Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for e-learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238–256. https://doi.org/10.1016/j.chb.2015.11.036

Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ perceived ease of use (PEOU) and perceived usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75–90. https://doi.org/10.1016/j.chb.2016.05.014

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. https://doi.org/10.21609/jsi.v16i2.1011

Al Mulhem, A. (2020). Investigating the effects of quality factors and organizational factors on university students’ satisfaction of e-learning system quality investigating the effects of quality factors and satisfaction of e-learning system quality. Cogent Education, 7(1), Article 1787004. https://doi.org/h9rp

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Al-Maroof, R. S., & Salloum, S. A. (2021). An integrated model of continuous intention to use of google classroom. In Al-Emran, M., Shaalan, K. & Hassanien, A. E. (Eds.), Recent advances in intelligent systems and smart applications (Vol. 295, pp. 311–335). Springer. https://doi.org/10.1007/978-3-030-47411-9_18

Alam, M. M., Ahmad, N., Naveed, Q. N., Patel, A., Abohashrh, M., & Khaleel, M. A. (2021). E-learning services to achieve sustainable learning and academic performance: An empirical study. Sustainability, 13(5), 1–20. https://doi.org/10.3390/su13052653

Alenezi, A. R., Karim, A. M. A., & Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students’ intention to use e learning: A case study from saudi arabian governmental universities. Turkish Online Journal of Educational Technology, 9(4), 22–34. http://tojet.net/articles/v9i4/943.pdf

Alqabbani, S., Almuwais, A., Benajiba, N., & Almoayad, F. (2020). Readiness towards emergency shifting to remote learning during COVID-19 pandemic among university instructors. E-Learning and Digital Media, 18(5), 460-479. https://doi.org/10.1177/2042753020981651

Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858. https://doi.org/10.1016/j.chb.2016.07.065

Ansong-Gyimah, K. (2020). Students’ perceptions and continuous intention to use e-learning systems: The case of google classroom. International Journal of Emerging Technologies in Learning, 15(11), 236–244. https://doi.org/10.3991/IJET.V15I11.12683

Aparicio, M., Bacao, F., & Oliveira, T. (2016). Cultural impacts on e-learning systems’ success. Internet and Higher Education, 31, 58–70. https://doi.org/10.1016/j.iheduc.2016.06.003

Aparicio, M., Bacao, F., & Oliveira, T. (2017). Grit in the path to e-learning success. Computers in Human Behavior, 66, 388–399. https://doi.org/10.1016/j.chb.2016.10.009

Arbaugh, J. B. (2000). Virtual classroom characteristics internet-based MBA courses. Journal of Management Education, 24(1), 32–54. https://doi.org/10.1177/105256290002400104

Arpaci, I., & Basol, G. (2020). The impact of preservice teachers’ cognitive and technological perceptions on their continuous intention to use flipped classroom. Education and Information Technologies, 25, 3503–3514. https://doi.org/10.1007/s10639-020-10104-8

Bezhovski, Z., & Poorani, S. (2011). The evolution of e-learning and new trends. Information and Knowledge Management, 6(3), 50–57. https://bit.ly/3pWRy7e

Bower, M., DeWitt, D., & Lai, J. W. M. (2020). Reasons associated with preservice teachers’ intention to use immersive virtual reality in education. British Journal of Educational Technology, 51(6), 2214–2232. https://doi.org/10.1111/bjet.13009

Chao, H. W., Wu, C. C., & Tsai, C. W. (2021). Do socio-cultural differences matter? a study of the learning effects and satisfaction with physical activity from digital learning assimilated into a university dance course. Computers and Education, 165, Article 104150. https://doi.org/10.1016/j.compedu.2021.104150

Chaw, L. Y., & Tang, C. M. (2018). What makes learning management systems effective for learning? Journal of Educational Technology Systems, 472, 152–169. https://doi.org/10.1177/0047239518795828

Ching-Ter, C., Hajiyev, J., & Su, C. R. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? the general extended technology acceptance model for e-learning approach. Computers and Education, 111, 128–143. https://doi.org/10.1016/j.compedu.2017.04.010

Cidral, W. A., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers and Education, 122, 273–290. https://doi.org/10.1016/j.compedu.2017.12.001

Cidral, W., Aparicio, M., & Oliveira, T. (2020). Students’ long-term orientation role in e-learning success: A Brazilian study. Heliyon, 6(12), Article e05735. https://doi.org/10.1016/j.heliyon.2020.e05735

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. https://doi.org/10.1287/mnsc.35.8.982

Dečman, M. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, 49, 272–281. https://doi.org/10.1016/j.chb.2015.03.022

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/gdxv7r

Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018

Dönmez-Turan, A., & Kir, M. (2019). User anxiety as an external variable of technology acceptance model: A meta-analytic study. Procedia Computer Science, 158, 715–724. https://doi.org/10.1016/j.procs.2019.09.107

Durak, H. Y. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31, 173-209. https://doi.org/10.1007/s12528-018-9200-6

