Skip to main content
SpringerLink
Log in

Exploring the Factors Affecting Learning Satisfaction in MOOC: A Case Study of Higher Education in a Developing Country

  • Conference paper
  • First Online:
Learning and Collaboration Technologies (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14041))

Included in the following conference series:

  • 696 Accesses

Abstract

Massive Open Online Courses (MOOCs) are regarded as an educational revolution in the present digital era, particularly in the context of COVID-19. Although students worldwide enroll in MOOCs, a high dropout rate is typically an issue, at least when compared with traditional education. In developing countries, MOOCs have become essential for higher education as a solution to continue providing their curriculums for students during the COVID-19 outbreak. However, under the pandemic context, it is vital to understand the influencing factors which drive learners to use MOOCs successfully. This research proposed a conceptual model for examining the influential factors of Learner Satisfaction in improving MOOC learner retention rate during COVID-19. This research reports the online survey with open-end questions of 1,122 university students enrolled in Thai MOOC as the mandatory part of the curriculum. The results showed that Video Design, Course Content, Assessment, and Learner to Learner Interaction significantly positively affect Learner Satisfaction. In contrast, Instructor Feedback, Instructor Support, Instructor to Learner Interaction, and course structure have no significant influence on Learner Satisfaction. In addition, the proposed conceptual model correctly predicted Learner Satisfaction by over 78%.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Purkayastha, N., Sinha, M.K.: Unstoppable study with MOOCs during COVID 19 pandemic: a study. Libr. Philos. Pract. 4791 (2021)

    Google Scholar 

  2. UNESCO, G.: Education: from disruption to recovery. UNESCO Building peace in the minds of men and women (2020)

    Google Scholar 

  3. Liliana, L., Santosa, P.I., Kusumawardani, S.S.: Completion factor in massive open online course in developing countries: a literature review in 2015–2021. World J. Educ. Technol. Curr. Issues 14(2), 456–472 (2022)

    Article  Google Scholar 

  4. Gütl, C., Rizzardini, R.H., Chang, V., Morales, M.: Attrition in MOOC: lessons learned from drop-out students. In: Uden, L., Sinclair, J., Tao, Y.-H., Liberona, D. (eds.) Learning Technology for Education in Cloud. MOOC and Big Data, pp. 37–48. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10671-7_4

    Chapter  Google Scholar 

  5. Khalil, H., Ebner, M.: MOOCs completion rates and possible methods to improve retention-a literature review. In: EdMedia+ Innovate Learning, pp. 1305–1313 (2014)

    Google Scholar 

  6. Badali, M., Hatami, J., Banihashem, S.K., Rahimi, E., Noroozi, O., Eslami, Z.: The role of motivation in MOOCs’ retention rates: a systematic literature review. Res. Pract. Technol. Enhanced Learn. 17(1), 1–20 (2022)

    Google Scholar 

  7. Theeraroungchaisri, A., Khlaisang, J.: Thai MOOC sustainability: alternative credentials for digital age learners. In: CEUR Workshop Proceedings, vol. 2356, pp. 203–209 (2019)

    Google Scholar 

  8. Chunwijitra, S., Khanti, P., Suntiwichaya, S.: Development of MOOC service framework for life long learning: a case study of Thai MOOC. IEICE Trans. Inf. Syst. 103(5), 1078–1087 (2020)

    Article  Google Scholar 

  9. Khalid, B., Chaveesuk, S., Chaiyasoonthorn, W.: MOOCs adoption in higher education: a management perspective. Pol. J. Manag. Stud. 23, 239–256 (2021)

    Google Scholar 

  10. Goopio, J., Cheung, C.: The MOOC dropout phenomenon and retention strategies. J. Teach. Travel Tour. 21(2), 177–197 (2021)

    Google Scholar 

  11. Xing, W., Du, D.: Dropout prediction in MOOCs: using deep learning for personalized intervention. J. Educ. Comput. Res. 57(3), 547–570 (2019)

