Environmental Learning as a Unique Context for Science Education
Bibliographic record
Abstract
Challenges faced by science and environmental educators in respect to the distinctions and interrelationships between these fields have been many over the past few decades. While some scholars note contradicting epistemologies and purposes in their critique of the nature of an environmental (science) education, this paper considers another perspective: through participatory methods it examines how environmental learning may form a unique and qualitatively different context for science education. The paper also highlights a collaborative inquiry into the practices of environmental learning as it is enacted in formal school curriculums in British Columbia, Canada. Our efforts involved critical document analysis of frameworks and resources from around the world. Focus groups and interviews conducted over a period of 16 months informed a collaborative writing process that included teachers, academics and government officials. The framework produced offers a conceptual view for environmental learning in all settings (including science) while providing several principles of teaching and learning to guide educators in designing activities for varied learning contexts. The framework provides a number of perspectives around which environmentally-focused lessons may be developed and demonstrates that environmental education should included scientific understandings but be broadened to include other forms of knowledge including aesthetic appreciation, social responsibility and the development of an environmental ethic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.029 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| 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".