ABSTRACT
Considerable literature exists regarding MOOCs. Evaluations of MOOCs range from ringing endorsements to its vilification as a delivery model. Much evaluation focuses on completion rates and/or participant satisfaction. Overall, MOOCs are ill-defined and researchers struggle with appropriate evaluation criteria beyond attrition rates. In this paper, we provide a brief history of MOOCs, a summary of some evaluation research, and we propose a new model for evaluation with an example from a previously-delivered MOOC. Measurement of the MOOC success framework through four student satisfaction types is proposed in this paper with a model for informal learning satisfaction, one of the proposed types, theorized and tested. Results indicated theoretical underpinnings, while intended to improve instruction, might not have influenced the same satisfaction construct. Therefore, future research into alternative satisfaction factor models is needed.
- Allen, I. E., and Seaman, J. 2014. Grade change: Tracking online education in the United States. Babson Survey Research Group and Quahog Research Group, LLC, Oakland, CA. Available at http://www.onlinelearningsurvey.com/reports/gradechange.pdfGoogle Scholar
- Anderson, T., and McGreal, R. 2012. Disruptive pedagogies and technologies in universities. Educ Technol Soc. 15, 4, 380--389. Retrieved from http://www.ifets.info/Google Scholar
- Baggaley, J. 2013. MOOC rampant. Distance Education. 34, 3, 368--378. DOI=http://dx.doi.org/10.1080/01587919.2013.835768Google ScholarCross Ref
- Belanger, Y., and Thornton, J. 2013. Bioelectricity: A quantitative approach Duke University's first MOOC. Available at http://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/6216/duke_bioelectricity_mooc_fall2012.pdf?sequence=1.Google Scholar
- Bragg, A. B. 2014. MOOCs: Where to from here? Train Dev J. 41, 1, 20--21.Google Scholar
- Browne, M. W., and Cudeck, R. 1993. Alternative ways of assessing model fit. Sage focus editions. 154, 136--136.Google Scholar
- CotoNet. 2015. MOOC List. Available at https://www.mooc-list.comGoogle Scholar
- Deci, E. L., Vallerand, R. J., Pelletier, L. G., and Ryan, R. M. 1991. Motivation and education: The self-determination perspective. Educational psychologist. 26, 3-4, 325--346.Google Scholar
- Delclos, V. R. and Harrington, C. 1991. Effects of strategy monitoring and proactive instruction on children's problem-solving performance. J Educ Psychol. 83, 35--42.Google ScholarCross Ref
- Downes, S. 2012. The rise of MOOCs. Recuperado el, 1.Google Scholar
- Fini, A. 2009. The technological dimension of a Massive Open Online Course: The case of the CCK08 course tools. International Review of Research in Open and Distance Learning. 10, 5. Available at http://www.irrodl.org/index.php/irrodl/article/view/643/1402Google ScholarCross Ref
- Heutte, J., Kaplan, J., Fenouillet, F., Caron, P. A., and Rosselle, M. 2014. MOOC user persistence: Lessons from French educational policy adoption and deployment of a pilot course. In Learning Technology for Education in Cloud. MOOC and Big Data, L. Uden, J. Sinclair, Y. H. Tao and D. Liberona Ed. vol. 446. Springer International Publishing, New York, NY, 13--24.Google Scholar
- Hoffman, E. S. and Menchaca, M. P. 2015. Personal learning goals versus attrition in MOOCs: A learner framework for MOOC 2.0. In World Conference on E-Learning (Kona, Hawaii, 2015) Association for the Advancement of Computing in Education.Google Scholar
- Hu, L. T., and Bentler, P. M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal. 6, 1, 1--55.Google Scholar
- 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, 133--160. Available at http://www.irrodl.org/index.php/irrodl/article/view/1651Google ScholarCross Ref
- Kassabian, D. W. 2014. The value of MOOCs to early adopter universities. EDUCAUSE Review. Available at http://www.educause.edu/ero/article/value-moocs-early-adopter-universitiesGoogle Scholar
- Kevan, J., and Ryan, P. 2015. Experience API: Flexible, decentralized and activity-centric data collection. Technology, Knowledge and Learning. 1--7. DOI=http://dx.doi.org/10.1007/s10758-015-9260-xGoogle Scholar
- King, A. 1991. Effects of training in strategic questioning on children's problem-solving performance. J Educ Psychol. 83, 307--317.Google ScholarCross Ref
