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(2016), 238–256. https://doi.org/10.1016%2Fj.chb.2015.11.036

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016%2F0749-5978%2891%2990020-t

Al-alak, B. A., & Alnawas, I. A. (2011). Measuring the acceptance and adoption of e-learning by academic staff. Knowledge Management & E-Learning: An International Journal, 3(2), 201-221. https://doi.org/10.34105/j.kmel.2011.03.016

Almaghaslah, D., Ghazwani, M., Alsayari, A., & Khaled, A. (2018). Pharmacy students’ perceptions towards online learning in a Saudi Pharmacy School. Saudi Pharmaceutical Journal, 26(5), 617-621. https://doi.org/10.1016/j.jsps.2018.03.001

Al-Samarraie, H., Teng, B. K., Alzahrani, A. I., & Alalwan, N. (2018). E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Studies in Higher Education, 43(11), 2003-2019. https://doi.org/10.1080/03075079.2017.1298088

Arbaugh, J. B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13(2), 203–223. https://doi.org/10.1016/S1047-8310(02)00049-4

Arbaugh, J. B., & Duray, R. (2002). Technological and structural characteristics, student learning and satisfaction with web-based courses. Management Learning, 33(3), 331–347. https://doi.org/10.5465/apbpp.2002.7516897

Artino Jr., A. R. (2010). Online or face-to-face learning? Exploring the personal factors that predict students' choice of instructional format. The Internet and Higher Education, 13(4), 272-276. https://doi.org/10.1016/j.iheduc.2010.07.005

Bandyopadhyay, S., & Natarajan, V. (2011). Service quality of educational websites: An empirical study. Journal of Business & Economics Research, 6(6), 49-54. https://doi.org/10.19030/jber.v6i6.2430

Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45(7), 659–686. https://doi.org/10.1177/001872679204500702

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295x.84.2.191

Bao, W. (2020). COVID‐19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113-115. https://doi.org/10.1002/hbe2.191

Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: Testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20(1), 1–15. https://doi.org/10.1016/s0747-5632(03)00049-9

Benlian, A., Koufaris, M., & Hess, T. (2011). Service quality in software-as-a-service: Developing the saaS-qual measure and examining its role in usage continuance. Journal of Management Information Systems, 28(3), 85-126. https://doi.org/10.2753/mis0742-1222280303

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921

Bhuasiri, W. Xaymoungkhoun, O., Zo, H., Rho, J. J., & Ciganek, A. P. (2012). Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843–855. https://doi.org/10.1016/j.compedu.2011.10.010

Blumenthal, S., & Blumenthal, Y. (2020). Tablet or paper and pen? Examining mode effects on German elementary school students’ computation skills with curriculum-based measurements. International Journal of Educational Methodology, 6(4), 669-680. https://doi.org/10.12973/ijem.6.4.669

Byrne, B. M. (2013). Structural equation modeling with AMOS. Routledge. https://doi.org/10.4324/9781410600219

Carillo, K., Scornavacca, E., & Za, S. (2017). The role of media dependency in predicting continuance intention to use ubiquitous media systems. Information & Management, 54(3), 317–335. https://doi.org/10.1016/j.im.2016.09.002

Computer Center of University of Maribor. (2020). Computer Center of University of Maribor through time. https://it.um.si/rcum/Strani/RCUM-skozi-cas.aspx

Cheawjindakarn, B., Suwannatthachote, P., & Theeraroungchaisri, A. (2012). Critical success factors for online distance learning in higher education: A review of the literature. Creative Education, 3(8), 61-66. https://doi.org/10.4236/ce.2012.38b014

Chroustová, K., Bílek, M., & Šorgo, A. (2015). Development of the research tool to identify factors affecting the use of chemistry educational software. Problems of Education in the 21st Century, 68(6), 6-21.

Corbeil, J. R., & Valdes-Corbeil, M. E., (2007). Are you ready for mobile learning?. Educause Quarterly, 30(2), 51-58.

Crawford, J., Butler-Henderson, K., Rudolph, J., & Glowatz, M. (2020). COVID-19: 20 countries' higher education intra-period digital pedagogy responses. Journal of Applied Teaching and Learning, 3(1), 1-20. https://doi.org/10.37074/jalt.2020.3.1.7

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%2F249008

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

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Debevc, M., Weiss, J., Šorgo, A., & Kožuh, I. (2020). Solfeggio learning and the influence of a mobile application based on visual, auditory and tactile modalities. British Journal of Educational Technology, 51(1), 177-193. https://doi.org/10.1111/bjet.12792

Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2010). User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19(1), 60–75. https://doi.org/10.1057/ejis.2009.50

Didakt.UM (2020). UM Teaching support center. https://didakt.um.si/center-za-podporo-poucevanju/predstavitev/Strani/default.aspx

Dolenc, K., Šorgo, A., & Ploj Virtič, M. (2021 ). Forced continuance intention model (FCIM) of distance online teaching in the time of the initial COVID-19 outbreak. Unpublished manuscript.

