia Economics and Finance, 35, 401-410.
Lind, D. A., Marchal, W.G., & Wathen, S. A. (2010). Statistical techniques in business & economics (15th ed.). McGraw-Hill Irwin.
Linjawi, A., & Alfadda, L. S. (2018). Students’ perception, attitudes, and readiness toward online learning in dental education in Saudi Arabia: A cohort study. Advances in Medical Education and Practice, 9, 855-863.
Linjawi, A. I., Walmsley, A. D., & Hill, K. B. (2012). Online discussion boards in dental education: Potential and challenges. European Journal of Dental Education, 16(1), 3-9.
Loyd, B. H., & Gressard, C. (1984). The effects of sex, age, and computer experience on computer attitudes. AEDS Journal, 18(2),
Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: An empirical study in Vietnam. Education and Information Technologies, 26(6), 6629-6649.
Mailizar, Almanthari, A., Maulina, S., & Bruce, S. (2020). Secondary school mathematics teachers’ views on e-learning implementation barriers during the Covid-19 pandemic: The case of Indonesia. Eurasia Journal of Mathematics, Science and Technology Education, 16(7), em1860.
Mills, G. E., & Gay, L. R. (2019). Educational research: Competencies for analysis and applications (12th ed.). Pearson Education.
Mukhtar, K., Javed, K., Arooj, M., & Sethi, A. (2020). Advantages, limitations and recommendations for online learning during COVID-19 pandemic era. 36(COVID19-S4):COVID19-S27-S31.
Murphy, M. P. A. (2020). COVID-19 and emergency eLearning: Consequences of the securitization of higher education for post pandemic pedagogy. Contemporary Security Policy, 41(3), 492-505.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
Odriozola-Gonz´alez, P., Planchuelo-G´omez. ´A., Irurtia, M. J., & de Luis-García, R. (2020). Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university. Psychiatry Research, 290, 113108.
Pedro, N. S., & Kumar, S. (2020). Institutional support for online teaching in quality assurance frameworks. Online Learning, 24(3), 50-66.
Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25(4), 401-425.
Reyes-Millan, M., Villareal-Rodríguez, M., Murrieta-Flores, M. E., Bedolla-Cornejo, L., Vazquez-Villegas, P., & Membrillo-Hernandez, J. (2023). Evaluation of online learning readiness in the new distance learning normality. Heliyon, 9, e22070.
Ryan, S. (2001). Is online learning right for you? American Agent & Broker, 73(6), 54-58.
Saafin, S. (2008). Arab tertiary student perceptions of effective teachers. Learning and Teaching in Higher Education: Gulf Perspectives, 5(2), 1–11.
Salloum, S. A. (2018). Investigating students’ acceptance of e-learning system in higher educational environments in the UAE: Applying the extended Technology Acceptance Model (TAM) [Masters dissertation ]. The British University, Dubai.
Scherer, R., Howard, S. K., Tondeur, J., & Siddiq, F.(2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in Human Behaviour, 118, 106675.
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.
Tabang, M. P., & Caballes, D. G. (2022). Grade 10 students’ online learning readiness and e-learning engagement in a science high school during pandemic. International Journal of Humanities and Education Development (IJHED), 4(3), 237–241.
Tuntirojanawong, S. (2013). Students’ readiness for e-learning: A case study of Sukhothai Tammathirat Open University, Thailand. Journal of Learning in Higher Education. 9(1),59-66.
Veletsianos, G., & Navarrete, C. (2012). Online social networks as formal learning environments: Learner experiences and activities. The International Review of Research in Open and Distributed Learning, 13(1), 144-166.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Webb, A., McQuaid, R.W., & Webster, C.W.R. (2021). Moving learning online and the COVID-19 pandemic: A university response. World Journal of Science, Technology and Sustainable Development, 18(1), pp. 1-19.
Yukselturk, E., & Yildirim, Z. (2008). Investigation of interaction, online support, course structure and flexibility as the contributing factors to students’ satisfaction in an online certificate program. Journal of Educational Technology & Society, 11(4), 51–65.
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