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Record W4389229407 · doi:10.46990/iquatro.2023.12.1.11

Capítulo 11. Relación entre los estilos de aprendizaje con el compromiso de los estudiantes universitarios en Videojuegos, Telemática, Computación y Comunicación Multimedia del Centro Universitario de la Costa.

2023· book-chapter· es· W4389229407 on OpenAlexaff
Oscar Solís Rodriguez, Claudia Patricia Figueroa Ypiña, María del Consuelo Cortés Velázquez, Aurelio Enrique López Barrón

Bibliographic record

Venuenot available
Typebook-chapter
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsImpact
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

El objetivo de la presente investigación es determinar la relación entre los estilos de aprendizaje, con el compromiso de los estudiantes de ingenierías del Centro Universitario de la Costa.Se presenta un estudio cuantitativo, no experimental de forma transversal y con un alcance causal.La pertinencia del estudio abona a la generación del conocimiento para el desarrollo de un modelo de mejora en el proceso de enseñanza -aprendizaje dentro de las universidades.Se consideraron los estilos de aprendizaje visual, auditivo y kinestésico, entre los principales resultados podemos observar que el estilo de aprendizaje auditivo es el que tiene un mayor impacto sobre el compromiso escolar con un impacto de 0.7380688, mientras la de menor impacto es kinestésico con 0.2141692.El impacto total que tiene los estilos de aprendizaje kinestésico, visual y auditivo sobre el compromiso de los estudiantes es de 3.1277922.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0510.010

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 head0.012
GPT teacher head0.264
Teacher spread0.251 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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