Bridging the gap between theory and practice: development of a framework and resources for school-based outdoor education through action research
Bibliographic record
Abstract
Abstract In Québec, Canada, interest in school-based outdoor education is growing, driven by educators’ grassroots efforts and ministerial support. Despite its increasing adoption, a shared understanding of school-based outdoor education remains lacking. In response to this lack of shared understanding, this study adopted an action research approach, engaging 37 practitioner-researchers across various educational and professional roles to co-develop a framework and resources for school-based outdoor education. Guided by Guay and Gagnon’s (2021) methodology, our research team and practitioner-researchers collaboratively identified the current situation, priority problems, and a desired situation, as well as the research, action, and educational aims of the study. The resulting framework includes a clear, consensus-based definition and eight guiding principles that reflect a diversity of practices and contexts. Additionally, six professional development resources were co-created to support outdoor education across different educational levels and sectors. These resources aim to promote a shared understanding and facilitate capacity-building among educators, administrators, and public health professionals. Findings highlight the importance of intersectoral collaboration, contextual sensitivity, and professional learning in developing a framework and resources for school-based outdoor education. The study’s contributions include a contextually grounded framework and practical resources to support policy development, pre-service and in-service training. While the framework was validated by collaborating practitioner-researchers involved in this action research, its relevance and transferability in other educational contexts—such as different provinces, international settings, or culturally diverse communities—remain to be further explored.
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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 | 0.230 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.008 |
| Science and technology studies | 0.020 | 0.071 |
| Scholarly communication | 0.030 | 0.023 |
| Open science | 0.012 | 0.030 |
| Research integrity | 0.009 | 0.010 |
| 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".