A Comparative Study of the Subjects on Ecosystem, Biological Diversity and Environmental Problems in Turkish Science Curriculum with the International Curricula
Bibliographic record
Abstract
In this study, Turkey’s Science Curriculum 2013 was compared with that of the other countries (England, Ireland, Finland, Canada, New Zealand, and USA (New Jersey and Massachusetts)) that produced above the average results in TIMSS (1995, 1997, 2003 and 2007) exams in subjects on Ecosystem, Biological Diversity, and Environmental Problems. In terms of vision, the curricula of Finland and England lay greater emphasis on the ‘environment’. “Technology-society-environment” relations are emphasized in only Turkey’s Curriculum. Understanding and discovery of the natural world, gaining environmental knowledge, and man-environmental relations are included in Turkey’s curriculum in terms of aims. Besides, there has been an emphasis on the development of sustainable natural resources in Turkey’s curriculum; whereas biological diversity is excluded just as in the curricula of Finland, England, New Zealand, Ireland, and New Jersey. The goals related to the man-environment interaction are included in the curricula of Turkey; whereas, those related to the mutual relationship between other living things are not considered. This indicates that Turkey’s curriculum is anthropocentric. There have been variations in the composition of curricula of different countries compared with Turkey’s curriculum, in terms of organization of the subjects such as ecosystem, biological diversity, and environmental problems. There is no separate course in Turkish curriculum as in Finland, and no different learning strand as in the science curriculum of Ireland and New Jersey province of the USA. In the curricula under study, while there is one subject in a country’s curriculum, others may not have the same. Some of the countries determined the topics by giving importance to their local needs or adopted approaches that prevent learning environment as an integrated and universal subject. In order to overcome these deficiencies, it is imperative to design a universal environmental education.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".