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Las actividades extracurriculares, un medio para aumentar la motivación en el aprendizaje del idioma inglés

2020· article· es· W3046023018 on OpenAlexvenueno aff
Silvia Narcisa Cazar Costales, Gabriela Paulina Dávila Yánez, Cristina Paola Chamorro Ortega, Karen Alexandra Plua Vinces

Bibliographic record

VenueConcienciaDigital · 2020
Typearticle
Languagees
FieldSocial Sciences
TopicEducation and Teacher Training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyCartographyPolitical scienceArt

Abstract

fetched live from OpenAlex

En la actualidad la globalización juega un papel importante en la comunicación mundial, esto ha incrementado el interés de los estudiantes universitarios sobre todo porque corresponde curricularmente una norma a ser cumplida para la obtención de su título académico en el Ecuador. La clave para el desarrollo exitoso de la sociedad del conocimiento en áreas de carácter comercial es la internacionalización, es por ello que el aprendizaje eficiente de un idioma extranjero desempeña un papel importante en la formación de las cualidades personales y culturales del estudiante. El presente trabajo ejemplifica la organización de varias actividades extra curriculares aplicada en cuatro grupos de prueba con estudiantes de administración, supervisadas por los docentes que imparten la asignatura inglesa en los niveles planificados por cada carrera. El factor asociativo y de convivencia es fundamental para el normal desenvolvimiento de las actividades como clubs de inglés, semanas y escuelas de verano y actividades artístico culturales como el teatro y el canto.

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)0.003
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: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.003

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 head0.051
GPT teacher head0.358
Teacher spread0.306 · 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".

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Citations4
Published2020
Admission routes1
Has abstractyes

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