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Estrategia pedagógica para el desarrollo de la competencia de autonomía emocional y moral en los estudiantes de Turismo de la Universidad de La Habana

2020· article· es· W3000670664 on OpenAlexvenueno aff
Yulima Daimet Valdés Bencomo, Orietta Martínez Chacón

Bibliographic record

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

Abstract

fetched live from OpenAlex

El trabajo presenta la elaboración de la Estrategia Pedagógica para el desarrollo de la competencia de autonomía emocional y moral (EPDCAEM) en la formación profesional de estudiantes de turismo de la Universidad de La Habana, se fundamentó en el enfoque histórico cultural del desarrollo humano que sustenta la concepción de enseñanza aprendizaje desarrollador. Resultado que constituyó el objetivo del estudio. La estrategia metodológica seguida fue el enfoque mixto complejo en tres etapas: exploratoria, descriptiva transformadora y transformadora, mediante recursos de la Investigación Acción Participativa (IAP), en los ciclos: planeación, observación, reflexión acción. Se precisa el concepto de competencia de autonomía emocional y moral resultante de la sistematización teórica, al considerar indicadores emergentes desde su desarrollo, mediante procedimientos vigotskianos de diagnóstico actual y potencial, durante la construcción progresiva y verificación de la estrategia, con la participación activa de profesores y estudiantes, desde la disciplina principal integradora, en el proceso formativo. Se concluye sobre el valor del fundamento teórico metodológico asumido, la perspectiva holística e integradora de la EPDCAEM del profesional de turismo y su carácter dinámico, flexible, funcional, transformador, transversal a la instrucción y educación en la formación, desde la ciencia pedagógica.

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)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0080.004
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.036
GPT teacher head0.362
Teacher spread0.325 · 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 designNot applicable
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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Citations1
Published2020
Admission routes1
Has abstractyes

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