The Effect of Non-linear Pedagogy of Hurdle on Physical Literacy of Qom City Female Students
Bibliographic record
Abstract
Background: Progress in physical literacy can significantly influence an individual's intrinsic motivation and overall quality of life. Objectives: The present study aimed to investigate the effect of non-linear pedagogy of hurdle training on the physical literacy (including physical competence, daily behavior, motivation and self-confidence, and knowledge and understanding) of female students in Qom. Methods: This study employed a semi-experimental design with a pre-test and post-test design, including a control group. The statistical population consisted of 85 female students (aged 9 - 10 years) from Nafiseh Primary School. A total of 40 participants were randomly assigned to either the control or experimental group. The research instrument used was the Canadian physical literacy test. The experimental group underwent 12 training sessions, each lasting 45 minutes. Results: The results of the Wilcoxon test indicated significant improvements in the experimental group from pre-test to post-test in the components of physical fitness (plank, pacer, and CAMSA), motor skills, and knowledge and understanding. While daily behavior, motivation, and self-confidence improved in both groups from pre-test to post-test, no significant differences were observed between the groups in these areas. Finally, the results of mixed ANOVA revealed that the total physical literacy score of the experimental group showed a significant improvement compared to the control group. Conclusions: Non-linear pedagogy, which emphasizes the importance of variability in the perceptual-motor system through exploratory learning, can enhance functional variability. The findings suggest that this approach effectively improves physical literacy among female students.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".