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Record W2156845779 · doi:10.5539/ies.v7n4p33

Environmental Education in the Teaching and the Learning of Scientific Disciplines in Moroccan High Schools

2014· article· en· W2156845779 on OpenAlexvenueno aff
A. El Moussaouy, Jamila Abderbi, Mimoune Daoudi

Bibliographic record

VenueInternational Education Studies · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)Mathematics educationStyle (visual arts)Teaching methodPsychologyPedagogyHigher educationEnvironmental educationGeographyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.326
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2014
Admission routes1
Has abstractyes

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