    Article  Google Scholar 

  12. Jordan, K.: Massive open online course completion rates revisited: assessment, length and attrition. Int. Rev. Res. Open Distrib. Learn. 16(3), 341–358 (2015)

    Google Scholar 

  13. Yang, M., Shao, Z., Liu, Q., Liu, C.: Understanding the quality factors that influence the continuance intention of students toward participation in MOOCs. Educ. Tech. Res. Dev. 65(5), 1195–1214 (2017). https://doi.org/10.1007/s11423-017-9513-6

    Article  Google Scholar 

  14. El Said, G.R.: Understanding how learners use massive open online courses and why they drop out: thematic analysis of an interview study in a developing country. J. Educ. Comput. Res. 55(5), 724–752 (2017)

    Article  Google Scholar 

  15. Rabin, E., Kalman, Y.M., Kalz, M.: An empirical investigation of the antecedents of learner-centered outcome measures in MOOCs. Int. J. Educ. Technol. High. Educ. 16(1), 1–20 (2019). https://doi.org/10.1186/s41239-019-0144-3

    Article  Google Scholar 

  16. Henderikx, M.A., Kreijns, K., Kalz, M.: Refining success and dropout in massive open online courses based on the intention–behavior gap. Distance Educ. 38(3), 353–368 (2017)

    Article  Google Scholar 

  17. Reich, J., Ho, A.: The tricky task of figuring out what makes a MOOC successful. The Atlantic (2014)

    Google Scholar 

  18. Chiu, T.K., Hew, T.K.: Factors influencing peer learning and performance in MOOC asynchronous online discussion forum. Australas. J. Educ. Technol. 34(4) (2018)

    Google Scholar 

  19. Davis, D., Jivet, I., Kizilcec, R.F., Chen, G., Hauff, C., Houben, G.-J.: Follow the successful crowd: raising MOOC completion rates through social comparison at scale (2017)

    Google Scholar 

  20. Du, B.: Research on the factors influencing the learner satisfaction of MOOCs. Educ. Inf. Technol. 28, 1935–1955 (2023). https://doi.org/10.1007/s10639-022-11269-0

    Article  Google Scholar 

  21. Hew, K.F., Hu, X., Qiao, C., Tang, Y.: What predicts student satisfaction with MOOCs: a gradient boosting trees supervised machine learning and sentiment analysis approach. Comput. Educ. 145, 103724 (2020)

    Article  Google Scholar 

  22. Rawat, S., Kumar, D., Kumar, P., Khattri, C.: A systematic analysis using classification machine learning algorithms to understand why learners drop out of MOOCs. Neural Comput. Appl. 33(21), 14823–14835 (2021). https://doi.org/10.1007/s00521-021-06122-3

    Article  Google Scholar 

  23. Anand Shankar Raja, M., Kallarakal, T.K.: “COVID-19 and students perception about MOOCs” a case of Indian higher educational institutions. Interact. Technol. Smart Educ. 18(3), 450–474 (2021)

    Google Scholar 

  24. Gaytan, J., McEwen, B.C.: Effective online instructional and assessment strategies. Am. J. Distance Educ. 21(3), 117–132 (2007)

    Article  Google Scholar 

  25. Luo, H., Robinson, A., Park, J.-Y.: Peer grading in a MOOC: reliability, validity, and perceived effects. Online Learn. J. 18(2) (2014)

    Google Scholar 

  26. Eriksson, T., Adawi, T., Stöhr, C.: “Time is the bottleneck”: a qualitative study exploring why learners drop out of MOOCs. J. Comput. High. Educ. 29(1), 133–146 (2016). https://doi.org/10.1007/s12528-016-9127-8

    Article  Google Scholar 

  27. Hew, K.F., Qiao, C., Tang, Y.: Understanding student engagement in large-scale open online courses: a machine learning facilitated analysis of student’s reflections in 18 highly rated MOOCs. Int. Rev. Res. Open Distrib. Learn. 19, 3 (2018)

