COMMUNITY TRACKING IN A cMOOC AND NOMADIC LEARNER BEHAVIOR IDENTIFICATION ON A CONNECTIVIST RHIZOMATIC LEARNING NETWORK

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.

How Learners Participate in Connectivist Learning: An Analysis of the Interaction Traces From a cMOOC

“…We also examined learners' participation by various technologies (technology network) by the social network of a space and around topic and topic generation process. Each of these approaches can be analysed and compared from both quantitative and qualitative perspectives (Skrypnyk et al, 2015;Bozkurt et al, 2016). This will be a future focus of our study.…”

“…Bozkurt and colleagues (2016) analysed interactions, community formation, and nomadic learner behavior in Twitter for a six-week long MOOC within a social network and Community of Inquiry framework. These studies have shown us how learners participate in cMOOCs from the information flow and community formulation perspectives; however, just as the author reported in their study, their limitation was that they only focused on the interaction in Twitter (Skrypnyk et al, 2015;Bozkurt et al, 2016). Though Twitter is one of the main media adopted by most participants, the cMOOC was also supported by the course website, blog, Facebook, and many other technologies.…”

“…These include the following perspectives: the delivery model innovation introduction of a cMOOC (Fini, 2009;Rodriguez, 2013); Personal Learning Environment design and development with distributed technologies (Kop, 2010;Fournier, Kop, & Durand, 2014); learners participation and learning experience (Saadatmand & Kumpulainen, 2014;Smith & Eng, 2013;Levy, 2011;Kop, 2011;Mackness, Mak, & Williams, 2010), and a focus on facilitators' experiences (Arnold, Kumar, Thillosen, & Ebner, 2014). Some studies (Siemens, 2011c;Milligan, Littlejohn, & Margaryan, 2013Skrypnyk, Joksimović, Kovanović, Gašević, & Dawson, 2015;Bozkurt et al, 2016, Wang et al, 2017 relate directly to the pattern of interaction and communication observed in these connectivist learning environments. However, in Milligan and his colleagues 's research, the number of participants interviewed is limited compared with the massive number of learners enrolled in the course.…”

Exploring a Personal Social Knowledge Network (PSKN) to aid the observation of connectivist interaction for high‐ and low‐performing learners in connectivist massive open online courses

“…Besides, a variety of approaches was used to diagnose learning behavior in cMOOCs contexts, for instance, deductive analysis of qualitative data (Wang et al, ), content analytics (Wang et al, ) as well as social media analytics (Bozkurt et al, ), etc. Specifically, deductive qualitative analysis is often used to establish the framework of connection interaction.…”

Developing a Strategic Approach to MOOCs

“…Other approaches that support discussion are to highlight content that contributes to learning by commenting on it, or asking learners to link to videos and photographs and then comment on these to initiate interactions. MOOC learners are often nomadic and will move between communities, forming sub-communities within those platforms, and hashtags can be used to bring those groups together (Bozkurt et al, 2016).…”