References
- Alizadeh, M., Mehran, P., Koguchi, I., & Takemura, H. (2019). Evaluating a blended course for Japanese learners of English: Why quality matters. International Journal of Educational Technology in Higher Education, 16(1), 1-21. https://doi.org/10.1186/s41239-019-0132-7
- Allen, I. E., & Seaman, J. (2010). Class differences: Online education in the United States. Sloan Consortium (NJ1).
- Baran, E., Correia, A. P., & Thompson, A. (2011). Transforming online teaching practice: Critical analysis of the literature on the roles and competencies of online teachers. Distance Education, 32(3), 421-439. https://doi.org/10.1080/01587919.2011.610293
- Bervell, B., Umar, I. N., & Kamilin, M. H. (2020). Towards a model for online learning satisfaction (MOLS): Re-considering non-linear relationships among personal innovativeness and modes of online interaction. Open Learning: The Journal of Open, Distance and e-Learning, 35(3), 236-259. https://doi.org/10.1080/02680513.2019.1662776
- Borup, J., Graham, C. R., & Davies, R. S. (2013). The nature of adolescent learner interaction in a virtual high school setting. Journal of Computer Assisted Learning, 29(2), 153-167. https://doi.org/10.1111/j.1365-2729.2012.00479.x
- Che, W. (2021). Exploring strategies to improve learning satisfaction in the online learning environment of higher education through learning theories in the preparedness of post-corona era. Journal of Learner-Centered Curriculum and Instruction, 21(5), 797-815. https://doi.org/10.22251/jlcci.2021.21.5.797
- Chen, W., & Cao, P. (2020). Implementation situation and reflection on online teaching in Double First-Cass universities. Edcation science, 36(2), 24.
- Chen, X., Han X., Wang Y., & Zhang, H. (2019). Reconstruction of curriculum teaching quality evaluation system and construction of "golden course". China University Teaching, (5), 43-48.
- Chitkushev, L., Vodenska, I., & Zlateva, T. (2014). Digital learning impact factors: Student satisfaction and performance in online courses. International Journal of Information and Education Technology, 4(4), 356. https://doi.org/10.7763/IJIET.2014.V4.429
- CIQA (China university Internal Quality Assurance). (2017). FD-QM Higher Education Online Course Quality Standard. Retrieved March 15, 2020, from http://fudan.cfd.chaoxing.com/portal
- CIQA (China university Internal Quality Assurance). (2019). Introduction to FD-QM. Retrieved January 30, 2021, from http://fudan.cfd.chaoxing.com/pubcontent/info?id=51
- Diekelmann, N., & Mendias, E. P. (2005). Being a supportive presence in online courses: Attending to students' online presence with each other. Journal of Nursing Education, 44(9), 393-395. https://doi.org/10.3928/01484834-20050901-02
- Eom, S. B., & Ashill, N. (2016). The determinants of students' perceived learning outcomes and satisfaction in university online education: An update. Decision Sciences Journal of Innovative Education, 14(2), 185-215. https://doi.org/10.1111/dsji.12097
- Eom, S. B., Wen, H. J., & Ashill, N. (2006). The determinants of students' perceived learning outcomes and satisfaction in university online education: An empirical investigation. Decision Sciences Journal of Innovative Education, 4(2), 215-235. https://doi.org/10.1111/j.1540-4609.2006.00114.x
- Fang, X., Cui, X., & Yang, G. (2016). Research on the satisfaction of MOOC learner support service based on structural equation model. Open Education Research, (5), 76-85.
- Gallien, T., & Oomen-Early, J. (2008). Personalized versus collective instructor feedback in the online course room: Does type of feedback affect student satisfaction, academic performance and perceived connectedness with the instructor?. International Journal on E-learning, 7(3), 463-476.
- Gong, S., Han, Y., Wang, L., Gao L., & Xiong, J. (2016) The relationships among task value, academic emotions and online learning satisfaction. e-Education Research, 37(3), 72-77.