    Google Scholar 

  28. Hone, K.S., El Said, G.R.: Exploring the factors affecting MOOC retention: a survey study. Comput. Educ. 98, 157–168 (2016)

    Article  Google Scholar 

  29. Wang, Y., Baker, R.: Content or platform: why do students complete MOOCs. MERLOT J. Online Learn. Teach. 11(1), 17–30 (2015)

    Google Scholar 

  30. Gomez-Zermeno, M.G., de La Garza, L.A.: Research analysis on MOOC course dropout and retention rates. Turk. Online J. Distance Educ. 17(2), 3–14 (2016)

    Google Scholar 

  31. Qu, H., Chen, Q.: Visual analytics for MOOC data. IEEE Comput. Graph. Appl. 35(6), 69–75 (2015)

    Article  Google Scholar 

  32. Tsai, Y.-H., Lin, C.-H., Hong, J.-C., Tai, K.-H.: The effects of metacognition on online learning interest and continuance to learn with MOOCs. Comput. Educ. 121, 18–29 (2018)

    Article  Google Scholar 

  33. Xiong, Y., Li, H., Kornhaber, M.L., Suen, H.K., Pursel, B., Goins, D.D.: Examining the relations among student motivation, engagement, and retention in a MOOC: a structural equation modeling approach. Glob. Educ. Rev. 2(3), 23–33 (2015)

    Google Scholar 

  34. Gregori, E.B., Zhang, J., Galván-Fernández, C., de Asís Fernández-Navarro, F.: Learner support in MOOCs: identifying variables linked to completion. Comput. Educ. 122, 153–168 (2018)

    Article  Google Scholar 

  35. Pursel, B.K., Zhang, L., Jablokow, K.W., Choi, G.W., Velegol, D.: Understanding MOOC students: motivations and behaviours indicative of MOOC completion. J. Comput. Assist. Learn. 32(3), 202–217 (2016)

    Article  Google Scholar 

  36. Alemayehu, L., Chen, H.-L.: Learner and instructor-related challenges for learners’ engagement in MOOCs: a review of 2014–2020 publications in selected SSCI indexed journals. Interact. Learn. Environ. 1–23 (2021)

    Google Scholar 

  37. Sujatha, R., Kavitha, D.: Learner retention in MOOC environment: analyzing the role of motivation, self-efficacy and perceived effectiveness. Int. J. Educ. Dev. ICT 14(2), 62–74 (2018)

    Google Scholar 

  38. Fesol, S.F.A., Salam, A., Shaarani, A.S.: An evaluation of students’ perception on MOOC instructional design elements. J. Appl. Environ. Biol. Sci. 7(10), 173–179 (2017)

    Google Scholar 

  39. Saxena, C., Baber, H., Kumar, P.: Examining the moderating effect of perceived benefits of maintaining social distance on e-learning quality during COVID-19 pandemic. J. Educ. Technol. Syst. 49(4), 532–554 (2021)

    Article  Google Scholar 

  40. Hair, J., Hollingsworth, C.L., Randolph, A.B., Chong, A.Y.L.: An updated and expanded assessment of PLS-SEM in information systems research. Ind. Manag. Data Syst. 117(3), 442–458 (2017)

    Article  Google Scholar 

  41. Hair, J.F., Gabriel, M., Patel, V.: AMOS covariance-based structural equation modeling (CB-SEM): guidelines on its application as a marketing research tool. Braz. J. Mark. 13(2), 44–55 (2014)

    Google Scholar 

  42. Anderson, J.C., Gerbing, D.W.: Structural equation modeling in practice: a review and recommended two-step approach. Psychol. Bull. 103(3), 411 (1988)

