Environmental Education in the Teaching and the Learning of Scientific Disciplines in Moroccan High Schools
Bibliographic record
Abstract
In this work we investigate the place and the importance of environmental education (EE) in Moroccan high school education with a focus on Physics/Chemistry and Biology/Geology classes. It is performed within a comparative method by using an interdisciplinary approach in order to understand the presence and the pedagogical styles adopted for the implementation of EE in both disciplines. This study is accomplished via an anthropological theory of knowledge to analyze textbooks and a questionnaire administered to 90 teachers of these disciplines throughout different high schools in Oujda academy, Morocco. The analyses of collected data were performed by adopting a statistical descriptive method. Results show that the presence and the importance of EE are mediocre and its contribution to learning activity is dominated by informative pedagogical style. Similarly, questionnaire results reveal that the implementation of EE in their practices cannot enable learners to construct competencies and skills that would help them adopt a positive behavior towards the environment because first, the presence of EE in their classes is almost absent especially in P/C classes, second, teachers’ practices are overwhelmed by the informative pedagogical style. Furthermore, respondents have never benefited from basic and in-service training and their interdisciplinary professional collaboration is totally lacking.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".