Bibliographic record
Abstract
En este artículo se presentan el diseño, desarrollo y resultados de una propuesta didáctica basada en un proyecto telecolaborativo al que llamamos intercambio virtual (IV) para la práctica de español e inglés como lenguas extranjeras entre estudiantes de la Universidad de Toronto (Canadá) y la Universidad Autónoma del Estado de Hidalgo (México). Dicha propuesta está basada en el modelo e-tandem (O’Rourke, 2007), en el que dos hablantes nativos de lenguas diferentes se comunican con el objetivo de crear un ambiente positivo que favorezca la práctica del idioma que aprenden. A lo largo de diez sesiones de intercambio virtual que tuvieron lugar durante un año (febrero de 2021-febrero de 2022), se observaron dos elementos que, en conjunto, muestran algunos de los beneficios de implementar un intercambio virtual: el desarrollo de la competencia comunicativa intercultural y la motivación como detonante de la proficiencia lingüística. La importancia de la comunicación mediatizada por la computadora (CMC) radica en que fomenta un acercamiento global y holístico del aprendizaje de lenguas extranjeras (LE).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".