Impacto del círculo de lectura para desarrollar habilidades blandas en futuros ingenieros
Bibliographic record
Abstract
En este artículo se presentan los resultados de un análisis cualitativo llevado a cabo en el Instituto Tecnológico Superior del Occidente del estado de Hidalgo, sobré estrategias de lectura, con el objetivo de gestionar el desarrollo de habilidades blandas en Estudiantes de Ingeniería. Cómo metodología en primera instancia, se implementó un prototipo de círculo de la lectura, donde se establecieron reglas por los integrantes, en el marco de actividades complementarias IV, los resultados de esta actividad reflejaron que los alumnos muestran interés por el material bibliográfico utilizado en los programas educativos. De esta manera se provee un ambiente mas libre para establecer vínculos emocionales con la lectura, elevando su confianza, para expresar sus ideas y madurez emocional. Lo cual propone una hipótesis de trabajó futuro, el saber si existe un mayor atractivo al estudiante para mejorar su redacción cuando han logrado un vinculo emocional con la lectura.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".