¿Tienen la banda ancha y las TIC un impacto positivo sobre el rendimiento escolar? Evidencia para Chile
Bibliographic record
Abstract
En este artículo se estudia el impacto de programas de masificación del uso de Tecnologías de la Información y la Comunicación (TIC) con fines pedagógicos en Chile. En particular, se mide el impacto de dos iniciativas del Ministerio de Educación (Mineduc), Fondos para Banda Ancha (2006-2010) y TIC en Aula (2007-2011), sobre el rendimiento de estudiantes del ciclo básico en las pruebas nacionales estandarizadas de lenguaje y matemáticas, establecidas por el Sistema de Medición de la Calidad de la Educación (SIMCE) y disponibles desde 1998. Los resultados muestran que estos programas no han tenido efectos significativos en el rendimiento, ni individual ni conjuntamente, pero si fue posible identificar efectos positivos y significativos de TIC en Aula sobre grupos específicos en lenguaje, no así en matemáticas
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".