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Record W4375861474 · doi:10.37811/cl_rcm.v7i2.5735

La Disciplina Positiva y su Impacto en el Rendimiento Académico de los Estudiantes.

2023· article· es· W4375861474 on OpenAlexaff
Edgar Ricardo Calderón Sánchez, Carlos Luis Montalván Manzanillas, Mirian Azucena Guartán Serrano, María Eugenia Moreta Segura, Ingrid Yulexi Troya Saldivia

Bibliographic record

VenueCiencia Latina Revista Científica Multidisciplinar · 2023
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

La disciplina positiva es un enfoque educativo que se centra en la enseñanza de habilidades sociales y emocionales, así como en la construcción de relaciones saludables entre el educando y el docente. Se enfoca en fomentar la responsabilidad y la autorregulación en los estudiantes a través de la enseñanza de habilidades sociales y emocionales. Por lo tanto, permite la creación de un ambiente escolar positivo y respetuoso entre compañeros. El objetivo del estudio es establecer la relación de la disciplina positiva con el rendimiento académico de los educandos en las diferentes instituciones educativas. En base al marco metodológico es un estudio con enfoque cuantitativo con diseño pre-experimental; para la recolección de datos se utilizó como técnica la encuesta y como instrumento el cuestionario; de igual forma, para procesar los datos recolectados se utilizó el software Microsoft Excel e IBM SPSS Statistics. Los hallazgos encontrados en la presente investigación dieron como resultado que el impacto de la disciplina positiva de los estudiantes en relación al rendimiento académico tiene un efecto significativo. Algunos estudios han encontrado que los estudiantes que reciben una educación basada en la disciplina positiva tienen mejores resultados educativos en los procesos áulicos que aquellos que no la reciben.

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)0.019
metaresearch head score (Gemma)0.053
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.053
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0040.006
Scholarly communication0.0090.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.021
GPT teacher head0.354
Teacher spread0.333 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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