Autonomy Support via Instructionally Irrelevant Choice Not Beneficial for Motor Performance or Learning
Bibliographic record
Abstract
Purpose: The Optimizing Performance Through Motivation and Attention for Learning (OPTIMAL) theory predicts that providing learners with choices during skill acquisition will enhance their acquisition performance, motor learning, and expectancies. Based on this theory, it is recommended that instructors ask learners to choose which tasks to practice in applied settings. This experiment tested these predictions and recommendation by crossing autonomy support with practice schedule in a 2 × 2 factorial design. Method: Participants (N = 128) practiced a novel non-dominant hand dart-throwing task either with choice over the color of the dart flights (autonomy) or yoked to a counterpart’s choices (yoked). Further, participants either practiced throwing darts to three different targets in equal amounts (variable) or throwing to the same target for all practice trials (constant). All participants completed a pretest, acquisition phase, 24-hr delayed retention and transfer tests, as well as baseline and post-acquisition autonomy, and self-efficacy measures. Data were analyzed according to a pre-registered analysis plan that included pretest and gender as covariates. Results: The autonomy groups reported significantly greater perceived autonomy at the end of acquisition. There were no significant effects of autonomy on self-efficacy, or motor performance uniquely during acquisition, or uniquely on the delayed transfer test. The autonomy groups, however, performed with significantly greater error across acquisition and transfer. Practice schedule interacted with the time of testing such that the constant groups performed significantly more accurately during acquisition but non-significantly less accurately during transfer than the variable groups. Conclusions: These results are inconsistent with OPTIMAL theory.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".