Literature review of empirical studies using constraints led approach for motor learning, motor performance, and decision making
Bibliographic record
Abstract
We examined the degree to which empirical support for a constraints led approach (CLA) was present in peer reviewed journals for investigations of motor learning, motor performance and decision making. While it is a relatively new methodology, our review provided evidence that the number of studies that examined linear vs non-linear approaches in motor learning was quite limited (n=3). However, there were a significant number of studies (n=44) that manipulated constraints (primarily environment and task) to examine the effect of these manipulations on performance and decision making. We analyzed the various characteristics that contributed to these investigations. Generally, the participants in these studies were male, between the ages of 12 to 25 with skill levels that were primarily intermediate or advanced and the majority of studies focused on team sports. While overall there was support for a performance effect, the body of evidence is insufficient to make any conclusive statements about its effectiveness in terms of learning and transfer of motor skills.Acknowledgments: Funded by the Roger Smith Undergraduate Research Award and the Faculty of Kinesiology, Sport and Recreation at the University of Alberta
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".