Getting Out of the Classroom and Into Nature: A Systematic Review of Nature-Specific Outdoor Learning on School Children's Learning and Development
Bibliographic record
Abstract
Background: The value of natural environments for developing children's self-identity and social skills has been known for some time, and more recently the potential of nature-specific (i.e., excluding built environments) outdoor learning for achieving academic outcomes has been explored. Connecting children with natural spaces has been shown to benefit their physical and mental health; however, the utility of nature-specific outdoor environments as a setting for curricular and non-curricular learning has yet to be clearly established. Our aim was to undertake a narrative synthesis of international evidence of nature-specific outdoor learning and its benefits for personal and social development, wellbeing and academic progress. Methods: This systematic review searched publications between 2000 and 2020 in nine academic databases for evidence of socio-emotional and academic benefits of nature-specific outdoor learning in school-aged educational settings, using concise search criteria registered with PROSPERO. The total search results of 17,886 records were initially screened by title, and then two reviewers made blind reviews of the title and abstract of 1,019 records. Results: 147 original research studies meeting the criteria were identified. Learning settings ranged across outdoor adventure education, school gardens, field trips, and traditional school subjects taught in natural environments. Study characteristics were summarized, and risk-of-bias tools assessed quality of research as generally moderate, although with a wide range. The reported benefits of learning in natural outdoor settings include: increased student engagement and ownership of their learning, some evidence of academic improvement, development of social and collaborative skills, and improved self-concept factors. Conclusions: Nature-specific outdoor learning has measurable socio-emotional, academic and wellbeing benefits, and should be incorporated into every child's school experience with reference to their local context. Teacher pre-service and in-service education needs to include a focus on how natural settings can be used effectively for learning. Further research is needed to clarify the conditions under which specific forms of outdoor learning are most efficacious for various target outcomes. It is recommended that future studies measuring outdoor learning adopt established methodologies to improve the quality of research in this field. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=153171.
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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 | 0.013 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".