- Knox, J., Bayne, S., Macleod, H., Ross, J., and Sinclair, C. 2012. MOOCs pedagogy: The challenges of developing for Coursera. Association for Learning Technology Online Newsletter. Available at https://newsletter.alt.ac.uk/2012/08/mooc-pedagogy-the-challenges-of-developing-for-coursera/Google Scholar
- Koller, D., Ng, A., Do, C., and Chen, Z. 2013. Retention and intention in massive open online courses: In depth. Educause Review. 48, 3, 62--63. Available at http://www.educause.edu/ero/article/retention-and-intention-massive-open-online-courses-depth-0Google Scholar
- Liyanagunawardena, T. R. 2014. MOOC experience: A participant's reflection. ACM SIGCAS Computers and Society. 44, 1, 9--14. DOI=http://dx.doi.org/10.1145/2602147.2602149 Google ScholarDigital Library
- Liyanagunawardena, T. R., Adams, A. A., and Williams, S. A. 2013. MOOCs: A systematic study of the published literature 2008-2012. International Review of Research in Open and Distance Learning. 14, 3, 202--227. Available at http://www.irrodl.org/Google ScholarCross Ref
- Martin, F. G. 2012. Education: Will massive open online courses change how we teach? (Viewpoints). Communications of the ACM. 55, 8, 26. DOI=http://dx.doi.org/10.1145/2240236.2240246 Google ScholarDigital Library
- Milligan, C., Littlejohn, A., and Margaryan, A. 2013. Patterns of engagement in connectivist MOOCs. MERLOT Journal of Online Learning and Teaching. 9, 2, 149--159. Available at http://jolt.merlot.org/vol9no2/milligan_0613.htmGoogle Scholar
- Pirani, J. 2013. A compendium of MOOC perspectives, research, and resources. EDUCAUSE Review. Available at http://www.educause.edu/ero/article/compendium-mooc-perspectives-research-and-resourcesGoogle Scholar
- Raykov, T., and Marcoulides, G. A. 2012. A first course in structural equation modeling. Routledge. DOI=http://dx.doi.org/10.4324/9780203930687Google Scholar
- Reich, J. 2014. MOOC completion and retention in the context of student intent. EDUCAUSE Review. Available at http://www.educause.edu/ero/article/mooc-completion-and-retention-context-student-intentGoogle Scholar
- Reich, J. 2015. Rebooting MOOC research. Science. 347, 6217, 34--35. DOI=http://dx.doi.org/10.1126/science.1261627Google Scholar
- Siemens, G. 2005. Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning. 2, 1, 3--10. Available at http://www.itdl.org/Journal/Jan_05/article01.htmGoogle Scholar
- Siemens, G. 2012. MOOCs are really a platform {Blog}. Elearnspace. Available at http://www.elearnspace.org/blog/2012/07/25/moocs-are-really-a-platform/Google Scholar
- Siemens, G. 2013. Massive Open Online Courses: Innovation in education, In Open Educational Resources: Innovation, Research and Practice, R. McGreal, W. Kinuthia and S. Marshall Ed. Vancouver, BC Canada: Commonwealth of Learning and Athabasca University. 5--16.Google Scholar
- Stein, R. M., and Allione, G. 2014. Mass attrition: An analysis of drop out from a Principles of Microeconomics MOOC. PIER Working Paper 14-031: Penn Institute for Economic Research. DOI=http://dx.doi.org/10.2139/ssrn.2505028Google Scholar
- Vardi, M. Y. 2012. Will MOOCs destroy academia? (Editor's Letter). Communications of the ACM. 55, 11, 5. DOI=http://dx.doi.org/10.1145/2366316.2366317 Google ScholarDigital Library
- Wiley, D. 2012. The MOOC misnomer {Blog}. Iterating toward Openness. Available at http://opencontent.org/blog/archives/2436Google Scholar
- Yang, D., Sinha, T., Adamson, D., and Rose, C. P. 2013. Turn on, tune in, drop out: Anticipating student dropouts in massive open online courses, in Proceedings of the 2013 Annual Conference on Neural Information Processing Systems, Data-Driven Education Workshop (Lake Tahoe, Nevada, 2013) 10, 13.Google Scholar
- Yuan, L., Powell, S., and Cetis, J. 2013. MOOCs and open education: Implications for higher education.Google Scholar
- Zheng, S., Rosson, M. B., Shih, P. C., and Carroll, J. M. 2015. Understanding student motivation, behaviors and perceptions in MOOCs. ACM Press. 1882-1895. DOI=http://dx.doi.org/10.1145/2675133.2675217 Google ScholarDigital Library
Index Terms
- Designing MOOCs for success: a student motivation-oriented framework
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