Estratégias para Inclusão Social e Digital na Educação de Jovens e Adultos
Bibliographic record
Abstract
Este artigo e um recorte de pesquisa de mestrado realizada entre os anos de 2013 e 2014 que teve como objetivo analisar as possiveis contribuicoes de um programa de intervencao em informatica na Educacao de Jovens e Adultos (EJA), tendo em vista o desenvolvimento da inclusao social e digital dos educandos. No presente artigo, apresentamos as estrategias de ensino desenvolvidas que compuseram o programa de intervencao que teve como meta o desenvolvimento da Inclusao Social e Digital de estudantes do primeiro segmento de uma sala de EJA de uma escola municipal da cidade de Presidente Prudente-SP. Participaram do estudo cinco estudantes, de ambos os sexos, com idades entre 26 e 63 anos. Para coleta de dados foram utilizadas entrevista, formulario e observacao participante por meio de uma pesquisa de cunho interventiva. Os dados coletados foram analisados pela analise de conteudo. As estrategias desenvolvidas que compuseram o programa de intervencao foram fundamentais e contribuiram no processo de aprendizagem dos estudantes e colaboraram, ainda que de forma inicial, para a inclusao social e digital dos sujeitos da pesquisa.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".