Cómo valoran y usan las Tecnologías de la Información y la Comunicación (TIC) los profesores de alumnos con Necesidades Educativas Especiales (NEE)
Bibliographic record
Abstract
La introducción paulatina de las (TIC) en todos lo ámbitos de la actividad humana está transformando la sociedad y, en consecuencia, emergen directamente dentro del escenario educativo.; por ello, en los diferentes tipos de centros de las diversas etapas educativas se están desarrollando experiencias muy interesantes, pero paulatinas y analíticas, que reflejan el aprovechamiento en las diversas áreas de la enseñanza-aprendizaje.Y desde aquí ya adelantamos que este trabajo ha pretendido abrir un foro de debate y reflexión sobre la articulación de las TIC en las aulas dando a conocer opiniones docentes con la finalidad de enriquecer formación para profesionales del diferente alumnado, contemplando, plenamente, sus nee de éste cuando las presenta.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".