Teachers’ perspectives about integrating environmental education in the English language curriculum in Seychelles, Mahé Island
Bibliographic record
Abstract
This inquiry explored teachers’ perspectives about integrating environmental education (EE) into the English language curriculum in a Seychelles secondary school. The Seychelles, whose economy relies primarily on tourism and fisheries, is facing a growing climate crisis due to anthropogenic activities. Accordingly, Seychelles’s National Curriculum Framework emphasizes the integration of EE at all levels in schools. This qualitative study used document analysis, analysis of teachers’ schemes of work, observations, and semi-structured interviews to examine the integration of EE into English language instruction at a Seychelles secondary school. The results suggest that implementation is impeded by a lack of resources, professional development, and teacher self-efficacy. Creating professional development experiences, improving teacher education, and developing better teaching resources can enhance the introduction of EE into English language instruction. Such instruction can promote the sustainability needed to foster the emerging blue economy of the island country.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".