Dünyada ve Türkiye’de Ortaokul Öğretim Programlarının İklim Değişikliği Eğitimi Yaklaşımına Göre Karşılaştırılması
Bibliographic record
Abstract
Climate Change Education (CCE) is an approach that has started to establish its own identity in recent years. Many countries have begun to integrate global climate change into their curricula according to the CCE approach, following the UNESCO call. The aim of this study is to compare the curricula of Turkey with those of other countries which cover Climate, Climate Change, and Global Warming in terms of goal (gain). The countries and states with the highest scores in PISA (2015) were selected. The data obtained in this study were collected using the document analysis method as a qualitative research method. According to the CCE approach, issues related to climate and climate change are covered using an interdisciplinary approach in Germany, USA, Australia, Canada, Spain, Republic of South Africa (RSA) and Turkey while they are covered using a disciplinary approach in Sweden. In Finland and England, both disciplinary and interdisciplinary approaches are used with students. Establish a connection between local environmental issues and climate change, which is one of the components of CCE, can be found in the curricula of Finland, Sweden, Spain, Canada, Germany and RSA. In addition, comparison of the effects of climate change on the continents are made in the curricula of Finland and Australia. The topics of local effect of climate change and sustainability are cursory in the curricula of Turkey and USA. Curricula are focused on the environmental problems of the Baltic region in Finland, environmental problems in the African continent in RSA, especially water scarcity, and Australia’s ecological problems in Australia. While teaching past climate changes is a highlight of the CCE approach, only students in the UK learn how to interpret climate changes from the ice age to the present.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".