Early Childhood Educators’ Knowledge, Self-Efficacy and Risk Tolerance for Outdoor Risky Play Following a Professional Risk Re-Framing Workshop
Bibliographic record
Abstract
Children’s outdoor risky play is important for healthy development. However, Early Childhood Educators (ECEs) concern for child safety often restricts risky play affordances during childcare. To reduce this trend, an Outdoor Play Risk Re-Framing workshop was delivered to ECEs in London, Ontario, and the immediate/short-term impact of the workshop on ECEs’ knowledge, self-efficacy, and risk tolerance for engaging children in outdoor risky play was examined. Via a natural experiment, using a quasi-experimental design, ECEs in the experimental group (n = 119) completed an Outdoor Play Risk Re-Framing workshop, while ECEs in the comparison group (n = 51) continued their typical curriculum. All ECEs completed the same survey assessing their knowledge (n = 11 items), self-efficacy (n = 15 items), and risk tolerance (n = 27 items) at baseline and 1-week post-intervention. A maximum likelihood linear mixed effects model was conducted, while deductive content analysis was used for open-ended items. The workshop intervention resulted in significant improvements in ECEs’ self-efficacy (p = 0.001); however, no significant changes were observed for knowledge (i.e., awareness and practices; p = 0.01 and p = 0.49, respectively) or risk tolerance (p = 0.20). Qualitative data revealed similar findings across both groups, highlighting physical development as a benefit to outdoor risky play and fear of liability as a barrier. In conclusion, providing ECEs with an Outdoor Play Risk Re-Framing workshop shows promise for supporting their self-efficacy to promote this behavior but does not impact ECEs’ knowledge or risk tolerance to lead outdoor risky play.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".