References
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
- Alabdullatif, H., & Velazquez-Iturbide, J. A. (2020). Personality traits and intention to continue using massive open online courses (ICM) in Spain: The mediating role of motivations. International Journal of Human-Computer Interaction, 36(20), 1953-1967. https://doi.org/10.1080/10447318.2020.1805873
- Anderson, J., & Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423. http://dx.doi.org/10.1037/0033-2909.103.3.411
- Barnard, L., Lan, W., To, Y., Paton, V., & Lai, S. (2009). Measuring self-regulation in online and blended learning environments. Internet and Higher Education, 12, 1-6. https://doi.org/10.1016/j.iheduc.2008.10.005
- Cao, J., Lin, M., Crews, J., Burgoon, J., & Nunamaker, J., Jr. (2005). Virtual interaction for effective e-learning. Proceedings of the International Conference on Information Systems, ICIS 2005, USA.
- Cardozo, R. N. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 3, 244-249. http://dx.doi.org/10.2307/3150182
- Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45(4), 399-416. https://doi.org/10.1016/j.compedu.2004.06.001
- Cunningham, C., & Billingsley, M. (2003). Curriculum Webs: A practical guide to weaving the Web into teaching and learning. Allyn and Bacon. https://umbrella.lib.umb.edu/discovery/fulldisplay?vid=01MA_UMB:01MA_UMB&tab=Everything&docid=alma993844093503746&context=L&lang=en
- Doll, W., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18(4), 453-461. https://doi.org/10.2307/249524
- Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.2307/3150980
- Ha, J., & Jang, S. (2010). Perceived values, satisfaction, and behavioral intentions: The role of familiarity in Korean restaurants. International Journal of Hospitality Management, 29, 2-13. https://doi.org/10.1016/j.ijhm.2009.03.009
- Hamdan, K., Al-Bashaireh, A., Zahran, Z., Al-Daghestani, A., Samira, A., & Shaheen, A. (2021). University students' interaction, internet self-efficacy, self-regulation and satisfaction with online education during pandemic crises of COVID-19(SARS-CoV-2). International Journal of Educational Management. https://doi.org/10.1108/IJEM-11-2020-0513.
- Han, S., Yoo, H. S., & Ju, D. Y. (2015). Contents experience according to deformation types of smart device. Proceedings of the 2015 Korea Contents Society General Conference. http://www.riss.kr/link?id=A100515505
- Hayashi, A., Chen, C., Ryan, T., & Wu, J. (2004). The role of social presence and moderating role of computer self-efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139-154. https://aisel.aisnet.org/jise/vol15/iss2/5
- Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Educause Review, 27. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
- Huber, F., Herrmann, A., & Wricke, M. (2001). Customer satisfaction as an antecedent of price acceptance: Results of an empirical study. Journal of Product & Brand Management, 10(3), 160-169. https://doi.org/10.1108/10610420110395403
- Jeong, H. (2022). A study on the relationship analysis between perceived relatedness, online self-regulated learning, perceived learning gains, and satisfaction of non-face-to-face classes in university. Global Creative Leader: Education & Learning, 12(1), 47-73. https://doi.org/10.34226/gcl.2022.12.1.47
- Jeong, H., Roh, S. Z., Jung, J. W., & Cho, Y. H. (2020). The challenge of the spread of Covid-19 to education: High quality remote learning for everyone. Journal of Educational Technology, 36(s), 645-669. https://doi.org/10.17232/KSET.36.3.645
- Joo, Y. J., & Eun, J. H. (2017). Investigating the structural relationships among service quality, time management behavior, satisfaction and learning persistence in K-MOOC for grades. The Journal of Educational Information and Media, 23(4), 763-788. http://dx.doi.org/10.15833/KAFEIAM.23.4.763
- Ju, R. (2020). In the context of COVID-19, a comparison of content quality according to universities' overall distance learning and the effect of content quality, service quality on students' satisfaction. Journal of Educational Technology, 36(s), 931-956. https://doi.org/10.17232/KSET.36.3.931
- Kim, H. J. (2021). Digital transformation of education brought by COVID-19 pandemic. Journal of the Korea Society of Computer and Information, 26(6), 183-193. https://doi.org/10.9708/JKSCI.2021.26.06.183
- Kim, S., Lim, E., Kim, B., & Lee, Y. (2021). An analysis of learner's experience in distance education at a university in the COVID-19 Situation. The Journal of Educational Information and Media, 27(1), 161-189. https://doi.org/10.15833/KAFEIAM.27.1.161
- Kline, R. B. (2005) Principles and practice of structural equation modeling (2nd ed.), Guilford Press. https://www.scirp.org/(S(351jmbntvnsjt1aadkozje))/reference/referencespapers.aspx?referenceid=869389
- Kramarski, B., & Gutman, M. (2006). How can self-regulated learning be supported in mathematical E-learning environments? Journal of Computer Assisted Learning Research, 22(1), 24-33. https://doi.org/10.1111/j.1365-2729.2006.00157.x
- Kwon, S. (2009). The analysis of differences of learners' participation, procrastination, learning time and achievement by adult learners' adherence of learning time schedule in e-Learning environments. The Journal of Learner-Centered Curriculum and Instruction, 9(3), 61-86. http://www.riss.kr/link?id=A105092039 105092039
- Lee, M. (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
- Lee, S., Park, H., & Sung, E. (2021). Exploration of self-regulated learning variables and learning behavior data affecting academic achievement in an online learning environment. Journal of Korean Association for Educational Information and Media, 27(2), 723-748. https://doi.org/10.15833/KAFEIAM.27.2.723
