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Participation Patterns in Formal, Non-Formal, and Informal Online Learning Environments
 

Participation Patterns in Formal, Non-Formal, and Informal Online Learning Environments

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  • Elements, Emphases, Elements
  • Social Network analysis, Sociograms, Reciprocity Plot SNA examines directional INDEGREE and OUTDEGREE - Nodes and links

Participation Patterns in Formal, Non-Formal, and Informal Online Learning Environments Participation Patterns in Formal, Non-Formal, and Informal Online Learning Environments Presentation Transcript

  • Patterns of Participation in Formal, Non-Formal and Informal Online Learning Communities Richard A. Schwier Jennifer X Seaton Virtual Learning Communities Research Laboratory Educational Technology and Design University of Saskatchewan
  • Central Concerns
    • Shifting focus of research
    • Atomized view of communities
    • Tools for analysis
    • Generation of models
    • Using research to inform development of online learning environments
  • Community Constituents Comparison Modeling
  •  
  • Formality of Learning Environment
    • Formal
    • Non-Formal
    • Informal
  • Selection of Groups
    • Active, regular online conversations
    • Discussion board transcripts
    • Membership
    • Active facilitator *
    • All conversations considered *
    • Topics not restricted
  • Two Measures of Participation
    • Interaction analysis
      • Transcript Analysis Tools (Fahy, Crawford & Ally)
      • Intensity, Density, Reciprocity
    • Engagement analysis
      • Density
      • Mean Reply Depth (Wiley)
  • Interaction analysis Messages/participant
      • “ levels of participation , " or the degree to which the number of postings observed in a group exceed the number of required postings
      • 858 actual/490 required = 1.75
      • Intensity = # of postings / # of expected postings = 73 actual / 9(14) expected = .579
    Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 1.55 3.90 8.08 21.9 57.8 95.5
  • Interaction analysis Messages/discussion Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 31.4 15.2 8.08 29.2 148.7 40.2
  • Interaction Analysis Intensity
    • Intensity
      • “ levels of participation , " or the degree to which the number of postings observed in a group exceed the number of required or expected postings
    Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 .03 * .09 * .34 1.82 4.1 2.51
  • Interaction analysis Density
    • Density = 2 a /N(N-1),
      • Included only peripheral interactions in formal environments
      • the ratio of the actual number of connections observed, to the total potential number of possible connections
    Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 cliques cliques .47 .40 1.0 .78
  • Interaction Analysis Reciprocity the parity of communication among participants
  • Interaction Analysis Reciprocity Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 Low Low .92 (sd=.94) 1.74 (sd=4.77) 1.10 (sd=.42) 2.51 (sd=.37)
  • Plotting Reciprocity
  • Engagement
  • Engagement analysis
    • Thread density and depth (Wiley, 2010)
      • Calculation of levels of replies in conversation threads
      • Data flawed, but useful
    Mean Reply Depth (MRD crude) = sum of reply depth for all messages/messages in the thread Mean Reply Depth (corrected)= MRD (crude) x ((n-b(childless messages)/n)
  • Mean reply depth (MRD) equations Mean Reply Depth (MRD crude) = sum of reply depth for all messages/messages in the thread Mean Reply Depth (corrected)= MRD (crude) x ((n-b(childless messages)/n)
  • Do not attempt to read this!
  • Do not attempt to read this! Mulitlogue/discussion Simple Q&A/chit-chat Monologue/no discussion
  • Engagement analysis Mean Reply Density Informal 1 Informal 2 Non-formal 1 Non-formal 2 Formal 1 Formal 2 .71 1.16 .60 .70 1.76 1.40
  • Formal 1 Formal 2 Informal 1 Informal 2 Non-formal 1 Non-formal 2 Regular
  • Formal 1 Formal 2 Informal 1 Informal 2 Non-formal 1 Non-formal 2 Extended
  •  
  • Conclusions
    • Interaction and engagement data tell similar stories
    • Baseline data are needed to situate findings
    • Most enjoyable part: the hunt, not the kill