A university sport coach community of practice: Using a value creation framework to explore learning and social interactions
Bibliographic record
Abstract
Coaches often identify social learning situations as the most valuable and influential to their learning. Thus, researchers have proposed implementing social learning initiatives, in particular, the community of practice approach. The purpose of the present study was to explore how an existing coach community of practice was created and sustained in a university setting, and to assess what value was created by participating in the community of practice. Participants included four National Collegiate Athletic Association Division 1 coaches from a university in the Southwestern United States. Data collection included an individual interview with each coach. Interviews were analysed using a value creation framework. The findings revealed that the coaches created value within all five cycles of Wenger et al.’s framework. In particular, the coaches learned a number of coaching strategies, some of which they were able to implement, and as a result, observe benefits in their coaching and athletes’ performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".