Physical literacy improves with the Run Jump Throw Wheel program among students in grades 4–6 in southwestern Ontario
Bibliographic record
Abstract
The purpose of this study was to determine whether the introduction of a fundamental movement skills (FMS) program to grade 4–6 physical education (PE) classes could improve students’ physical literacy (PL) and influence the amount of effort exerted in PE class. Athletics Canada’s grassroots Run Jump Throw Wheel (RJTW) Program was delivered for 10 weeks during PE classes (2 schools: four grade 4, four grade 5, two grade 6, one split grade 5–6 class, and one split grade 6–7 class, totalling 310 students). Participants completed the Canadian Assessment of Physical Literacy (CAPL) and wore heart rate monitors and pre- and postintervention. The CAPL score increased 3.3 (±8.8) points from the pretest to the post-test (t = 6.47, p < 0.001). Improvements were not significantly different by grade or gender, but those in the suburban-area school improved more so than those attending the rural-area school (F[1,294] = 4.82, p < 0.004). Among those participants that increased their PL (n = 186), the CAPL scores increased by 8.6 (±5.9) points versus those that decreased (n = 110; –5.6 ± 4.8 points), F[1,294] = 452.11, p < 0.001. No significant differences in time spent in physical activity were observed between the pre- and post-test (i.e., 17.0 ± 7.0 min and 19.3 ± 7.0 min, respectively, t = 1.70, p = 0.091). The RJTW program increased participants’ overall FMS, as well as their knowledge and understanding regarding these FMS, both key components of PL.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".