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Record W2786948755 · doi:10.5430/wje.v8n1p27

Mapping of Student Sustainable Development Education Knowledge in Malaysia using Geographical Information System (GIS)

2018· article· en· W2786948755 on OpenAlexvenueno aff
Hanifah Mahat, Norkhaidi Saiyidatina Balkhis

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityEnvironmental educationGeographySampling (signal processing)Education for sustainable developmentSustainable developmentNorth eastEnvironmental resource managementSocioeconomicsEcologyPsychologySociologyEnvironmental sciencePedagogyEngineeringBiology

Abstract

fetched live from OpenAlex

This article aims to examine the levels of education for sustainable development (ESD) knowledge among studentsin secondary schools according to zones in Malaysia by using GIS mapping. The five main zones of the study werethe north zone, the south zone, the east coast zone, the central zone, and the East Malaysia zone. This quantitativeform of study used a questionnaire as research instrument. Two types of sampling techniques were applied, namelystratified sampling for school selection and simple random sampling for choosing respondents from the selectedschools. The three ESD knowledge variables measured in this study were knowledge of ESD content, knowledge ofenvironmental education and knowledge of health. The study results showed that in general the levels of sustainabledevelopment education knowledge of secondary school students in all zones were high for ESD content knowledgewhile moderate for environmental education knowledge and health knowledge. Meanwhile, the GIS map clearlyindicates the levels of knowledge among students seemed high in the north zone, central zone and east Malaysia zone,at moderate levels in the south zone, and low in the east coast zone. In conclusion, there are differences between thezones in terms of levels of knowledge of sustainable development education, and this gives an indication thatincreasing sustainability-related activities in these zones with the participation of all parties—especially schools,local communities and non-governmental organisations—may disseminate sustainability knowledge and practices atall age levels and all school locations.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.083
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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