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Analysis of the Impact of Students' Perception of Course Quality on Online Learning Satisfaction

  • Received : 2021.09.12
  • Accepted : 2021.10.18
  • Published : 2021.10.31

Abstract

In the early 2020, COVID-19 changed the traditional way of teaching and learning. This paper aimed to explore the impact of college students' perception of course quality on their online learning satisfaction. A total of 4,812 valid samples were extracted, and the difference analysis and hierarchical regression analysis were used to make an empirical analysis of college students' online learning satisfaction. The research results were as follows. Firstly, there was no difference in online learning satisfaction among students by gender and grade. Secondly, learning assessment, course materials, course activities and learner interaction, and course production had a significant positive impact on online learning satisfaction. Course overview and course objectives had an insignificant correlation with online learning satisfaction. Thirdly, the total effect of online learning satisfaction was as follows. Course production had the greatest effect, followed by course activities and student-student interactions, followed by course materials. It was the learning evaluation that showed the least effect. This study can provide empirical reference for college teachers on how to continuously improve online teaching and increase students' satisfaction with online learning.

Keywords

References

  1. 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
  2. Allen, I. E., & Seaman, J. (2010). Class differences: Online education in the United States. Sloan Consortium (NJ1).
  3. 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
  4. 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
  5. 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
  6. 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
  7. Chen, W., & Cao, P. (2020). Implementation situation and reflection on online teaching in Double First-Cass universities. Edcation science, 36(2), 24.
  8. 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.
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. Hanna, D. E., Glowacki-Dudka, M., & Conceigao-Runlee, S. (2000). Practical tips for teaching online groups: Essentials of web-based education. Wisconsin: Atwood Publishing.
  20. Hara, N., & Kling, R. (1999). Students' frustrations with a web-based distance education course. Communication & Society, 3(4), 557-579.
  21. 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
  22. Hu, Y., & Zhao, F. (2015). Theoretical analysis model and measurement of online learning effectiveness. e-Education Research, 36(10), 37-45.
  23. 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.
  24. 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
  25. 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.
  26. 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.
  27. Jones, I. S., & Blankenship, D. (2017). Student perceptions of online courses. Research in Higher Education Journal, 32, 1-9.
  28. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. https://doi.org/10.1007/BF02291575
  29. 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
  30. Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). New York: Guilford publications.
  31. 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
  32. 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
  33. 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
  34. 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.
  35. 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
  36. 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.
  37. 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
  38. Mumford, S., & Dikilitas, K. (2020). Pre-service language teachers reflection development through online interaction in a hybrid learning course. Computers & Education, 144, 1-25.
  39. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
  40. 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
  41. Qian, Y. (2015). Factors affecting the continued use of online learning user behavior. Journal of Modern Information, 2015(3), 50-56.
  42. 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
  43. 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.
  44. 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.
  45. Roach, V., & Lemasters, L. (2006). Satisfaction with online learning: A comparative descriptive study. Journal of Interactive Online Learning, 5(3), 317-332.
  46. 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
  47. 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
  48. Sener, J., & Humbert, J. (2003). Student satisfaction with online learning: An expanding universe. Elements of quality online education: Practice and direction, 4, 245-260.
  49. 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
  50. 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.
  51. Stevens, J. P. (1992). Applied multivariate statistics for the social sciences (2nd ed.). New Jersey: Lawrence Erlbaum Associates.
  52. 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.
  53. 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
  54. 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.
  55. 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
  56. 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.
  57. Xu, X., Zhao, W., & Liu, H. (2017). Factors influencing college students' satisfaction in online learning. Distance Education in China, (5), 43-50.
  58. 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.
  59. 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.
  60. Zheng, L., & Liang, M. (2014). An empirical study on the effect of teacher guidance on collaborative learning. e-Education Research, 35(8), 89-94.
  61. Zuo, Q., Zhang, Y., & Li, B. (2021). Demand of online course teachers' teaching ability based on "student satisfaction model". China Poultry, 43(3), 118.