    Article  Google Scholar 

  43. Rust, R.T., Cooil, B.: Reliability measures for qualitative data: theory and implications. J. Mark. Res. 31(1), 1–14 (1994)

    Article  Google Scholar 

  44. Hair, J.F., Ortinau, D.J., Harrison, D.E.: Essentials of Marketing Research. McGraw-Hill/Irwin, New York (2010)

    Google Scholar 

  45. Fornell, C., Larcker, D.F.: Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Sage Publications, Los Angeles (1981)

    Google Scholar 

  46. Hair, J.F., Jr., Sarstedt, M., Ringle, C.M., Gudergan, S.P.: Advanced Issues in Partial Least Squares Structural Equation Modeling. Sage Publications, Los Angeles (2017)

    Google Scholar 

  47. Henseler, J., Ringle, C.M., Sarstedt, M.: A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 43(1), 115–135 (2014). https://doi.org/10.1007/s11747-014-0403-8

    Article  Google Scholar 

  48. Albelbisi, N.A., Al-Adwan, A.S., Habibi, A.: Impact of quality antecedents on satisfaction toward MOOC. Turk. Online J. Distance Educ. 22(2), 164–175 (2021)

    Article  Google Scholar 

  49. Dai, H.M., Teo, T., Rappa, N.A.: Understanding continuance intention among MOOC participants: the role of habit and MOOC performance. Comput. Hum. Behav. 112, 106455 (2020)

    Article  Google Scholar 

  50. Guo, P.J., Kim, J., Rubin, R.: How video production affects student engagement: an empirical study of MOOC videos (2014)

    Google Scholar 

  51. Li, N., Kidziński, Ł, Jermann, P., Dillenbourg, P.: MOOC video interaction patterns: what do they tell us? In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, É. (eds.) EC-TEL 2015. LNCS, vol. 9307, pp. 197–210. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24258-3_15

    Chapter  Google Scholar 

  52. Costello, E., Holland, J., Kirwan, C.: The future of online testing and assessment: question quality in MOOCs. Int. J. Educ. Technol. High. Educ. 15(1), 1–14 (2018). https://doi.org/10.1186/s41239-018-0124-z

    Article  Google Scholar 

  53. Alexandron, G., Wiltrout, M.E., Berg, A., Ruipérez-Valiente, J.A.: Assessment that matters: balancing reliability and learner-centered pedagogy in MOOC assessment (2020)

    Google Scholar 

  54. Gameel, B.G.: Learner satisfaction with massive open online courses. Am. J. Distance Educ. 31(2), 98–111 (2017)

    Article  MathSciNet  Google Scholar 

  55. Watted, A., Barak, M.: Motivating factors of MOOC completers: comparing between university-affiliated students and general participants. Internet High. Educ. 37, 11–20 (2018)

    Article  Google Scholar 

  56. Sunar, A.S., Abbasi, R.A., Davis, H.C., White, S., Aljohani, N.R.: Modelling MOOC learners’ social behaviours. Comput. Hum. Behav. 107, 105835 (2020)

    Article  Google Scholar 

Download references

Acknowledgment

We would like to convey our sincere gratitude to the School of Languages and General Education at Walailak University for their assistance in conducting a research survey of students and faculty regarding ThaiMOOC teaching and learning.

Author information

Authors and Affiliations

  1. Brunel University London, Uxbridge, UB8 3FG, UK

    Kanitsorn Suriyapaiboonwattana & Kate Hone

Authors
  1. Kanitsorn Suriyapaiboonwattana
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kate Hone
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kanitsorn Suriyapaiboonwattana .

Editor information

Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  2. Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Suriyapaiboonwattana, K., Hone, K. (2023). Exploring the Factors Affecting Learning Satisfaction in MOOC: A Case Study of Higher Education in a Developing Country. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14041. Springer, Cham. https://doi.org/10.1007/978-3-031-34550-0_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-34550-0_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34549-4

  • Online ISBN: 978-3-031-34550-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation