Finding Vlcs

Finding VLCs: A methodology for examining selfdirected virtual communities in nonformal learning environments

Background: •

Funded by the Social Sciences and Humanities Research Council (SSHRC) a 4-year study; we are just finishing year 1

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a continuation of research performed by the Virtual Learning Communities Research Laboratory

Virtual Learning Communiti es The model

Central Questions: Are characteristics identified in formal virtual learning communities manifest in non-formal online learning environments, and do they inform our understanding of how these communities contribute to self-directed learning?

Central Questions: How do contextual, situational, social and cultural issues influence participation in and self-directed learning from virtual learning communities in non-formal learning environments?

The research team: •

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We operate collaboratively and cooperatively All members are involved in all aspects of the research activities and processes

Learning Contexts: non-formal learning formal learning

informal learning

Formal Learning: •

Learners are grouped in classes Taught by teachers

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Curriculum is defined by an institution Often part of a graduated system of certification

Informal Learning: •

Learner-organized and directed Less systematic or planned

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Sometimes marked by unintentional or serendipitous learning

Non-formal Learning: •

Includes features of formal contexts: externally organized and supported Includes features of informal contexts: learner self-directedness, independence within a sturctured domain

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examples: webinars, PLEs, optional elements in a course

Contexts of study:

Contexts of study: •

University-based blended delivery environment: PD course on teaching in higher education •

Data collected from online discussion forums and blog postings

Contexts of study: •

MUVE (Second Life) environment: SL basic skills training courses provided to University students, staff and faculty •

Data collected from capture of online chat transcripts and recordings

Contexts of study: •

Online social networking environment: Constructed for a national council and advocacy group for teaching and learning in higher education •

Data collected from transcripts of blogs, forums and social networking platform activity

Inductive vs. Deductive

Deductive

applying an existing, predefined model to a new context

Inductive the model may need to be modified, or it simply might not be applicable to this context

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Method of Analysis: •

Data is analysed using NVivo qualitative analysis software Unit of analysis: the message

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both qualitative and quantitative strategies are employed

Coding Procedure: •

First pass: agreement is negotiated •

code definitions are refined codebook is written

Rick

Me

Coding Procedure: •

Second pass: a further test of operational definitions •

some clarification of the codebook a test of training procedures

Ben

Dirk

Kirk

Coding Procedure: •

Third pass:

Coders

the codebook has been finalized •

coders are hired and trained inter-rater reliability is recorded

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Challenges: •

The Model: the VLC model itself tends to be weighted towards certain areas •

looking for the ephemeral are there certain aspects of the VLC model more concerned with community?

Challenges: •

Unit of analysis: message is generally standard for computer conference transcripts •

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other units are possible (paragraph, unit of meaning, sentence) but there are problems there too many ideas are often conveyed in a single message this can result in “deep” coding - many codes applied to the same text

Challenges:

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Data Collection: voluntary participation can result in inconsistent amounts of data •

chat transcripts research ethics in online environments (esp. Second Life)

One more paper...

Thank you!

http://www.vlcresearch.ca http://www.pdfcoke.com/peo ple/documents/2662341-jaymie-koroluk