The effect of watching models of teaching physical activity on cognitive-motor components and physical competence among children
Bibliographic record
Abstract
Introduction: The increase in immobility in all sections of society, especially children and adolescents, has become one of the most important concerns in the health status of this age group. Aim: The main purpose of this study was to investigate the effect of watching models of teaching physical activity on cognitive-motor components and physical competence among children. Method: The current research was a semi-experimental study with two experimental and control groups. The statistical population included all 8-10 year-old boy students of Khoi city in the academic year of 2021-2022. 30 males with aged 8-10 years were voluntarily selected and randomly divided into two experimental groups and one control group. To data collection, we used the Canadian Physical Literacy Assessment Tool (CAPL), Physical Fitness Scale, Progressive Aerobic Fitness Test, Health-Related Physical Fitness Test and Basic Physical Education Training. Univariate and multivariate analysis of covariance were used to compare the groups using SPSS-20. Results: The results of the covariance test showed that virtual education using watching video models and teaching the basic concepts of physical activity have a significant positive effect on the physical competence and cognitive-motor dimensions among children aged 8 to 10 years (P<0.05). Also, the results showed that the group effect is significant (P=0.001, Eta square=0.70, F=56.65). Therefore, the amount of cognitive-motor dimension in the post-test has a significant difference. Conclusion: Based on the results, the virtual education using watching video models and teaching the basic concepts of physical activity increases cognitive-motor function, physical literacy and physical activity among children. Therefore, researchers, teachers and parents of children are recommended to use this method of education to improve the level of physical activity and cognitive-behavioral components of children.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".