Effective practice and instruction: A skill acquisition framework for excellence
Bibliographic record
Abstract
We revisit an agenda that was outlined in a previous paper in this journal focusing on the importance of skill acquisition research in enhancing practice and instruction in sport. In this current narrative review, we reflect on progress made since our original attempt to highlight several potential myths that appeared to exist in coaching, implying the existence of a theory-practice divide. Most notably, we present five action points that would impact positively on coaches and practitioners working to improve skill learning across sports, as well as suggesting directions for research. We discuss the importance of practice quality in enhancing learning and relate this concept to notions of optimising challenge. We discuss how best to assess learning, the right balance between repetition and practice that is specific to competition, the relationship between practice conditions, instructions, and individual differences, and why a more "hands-off" approach to instruction may have advantages over more "hands-on" methods. These action points are considered as a broad framework for advancing skill acquisition for excellence (SAFE) in applied practice. We conclude by arguing the need for increased collaboration between researchers, coaches, and other sport practitioners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".