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Ge Mu

Diplômé DBA - 2019

Titre de thèse

Structure and evolution of virtual learning communities in massive open online courses

Superviseur(s)

Jie Yan
Purpose MOOC has seen rapid development worldwide. It is expected to help reduce the cost of higher education, realize educational equality, and promote life-long learning and continuing professional development. However, research shows that MOOC learners receive insufficient instructor feedback and social support and cannot get a high-quality learning experience. The virtual learning community in MOOCs is believed to be helpful to solve these problems, but there are only limited studies on the interaction between MOOC lecturers and students. Moreover, such studies are based on individual cases, so it is difficult to draw generalizable conclusions. This study is dedicated to improving the holistic understanding of the actual interaction patterns in the MOOC communities and focuses on exploring what network structure characteristics the learning community formed in the MOOC forum have, and how such structures are formed out of the interaction of MOOC participants and evolve over time.Design/methodology/approach In this study, the social network analysis method is used to visualize and quantitatively calculate the network structure of more than two hundred MOOC communities, with a view to identifying the important structural features and metrics for MOOC communities. It also performs power-low fitting on the distribution of node's degrees to identify the network’s scale-free characteristics and calculate the exponent of the scale-free network and its changes. Finally, this study classifies MOOC communities according to their network structures, observes their changes over time, and summarizes MOOC communities' patterns of growth.Findings This study found that MOOC communities are generally scale-free networks. In addition, it is also found that some MOOC communities have changed from star-network or random network to a scale-free network. The mean of the exponents is calculated to be about 1.3. MOOC communities most often present a structure of "low-centralization, a high proportion of isolates, and low density", which is far from satisfactory. However, following certain paths, they can turn into a "low proportion of isolates, high density" structure.Research limitations/implications This study provides important insights into the MOOC community structure and a large number of examples, which could be used as the basis for proposing a network growth model to better describe MOOC communities. However, it does not further explore the growth process of network nodes and connections. Since all the MOOC communities studied herein are from the same MOOC platform, whether the research conclusions can be generalized needs to be verified on other platforms. Practical implications This study calculates the values of several network metrics and the structural evolution path of MOOC communities. It can help MOOC platforms, universities, educational institutions and instructors to better quantify the structural characteristics of MOOC communities, so as to guide the MOOC communities to transform into a structure more commensurate with social learning.Originality/value The conclusions of this study are based on a large number of examples, and therefore help enhance the academic community's understanding of MOOC learning communities and have practical value for the educators in managing MOOC communities and improving instructional practice.Keywords MOOC; virtual learning community; scale-free network; network evolution