Theoretical Development of Connectivism through Innovative Application in China
DOI:
https://doi.org/10.21432/cjlt28255Keywords:
Connectivism, Online Learning, Principles, Innovative Application, Technology and learningAbstract
As a learning theory that reveals a new learning in the Internet environment, connectivism has become a popular academic topic at the forefront of online learning. The MOOC Research Team at the Distance Education Research Centre at Beijing Normal University designed and developed the first massive open online course, adapting a connectivist (cMOOC) approach in China. Using the data collected from six offerings of the cMOOC over 3 years, the big data paradigm was used for data analysis including complex network analysis, content analysis, text mining, behaviour sequence analysis, epistemic network analysis, and statistical and econometric models. This paper summarizes the findings of the patterns of connectivist learning, including a) the basic characteristics and evolutional patterns of complex networks, b) the characteristics and modes of knowledge production, c) the patterns of instructional interactions, and d) the relationships between pipe and content and between facilitators and learners. It is expected that the outcome of this study could make contributions to understanding the changes of online learning in depth and further promote the theoretical development and practical application of a connectivist approach.
References
Chen, L., Lu, H., & Zheng, Q. H. (2019). 互联网+教育”的知识观:知识回归与知识进化[Conceptualizing knowledge in “Internet + education:” The nature of knowledge and knowledge evolution]. Distance Education in China, (07), 10-18, 92. https://doi.org/10.13541/j.cnki.chinade.2019.07.003
Downes, S. (2005). An introduction to connective knowledge. https://www.downes.ca/post/33034
Downes, S. (2012). Massively open online courses are “here to stay.” http://www.downes.ca/post/58676
Dron, J. (2013). Soft is hard and hard is easy: Learning technologies and social media. Form, 13, 32-43. https://doi.org/10.13128/formare-12613
Guo, Y. J., Chen, L., Xu, L., & Gao, X. F. (2020). 联通主义学习中学习者社会网络特征研究[Social network characteristics of learners in connectivist learning]. Distance Education in China, (02), 32-39, 67, 76-77. https://doi.org/10.13541/j.cnki.chinade.2020.02.004.
Huang, L., & Tan, W. (2017). Survey on process mining in complex evolving social networks. Computer Engineering and Applications, 53(16), 18-28+49. https://doi.org/10.3778/j.issn.1002-8331.1704-0376
Huang, L. Y., Chen, L., Tian, H., & Wang, R. X. (2020). 联通主义学习教学交互的关系及其特征研究 [Instructional interactions in connectivist learning]. Distance Education in China, (09), 53-61+77. https://doi.org/10.13541/j.cnki.chinade.2020.09.007
Li, X. S., Chen, L., Wang, W. J., & Li, Y. Y. (2020). 联通主义视阈下的cMOOC知识生产的实证研究——基于机器学习的对比分析 [An empirical study of knowledge production from the perspective of connectivism: Comparative analysis based on machine learning]. Distance Education in China, (01), 23-34+76. https://doi.org/10.13541/j.cnki.chinade.2020.01.002
Lu, H., & Chen, L. (2019). 知识生产与进化:“互联网+”时代在线课程形态表征与演化研究[Knowledge production and evolution: Online course representation and evolution in the Internet age]. Distance Education in China, 2019(09), 1-9+92. https://doi.org/10.13541/j.cnki.chinade.2019.09.001
Porter, C. M., & Woo, S. E. (2015). Untangling the networking phenomenon: A dynamic psychological perspective on how and why people network. Journal of Management, 41(5), 1477-1500. https://doi.org/10.1177/0149206315582247
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10. http://www.itdl.org/Journal/Jan_05/article01.htm
