Elementos do Ensino por Investigação em atividades elaboradas por licenciandos em Química
Bibliographic record
Abstract
Ensino dE Química Em Foco Recebido em 16/03/2023; aceito em 15/01/2024 Jean M. S. Menezes e Sidilene A. Farias Compreendendo a importância do Ensino por Investigação (EI) no processo educativo, o objetivo desta pesquisa foi analisar elementos investigativos em atividades elaboradas por licenciandos em Química de Instituições de Ensino Superior públicas de Manaus, AM.Participaram da oficina 11 graduandos, cujas produções didáticas foram analisadas por meio do instrumento Diagnóstico de Elementos do Ensino de Ciências por Investigação (DEEnCI) e da Análise Textual Discursiva.Percebeu-se que os licenciandos entendem a importância que o EI possui e destacaram que tiveram contato com a estratégia de ensino somente em disciplinas de caráter pedagógico, sendo as disciplinas de conteúdo específico ainda ministradas totalmente de maneira tradicional.Os elementos do EI mais evidentes nos planos elaborados foram a definição da situação-problema, dos procedimentos e a coleta de dados e envolvimento dos alunos durante a atividade.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".