Learning Design for Student Retention
DOI:
https://doi.org/10.14297/jpaap.v6i2.318Keywords:
Retention, learning design, higher education, distance education, student completionAbstract
Student retention is an issue of increasing interest to higher education institutions, educators and students. Much of the work in this area focuses on identifying and improving interventions that occur during the presentation of a course. This paper suggests that these represent only one set of factors that can influence student withdrawal, and equally important are design based factors that can aid retention throughout the course. The main research question addressed by the paper is what design-related factors impact on student retention. An analysis of student withdrawal at the UK Open University conducted by the researchers produced a synthesis of seven key factors in the design phase that can influence retention. These factors have been given the ICEBERG acronym: Integrated, Collaborative, Engaging, Balanced, Economical, Reflective and Gradual. Examples of how these factors can be implemented are provided, and conclusions focus on how the model has been embedded in the module production process at the Open University.
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doi: https://doi.org/10.1080/02680513.2013.847363
Terry, N. (2001). Assessing enrollment and attrition rates for the online MBA. T.H.E. Journal, 28(7): 64–68.
Thompson, E. (1997). Distance education drop-out: What can we do? In R. Pospisil & L. Willcoxson (Eds.), Learning Through Teaching, 324–332. Proceedings of the 6th Annual Teaching Learning Forum, Perth, Australia: Murdoch University.
Thorpe, K. (2004). Reflective learning journals: From concept to practice. Reflective practice, 5(3), 327-343.
doi: https://doi.org/10.1080/1462394042000270655
Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1), 89-125.
doi: https://doi.org/10.3102/00346543045001089
Van Ameijde, J. (2014). Student Workload Evaluation Project – Interim Findings and Recommendations. Internal report. Milton Keynes: The Open University.
Whitelock, D., Thorpe, M., & Galley, R. (2015). Student Workload: a case study of its significance, evaluation and management at the Open University. Distance Education, 36(2) 161-176.
doi: https://doi.org/10.1080/01587919.2015.1055059
Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 13(3), 115-127.
Yuan, L., & Powell, S. (2013). MOOCs and open education: Implications for higher education. Jisc/CETIS
Astleitner, H. (2000). Dropout and distance education. A review of motivational and emotional strategies to reduce dropout in web-based distance education. Online. Available: http://daisy.fmi.uni-passau.de//lebre/ss99/ringvorlesung/material/astleitnerabstract.html.
Australian Dept of Education and Training (2017). Discussion Paper on Improving Completion, Retention and Success in Higher Education. https://docs.education.gov.au/documents/discussion-paper-improving-completion-retention-and-success-higher-education
Bean, J., & Metzner, B. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research, 55, 485- 650.
doi: https://doi.org/10.3102/00346543055004485
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77-101.
doi: https://doi.org/10.1191/1478088706qp063oa
Clegg, S., Tan, J., & Saeidi, S. (2002). Reflecting or acting? Reflective practice and continuing professional development in higher education. Reflective Practice, 3(1), 131-146.
doi: https://doi.org/10.1080/14623940220129924
Chyung, Y., Winiecki, D., & Fenner, J. A. (1999). Evaluation of effective interventions to solve the dropout problem in adult distance education. Proceedings of EdMedia 1999, 51-55. Seattle, WA.
Dutton, J., Dutton M., & Perry, J. (1999). Do online students perform as well as lecture students? Journal of Engineering Education, 90(1), 131–139.
doi: https://doi.org/10.1002/j.2168-9830.2001.tb00580.x
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking and computer conferencing: a model and tool to access cognitive presence. American Journal of Distance Education, 15(1), 7–23.
doi: https://doi.org/10.1080/08923640109527071
Glaser, B. G., & Strauss, A. (1967). A Discovery of Grounded Theory. Strategies for Qualitative Research, Sociology Press.
Glogowska, M., Young, P., & Lockyer, L. (2007). Should I go or should I stay? A study of factors influencing students’ decisions on early leaving. Learning in Higher Education, 8(1), 63–77.
doi; https://doi.org/10.1177/1469787407074115
Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks: Some preliminary results. Journal of Asynchronous Learning Networks, 1(2): 1-19.
