Informal Learning in an Online Community of Practice
Bibliographic record
Abstract
What role can online communities play in meeting the informal learning needs of a professional association? This article presents the results of an interpretive study of the experiences of coordinators of Alberta Community Adult Learning Councils who participated in an online community of practice designed to support informal workplace learning. Through active participation and peripheral “lurking, ” new-comers were oriented into the skills and culture of the practice, and experienced practitioners gained new insights into their own professional identities and the meaning of their work. Telling their stories helped to develop not only identity as individual practitioners, but also served to reconstruct the identity of the collective community on an ongoing basis. Motivations to participate included an opportuni-ty to learn new skills and work practices, a means of social and professional connection to colleagues, and a mechanism to reduce the isolation that was in-herent in the job function and geographical location. The role of the online moderator was identified as critical in sustaining the online community over an
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".