Supporting the emergence of outdoor teaching practices in primary school settings: a literature review
Bibliographic record
Abstract
Outdoor teaching practices seem to be gaining in importance in many countries, and their positive effects are increasingly being documented. With the aim of providing an overview of what is known about what can support teachers who wish to teach outdoors, this article proposes a literature review on this topic. It poses the following question: What supports the emergence of outdoor teaching practices in primary schools? To answer this question, 33 texts published between 2012 and 2022 and presenting empirical results relating to outdoor teaching with primary school pupils (aged 5–12) were analysed. The results suggest six ways to support the emergence of outdoor practice: (1) building a common culture; (2) securing initiative through experimentation; (3) offering practical training in real-life contexts; (4) networking communities of professionals interested in outdoor pedagogy; (5) peer-to-peer planning, implementation and evaluation; and (6) including outdoor pedagogy in the school curriculum. Actions that could be undertaken by key players in the school field – teachers, pedagogical advisors, principals and school board administrators – to contribute to the emergence of outdoor teaching practices at the primary level are proposed.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".