As I mentioned in the EDTECH537 – Week 5 entry for my EDTECH537 – Blogging In The Classroom course, I wanted to post a sample of a guest blog entry.
This guest post is contributed by Cathy Cavanaugh, PhD, who is the Director of Teaching and Learning, Worldwide Education, Microsoft Corporation. She can be reached at cathy.cavanaugh-at-microsoft.com. As is the tradition at Virtual School Meanderings, this will be the only entry today.
Massively Open Online Courses (MOOCs) were developed in the mid-2000s to open access to US higher education to the global audience, especially learners who were not enrolled in a degree program, by offering free course materials and experiences without credit or entry requirements (Liyanagunawardena, Adams, & Williams, 2013). Hundreds of MOOCs for millions of learners have been offered under a range of models around the world, as shown in the table below. See MOOC List for examples, http://www.mooc-list.com/
Table. MOOC delivery models
|Public college or universityPrivate or profit college or university
K-12 education authority
For-profit education provider
|PublicStudents enrolled at sponsor institution
Target audience, such as a profession or interest group
|By providerBy sponsor or advertisers
By students seeking a credential (certificate, badge)
By students seeking credit
Likewise, the learner experiences vary in MOOCs.
- Course lengths range from a few weeks to a year, or self-paced
- Student engagement may center on receptive activity such as using video lectures and other media, and reading ebooks; moderate episodic productive engagements such as brief computer-scored knowledge assessments or lower-order responses in forums; or intensive productive interactions such as sustained discussions, projects, and media creation
- Feedback to learners may be automated, peer-to-peer, or from instructors; often differential feedback depends on whether students pay fees or take the course for credit
- Pedagogical approaches include cMOOC, Downes’ learner-centered Connectivist type driven by human networks (Pence, 2013); xMOOC, a instructor/content-centered commercial and automated type driven by data (Pence, 2013); MOORC, Cavanaugh’s discovery-centered open research community driven by knowledge generation
Because the purposes of MOOCs vary and learners self-identify, they are designed to prioritize access rather than success. Therefore completion rates have been quite low. Critics see this situation as a disadvantage and focus on the cost/completer as a reason to discourage providers and learners from participating (Morris, 2013). Proponents see the large discrepancy between starters and finishers as evidence that the mission has been accomplished because a great many participants have experienced at least part of a course that otherwise would not be available to them, and most participants complete some learning (Morris, 2013). In a MOOC, the learners decide what and how much to learn. Their goals are individual and often do not have complete correspondence with course objectives.
Therefore, MOOCs are currently suited to some learning goals, as shown in the table below.
|MOOCs are well suited for
||MOOCs are less suited for
|Learners unable to access other education programsInformal learning by individuals seeking new skills or community networks
Learners using modules for specific learning that is more structured than using text or other media
Students assessing readiness, remediation, or a refresher for a credit course
Instructors expanding their teaching repertoire
Independent exploration of a domain
Institutional marketing or orientation
Public outreach by organizations
Experimenting with content and design due to the large amount of data generated
|Learners in need of structure and feedbackLearning in ill-defined or complex performance-based domains
Developing high levels of expertise requiring coaching or mentoring
The full range of experiences that comprise most degree programs
Existing communities with specific product goals
For online and blended professional learning, a MOOC is a feasible and valuable model to consider for certain informal knowledge bases when openness and inclusivity are priorities, but not when acquiring specific objectives by specific audiences are priorities. A MOOC as a long-term goal would broaden the professional community.
For online and blended student learning, a MOOC is a scalable way to personalize learning for students who seek or need specialized knowledge, accelerated learning, or connections with specific communities of scholars.
Learning Theory applied to MOOCs
||Research on Practice
||Social Learning: observational learning (Bandura)
||Class sizes optimal at under 20: accommodated using fluid and focused discussion and project groups (Monks & Schmidt)
||Andragogy: choice and differentiation to account for varying experience and goals (Knowles)Expertise: time, practice, and feedback are needed (Ericsson, Krampe & Tesch-Romer)
||Personalized learning and Flexible pathways: afford individualized mastery learning (Gates Foundation; iNACOL)Expanded learning time: efficient online (Liu & Cavanaugh)
Control and Connection: contribute to online learning (Repetto, Cavanaugh, Wayer & Liu)
||Effective when well-designed and facilitated: meta-analyses (Cavanaugh)
||Transactional distance: minimized with more interaction, structure and autonomy (Moore)Motivation: enhanced through feedback (Keller)
||Attention and Relevance are supported by course designs; Confidence and Satisfaction are supported by experienced instructors. (Carpenter & Cavanaugh)
Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice Hall.