Ebner, M., Schön, S., Braun, C., Ebner, M., Grigoriadis, Y., Haas, M., Leitner, P., & Taraghi, B. (2020). COVID-19 epidemic as E-learning boost? Chronological development and effects at an Austrian university against the background of the concept of “e-learning readiness.” Future Internet, 12(6), 1-20. https://doi.org/10.3390/FI12060094

Fianu, E., Blewett, C., & Ampong, G. O. (2020). Toward the development of a model of student usage of MOOCs. Education and Training, 62(5), 521–541. https://doi.org/10.1108/ET-11-2019-0262

Fianu, E., Blewett, C., Ampong, G. O. A., & Ofori, K. S. (2018). Factors affecting MOOC usage by students in selected Ghanaian universities. Education Sciences, 8(2), 1-15. https://doi.org/10.3390/educsci8020070

Garfield, M. J., & Watson, R. T. (1997). Differences in national information infrastructures: The reflection of national cultures. Journal of Strategic Information Systems, 6(4), 313–337. https://doi.org/10.1016/S0963-8687(98)00012-2

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

Hamid, R., Sentryo, I., & Hasan, S. (2020). Online learning and its problems in the COVID-19 emergency period. Jurnal Prima Edukasia, 8(1), 86–95. https://doi.org/10.21831/jpe.v8i1.32165

He, Y., Chen, Q., & Kitkuakul, S. (2018). Regulatory focus and technology acceptance: Perceived ease of use and usefulness as efficacy. Cogent Business and Management, 5(1), 1–22. https://doi.org/h9rq

Junus, K., Santoso, H. B., Putra, P. O. H., Gandhi, A., & Siswantining, T. (2021). Lecturer readiness for online classes during the pandemic: A survey research. Education Sciences, 11(3), 1-15. https://doi.org/h9rr

Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the UTAUT model. British Journal of Educational Technology, 51(6), 2306–2325. https://doi.org/10.1111/bjet.12905

Khlifi, Y., & El-Sabagh, H. A. (2017). A novel authentication scheme for e-assessments based on student behavior over E-learning platform. International Journal of Emerging Technologies in Learning, 12(4), 62–89. https://doi.org/10.3991/ijet.v12i04.6478

Kim, J. (2020). Learning and teaching online during COVID ‑ 19 : Experiences of student teachers in an early childhood education practicum. International Journal of Early Childhood, 52(2), 145–158. https://doi.org/10.1007/s13158-020-00272-6

Kukulska-Hulme, A. (2012). How should the higher education workforce adapt to advancements in technology for teaching and learning? Internet and Higher Education, 15(4), 247–254. https://doi.org/cr363x

Lee, J. W. (2010). Online support service quality, online learning acceptance, and student satisfaction. Internet and Higher Education, 13(4), 277–283. https://doi.org/10.1016/j.iheduc.2010.08.002

Leidner, D. E., & Kayworth, T. (2006). Review: A review of culture in information systems research: Toward a theory of information technology culture conflict. MIS Quarterly: Management Information Systems, 30(2), 357–399. https://doi.org/10.2307/25148735

Limayem, M., & Cheung, C. M. K. (2008). Understanding information systems continuance: The case of Internet-based learning technologies. Information and Management, 45(4), 227–232. https://doi.org/10.1016/j.im.2008.02.005

Lin, C.-L., Jin, Y. Q., Zhao, Q., Yu, S.-W., & Su, Y.-S. (2021). Factors influence students’ switching behavior to online learning under COVID-19 pandemic: A push–pull–mooring model perspective. Asia-Pacific Education Researcher, 30(3), 229–245. https://doi.org/10.1007/s40299-021-00570-0

Lin, S. H., Lee, H. C., Chang, C.-T., & James Fu, C. (2020). Behavioral intention towards mobile learning in Taiwan, China, Indonesia, and Vietnam. Technology in Society, 63, Article 1010387. https://doi.org/h9rs

Lwoga, E. (2012). Making learning and Web 2.0 technologies work for higher learning institutions in Africa. Campus-Wide Information Systems, 29(2), 90–107. https://doi.org/10.1108/10650741211212359

Majid, F. A., & Shamsudin, N. M. (2019). Identifying factors affecting acceptance of virtual reality in classrooms based on Technology Acceptance Model (TAM). Asian Journal of University Education, 15(2), 52–60. https://eric.ed.gov/?id=EJ1238733

Mohan, M. M., Upadhyaya, P., & Pillai, K. R. (2020). Intention and barriers to use MOOCs: An investigation among the post graduate students in India. Education and Information Technologies, 25(6), 5017–5031. https://doi.org/10.1007/s10639-020-10215-2

Mutambik, I., Lee, J., & Almuqrin, A. (2020). Role of gender and social context in readiness for e-learning in Saudi high schools. Distance Education, 41(4), 515–539. https://doi.org/10.1080/01587919.2020.1821602

Ouajdouni, A., Chafik, K., & Boubker, O. (2021). Measuring e-learning systems success: Data from students of higher education institutions in Morocco. Data in Brief, 35, Article 106807. https://doi.org/10.1016/j.dib.2021.106807

Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(7), 2–26. https://doi.org/10.1186/s41239-019-0136-3

Prasojo, L. D., Habibi, A., Mukminin, A., Sofyan, Indrayana, B., & Anwar, K. (2020). Factors influencing intention to use web 2.0 in Indonesian vocational high schools. International Journal of Emerging Technologies in Learning, 15(5), 100–118. https://doi.org/10.3991/ijet.v15i05.10605

Pynoo, B., Devolder, P., Tondeur, J., Van Braak, J., Duyck, W., & Duyck, P. (2011). Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(1), 568–575. https://doi.org/10.1016/j.chb.2010.10.005

Ramadiani, Azainil, Haryaka, U., Agus, F., & Kridalaksana, A. H. (2017). User satisfaction model for e-learning using smartphone. Procedia Computer Science, 116, 373–380. https://doi.org/10.1016/j.procs.2017.10.070

Ramírez-Hurtado, J. M., Hernández-Díaz, A. G., López-Sánchez, A. D., & Pérez-León, V. E. (2021). Measuring online teaching service quality in higher education in the COVID-19 environment. International Journal of Environmental Research and Public Health, 18(5), 1–14. https://doi.org/10.3390/ijerph18052403

Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2020). Social isolation and acceptance of the learning management system (LMS ) in the time of COVID-19 pandemic : An expansion of the UTAUT model. Journal of Educational Computing Research, 58(8), 1–26. https://doi.org/10.1177/0735633120960421

Rizun, M., & Strzelecki, A. (2020). Students’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. International Journal of Environmental Reseach and Public Health, 17, 1–19. https://doi.org/10.3390/ijerph17186468

Rokhman, F., Mukhibad, H., Hapsoro, B. B., & Nurkhin, A. (2022). E-learning evaluation during the COVID-19 pandemic era based on the updated of Delone and McLean information systems success model. Cogent Education, 9(1), 1–25. https://doi.org/h9rt

Romi, I. M. (2017). A model for e-learning systems sueeess: Systems, determinants, and performance. International Journal of Emerging Technologies in Learning, 12(10), 4–20. https://doi.org/10.3991/ijet.v12i10.6680

Russell, G., & Bradley, G. (1997). Teachers’ computer anxiety: Implications for professional development. Education and Information Technologies, 2(1), 17–30. https://doi.org/10.1023/A:1018680322904

Safsouf, Y., Mansouri, K., & Poirier, F. (2020). An analysis to understand the online learners’ success in public higher education in Morocco. Journal of Information Technology Education: Research, 19, 087–112. https://doi.org/10.28945/4518

Salikhova, N. R., Lynch, M. F., & Salikhova, A. B. (2020). Psychological aspects of digital learning: A self-determination theory perspective. Contemporary Educational Technology, 12(2), 1–13. https://doi.org/10.30935/cedtech/8584

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 Behavior, 118, Article 106675. https://doi.org/10.1016/j.chb.2020.106675

Siron, Y., Wibowo, A., & Narmaditya, B. S. (2020). Factors affecting the adoption of e-learning in Indonesia : Lesson from COVID-19. Journal of Technology and Science Education, 10(2), 282–295. https://doi.org/10.3926/jotse.1025

Srite, M., & Karahanna, E. (2015). The role of espoused in technology values national cultural introduction. MIS Quarterly, 30(3), 679–704. https://doi.org/10.2307/25148745

Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Alfrets, F., & Hakim, H. (2020). Using an extended technology acceptance model to understand students’ use of e-learning during COVID-19 : Indonesian sport science education context. Heliyon, 6(11), Article e05410. https://doi.org/10.1016/j.heliyon.2020.e05410

Tam, C., & Oliveira, T. (2017). Understanding mobile banking individual performance: The DeLone & McLean model and the moderating effects of individual culture. Internet Research, 27(3), 538–562. https://doi.org/10.1108/IntR-05-2016-0117

Tang, Y. M., Chen, P. C., Law, K. M. Y., Wu, C. H., Lau, Y., Guan, J., He, D., & Ho, G. T. S. (2021). Comparative analysis of student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector. Computers & Education, 168, 104211. https://doi.org/10.1016/j.compedu.2021.104211

Thongsri, N., Shen, L., Bao, Y., & Alharbi, I. M. (2018). Integrating UTAUT and UGT to explain behavioural intention to use m-learning a developing country’s perspective. Journal of Systems and Information Technology, 20(3), 278–297. https://doi.org/10.1108/JSIT-11-2017-0107

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 47(3), 425–478. https://doi.org/10.2307/30036540

Yakubu, M. N., & Dasuki, S. I. (2018). Assessing elearning systems success in Nigeria: An application of the Delone and Mclean information systems success model. Journal of Information Technology Education: Research, 17, 183–203. https://doi.org/10.28945/4077

Yuen, A. H. K., & Ma, W. W. K. (2008). Exploring teacher acceptance of e-learning technology. Asia-Pacific Journal of Teacher Education, 36(3), 229–243. https://doi.org/10.1080/13598660802232779