- Guo, L., & Cao, Y. (2018). Research on the influencing mechanism of college students learning satisfaction with MOOCs. Journal of Higher education research, 12, 69-75.
- Hanna, D. E., Glowacki-Dudka, M., & Conceigao-Runlee, S. (2000). Practical tips for teaching online groups: Essentials of web-based education. Wisconsin: Atwood Publishing.
- Hara, N., & Kling, R. (1999). Students' frustrations with a web-based distance education course. Communication & Society, 3(4), 557-579.
- Hoffman, G. L. (2012). Using the quality matters rubric to improve online cataloging courses. Cataloging & classification quarterly, 50(2-3), 158-171. https://doi.org/10.1080/01639374.2011.651194
- Hu, Y., & Zhao, F. (2015). Theoretical analysis model and measurement of online learning effectiveness. e-Education Research, 36(10), 37-45.
- Ismuratova, G. S., Naurzbaev, B. T., Maykopova, G. S., Madin, V. A., & Ismuratova, R. B. (2017). E-learning: Concept and its main characteristics. International Journal of Economic Perspectives, 11(2), 847-852.
- Jackson, M. J., & Helms, M. M. (2008). Student perceptions of hybrid courses: Measuring and interpreting quality. Journal of Education for Business, 84(1), 7-12. https://doi.org/10.3200/JOEB.84.1.7-12
- Jeffery, S. D., Charles, R. G., Kristian, J. S., & Lisa, R. H. (2013). An analysis of research trends in dissertations and theses studying blended learning. The Internet and Higher Education, 21(1), 100-122.
- Jeong, S. (2021). Analysis of differences in satisfaction with remote learning between two-year college students and four-year university students after the Outbreak of COVID-19. Journal of the Korean Contents Association, 21(5), 276-284.
- Jones, I. S., & Blankenship, D. (2017). Student perceptions of online courses. Research in Higher Education Journal, 32, 1-9.
- Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. https://doi.org/10.1007/BF02291575
- Kim, M., & Kang, T. (2020). The effects of EBS CAST online services on Korean academic achievement and learning attitude. Education Research, 77, 9-34. https://doi.org/10.17253/SWUERI.2020.77..001
- Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). New York: Guilford publications.
- Kuo, Y. C., Walker, A., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35-50. https://doi.org/10.1016/j.iheduc.2013.10.001
- Lee, Y., & Hwang, S. (2019). The determinants of happiness in participants of leisure sports: hierarchical regression analysis. Korean Journal of Leisure, Recreation & Park, 43(1), 43-53. https://doi.org/10.26446/kjlrp.2019.3.43.1.43
- Legon, R. (2015). Measuring the impact of the Quality Matters RubricTM: A discussion of possibilities. American Journal of Distance Education, 29(3), 166-173. https://doi.org/10.1080/08923647.2015.1058114
- Li, Y., Zhang, H., & Zhang, H. (2020). Model construction and empirical test of college students' satisfaction with online learning during epidemic prevention and control period: based on the survey of 15 universities in Shanghai. Open Educ. Res, 26, 112-111.
- Liu, H. (2011). Research on the evaluation of Chinese higher education students' satisfaction based on PLS-SEM (Doctoral dissertation, Jiangsu University). Retrieved February 20, 2020, from https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFD0911&filename=1011148357.nh
- Liu, X., & Cui, J. (2020). Research on the influencing factors of college students' satisfaction with online teaching. Journal of Shaanxi Xueqian Normal University, 36(9), 120-127.
- Lowenthal, P., Bauer, C., & Chen, K. Z. (2015). Student perceptions of online learning: An analysis of online course evaluations. American Journal of Distance Education, 29(2), 85-97. https://doi.org/10.1080/08923647.2015.1023621
- Mumford, S., & Dikilitas, K. (2020). Pre-service language teachers reflection development through online interaction in a hybrid learning course. Computers & Education, 144, 1-25.
- Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
- Prior, D. D., Mazanov, J., Meacheam, D., Heaslip, G., & Hanson, J. (2016). Attitude, digital literacy and self-efficacy: Flow-on effects for online learning behavior. The Internet and Higher Education, 29, 91-97. https://doi.org/10.1016/j.iheduc.2016.01.001
- Qian, Y. (2015). Factors affecting the continued use of online learning user behavior. Journal of Modern Information, 2015(3), 50-56.
- QM (Quality Matters). (2020). Higher Ed Course Design Rubric (6th ed.). Retrieved January 30, 2021, from https://www.qualitymatters.org/sites/default/files/PDFs/StandardsfromtheQMHigherEducationRubric.pdf
- Ralston-Berg, P., Buckenmeyer, J., Barczyk, C., & Hixon, E. (2015). Students' perceptions of online course quality: How do they measure up to the research?. Internet Learning Journal, 4(1), 38-55.
- Ralston-Berg, P., & Nath, L. (2008). What makes a quality online course? The student perspective. Proceedings from the 24th annual conference on distance teaching and learning, 1-5.
- Roach, V., & Lemasters, L. (2006). Satisfaction with online learning: A comparative descriptive study. Journal of Interactive Online Learning, 5(3), 317-332.
- Roberts, J. (2016). Can technology genuinely reduce teacher workload? Retrieved March 15, 2020, from https://johnroberts.me/wp-content/uploads/2018/03/FINAL-FINAL.pdf
- Saade, R. G., & Kira, D. (2006). The emotional state of technology acceptance. Issues in Informing Science & Information Technology, 2006(3), 529-539. https://doi.org/10.28945/913
- Sener, J., & Humbert, J. (2003). Student satisfaction with online learning: An expanding universe. Elements of quality online education: Practice and direction, 4, 245-260.
- Shattuck, K. (2015). Focusing research on quality matters. American Journal of Distance Education, 29(3), 155-158. https://doi.org/10.1080/08923647.2015.1061809
- Sheng, D., & Chen, G. (2009). On the index model of teaching perceived quality and classroom teaching satisfaction. China Science and technology information, (23), 260-261.
- Stevens, J. P. (1992). Applied multivariate statistics for the social sciences (2nd ed.). New Jersey: Lawrence Erlbaum Associates.
- Su, H. (2021). Study on users, willingness to continue using online teaching platform under the epidemic situation-based on customer value theory. Journal of Hubei Radio & Television University, 41(03), 29-35.
- Swan, K. (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance education, 22(2), 306-331. https://doi.org/10.1080/0158791010220208
- Wang, N., Ju X., & Ge, Z. (2014). The analysis of influencing factors on learning satisfaction in open education network courses. Open Education Research, 20(6), 111-118.
- Wei, H. C., & Chou, C. (2020). Online learning performance and satisfaction: do perceptions and readiness matter?. Distance Education, 41(1), 48-69. https://doi.org/10.1080/01587919.2020.1724768
- Xie, Y., Liu C., Zhu J., & Yin, R. (2011). Research on the structure, influencing factors and training strategies of college students' e-learning self-efficacy. e-Education Research, (10), 30-34.
- Xu, X., Zhao, W., & Liu, H. (2017). Factors influencing college students' satisfaction in online learning. Distance Education in China, (5), 43-50.
- Yang, Li., & Wang, M. (2020). Study on college students' online learning satisfaction and analysis of the influencing factors during COVID-19: A case study of Nanjing University of Posts and Telecommunications. Jiangsu Science & Technology Information, (30), 51-56.
- Zhang, B., & Lin, B. (2014). An empirical research on students' satisfaction levels regarding undergraduate teaching quality: The perspectives of student expectations and student perceptions of quality. Fudan Education Forum, (04), 59-65.
- Zheng, L., & Liang, M. (2014). An empirical study on the effect of teacher guidance on collaborative learning. e-Education Research, 35(8), 89-94.
- Zuo, Q., Zhang, Y., & Li, B. (2021). Demand of online course teachers' teaching ability based on "student satisfaction model". China Poultry, 43(3), 118.