Bandura, A. (1986). Social Foundations of Thought and Action. Englewood Cliffs, NJ: Prentice-Hall.
Carpenter, J. & Cavanaugh, C. (2012). Increasing Student Motivation through Mentoring Practices. In L. Archambault & K. Kennedy (Eds.), Lessons Learned in Teacher Mentoring: Supporting Educators in K-12 Online Learning Environments. Vienna, VA: iNACOL.
Cavanaugh, C. (2009). Distance education in support of extended learning time in K-12 schools. Washington, DC: Center for American Progress.
Downes, S. (2006). Learning networks and connective knowledge. Accessed at http://it.coe.uga.edu/itforum/paper92/paper92.html
Downes, S. (2007). What connectivism is [Web log post]. Accessed at http://halfanhour.blogspot.com/2007/02/what-connectivism-is.html
Downes, S. (2009, December 4). Re: The reciprocity economy [Web log post comment]. Accessed at http://nogoodreason.typepad.co.uk/no_good_reason/2009/04/the-reciprocity-economy.html?cid=6a00d8341c0c0e53ef01156f1ec449970c#comment-6a00d8341c0c0e53ef01156f1ec449970c
Ericsson K, Krampe R, Tesch-Romer, C: The Role of Deliberate Practice in the Acquisition of Expert Performance. Psychological Review 1993, 100:3, 363-406.
Keller, J. (1983). Motivational design of instruction. In C. Riegeluth (ed.), Instructional Design Theories and Models. Hillsdale, NJ: Erlbaum.
Knowles, M. (1984). Andragogy in Action. San Francisco: Jossey-Bass.
Liu, F. & Cavanaugh, C. (2011). Online Core Course Success Factors in Virtual School: Factors influencing student academic achievement. International Journal of E-Learning 10(4)43-65.
Liyanagunawardena, T; Adams, A; & Williams, S. (2013). MOOCs: A systematic study of the published literature 2008-2012. The International Review of Research in Open and Distance Learning, [S.l.], v. 14, n. 3, p. 202-227. SSN 1492-3831. Available at http://www.irrodl.org/index.php/irrodl/article/view/1455/2531
Monks, J., & Schmidt, R. M. (2011). The Impact of Class Size on Outcomes in Higher Education. The BE Journal of Economic Analysis & Policy, 11(1).
Moore, M.G. (2007). The Theory of Transactional Distance. In M.G.Moore (Ed.) (2007) The Handbook of Distance Education. Second Edition. Mahwah, N.J. Lawrence Erlbaum Associates. pp. 89–108.
Morris, L. V. (August 08, 2013). MOOCs, Emerging Technologies, and Quality. Innovative Higher Education, 38, 4, 251-252.
Pence, H. E. (2012). When Will College Truly Leave the Building: If MOOCs are the Answer, What Is the Question?. Journal Of Educational Technology Systems, 41(1), 25-33.
Repetto, J., Cavanaugh, C., Wayer, N., & Liu, F. (2010). Virtual High Schools: Improving Outcomes for Students with Disabilities. Quarterly Review of Distance Education, 11(2), 91-104.
Siemens, G. (2003). Learning ecology, communities, and networks: Extending the classroom. elearnspace. Available at http://www.elearnspace.org/Articles/learning_communities.htm
Siemens, G. (2005). Connectivism: A learning theory for the digital age. Available at http://www.itdl.org/Journal/Jan_05/article01.htm
Siemens, G. (2006). Knowing knowledge. Available at http://ltc.umanitoba.ca/KnowingKnowledge/index.php/Main_Page
Siemens, G. (2008). Learning and knowing in networks: Changing roles for educators and designers. Available at http://www.ipcp.org.br/References/Education/Siemens.pdf
This guest post is contributed by Cathy Cavanaugh, PhD, who is the Director of Teaching and Learning, Worldwide Education, Microsoft Corporation. She can be reached at cathy.cavanaugh-at-microsoft.com.