Mapping of Student Sustainable Development Education Knowledge in Malaysia using Geographical Information System (GIS)
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".