Physical activity and social-emotional learning in Canadian children: Multilevel perspectives within an early childhood education and care setting
Bibliographic record
Abstract
Early childhood education and care programs can support physical activity and socio-emotional skills development. However, limited research has investigated the longitudinal associations between these constructs and whether they vary across child-specific and classroom-wide levels of analysis. The present study evaluated three-month trajectories of social and emotional competencies, with an emphasis on associations with physical activity. Participants were children enrolled in a licensed not-for-profit early childhood education and care provider in Canada. Educators (n = 37) across 22 classrooms completed monthly assessments of children (N = 235) from January–March 2020. Intraclass correlation coefficients revealed that significant variability in socio-emotional strengths could be attributed to between- and within-classroom differences (21 % and 47 %, respectively), and change over time (32 %). In three-level random-slopes growth curve models, socio-emotional strengths increased over time, with significant between-classroom differences in initial averages and rates of change. Child-specific and classroom-average levels of physical activity were also associated with socio-emotional strengths. These findings underscore the importance of considering child and classroom differences in early learning contexts. Moreover, incorporating physical activity in these settings holds promise as an accessible strategy to support children’s social and emotional development. Impact Statement: Children develop many social and emotional skills by participating in early childhood education and care. These programs often include opportunities for physical activity, which may be associated with socio-emotional well-being. Understanding whether these links operate in individual children and overall classrooms can help educators design curricula and allocate resources. This study showed that children in early childhood education and care programs develop socio-emotional skills over time, and these increases were associated with physical activity. Thus, incorporating physical activity into early learning could help support the development of social and emotional strengths for individual children and across classrooms.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".