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Record W4311789148 · doi:10.3389/feduc.2022.961054

School-based outdoor education and teacher subjective well-being: An exploratory study

2022· article· en· W4311789148 on OpenAlexaffabout
Antoine Deschamps, R. A. Scrutton, Jean‐Philippe Ayotte‐Beaudet

Bibliographic record

VenueFrontiers in Education · 2022
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologySubjective well-beingExploratory researchWell-beingPositive correlationSchool teachersDevelopmental psychologyPedagogyHappinessSocial psychologyMedicineSociology

Abstract

fetched live from OpenAlex

Can school-based outdoor education (OE) benefit teachers’ well-being? Multiple studies have reported the positive impact of OE on students’ well-being and the benefits of contact with nature for adults. However, a literature review revealed no research on the impact of OE on teachers’ well-being. This study explores the possible relationships between OE and preschool and primary school teachers’ subjective well-being (SWB) in Québec, Canada, during COVID-19. A survey measuring teacher SWB was conducted; 381 teachers responded, 164 practiced OE, and 217 did not. The questionnaire results indicated that teachers who practice OE have significantly higher SWB than their colleagues ( d = 0.21 to d = 0.36). However, only a limited positive correlation was found between teacher SWB and the number of times teachers practice OE ( rho = 0.184). This study suggests that school-based OE is positively related to teacher SWB and therefore has the potential to benefit teachers and students alike.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.319
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2022
Admission routes2
Has abstractyes

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