Sistema de Ensino Naval: uma experiência na pratica do ensino por competências
Bibliographic record
Abstract
O presente artigo aborda a experiencia do Curso de Formação de Marinheiros (MN) na Marinha do Brasil na concepcao de Curriculo por competencias. Tem como objetivo apresentar a metodologia de mapeamento das competencias e dos perfis profissionais sistematizados pelo itinerario formativo atinente à profissao do MN, para o exercicio de tarefas, atividades e funcoes da Forca. Para acompanhar esse processo de formação, foi adotado um calendario unificado de atividades nas quatro Escolas de Aprendizes-Marinheiros (EAM) e desenvolvida uma sistematica de avaliação que possibilite avaliar as competencias delineadas no curriculo por meio de provas padronizadas. Serao apresentados os resultados do desempenho academico dos alunos das quatro EAM e analisados, comparativamente, em relação ao desempenho da turma do ano anterior, indicando uma melhora do desempenho dos alunos e a evolução qualitativa da turma de 2017, apos implementadas acoes em busca de uma formação continua e progressiva.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".