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Research on the correlativity between individual status in social network and corresponding concept network characteristics in a cMooc

Bibliographic Data

ID21631469
AuthorsYaqian Xu (0000-0002-6539-8625, Research Centre of Distance Education, Beijing Normal University, Beijing, People’s Republic of China.), Qinhua Zheng (0000-0003-4874-3295, Beijing Normal University, corresponding author), Zheng Qinhua (Research Centre of Distance Education, Beijing Normal University, Beijing, People’s Republic of China.)
Year2023
Pages1-15
Publication date2023-03-21
Open AccessNo
TypeARTICLE
VenueInteractive Learning Environments (JOURNAL)
Journal identifiersISSN: 1049-4820 • E-ISSN: 1744-5191
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10494820.2023.2170421
OpenAlexW4328052790
LanguageEN
Citations received7
References cited14

The interactive mechanism between social and concept networks is a key question in connectivist learning, which explains the impact of interaction on cognitive development and knowledge generation. The successful practice of “Internet Change Education: Dialogue between Theory and Practice”, the first cMOOC in China, provides data support and research context for exploring the learning rules. This study proposed an evaluation framework of individual social network status in cMOOCs and a model for concept network characteristics analysis in cMOOCs. Analysis from 10,598 interactive data points of cMOOC1.0 using complex network analysis, topic clustering algorithm and correlation analysis found that there was a correlation between a learner’s individual network status and concept network characteristics, and there are two kinds of special connectivist learners in cMOOC learning: someone with higher network status but lower knowledge output, and someone with higher knowledge output but weaker network status. Furthermore, we put forward three practical suggestions: (1) facilitators should focus on guiding learners’ expression and connection to important individuals; (2) according to different correlation trends, facilitators can flexibly tailor activity design strategies, such as providing additional wayfinding support for learners with low centrality; and (3) carry out adaptive learning evaluations and design diversified certificates

Centrality · Cluster analysis · Data science · Knowledge management · Network analysis · Organizational network analysis · Social network analysis · The Internet · World Wide Web · Computer Science · Innovative Teaching and Learning Methods · Online and Blended Learning · Online Learning and Analytics · Artificial Intelligence

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    Yujuan Guo, Luoying Huang et al.•Interactive Learning Environments•2025

  • Analysis and comparison of learners’ epistemic networks based on interaction content in connectivist learning

    Yujuan Guo, Luoying Huang•Interactive Learning Environments•2025

  • Social networking learning through enterprise social networks

    Ramona-Diana Leon, Raúl Rodríguez Rodríguez et al.•Interactive Learning Environments•2025

  • The evolution of cMooc learners’ resource use behaviour

    Yun-Qi Bai, Chen Li et al.•Interactive Learning Environments•2025

  • CMOOC in Iranian higher education curriculum in the new normal era

    Esmaeil Jafari•Interactive Learning Environments•2025

Citations per year7
Citation span2025 - 2026 (2)
Highly citedNo

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