Physical activity motivation and confidence predict performance on effortful tasks
Bibliographic record
Abstract
The Canadian Assessment of Physical Literacy evaluates children across four core domains: physical competence, daily behaviour, physical activity knowledge, and motivation for physical activity. The motivation and confidence score is comprised of four characteristics of motivation: 1) choosing a physical activity over a sedentary activity, 2) feelings of adequacy towards physical activity, 3) comparing levels of physical activity and physical skills to peers, 4) perceived benefits versus barriers for physical activity. The physical competence domain is comprised of eight competencies; the present study focused on plank (muscular endurance) and beep test (aerobic endurance) results, as both would be partially influenced by effort rather than pure fitness or skill. Motivation and confidence were expected to influence kids' persistencce and effort in tasks such as plank and beep test (PACER). Twenty-seven grade 6 children completed online copies of self-report questionnaires assessing their physical activity motivation and physical competence (HALO, 2013), performed the Fitnessgram 20m PACER (Progressive Aerobic Cardiovascular Endurance Run; Meredith & Welk, 2010), and the plank isometric hold (Boyer et al., 2013). A regression analysis predicted plank score by physical activity motivation and confidence (accounting for 44.6% of the variance); F(1, 25) = 20. 15, p < .001.). A regression analysis predicted PACER score by physical activity motivation and confidence (accounting for 56.3% of the variance); F(1, 25) = 32.25, p < .001. Acknowledgments: Funding support from ParticipAction through CHEO.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".