B-learning: Aula invertida para el aprendizaje de los verbos “ser” y “estar” en estudiantes de español como lengua extranjera
Bibliographic record
Abstract
Este capítulo presenta los resultados de una investigación que evalúa la efectividad del modelo ‘b-learning’ y la estrategia del aula invertida en la enseñanza de los verbos “ser” y “estar” a estudiantes de español como lengua extranjera en el colegio Halifax County High School. Se utilizó la plataforma Canvas para facilitar la implementación de módulos educativos con actividades interactivas. La investigación se desarrolló bajo una metodología cualitativa y un diseño de estudio de caso, empleando herramientas de recolección de datos como entrevistas, cuestionarios y análisis documental. Los resultados mostraron que, aunque algunos estudiantes continuaron enfrentando dificultades para distinguir los usos y formas de los verbos “ser” y “estar”, el modelo b-learning, combinado con la estrategia del aula invertida, mejoró significativamente su comprensión y aplicación. Los módulos interactivos permitieron a los estudiantes aprender de forma autónoma y a su propio ritmo, mientras que las actividades colaborativas fortalecieron la interacción y el aprendizaje compartido.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".