Exploring Effective Pedagogies in Environmental and Sustainability Education for Teachers: A Story of New Zealand Pre-Service Teachers’ Learning Experiences
Bibliographic record
Abstract
Although teachers have been identified as key change agents in the shift towards a flourishing planet for all, research into effective pedagogies for embedding environmental and sustainability education (ESE) into teacher education courses is an emerging area. Understandings about the most effective approaches and activities are needed, along with theories that could underpin teachers’ learning. This study explores 21 pre-service primary school teachers’ learning following their engagement in an elective course designed to help them embed ESE into their future practice. Qualitative data were gathered using reflections as well as peer and individual interviews. An analysis showed that the activities considered most valuable for learning were those that gave pre-service teachers space and time to think more deeply and in different ways. Mezirow’s transformative learning theory was used to explore their learning. The use of its three elements and six components identified that transformative learning took place for about half of these pre-service teachers. While it seems this theory has potential to underpin ESE teacher education courses, further research is needed to explore how transformation can occur for more teachers.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.022 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".