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Record W4415775555 · doi:10.1177/10538259251359572

From ‘Pool Noodle Tag’ to Building Snow Forts: Experiential Outdoor Education as Pedagogical job Crafting During the COVID-19 Pandemic

2025· article· en· W4415775555 on OpenAlexaffabout
J M Laidlaw, Jay Johnson

Bibliographic record

VenueJournal of Experiential Education · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsExperiential learningOutdoor educationThematic analysisFlourishingPhysical educationExperiential educationReflexivityPandemic

Abstract

fetched live from OpenAlex

Background The coronavirus disease 2019 pandemic significantly impacted education systems across the world. Physical education teachers were particularly affected by public health mandates, as many were displaced to teach in virtual and/or outdoor contexts while their gymnasiums were co-opted to become classroom learning spaces. Purpose Our research objective was to explore how physical education teachers engaged in job crafting via their pedagogical practices to accommodate public health mandates throughout the pandemic. Method Through semistructured interviews, ten ( n = 10) Canadian physical education teachers unpacked their professional experiences. Interview discussions were textually transcribed and analyzed via coding and reflexive thematic analysis approaches. Findings We conceptualized these teachers’ pivoting to experiential education approaches as a form of pedagogical job crafting, efforts to not only support their students’ learning and engagement, but also to sustain their own occupational flourishing and sense of meaningfulness. By adapting their pedagogical practices, these teachers were able to circumvent various occupational stressors, supported their students’ learning and engagement, and demonstrated attitudinal developments regarding their own occupational roles and identities within the school system. Implications These findings may provide insight for future researchers to explore and better understand how pedagogical job crafting may support and sustain teachers’ practices, particularly during strenuous circumstances.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.117
GPT teacher head0.544
Teacher spread0.428 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations0
Published2025
Admission routes2
Has abstractyes

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