Estudio de la aplicabilidad de un entorno integrado de diseño de aprendizaje (ILDE) en Educación Secundaria y Bachillerato
Bibliographic record
Abstract
El ILDE (Entorno Integrado de Diseño de Aprendizaje) es un resultado del proyecto\n\t\t\t\t METIS, que trata de fomentar y mantener la adopción por parte de los docentes de las\n\t\t\t\t prácticas de Diseño de Aprendizaje. El ILDE integra en una única plataforma todas las\n\t\t\t\t herramientas Diseño de Aprendizaje que los profesores necesitan durante el ciclo de\n\t\t\t\t diseño de aprendizaje para (co-)crear, explorar, compartir e implementar diseños de\n\t\t\t\t aprendizaje en los principales VLEs (Entornos de Aprendizaje Virtuales).\n\t\t\t\t El ILDE ha sido puesto a prueba en la práctica educativa real en los tres sectores a los\n\t\t\t\t que se dirigía el proyecto METIS: Formación Profesional, Educación Universitaria y\n\t\t\t\t Educación de Adultos. En este Trabajo Fin de Máster exploramos la capacidad del\n\t\t\t\t ILDE para adaptarse al contexto de Secundaria y Bachillerato. Con ese objetivo,\n\t\t\t\t describimos un estudio de caso en el que hemos utilizado el ILDE para diseñar y\n\t\t\t\t desplegar una actividad de aprendizaje colaborativo mediante TICs en una asignatura de\n\t\t\t\t electrónica de Bachillerato.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".