A história da ciência na educação em ciências Da investigação realizada ao seu impacte no processo de ensino-aprendizagem
Bibliographic record
Abstract
A Educação para a Cidadania exige colocar uma maior ênfase no estudo das ciências e da sua história. A relevância da História da Ciência para o desenvolvimento da cidadania encontra eco no currículo português de Ciências Físicas e Naturais quando se afirma a importância de conhecer relatos de como ideias importantes foram aceites e desenvolvidas, ou rejeitadas e substituídas, bem como reconhecer que o conhecimento científico está em evolução permanente, sendo um conhecimento inacabado Neste artigo procurar-se-á apresentar: (a) uma revisão de investigação realizada onde se recomenda ou utiliza a História da Ciência no ensino das ciências; (b) o impacte dos seus resultados ao nível das práticas dos professores e dos manuais escolares de ciências.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.023 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".