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Social Network Analysis: A Framework for Identifying Communities in Higher Education Online Learning

机译:社交网络分析:识别高等教育在线学习中社区的框架

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This paper presents the Integrated Methodological Framework (IMF) which uses social network analysis (SNA) to structurally identify communities in higher education online learning (HEOL). Decades of research speaks for the value of community-based learning albeit in traditional, blended, or online environments. The communities of practice (CoP) and community of inquiry (CoI) are well-established, empirically tested frameworks that have been effectively used for exploration of community-based learning in professional and educational contexts. Typically, research using these frameworks has required extensive qualitative analysis making it tedious and time-consuming. Pivoting on structural similarities between networks and communities, the IMF embeds SNA constructs in structural components of the CoP and CoI frameworks. By structurally identifying a CoP and CoI, the IMF allows targeted, selective qualitative analysis thus reducing the extent of qualitative analysis required previously in research using the CoP and CoI frameworks. Application of the IMF is demonstrated in a case study on an online blogging network. The study substantiates the IMF as an effective framework for structural identification of a CoP and CoI. The validity and robustness of the IMF is being further tested in ongoing research.
机译:本文介绍了综合方法框架(IMF),它使用社交网络分析(SNA)在结构上识别高等教育在线学习(HEOL)中的社区。几十年的研究虽然是传统,混合或在线环境的社区学习的价值。实践社区(COP)和咨询社区(COI)是完善的经验测试的框架,已有效地用于探索专业和教育环境中的社区学习。通常,使用这些框架的研究已经需要广泛的定性分析,使其令人疑惑和耗时。 IMF在网络和社区之间的结构相似性上枢转,在警察和COI框架的结构组件中嵌入SNA结构。通过在结构上识别COP和COI,IMF允许目标,选择性定性分析,从而降低了先前使用COP和COI框架在研究中所需的定性分析的程度。在线博客网络的案例研究中对IMF的应用进行了演示。该研究证实了IMF作为警察和COI的结构鉴定的有效框架。在正在进行的研究中进一步测试了IMF的有效性和稳健性。

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