The Optimal Model of Curriculum in the Field of Ecological Literacy Education in the Elementary Schools
Bibliographic record
Abstract
The purpose of this study is to design and validate the integrated curriculum model of ecological literacy in elementary school. To this aim, descriptive-analytical-comparative method was used in model designing phase and Delphi technique was used in validation phase. The statistical population of the study in model design included eight leading countries in the field of ecology (Costa Rica, Canada, Sweden, Norway, France, Austria, Colombia, Finland) and in the validation phase 15 specialists in curriculum as well as ecology were selected by purposeful sampling. The optimal model was designed based on the four elements of Tyler curriculum where the main elements include the purpose (conservation of biodiversity, etc.) content (combination of theoretical and practical ecological training, etc.), learning activities (activities-tasks-research-oriented As a group and) and evaluation (test of naturalistic intelligence, etc.). The validation results showed that the proposed model was suitable for curriculum studies and environmental education experts and these people approved the model at a high level.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".