Can athletes’ reports of self-regulated learning distinguish deliberate practice from physical preparation activity?
Bibliographic record
Abstract
Sustained persistence in deliberate practice (DP) could be aided by engagement in adaptive motivational and metacognitive types of self-regulated learning (SRL) processes. We examined relationships between SRL and each of DP and physical preparation (PP; e.g., cross-training) in supervised, unsupervised, social and non-social practice contexts. 272 individual-sport athletes (from city to international level; M sport activity = 13.54 hrs/wk; 200 males, ages 18-35) completed the Self-Regulation of Learning Self-Report Scale and reported weekly DP and PP amounts. We found contrasting results depending on specific SRL processes. Self-monitoring was related to DP (total, supervised, social conditions) but inversely related to PP. Effort was inversely related to supervised DP but positively associated with PP. Planning was associated with DP, and reflection and self-efficacy related to PP. We discuss the contrast between DP and PP, highlighting differences in the nature of these practice activities, and self-monitoring as a key SRL process for DP.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".