The Experiences and Understandings of Environmental, Outdoor, and Experiential Educators: A Narrative Inquiry Approach
Bibliographic record
Abstract
The purpose of this study was to explore the experiences of an exceptional subset of environmental, outdoor, and experiential educators. This study sought to understand how and why their experiences were most significant for their understanding and relationships with nature and led to their lifelong commitment and development of a career in the field of environmental, outdoor, and experiential education. Participants of this study consisted of environmental, outdoor, and experiential educators within Canada. Data was collected through two sixty to ninety-minute semi-structured interviews. The data was analyzed using an inductive process according to the narrative analysis and analysis of narrative approach outlined by Polkinghorne (1995). A deductive approach was also used to apply the place-based education design principles (Sobel, 2008) to the study findings. The participant narratives have been re-storied to emphasize their experiences and perspectives that align with the overall study intent. Themes pertaining to each narrative have been identified, and represent the expressions, understanding and memories of participants in relation to the research questions. In the discussion section, key findings that emerged across all participant narratives are detailed in connection to the research questions, literature, and place-based education design principles (Sobel, 2008). There are implications and considerations for educators from this study, and this research adds to scholarship in the field of environmental, outdoor, and experiential education through the stories of seven exceptional educators.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| 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".