Skip to main content

Attrition in MOOC: Lessons Learned from Drop-Out Students

  • Conference paper
Learning Technology for Education in Cloud. MOOC and Big Data (LTEC 2014)

Abstract

Despite the popularity of Massive Open Online Course (MOOC), recent studies have found that completion rates are low with some reported to be significantly lower than 10%. The low retention and completion rates are major concerns for educators and institutions. This paper investigates motivations for enrolling in a MOOC on the topic of ‘e-learning’ and discusses reasons for the attrition rates during the course. A survey of 134 students who had not completed the MOOC reveals that only 22% of the students had intended to complete the MOOC but was unable to due to various factors including academic and personal reasons. A big majority of the students indicated that changes in their job, insufficient time, difficulty with the subject matter and unchallenging activities are some of the reasons for the drop-out.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adamopoulos, A.: What Makes a Great MOOC? An Interdisciplinary Analysis of Student Retention in Online Courses. In: Proceedings of the 34th International Conference on Information Systems (ICIS), Milan, Italy (2013)

    Google Scholar 

  2. Bean, J., Metzner, B.S.: A Conceptual Model of Nontraditional Undergraduate Student Attrition. Review of Educational Research 55, 485–540 (1985)

    Article  Google Scholar 

  3. Berge, Z.L., Huang, Y.P.: A Model for Sustainable Student Retention: A Holistic Perspective on the Student Dropout Problem with Special Attention to e-Learning. DEOSNEWS 13(5) (May 2004)

    Google Scholar 

  4. Brooke, J.: SUS: A ‘quick and dirty’ usability scale. Usability Evaluation in Industry. Taylor & Francis, London (1996)

    Google Scholar 

  5. Chamberlin, L., Parish, T.: MOOCs: Massive open online courses or massive and often obtuse courses? eLearn 8 (2011), http://doi.acm.org/10.1145/2016016.2016017 , doi:10.1145/2016016.2016017

  6. Croft, N., Dalton, A., Grant, M.: Overcoming Isolation in Distance Learning: Building a Learning Community through Time and Space. Journal for Education in the Built Environment 5(1) (July 2010)

    Google Scholar 

  7. Daniel, J.: Making sense of MOOCs: Musings in a maze of myth, paradox and possibility. Journal of Interactive Media in Education, 18 (2012), http://jime.open.ac.uk/2012/18 (accessed February 26, 2013)

  8. Hernández Rizzardini, R., Amado-Salvatierra, H., Gütl, C.: Cloud-based Learning Environments: Investigating learning activities experiences from Motivation, Usability and Emotional Perspective. In: Proceedings of the 5th International Conference on Computer Supported Education, Aachen, Germany (May 2013)

    Google Scholar 

  9. Hernández Rizzardini, R., Gütl, C., Chang, V., Morales, M.: MOOC in Latin America: Implementation and Lessons Learned. In: 2nd International Workshop on Learning Technology for Education in Cloud (LTEC), Knowledge Management in Organizations, pp. 147–158. Springer Netherlands (2013)

    Google Scholar 

  10. Kay, R.H., Loverock, S.: Assessing emotions related to learning new software: The computer emotion scale. Computers in Human Behavior 24, 1605–1623 (2008)

    Article  Google Scholar 

  11. Kizilcec, R.F., Piech, C., Schneider, E.: Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses. In: Proceedings of 3rd International Conference on Learning Analytics and Knowledge, Leuven, Belgium (2013), http://www.stanford.edu/~cpiech/bio/papers/deconstructingDisengagement.pdf . (accessed April 22, 2013)

  12. Lee, Y., Choi, J., Kim, T.: Discriminating factors between completers of and dropouts from online learning courses. British Journal of Educational Technology 44(2), 328–337 (2013)

    Article  Google Scholar 

  13. Liu, M., Kang, J., Cao, M., Lim, M., Ko, Y., Schmitz Weiss, A.: Understanding MOOCs as an Emerging Online Learning Tool: Perspectives from the Students. In: Proceedings of E-Learn (2013)

    Google Scholar 

  14. McAuley, A., Stewart, B., Siemens, G., Cormier, D.: The MOOC model for digital practice (2010), http://www.elearnspace.org/Articles/MOOC_Final.pdf (accessed February 2, 2013)

  15. Rodriguez, O.: The concept of openness behind c and x-MOOCs (Massive Open Online Courses). Open Praxis 5(1), 67–73 (2013)

    Article  Google Scholar 

  16. Rovai, A.P.: In search of higher persistence rates in distance education online programs. The Internet and Higher Education 6, 1–16 (2003), http://cmapspublic2.ihmc.us/rid%3D1150160110784_1923299501_2758/rovai%25202003%2520persistenace%2520in%2520de%2520and%2520online%2520ed-%2520theory.pdf (accessed February 2, 2014)

  17. Siemens, G.: MOOCs are really a platform. Elearnspace (2012), http://www.elearnspace.org/blog/2012/07/25/moocs-are-really-a-platform/ (last edited July 25, 2012) (accessed 15 February 2013)

  18. Tseng, S.C., Tsai, C.C.: Taiwan college students’ self-efficacy and motivation of learning in online peer-assessment environments. Internet and Higher Education 13, 164–169 (2010)

    Article  Google Scholar 

  19. Willging, P.A., Johnson, S.D.: Factors that Influence Students’ Decision to Dropout of Online Courses. Journal of Asynchronous Learning Networks, 8(4) (December 2004)

    Google Scholar 

  20. Yang, D., Sinha, T., Adamson, D., Rose, C.P.: Turn on, Tune in, Drop out: Anticipating student dropouts in Massive Open Online Courses. In: NIPS Data-Driven Education Workshop (2013), http://lytics.stanford.edu/datadriveneducation/papers/yangetal.pdf (accessed February 2, 2014)

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Gütl, C., Rizzardini, R.H., Chang, V., Morales, M. (2014). Attrition in MOOC: Lessons Learned from Drop-Out Students. In: Uden, L., Sinclair, J., Tao, YH., Liberona, D. (eds) Learning Technology for Education in Cloud. MOOC and Big Data. LTEC 2014. Communications in Computer and Information Science, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-319-10671-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10671-7_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10670-0

  • Online ISBN: 978-3-319-10671-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics