The perspectives of early childhood education and care practitioners in British Columbia on their outdoor play pedagogy
Bibliographic record
Abstract
Compared with previous generations, young children in Canada have fewer opportunities to play outdoors and to experience the benefits of outdoor play such as improved physical and mental health and increased connection to the natural world. Early childhood education and care (ECEC) practitioners can increase young children’s access to outdoor play; however, they encounter challenges providing such opportunities. The purpose of this research project was to explore how ECEC practitioners who used an online outdoor play risk reframing tool (the ECO tool) describe outdoor play, their outdoor play pedagogy and the influences on their outdoor play pedagogy including the ECO tool and the COVID-19 pandemic. Eight ECEC practitioners in BC who used the ECO tool in a separate randomized control trial study of the tool were recruited for the present study. Using Symbolic Interactionism as the theoretical and methodological framework, qualitative data were collected from the participants through semi-structured online participant interviews. The ECEC practitioners described outdoor play as a valuable aspect of their programs, being child-driven, involving various forms of play, spending time in nature, and fun for children. The practitioners characterized their outdoor play pedagogy as being child-directed, and correspondingly that they minimized intervening in children’s outdoor play. Most practitioners portrayed their outdoor play pedagogy as juxtaposed to their indoor play pedagogy, where they adopted a more hands-off and less structured approach outdoors relative to indoors. Their outdoor play pedagogy also involved prioritizing time outdoors with children and providing a variety of affordances outdoors. The practitioners spoke of relationships with children, families, licensing, and colleagues as both constraints and supports on their outdoor play pedagogy. Most of the participants found that the ECO tool supported their outdoor play pedagogy; however, it had a neutral impact for a few participants. Finally, the COVID-19 created an impetus for these practitioners to enhance children’s opportunities for outdoor play, but they also encountered challenges related to the pandemic. Implications of the practitioners’ outdoor play pedagogy are discussed.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".