EXAMINING UNIVERSITY STUDENTS’ BEHAVIOURAL INTENTION TO DISTANCE LEARNING DURING COVID-19: AN EXTENDED TAM MODEL

Learning was obliged to be transformed to distance learning due to the long-lasting COVID-19 lockdown period. This situation has brought to investigate the critical factors influencing students’ intention and actual use of distance learning tools. In this context, this study aims to evaluate the effects of distance learning, deriving independent variables adopted from ETAM. Data was gathered from 92 undergraduate students enrolled in five and other courses in Turkiye. Data were investigated via SmartPLS 3.0 through Structural Equation Modelling (SEM). Results indicate that Computer Anxiety had a negative impact on Self-efficacy. Self-efficacy had a positive influence on Experience. Experience and Enjoyment had positive effects on Perceived Ease of Use. Enjoyment had a positive influence on Perceived Usefulness. The proposed model explained 87.7% of the variance of the actual use of distance learning tools. Computer anxiety and selfefficacy, which were proposed to measure experience, made this study unique and valuable. This contributes to acknowledging higher education institutions and lecturers to understand the benefits and barriers of distance learning tools for students used during the unpredicted pandemics in the future.

Keywords:

Distance learning, Structural equation modelling, Extended technology acceptance model COVID-19,

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Achim, N., & Al Kassim, A. (2015). Computer usage: the impact of computer anxiety and computer self-efficacy. Procedia-Social and Behavioral Sciences, 172, 701-708. https://doi.org/10.1016/j.sbspro.2015.01.422
Anadolu University. (2021). 2021-2022-Academic Year. Retrieved April 30, 2020 from https://anadolu.edu.tr/universitemiz/sayilarla-universitemiz/ogrenci-sayilari/2021-2022/2021-ekim
Bahcesehir University. (2021). Bahcesehi̇r University Starts The Online Classes. Retrieved March 05, 2022, from https://bau.edu.tr/news/15488-bahcesehir-university-starts-the-online-classes
Cacault, M. P., Hildebrand, C., Laurent-Lucchetti, J., & Pellizzari, M. (2021). Distance learning in higher education: Evidence from a randomized experiment. Journal of the European Economic Association, 19(4), 2322-2372. https://doi.org/10.1093/jeea/jvaa060
Chua, S. L., Chen, D.-T., & Wong, A. F. (1999). Computer anxiety and its correlates: A meta-analysis. Computers in Human Behavior, 15(5), 609-623. https://doi.org/10.1016/S0747-5632(99)00039-4
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 189-211. https://doi.org/10.2307/249688
Crawford, J., Butler-Henderson, K., Rudolph, J., Malkawi, B., Glowatz, M., Burton, R., & Lam, S. (2020). COVID-19: 20 countries' higher education intra-period digital pedagogy responses. Journal of Applied Learning &Teaching, 3(1), 1-20. https://doi.org/10.37074/jalt.2020.3.1.7
Da Costa Barreto, L. S., Marañón-Vásquez, G. A., Lopes, R., de Lima, A. M. B., & de Souza, M. M. G. (2020). Distance learning approach in interprofessional higher education, International Journal of Education, 12(4). https://doi.org/10.5296/ije.v12i4.17821
Mundfrom, D. J., Shaw, D. G., & Ke, T. (2005). Minimum sample size recommendations for conducting factor analyses. International Journal of Testing, 5(2), 159-168, https://doi.org/10.1207/s15327574ijt0502_4
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
El Said, G. R. (2021). How did the COVID-19 pandemic affect higher education learning experience? An empirical investigation of learners’ academic performance at a university in a developing country. Advances in Human-Computer Interaction, 2021. https://doi.org/10.1155/2021/6649524
Ferran, F. M. (2021). Extended technology acceptance model to examine the use of Google Forms–based lesson playlist in online distance learning. Recoletos Multidisciplinary Research Journal, 9(1), 147-161. https://doi.org/10.32871/rmrj2109.01.13
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Hair, J. F., Black, W.C., Babin, B. J., & Anderson, R. E. (2010), Multivariate data analysis: A global perspective (7th EDİTİON). Pearson Education, Upper Saddle River.
Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modelling. Sage publications Inc.
Kaçan, A., & Gelen, İ. (2020). An overview of the distance education program in Turkey. International Journal of Education Science and Technology, 6(1), 1-21. Retrieved from https://dergipark.org.tr/tr/pub/uebt/issue/53891/713456
Kazakova, O. P., & Murzich, A. N. (2020). Teaching and learning skills in the organization of distance learning in higher education institutions. Proceedings of the Research Technologies of Pandemic Coronavirus Impact (RTCOV 2020), Advances in Social Science, Education and Humanities Research, (pp. 380-387). Atlantis Press. https://doi.org/10.2991/assehr.k.201105.069
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. https://doi.org/10.1037/1082-989X.1.2.130
Özbay, Ö. (2015). The current status of distance education in the world and Turkey. The Journal of International Education Science, INES Journal, 5, 376-394. Retrieved from https://dergipark.org.tr/tr/pub/inesj/issue/40015/475774
Park, E. S., & Park, M. S. (2020). Factors of the technology acceptance model for construction IT. Applied Sciences, 10(22), 8299. https://doi.org/10.3390/app10228299
Rahmadi, I. F. (2021). Teachers’ technology integration and distance learning adoption amidst the Covid-19 crisis: A reflection for the optimistic future. Turkish Online Journal of Distance Education, 22(2), 26-41. https://doi.org/10.17718/tojde.906472
Rahmi, B., Birgoren, B., & Aktepe, A. (2021). Identifying factors affecting intention to use in distance learning systems. Turkish Online Journal of Distance Education, 22(2), 58-80. https://doi.org/10.17718/tojde.906545
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). (Master’s thesis). The British University in Dubai. The British in Dubai Digital Repository. https://bspace.buid.ac.ae/handle/1234/1150
Santos, J., De Jesus, L. F., Sealmoy, R. R., & Fajardo, R. R. C. (2021). Online distance learning amidst COVID-19. IJERI: International Journal of Educational Research and Innovation, (15), 291-304. https://doi.org/10.46661/ijeri.5271
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. http://www.jstor.org/stable/2632151
The World Bank (2020). How countries are using EdTech (including online learning, radio, television, texting) to support access to remote learning during the Covid-19 Pandemic. Retrieved April 30, 2022 from https://reliefweb.int/report/austria/how-countries-are-using-edtech-including-online-learning-radio-television-texting
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. https://www.jstor.org/stable/23011042
Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x