- Liu, X., He, X., Wang, M., & Shen, H. (2022). What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics. Technology in Society, 70, 101996. https://doi.org/10.1016/j.techsoc.2022.101996
- Madani, H., Adhikari, A., & Hodgdon, C. (2023). Understanding faculty acceptance of online teaching during the COVID-19 pandemic: A Saudi Arabian case study, Journal of International Education in Business, 16(2), 152-166. https://doi-orgssl.access.ewha.ac.kr/10.1108/JIEB-12-2021-0109
- Mahajan, R., Lim, W. M., Kumar, S., & Sareen, M. (2023). COVID-19 and management education: From pandemic to endemic. The International Journal of Management Education, 21(2), 100801. https://doi.org/10.1016/j.ijme.2023.100801
- McManus, T. F. (2000). Individualizing instruction in a Web-based hypermedia learning environment: Nonlinearity, advance organizers, and self-regulated learners. Journal of Interactive Learning Research, 11, 219-251. https://www.learntechlib.org/primary/p/8486/
- Ministry of Education (2021, February 15). Instruction on the operation of distance learning in general universities (Ministry of Education Ordinance No. 367). https://www.moe.go.kr/boardCnts/viewRenew.do?boardID=72755&lev=0&statusYN=W&s=moe&m=031303&opType=N&boardSeq=88651
- Moon, E., & Shin, W. S. (2022). A study on continuous intention of taking online course: focusing on the expectation-confirmation model. The Korean Journal of Educational Methodology Studies, 34(4), 901-922. http://dx.doi.org/10.17927/tkjems.2022.34.4.901
- Oliver, R. L., & Swan, J. E. (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions: A field survey approach. Journal of Marketing, 53(2), 21-35. https://doi.org/10.2307/1251411
- Park, M., & Heo, G. (2020). A case study on the uncontact-era distance education for personality education : Focused on the role of professors. Journal of Character Education & Research, 5(2), 25-42. https://doi.org/10.46227/JCER.5.2.2
- Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie, W. J. (1993) Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801-813. https://doi.org/10.1177/0013164493053003024
- Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. The American Journal of Distance Education, 22(2), 72-89. https://doi.org/10.1080/08923640802039024
- Richardson, J., & Swan, K. (2003). Examining social presence in online courses in relation to students' perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7, 68-88 .https://doi.org/10.24059/olj.v7i1.1864
- Saxena, C., Baber, H., & Kumar, P. (2021). Examining the moderating effect of perceived benefits of maintaining social distance on e-learning quality during COVID-19 pandemic. Journal of Educational Technology Systems, 49(4), 532-554. https://doi.org/10.1177/0047239520977798
- Schraw, G. (2007). The use of computer-based environments for understanding and improving self-regulation. Metacognition Learning, 2, 169-176. https://doi.org/10.1007/s11409-007-9015-8
- Schunk, D. H. (2001). Social Cognitive Theory and Self-Regulated Learning. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-Regulated Learning and Academic Achievement: Theoretical Perspectives (pp. 125-151). Lawrence Erlbaum Associates Publishers. https://www.scirp.org/(S(351jmbntv-nsjt1aadkposzje))/reference/referencespapers.aspx?referenceid=3245847
- Shin, N. & Chan, J. (2004). Direct and indirect effects of online learning on distance education. British Journal of Education Technology, 55(3), 275-288. https://doi.org/10.1111/j.0007-1013.2004.00389.x
- Smarkola, C. (2008). Efficacy of a planned behavior model: Beliefs that contribute to computer usage intentions of student teachers and experienced teachers. Computers in Human Behavior, 24(3), 1196-1215. https://doi.org/10.1016/j.chb.2007.04.005.
- Song, D., & Kim, D. (2021). Effects of self-regulation scaffolding on online participation and learning outcomes. Journal of Research on Technology in Education, 53(3), 249-263. https://doi.org/10.1080/15391523.2020.1767525
- Steffens, K. (2006). Self-regulated learning in technology-enhanced learning environments: Lessons of a European peer review. European Journal of Education, 41(3), 353-379. http://dx.doi.org/10.1111/j.1465-3435.2006.00271.x
- Sung, J., & Kwon, S. (2021). Comparison of students' perceptions of synchronous video conferencing lectures and asynchronous video-recorded lectures: Focusing on students' levels of concentration, understanding, and satisfaction. Journal of Education & Culture, 27(5), 239-267.
- Szymanski, D. M., & Hise, R. T. (2000) E-satisfaction: An initial examination. Journal of Retailing, 76, 309-322. https://doi.org/10.1016/S0022-4359(00)00035-X
- Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176. https://www.jstor.org/stable/23011007 1007
- Tse, D. K., & Wilton, P. C. (1988), Models of consumer satisfaction formation: An extension. Journal of Marketing Research, 25(2), 204-212. http://dx.doi.org/10.2307/3172652
- Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27, 451-481. http://dx.doi.org/10.1111/j.1540-5915.1996.tb01822.x
- Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students' characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302-323. https://doi.org/10.1080/01587919.2013.835779
- Ye, J.-H., Lee, Y.-S., Wang, C.-L., Nong, W., Ye, J.-N., & Sun, Y. (2023). The continuous use intention for the online learning of Chinese vocational students in the post-epidemic era: The extended technology acceptance model and expectation confirmation theory. Sustainability, 15, 1819. https://doi.org/10.3390/su15031819
- Zhou, X., Chai, C., Jong, M., & Xiong, X. (2021). Does relatedness matter for online self-regulated learning to promote perceived learning gains and satisfaction? Asia-Pacific Education Researcher, 30(3), 205-215. https://doi.org/10.1007/s40299-021-00579-5
- Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45, 166-183. https://doi.org/10.3102/0002831207312909