Blended Methods for Measuring and Modeling Community in Formal Online Learning Environments

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Transcript of Blended Methods for Measuring and Modeling Community in Formal Online Learning Environments

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    Curriculum Studies Mini-Conference, November 25, 2006

    Blended methods for measuring and modelingcommunity in Formal Blended Learning

    Environments

    Based on: Schwier, R.A., & Daniel, B.K. (2007). Did we become a community?

    Multiple methods for identifying community and its constituent elements in formalonline learning environments. In N. Lambropoulos, & P. Zaphiris (Eds.), User-

    evaluation and online communities (pp. 29-53). Hershey, PA: Idea Group Publishing.

    Richard A. Schwier

    Ben K. Daniel

    Virtual Community Research Laboratory

    University of Saskatchewan

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    Central Concerns

    Focus of research

    Atomized view of communities

    Generation of models Using research to inform online

    learning environments

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    Sense of Community

    Chavis Sense of Community Index

    Rovai & Jordans ClassroomCommunity Scale

    Connectedness

    Learning

    Pre-post design (t-Test, p

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    Interaction Analysis

    Fahy, Crawford & Ally (TAT)

    Included only peripheral interactions

    Density the ratio of the actual number of connections observed,

    to the total potential number of possible connections

    2a/N(N-1) = 2(122)/13(12) = .78

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    Reciprocity ratio

    the parity of communication among participants

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    Reciprocity

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    Characteristics of Community

    Transcript analysis

    Interviews

    Focus groups

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    Characteristics

    Awareness

    Social protocols

    Historicity

    Identity

    Mutuality

    Plurality

    Autonomy

    Participation

    Trust

    Trajectory

    Technology

    Learning

    Reflection

    Intensity

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    Comparison of characteristics

    Thurstone analysis

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    Thurstone Scale

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    Modeling

    Bayesian Belief Network

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    Conclusions

    Cycle of analysis is more important thanspecific tools used

    Mixed methods seems reasonable, and

    worked well in practice Baseline data are needed to situate findings

    Modeling is an act of systematic speculation

    influenced by data (not limited by data)