Avaliação dos Indicadores da Qualidade do Ensino Online: Um estudo de Caso
Bibliographic record
Abstract
This research aims to evaluate the quality of continuing education courses, Education for Human Rights and Environmental Education, in semipresential modality of a Public Institution of Higher Education.The SETE methodology was performe, through the application of a data collection instrument, to assess the students' opinions about the quality of the courses.The results showed good levels of evaluation in both courses, including not being perceived no statistical difference from the average of the factors F1, F2, F3 and F4.Only the fator F5 was highlighted as the best evaluated in the course of Education in Human Rights when compared to the Environmental Education course.Resumo.Esta pesquisa tem como objetivo avaliar a qualidade dos cursos de extensão, Educação em Direitos Humanos e Educação Ambiental, na modalidade semipresencial de uma Instituição Pública de Ensino Superior.A metodologia SETE foi utilizada, a partir da aplicação de um instrumento
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".