Environmental and sustainability education in teacher education research: an international scoping review of the literature
Bibliographic record
Abstract
Purpose Halfway into the United Nations (UN) sustainable development goals (SDGs) timeline, we deemed fruitful an injunction into current teacher education (TE) practices at higher educational institutes (HEIs). The scoping literature review used all known English nomenclature interrelating to environment, sustainability, development, and education as regards TE. We explicated and modelled the data through timelines favourable to UN initiatives within a spatiotemporal metric. Thematic research topics and research methodologies strictly pertaining to TE were rigorously researched and delineated. Our study aims to elucidate a grander picture of the trends-as-patterns of environmental and sustainability education in teacher education (ESE-TE) research in HEI and potential contributions to come. Design/methodology/approach The spatiotemporal study adopts a scoping review as an investigative tool to probe current research trends on ESE-TE in the academic literature with respect to thematic research topics and research methodologies midway through the SDGs. Findings A total of 2,142 research papers spanning five decades, 152 journals and 96 countries were screened equally by two researchers. Of the 788 papers deemed eligible (i.e. English-language, peer-reviewed, pre-service/in-service TE that explicitly mentioned ESE-TE research), data from 638 studies have been included in the authors’ study. Originality/value Comprehensive trends in the international literature of all known environmental and sustainable education nomenclature specific to international ESE-TE research throughout the time period (1974 – 2021) were identified. Value is accrued by illuminating international trends in research topics and methodologies, exposing gaps in the history of the subfield, and predicting future trends for Agenda 2030 (e.g. SDG 4 – education) to mature the field.
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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 | 0.042 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.043 | 0.048 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".