Understanding Teachers’ Participation in Nature-based Field Trips: A Study from an Alberta Conservation Area
Bibliographic record
Abstract
Exposure to and engagement with nature may improve children’s health, physical activity levels and foster positive physical and psychological development. Outdoor experiences can be supported through nature-based school field trips; however little is known of the motivation for teachers to select natural educational experiences. This study explored teachers’ environmental attitudes, their perception of benefits, and their perception of supports and challenges in planning and implementing nature-based field trips for their students. 34 teacher participants filled out a modified version of the New Environmental Paradigm (NEP), consisting of 37 Likert-scale questions on environmental attitudes, prior experiences with nature, and school culture in relation to nature-based programming. Descriptive statistics were used to identify three distinct categories of findings: (a) attitudes, (b) perceived benefits, and (c) supports. Analysis indicates that the majority of participants reported a pro-ecological attitude. The paper concludes that early nature experiences, in company with a pro-ecological attitude, may be a factor contributing to teachers’ motivation in planning, facilitating, and promoting nature-based experiences with and for students. Without attempts to generalize from this small sample size, findings are promising for the endorsement of all types of outdoor experiences to support school programming and curricular planning.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".