Siemens, G. (2006). Knowing knowledge. http://www.elearnspace.org/Articles/networks.htm
Skrypnyk, O., Srec´ko, J., Kovanovic, V., Gasevic, D., & Dawson, S. (2014). Roles of course facilitators, learners, and technology in the flow of information of a cMOOC. International Review of Research in Open & Distance Learning, 16(3), 188-217. https://doi.org/10.19173/irrodl.v16i3.2170
Tawfik, A. A., Reeves, T. D., Stich, A. E., Gill, A., Hong, C., McDade, J., Pillutla, V. S., Zhou, X., & Giabbanelli, P. J. (2017). The nature and level of learner–learner interaction in a chemistry massive open online course (MOOC). Journal of Computing in Higher Education, 29(3), 411-431. https://doi.org/10.1007/s12528-017-9135-3
Tian, H., Chen, L., Huang, L. Y., & Wang, R. X. (2020). cMOOC学习者知识流动特征与交互水平关系研究[The relationship between the knowledge flow characteristics and the interaction level of cMOOC learners]. Distance Education in China, (08), 15-24+76. https://doi.org/10.13541/j.cnki.chinade.2020.08.003
Tirado, M. R., Maraver, L. P., & Hernando, G. (2017). Patterns of participation and social connections in online discussion forums. Small Group Research, 48(6), 639-644. https://doi.org/10.1177/1046496417710726
Wang, H. B., & Chen, L. (2020). 网络化知识的内涵解析与表征模型构建[Conceptualizing networked knowledge and constructing its representation model]. Distance Education in China, (05), 10-17+76. https://doi.org/10.13541/j.cnki.chinade.2020.05.002
Wang, H. M., & Chen, L. (2019). cMOOC微信群社会网络特征及其对学习者认知发展的影响[Impact of social networking features of cMOOC WeChat groups on learners’ cognition development]. Distance Education in China, 11, 15-23+92. https://10.13541/j.cnki.chinade.2019.11.002
Wang, Z. J., & Chen, L. (2019). 联通主义:“互联网+教育”的本体论[Connectivism: The ontology of “Internet Plus Education.”] Distance Education in China, (08), 1-9+26+92. https://doi.org/10.13541/j.cnki.chinade.2019.08.002
Wang, Z. J., Chen, L., & Anderson, T. (2014). A framework for interaction and cognitive engagement in connectivist learning contexts. The International Review of Research in Open and Distance Learning, 15(2), 121-141. https://doi.org/10.19173/irrodl.v15i2.1709
Xiong, L. Y. (2020). 基于复杂网络建模的联通主义学习交互规律研究[Research on connectivist learning interactive law based on complex network]. [Master’s thesis, Beijing Normal University]. http://etd.lib.bnu.edu.cn/Detail?dbID=5&dbCode=ETD1&sysID=76844
Xu, Y. & Du, J. (2021). What participation types of learners are there in connectivist learning: An analysis of a cMOOC from the dual perspectives of social network and concept network characteristics. Interactive Learning Environments, 1-18. https://doi.org/10.1080/10494820.2021.2007137
Xu, Y. Q. (2020). cMOOC个体网络地位与其概念网络特征水平的关系探究[Research on the relationship between individual status in social network and corresponding concept network characteristics in cMOOC]. [Master’s thesis, Beijing Normal University]. http://etd.lib.bnu.edu.cn/Detail?dbID=5&dbCode=ETD1&sysID=76127
Yang, Y. H., Zhang, J. J., & Zheng, R. X. (2020). 联通主义学习中社会交互与话题交互的网络化特征[The network characteristics of social interaction and topic interaction in connectivism-based learning]. Modern Distance Education, 01, 36-45. https://doi.org/10.13927/j.cnki.yuan.2020.0005
Yu, B., Xu, J. Y., & Tan, L. Q. (2020). 基于社会网络和话题相似度的cMOOC学习者聚类研究[Clustering of cMOOC Learners Based on Social Network and Topic Similarity]. Journal of Open Learning, 25(01), 10-21. https://doi.org/10.19605/j.cnki.kfxxyj.2020.01.02
Zhou, J. Y. (2010). 网络教研讨论区的社会网络分析[Social network analysis of online teaching and research forum]. Distance Education in China, 10, 37-40. https://doi.org/10.13541/j.cnki.chinade.2010.10.015
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