“Putting” in the effort: Effects of gender on psychosocial outcomes of paired practice in a golf-putting task
Bibliographic record
Abstract
The efficiency of motor learning can be increased through paired practice, in which observation and physical performance are interspersed. Paired practice in motor learning contexts may also yield psychosocial benefits, including enhanced motivation, self-efficacy, and positive affect. Previous research has evaluated these advantages in relation to factors such as competition, goal-setting, or reduced self-conscious emotions through engaging in interdependent dyadic roles. However, gender influences on psychosocial outcomes of dyadic motor learning have not been examined. The current study investigated effects of gender on motivation, efficacy, and affect in paired practice of a golf-putting task. It was hypothesized that matched-gender pairs would show more positive psychosocial outcomes compared to mixed-gender pairs. Furthermore, the effects of dyad composition (mixed versus matched-gender pairs) may differ between females and males. 79 novice participants (14 female-female pairs, 7 male-male pairs, 19 female-male pairs) completed individual putting tests before and after paired practice, where physical practice and observation alternated for 5 blocks of 20 trials. Following paired practice, the Intrinsic Motivation Inventory (IMI), the Positive and Negative Affect Schedule (PANAS), and self-efficacy, other-efficacy, and relation-inferred efficacy scales were completed. Males scored higher overall on relation-inferred efficacy. Additionally, in mixed-gender dyads, males scored higher than females (non-significant interaction trend; p = .052) on the IMI effort/importance subscale. These findings indicate that psychosocial outcomes of motor skill acquisition may be more influenced by paired practice and gender matching in males than in females. The relationship between psychosocial measures and motor performance will be explored in further analysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".