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Community tracking in a cMOOC and nomadic learner behaviour identification on a connectivist rhizomatic learning network

TitleCommunity tracking in a cMOOC and nomadic learner behaviour identification on a connectivist rhizomatic learning network
Publication TypeJournal Article
Year of Publication2016
AuthorsBozkurt, A., Honeychurch S., Caines A., Bali M., Koutropoulos A., & Cormier D.
PublisherTurkish Online Journal of Distance Education
Volume17
Start Page4
Issue4
Pagination4-30
Date Published10/2016
Type of WorkJournal Article
Publication LanguageEnglish
ISSN1302-6488
Keywordscommunity tracking, connectivism, massive open online courses, MOOCs, nomadic learner behaviors, rhizomatic learning
Abstract

This article contributes to the literature on connectivism, connectivist MOOCs (cMOOCs) and rhizomatic learning by examining participant interactions, community formation and nomadic learner behavior in a particular cMOOC, #rhizo15, facilitated for 6 weeks by Dave Cormier. It further focuses on what we can learn by observing Twitter interactions particularly. As an explanatory mixed research design, Social Network Analysis and content analysis were employed for the purposes of the research. SNA is used at the macro, meso and micro levels, and content analysis of one week of the MOOC was conducted using the Community of Inquiry framework. The macro level analysis demonstrates that communities in a rhizomatic connectivist networks have chaotic relationships with other communities in different dimensions (clarified by use of hashtags of concurrent, past and future events). A key finding at the meso level was that as #rhizo15 progressed and number of active participants decreased, interaction increased in overall network. The micro level analysis further reveals that, though completely online, the nature of open online ecosystems are very convenient to facilitate the formation of community. The content analysis of week 3 tweets demonstrated that cognitive presence was the most frequently observed, while teaching presence (teaching behaviors of both facilitator and participants) was the lowest. This research recognizes the limitations of looking only at Twitter when #rhizo15 conversations occurred over multiple platforms frequented by overlapping but not identical groups of people. However, it provides a valuable partial perspective at the macro meso and micro levels that contribute to our understanding of community-building in cMOOCs.

URLhttps://www.academia.edu/28829039/Community_Tracking_in_a_cMOOC_and_Nomadic_Learner_Behaviour_Identification_on_a_Connectivist_Rhizomatic_Learning_Network
DOIhttp://dx.doi.org/10.17718/tojde.09231
Rights

Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

Short TitleTOJDE
Refereed DesignationRefereed
AttachmentSize
1368-published.pdf1.42 MB
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