Research at the Nexus Between Physical Education and Environmental Education: A Narrative Integrative Review Through a Physical Literacy Lens
Bibliographic record
Abstract
Abstract Following inter-/transdisciplinary ideas, environmental education inherently collaborates with other subjects, including physical education. As the work with other subjects might be jeopardised by differing worldviews and paradigms, it is worth illuminating compatible and incompatible positions for inter-/transdisciplinary work. In physical education, the concept of physical literacy (PL) has recently gained considerable attention and adopts a student-centred perspective on human existence and learning. Therefore, the goal of the present narrative integrative review was to review the existing literature at the nexus between physical education and environmental education through a PL lens (five pre-defined concept assumptions). After screening for eligibility, a total of 129 articles were assigned to five different thematic categories: (a) conceptual discussion/argumentative patterns, (b) curricular discussion and international comparisons, (c) programming/intervention content, (d) teacher and enabler perspectives and (e) student outcomes/perspectives. The synthesis revealed that PL can harmonise with the educative work when respecting the disciplinary interests of both physical education and environmental education. However, few intervention studies translate the holistic PL claims into interventions. Accordingly, evaluations with teachers or students less frequently integrated holistic learning experiences in line with PL. In summary, previous research at the nexus has not yet exhausted its full inter-/transdisciplinary potential.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".