Research Methods for Identifying and Analysing Virtual Learning Communities
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Transcript of Research Methods for Identifying and Analysing Virtual Learning Communities
Methods for Identifying and Analysing Learning Communities
Richard A. SchwierVirtual Community Research LaboratoryEduca;onal Technology and Design
University of Saskatchewan
Higher Educa;on Development CentreUniversity of Otago
Dunedin, New ZealandFebruary 7, 2011
Central Concerns
• ShiNing focus of research
• Atomized view of communi;es
• Tools for analysis
• Genera;on of models
• Using research to inform development of online learning environments
Community
Cons;tuents
Comparison
Modeling
Sense of Community
• Chavis’ “Sense of Community Index”• Rovai & Jordan’s “Classroom Community Scale” (Chronbach’s alpha = .93)– Connectedness (.92)– Learning (.87)
• Pre-‐post design (t-‐Test, p<.005)
Interac;on Analysis
• Fahy, Crawford & Ally (TAT)• Intensity
– “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
Interac;on analysis
• Density – Included only peripheral interac;ons– the ra;o of the actual number of connec;ons observed, to the total poten;al number of possible connec;ons
2a/N(N-‐1) = 2(122)/13(12) = .78
Reciprocity ra;othe parity of communication among participants
Plodng Reciprocity
Characteris;cs of Community
• Transcript analysis
• Interviews
• Focus groups
Characteris;cs
• Awareness
• Social protocols
• Historicity
• Iden;ty
• Mutuality
• Plurality
• Autonomy
• Par;cipa;on
• Trust
• Trajectory
• Technology
• Learning
• Reflec;on
• Intensity
Comparison of characteris;cs• Thurstone analysis
Thurstone Scale
ModelingBayesian Belief Network Model of a Virtual
Learning Community
BBN -‐ Query the network
BBN -‐ Query the network
Sense of CommunityRovai & Jordan’s “Classroom Community Scale” (Chronbach’s alpha = .93)
0
22.5
45.0
67.5
90.0
FormalNon-Formal
IntensityFahy, Crawford & Ally (TAT)
0
0.5
1.0
1.5
2.0
Formal
Non-Formal
DensityFahy, Crawford & Ally (TAT)
0
0.2
0.4
0.6
0.8
FormalNon-Formal
Reciprocity ra;o Instructors
0
3.8
7.5
11.3
15.0
Formal
Non-Formal
Reciprocitypar;cipants
0
0.3
0.5
0.8
1.0
FormalNon-Formal
0.376276399
Mean Mean
sd
sd
Order of importance -‐ elementsElement Formal Non-‐formal
Trust 1 7
Learning 2 3
Par;cipa;on 3 6
Mutuality 4 10
Intensity 5 7
Protocols 6 10
Reflec;on 7 2
Autonomy 8 10
Awareness 9 1
Iden;ty 10 4
Trajectory 11 13
Technology 12 4
Historicity 13 13
Plurality 14 7
And lately...
Par;cipa;on Pakerns
Interac;on analysis
• Thread density and depth (Wiley, 2010)
– Calcula;on of levels of replies in conversa;on 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)
Do not akempt to read this!
Do not akempt to read this!
Mulitlogue/discussion
Simple Q&A/chit-‐chat
Monologue/no discussion
SNAPP
hkp://research.uow.edu.au/learningnetworks/seeing/snapp/
Keep an eye on...
Technology Enhanced Knowledge Research Ins;tute (TEKRI)-‐ hkps://tekri.athabascau.ca/
George Siemens & data analy;cs
Conclusions
• Cycle of analysis is more important than specific tools used
• Mixed methods seems reasonable, and worked well in prac;ce
• Baseline data are needed to situate findings
• Modeling is an act of systema;c specula;on influenced by data (not limited by data)
• Most enjoyable part: the hunt