Turn-Taking and Concurrent Dyad Practice Aid Efficiency but not Effectiveness of Motor Learning in a Balance-Related Task
Bibliographic record
Abstract
We studied two forms of dyad practice, compared to individual practice, to determine whether and how practice with a partner impacts performance and learning of a balance task, as well as learners’ subjective perceptions of the practice experience. Participants were assigned to practice alone or in pairs. Partners either alternated turns practicing and observing one another, or they practiced and observed one another concurrently. Concurrent action observation impacted online action execution such that partners tended to show coupled movements, and it was perceived as more interfering than practicing in alternation. These differences did not impact error during practice. While dyad practice was associated with higher ratings of effort than individual practice, all groups improved and showed similar immediate and delayed retention irrespective of whether practice was alone or in pairs. These data provide evidence that a partner’s concurrent practice influences one’s own performance, but not to the detriment (or benefit) of learning. Thus, both alternating and concurrent forms of dyad practice are viable means of enhancing the efficiency, albeit not necessarily the effectiveness, of motor learning.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".