Fryer, L. K., & Bovee, H. N. (2016). Supporting students' motivation for e-learning: Teachers matter on and offline. The Internet and Higher Education, 30, 21-29. https://doi.org/10.1016/j.iheduc.2016.03.003

Gattiker, U. E., & Hlavka, A. (1992). Computer attitudes and learning performance: Issues for management education and training. Journal of Organizational Behavior, 13(1), 89–101. https://doi.org/10.1002/job.4030130109

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis. Prentice Hall.

Hepp, P., Hinostroza, J. E., Laval, E., & Rehbein, L. (2004). Technology in schools: Education. ICT and the knowledge society. World Bank Education Advisory Service.

Hodges, C., Moore, S., Lockee, B., Trust, T. & Bond, A. (2020, March 27). The difference between emergency remote teaching and online learning. Educause Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning

Ho, L.-A., & Kuo, T.-H. (2010). How can one amplify the effect of e-learning? An examination of high-tech employees’ computer attitude and flow experience. Computers in Human Behavior, 26(1), 23–31. https://doi.org/10.1016/j.chb.2009.07.007

Igbaria, M., Parasuraman, S., & Baroudi, J. J. (1996). A motivational model of microcomputer usage. Journal of Management Information Systems, 13(1), 127-143. https://doi.org/10.1080/07421222.1996.11518115

Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21(3), 279-305. https://doi.org/10.2307/249498.

Julia, J., Afrianti, N., Soomro, K.A., Supriyadi, T., Dolifah, D., Isrokatun, I., Erhamwilda, E., & Ningrum, D. (2020). Flipped classroom educational model (2010-2019): A bibliometric study. European Journal of Educational Research, 9(4), 1377-1392. https://doi.org/10.12973/eu-jer.9.4.1377

Kline, R. B. (1998). Structural equation modeling. Guilford.

Koehler, M. J., & Mishra, P. (2008). Introducing TPCK. AACTE committee on innovation and technology. In M. C. Herring, M. J. Koeler & P. Mishra (Eds.), The handbook of technological pedagogical content knowledge (TPCK) for educators (pp. 3-29). Taylor & Francis Group.

Krishnan, S. (2018). Students’ perceptions of learning mode in mathematics. MOJES: Malaysian Online Journal of Educational Sciences, 4(2), 32-41.

Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54(2), 506–516. https://doi.org/10.1016/j.compedu.2009.09.002

Liao, C., Palvia, P. C., & Chen, J. (2009). Information technology adoption behavior life cycle: Toward a technology continuance theory (TCT). International Journal of Information Management, 29(4), 309-320. https://doi.org/10.1016/j.ijinfomgt.2009.03.004

Liaw, S. S., Huang, H.M., & Chen, G. D. (2007). An activity-theoretical approach to investigate learners’ factors toward e-learning systems. Computers in Human Behavior, 23(4), 1906–1920. https://doi.org/10.1016/j.chb.2006.02.002

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

Lu, J., Yao, J., & Yu, C. S. (2005). Personal innovativeness. Social influences and adoption of wireless internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268. https://doi.org/10.1016/j.jsis.2005.07.003

Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). E-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129-135. https://doi.org/10.1016/j.iheduc.2010.10.001

Nijs, L., & Leman, M. (2014). Interactive technologies in the instrumental music classroom: A longitudinal study with the music paint machine. Computers & Education, 73, 40–59. https://doi.org/10.1016/j.compedu.2013.11.008

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.2307/3150499

Otter, R. R., Seipel, S., Graeff, T., Alexander, B., Boraiko, C., Gray, J., Petersen, K., & Sadler, K. (2013). Comparing student and faculty perceptions of online and traditional courses. The Internet and Higher Education, 19, 27-35. https://doi.org/10.1016/j.iheduc.2013.08.001

Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150-162.

