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Record W7132990167

Fortalecimiento de los procesos lecto-escritores a través de la ilustración

2019· dissertation· es· W7132990167 on OpenAlexaboutno aff
Edilson Ayen Poveda Rodríguez

Bibliographic record

VenueRepositorio Institucional FULL · 2019
Typedissertation
Languagees
FieldSocial Sciences
TopicLiteracy and Educational Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeContext (archaeology)Order (exchange)Subjectivity
DOInot available

Abstract

fetched live from OpenAlex

El proyecto de intervención disciplinar El fortalecimiento de los procesos de lecto-escritura a través de la ilustración que se llevó a cabo en la institución Provincia de Quebec I.E.D, surge de la apatía hacia la lectura y la escritura encontrada en el aula de clase. Durante la búsqueda de una solución se encuentra que los estudiantes compartían el gusto por el dibujo y tomando este aspecto como base de la intervención pedagógica, se planteó como objetivo, fortalecer los procesos de lecto-escritura en los niños y niñas del grado 4 de primaria jornada tarde de dicha institución a través del dibujo (ilustración). De esta manera, la estrategia “Construyendo mi Macondo”, se dividió en algunos talleres donde los estudiantes a través del uso de diferentes técnicas artísticas representaban sus interpretaciones del texto Cien Años de Soledad, al mismo tiempo que se promovía el desarrollo de las habilidades artísticas y comunicativas. A partir de esto se reflexiona acerca de la importancia del arte no solo en el mejoramiento de los procesos académicos sino en la construcción de mejores relaciones convivenciales en el aula de clase.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0080.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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.

Opus teacher head0.015
GPT teacher head0.361
Teacher spread0.346 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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