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Programa de animación a la lectura digital y su incidencia en la comprensión de textos

2024· book-chapter· es· W4406094111 on OpenAlex
María Antonella Cornejo, Nathalí Pantigoso-Leython, Sindili Margarita Varas Rivera, Ennio Rodríguez, Mirelly Zulema Chávez Ojeda

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReligación Press eBooks · 2024
Typebook-chapter
Languagees
FieldSocial Sciences
TopicLiteracy and Educational Practices
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Se realizó esta investigación con la finalidad de promover el desarrollo de la comprensión lectora en niños de 4 años; a través de la aplicación de un programa de lectura digital interactiva, diseñado para fortalecer los niveles de comprensión de textos escritos, donde los estudiantes se pueden apropiar del sistema de escritura, recuperar información de diversos textos escritos e inferir el significado de los textos escritos. Para comprobar la eficacia de dicho programa, se recogió información, mediante dos instrumentos una encuesta para la variable programa de interacción a la lectura digital aplicado a las familias, y una rúbrica de observación para identificar el nivel de comprensión lectora, con siete niveles de complejidad, en el que se ubican los estudiantes. Para el análisis estadístico se utilizó la prueba no paramétrica de Wilcoxon, para describir, analizar, contrastar y comprobar las hipótesis planteadas. Arribando a la conclusión que la aplicación sistemática del programa de animación a la lectura digital fortalece significativamente los niveles de comprensión de textos escritos en los niños y niñas.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0060.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.344
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it