Hone, K. S., & El Said, G. R. (2016). Exploring the factors affecting MOOC retention: A survey study. Computers & Education, 98, 157-168.
doi: https://doi.org/10.1016/j.compedu.2016.03.016
Johnson, D. W., & Johnson, R. T. (1999). Learning together and alone: cooperative, competitive, and individualistic learning (5th ed.). Boston: Allyn & Bacon.
Jordan, K. (2014). Initial trends in enrolment and completion of massive open online courses. The International Review of Research in Open and Distributed Learning, 15(1).
doi: https://doi.org/10.19173/irrodl.v15i1.1651
Kember, D. (1995). Open learning courses for adults: A model of student progress. Englewood Cliffs, NJ: Educational Technology Publications.
Khalil, H., & Ebner, M. (2014). MOOCs completion rates and possible methods to improve retention-A literature review. In EdMedia: World Conference on Educational Media and Technology (pp. 1305-1313). Association for the Advancement of Computing in Education (AACE).
Kizilcec, R.F., Piech, C., & Schneider, E. (2013). Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. Proceedings of the Third International Conference on Learning Analytics and Knowledge, ACM (2013), 170-179.
doi: https://doi.org/10.1145/2460296.2460330
Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59(5), 593-618.
doi: https://doi.org/10.1007/s11423-010-9177-y
Martinez, P., & Munday, F (1998). 9000 voices: Student persistence and dropout in further education. FEDA Report Vol. 2 No 7. London, UK: Further Education Development Agency.
OECD (2014). Education at a Glance 2014 OECD indicators. https://www.oecd.org/edu/Education-at-a-Glance-2014.pdf
Park, C.L., Perry, B., & Edwards, M. (2011). Minimising attrition: strategies for assisting students who are at risk of withdrawal. Innovations in Education and Teaching International, 48(1), 37-47.
doi: https://doi.org/10.1080/14703297.2010.543769
Perry, B., Boman, J., Care, W. D., Edwards, M., & Park, C. (2008). Why do students withdraw from online graduate nursing and health studies education: A descriptive study. Journal of Educators Online, 5(1), 1-17.
doi: https://doi.org/10.9743/JEO.2008.1.2
Poellhuber, B., Chomienne, M., & Karsenti, T. (2008). The effect of peer collaboration and collaborative learning on self-efficacy and persistence in a learner-paced continuous intake model. Journal of Distance Education, 22(3), 41–62.
Rovai (2003). In search of higher persistence rates in distance education online programs. The Internet and Higher Education, 6, 1-16.
Simpson, O. (2004). The impact on retention of interventions to support distance learning students. Open Learning: The Journal of Open and Distance Learning, 19(1), 79–95.
doi: https://doi.org/10.1080/0268051042000177863
Simpson, O. (2013). Student retention in distance education: are we failing our students? Open Learning, 28(2), 105-119.
doi: https://doi.org/10.1080/02680513.2013.847363
Terry, N. (2001). Assessing enrollment and attrition rates for the online MBA. T.H.E. Journal, 28(7): 64–68.
Thompson, E. (1997). Distance education drop-out: What can we do? In R. Pospisil & L. Willcoxson (Eds.), Learning Through Teaching, 324–332. Proceedings of the 6th Annual Teaching Learning Forum, Perth, Australia: Murdoch University.
Thorpe, K. (2004). Reflective learning journals: From concept to practice. Reflective practice, 5(3), 327-343.
doi: https://doi.org/10.1080/1462394042000270655
Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1), 89-125.
doi: https://doi.org/10.3102/00346543045001089
Van Ameijde, J. (2014). Student Workload Evaluation Project – Interim Findings and Recommendations. Internal report. Milton Keynes: The Open University.
Whitelock, D., Thorpe, M., & Galley, R. (2015). Student Workload: a case study of its significance, evaluation and management at the Open University. Distance Education, 36(2) 161-176.
doi: https://doi.org/10.1080/01587919.2015.1055059
Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 13(3), 115-127.
Yuan, L., & Powell, S. (2013). MOOCs and open education: Implications for higher education. Jisc/CETIS
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2018-09-05
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