Nature-based early childhood activities as environmental education?: A review of Japanese and Australian perspectives
Bibliographic record
Abstract
In this paper we review the forest kindergartens and Skogsmulle programs (Swedish outdoor programs) as well as the formally registered early childhood services in Japan. All of these different service types are known to include nature-based activities for young children. The formally registered early childhood services are subject to national guidelines (CAO et al. 2017, MEXT 2017, MHLW 2017) that require nature-based activities to promote children’s development. However, these guidelines fall short on matters of global sustainability, environmental issues, environmental education (EE), or education for sustainability (EfS), thus we argue a comprehensive approach is lacking and a gap in practices evident. We suggest that the two alternative service types, forest kindergartens and Skogsmulle programs, offer more potential to promote EE/EfS than the formally registered early childhood services. We also briefly review Australian early childhood policies and settings and identify a similar situation, where nature-based activities appear to deflect from a comprehensive approach to EE/EfS. We argue that a critical analysis of policies and improvement of pre-service and in-service teacher programs to build sustainability knowledge and pedagogical skills is required. Also the establishment of collective professional networks across the varied nature-based activity programs and service types is necessary across each nation to transform existing nature-based activities into effective EE/EfS approaches and practices for global sustainability. We also identify this review paper as a precursor to further research in this topical area.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".