Can active play replace skill-oriented physical education in enhancing fundamental movement skills among preschool children? A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Active play emphasizes the enjoyment of physical activity, it is affordable and unconstrained. In contrast, skill-oriented physical education, a mainstream physical activity intervention, is more formalized. However, the comparative effects of these interventions on fundamental movement skills in preschool children remain a subject of debate. PURPOSE: Determine the effectiveness of active play and compare it with skill-oriented physical education on fundamental movement skills. METHODS: We searched four databases (MEDLINE, ERIC, Web of Science, and SPORTDiscus) from January 2004 to March 2024. Included studies assessed FMS in children aged 2-6 years, with active play interventions lasting ≥ 4 weeks. The effects of active play and skill-oriented physical education on total fundamental movement skills, locomotor skills, object control, and balance were calculated within random effects models (weighted SMD) in meta-analysis. RESULTS: This systematic review included 23 studies involving 2201 preschool children, with 15 eligible for meta-analysis. The meta-analysis showed no significant differences in the effects of active play compared to skill-oriented physical education on total FMS, locomotor skills, object control, balance (p > 0.05). Subgroup analyses indicated that skill-oriented physical education marginally outperformed unstructured active play in total fundamental movement skills and locomotor skills (SMD=-1.0172, 95% CI -1.6748~ -0.3595, p = 0.0073; SMD=-1.6956, 95% CI -3.3511~ -0.0401, p = 0.0471). CONCLUSIONS: Both structured active play and skill-oriented physical education are comparable effective in improving fundamental movement skills. However, unstructured active play is less effective. In resource-limited educational settings, structured active play may serve as a viable complement to partial skill-oriented physical education programming.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".