Positive effects of a 9-week programme on fundamental movement skills of rural school children
Bibliographic record
Abstract
Background: Motor development of many children in rural areas of South Africa is compromised because of various socio-economic factors, hence, the need to address these developmental needs. Aim: To examine the immediate and sustainable effects of a 9-week movement programme on fundamental movement skills (FMS) of school children. Setting: Seven to eight years old school children in Raymond Mhlaba Municipality, Eastern Cape province. Methods: A two-group, pre-post-re-test research design was used. Fundamental movement skills (FMS) proficiency was assessed using the Test of Gross Motor Development-Third Edition (TGMD-3) at pre-test, post-test and re-test after 6 months. Ninety-three school children (intervention group [IG] = 57) and (control group = 36), with a mean age of 7.12 (± 0.71) participated in the study. The twice-a-week FMS programme of 30 min was conducted during school hours. Statistical analysis included an ANOVA type of hierarchical linear model (HLM) (mixed models) procedure to test for intervention effects with school, time, sex and group as covariants. Cohen’s effect size was calculated to assess the practical significance of changes. Results: Immediate and sustainable effects were found on locomotor (p < 0.05; d > 1.7, p < 0.05; d > 2.0), ball skills (p < 0.05; d > 0.7, p < 0.05; d > 1.5) and the gross motor index (GMI) of the IG (p < 0.05; d > 1.0, p < 0.05; d > 2.0). Conclusions: A short-duration FMS intervention significantly improve locomotor, ball skills, and GMI of school children in rural areas. Contributions: Interventions of this nature are encouraged to improve the FMS development of school children, especially in rural areas, as it can enhance the building blocks required in the future development of these children.
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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 | 0.001 | 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".