Same coach, different approach? How masters and youth athletes perceive learning opportunities in training
Bibliographic record
Abstract
While traditional, coach-directed pedagogies have dominated youth sport coaching practice, little is known about how coaches orient their approaches to facilitate adult athletes’ learning. This study explored a group of Masters athletes’ and a group of youth athletes’ perspectives of their common canoe/kayak coach’s approaches, with an aim to understand if and how the coach’s approaches differed based on the age cohort she was coaching. Four focus group interviews (two with each age cohort lasting 60–90 min) were conducted with nine youth (five male, four female; 14–15 years old) and 12 Masters athletes (six male, six female; 27–70 years old). Data were inductively analysed resulting in three higher order themes: (1) communication, exchanges, and interactions; (2) coaching on the basis of the athletes’ self-concept; (3) norms, goals, and expectations for learning within the climate. Results indicated that Masters athletes felt their coach responded well to their need for information, gave them room to make decisions, and engaged them in collaborative conversations. Youth athletes described their coach’s approaches as more directive: she made decisions for when and how they trained, provided information linearly, and maintained a climate of highly competitive expectations. Whereas coaching approaches with Masters athletes closely paralleled andragogical principles, those for youth aligned with more directed instructional methods. Findings illustrate how one coach’s approaches varied on a continuum from coach-directed (i.e. traditional pedagogical) to athlete-directed (i.e. andragogical) styles, both evident to some degree with each cohort.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".