Parkes, M., Stein, S., & Reading, C. (2015). Student preparedness for university e-learning environments. The Internet and Higher Education, 25, 1-10. https://doi.org/10.1016/j.iheduc.2014.10.002

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), 401-426. https://doi.org/10.2307/3250989

Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683–696. https://doi.org/10.1016/j.ijhcs.2006.01.003

Rodríguez-Ardura, I., & Meseguer-Artola, A. (2016). E-learning continuance: The impact of interactivity and the mediating role of imagery, presence and flow. Information & Management, 53(4), 504-516. https://doi.org/10.1016/j.im.2015.11.005

Rogers. E. (1995). Diffusion of innovations. Free Press.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation. social development. and well-being. American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066x.55.1.68

Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35. https://doi.org/10.1016/j.compedu.2018.09.009

Schwarz, A., Rizzuto, T., Carraher-Wolverton, C., Roldán, J. L., & Barrera-Barrera, R. (2017). Examining the impact and detection of the" urban legend" of common method bias. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 48(1), 93-119. https://doi.org/10.1145/3051473.3051479

Soh, O. K., Lim, L. A. D., Yee, L. Y., Ying, L. K., & Yin, L. L. (2018). A Review on the students’ perceptions of online learning tools in improving english writing skills. International Journal of Academic Research in Progressive Education and Development, 7(4), 324-348. http://dx.doi.org/10.6007/IJARPED/v7-i4/4979

Suartama, I. K., Triwahyuni, E., Abbas, S., Hastuti, W. D., Usman, M., Subiyantoro, S., & Salehudin, M. (2020). Development of e-learning oriented inquiry learning based on character education in multimedia course. European Journal of Educational Research, 9(4), 1591-1603. http://doi.org/10.12973/eu-jer.9.4.1591

Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202. https://doi.org/10.1016/j.compedu.2006.11.007

Šumak, B., Polančič, G., & Heričko, M. (2010). An empirical study of virtual learning environment adoption using UTAUT. In A.M. Gadomski, B. Krämer, C.Y. Lester, & M. Popescu (Eds.), 2010 Second international conference on mobile, hybrid, and on-line learning (pp. 17-22). IEEE. https://doi.org/10.1109/elml.2010.11

Šumak, B., Heričko, M., Pušnik, M., & Polančič, G. (2011). Factors affecting acceptance and use of Moodle: An empirical study based on TAM. Informatica, 35(1), 91-100.

Šumak, B., & Šorgo, A. (2016). The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre-and post-adopters. Computers in Human Behavior, 64, 602-620. https://doi.org/10.1016/j.chb.2016.07.037

Šumak, B., Pušnik, M., Heričko, M., & Šorgo, A. (2017). Differences between prospective, existing, and former users of interactive whiteboards on external factors affecting their adoption, usage and abandonment. Computers in Human Behavior, 72, 733-756. https://doi.org/10.1016/j.chb.2016.09.006

Šumak, B., Heričko, M., & Pušnik, M. (2011). A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types. Computers in Human Behavior, 27(6), 2067-2077. https://doi.org/10.1016/j.chb.2011.08.005

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143. https://doi.org/10.2307/249443

Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810. https://doi.org/10.1016/j.ijhcs.2006.05.001

Toquero, C. M. (2020). Challenges and opportunities for higher education amid the COVID-19 pandemic: The Philippine Context. Pedagogical Research, 5(4), em0063. https://doi.org/10.29333/pr/7947

University of Maribor (2020). Annual program of University of Maribor. University of Maribor. https://cutt.ly/OjjP8Dv

Urbach, N., Smolnik, S., & Riempp, G. (2010). An empirical investigation of employee portal success. The Journal of Strategic Information Systems, 19(3), 184–206. http://doi.org/10.1016/j.jsis.2010.06.002

Usak, M., Masalimova, A. R., Cherdymova, E. I., & Shaidullina, A. R. (2020). New playmaker in science education: COVID-19. Journal of Baltic Science Education, 19(2), 180-185. https://doi.org/10.33225/jbse/20.19.180

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

Witze, A. (2020). Universities will never be the same after the coronavirus crisis. Nature, 582(7811), 162-164. https://doi.org/10.1038/d41586-020-01518-y

Wu. B., & Zhang, C. (2014). Empirical study on continuance intentions towards e-learning 2.0 systems. Behaviour & Information Technology, 33(10), 1027-1038. https://doi.org/10.1080/0144929x.2014.934291

Zhou, Z., Fang, Y., Vogel, D. R.., Jin, X.-L., & Zhang, X. (2012). Attracted to or locked in? Predicting continuance intention in social virtual world services. Journal of Management Information Systems, 29(1), 273–306. https://doi.org/10.2753/mis0742-1222290108