A Case Study of Using an Adult-Oriented Coaching Survey and Debrief Session to Facilitate Coaches’ Learning in Masters Sport
Bibliographic record
Abstract
The Adult-Oriented Sport Coaching Survey (AOSCS) can be used by coaches to reflect on how they coach competitive adult sports participants. There are coach (AOSCS-C) and athlete (AOSCS-A) versions. The purpose of this case study is to portray how coaches reflect on scores from the AOSCS with a coach developer. Nine coaches (White; ages 23–72; five men and four women; six sports) and their respective athletes were invited to complete the AOSCS twice during a season. Coaches were given their survey scores and undertook a debriefing interview with a coach developer. We reflected on four key topics in this dedicated professional development session: coach impressions on receiving an AOSCS personal scorecard, leveraging comparisons between coach and athlete scores, leveraging comparisons in scores over time, and misunderstandings/inadequacies of numerical scores. We reflect on meaningful interventions for coach development in adult sport.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".