Expanding understandings of outdoor play and learning in K-8 elementary schools
Bibliographic record
Abstract
This critical participatory action research (CPAR) study examined how experienced elementary (K-8) schoolteachers across the province of British Columbia (B.C.) enacted outdoor play and learning (OPAL) during instructional hours of the school day. Data for this study were collected from January to June 2022, which coincided with the COVID-19 pandemic, when interest in OPAL increased due to pandemic-related challenges with indoor instruction. In this study 18 teachers experienced with OPAL came together in an online community of practice (CoP) over a six-month period. Participants in this study were professionally employed as K-8 teachers in rural, suburban, and urban schools representing all five health authorities across the province of B.C. This research explored three questions: 1) Which skills, dispositions, and knowledge do educators who facilitate education outdoors enact? 2) Which OPAL practices and instructional routines are enacted by experienced K-8 teachers? and 3) What collective action did the CoP take to support teachers who wish to enact pedagogies of outdoor play and learning in elementary schools? Findings informed an understanding of how children access curricular learning along an OPAL continuum, in relationship to the pedagogical choices of classroom teachers. Pedagogical choices identified in this study included planning for emergent learning and the affordances of loose parts when provisioning OPAL in the K-8 school context. Findings also included the CoP identifying a need for quality professional learning, curated resources, and seasoned mentorship to build systemic capacity for OPAL. Findings from this study help resolve differences in nomenclature specific to Outdoor Education, Outdoor Learning, Outdoor Play, and Education Outdoors located under a pedagogical umbrella of OPAL in elementary schools. Finally, risky play was specifically identified by participants as a promising and enduring pedagogical approach to OPAL in the elementary school context, which may serve to disrupt existing paradigms of where and how learning happens in elementary schools. This study offers the wisdom of professional teachers, privileges their lived experience, and reports on the collective action taken to build a digital colleague (available at https://teacher.outsideplay.org) in support of OPAL in Canadian elementary schools.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".