L’enseignement par projets comme objet d’étude en didactique des sciences et technologies
Bibliographic record
Abstract
Resumo: O ensino por projetos (EPP) é um dos enfoques pedagógicos que marca as reformas curriculares em vários países. No caso do ensino de Ciências e Tecnologias (ST), apesar do grande número de estudos que mostrou o impacto positivo do recurso ao EPP nas aprendizagens dos alunos (Hasni et al., 2016), outros textos científicos tendem a demonstrar que as condições de sucesso de sua implementação exige muito dos docente (Bousadra, 2014; Chin & Chia, 2006; Kanter, 2009; Krajcik et al., 2007). Se o leque das finalidades educativas visadas por esse tipo de ensino assim como a diversidade de seus referentes teóricos podem explicar a divergência dos resultados das pesquisas empíricas, a questão da fragilidade dos saberes disciplinares para esse tipo de enfoque permanece ainda pouco considerada na pesquisa atual em didática das ST. Nesse texto, propomos um quadro conceitual e metodológico que permite abordar esse ponto de vista. Palavras-chaves: ensino por projetos, didática das ciências, prática de ensino
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".