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Record W4200315879 · doi:10.52080/rvgluz.26.e6.42

Modelo de calidad educativa de programas virtuales: Caso de la Universidad de San Martín de Porres

2021· article· es· W4200315879 on OpenAlexaff
Juan José Flores-Cueto, Rafael Garay-Argandoña, Ronald M. Hernández

Bibliographic record

VenueRevista Venezolana de Gerencia · 2021
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsQuebec Rehabilitation Research Network
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

El presente describe un modelo de calidad de programas de educación virtual de la Universidad de San Martín de Porres, Perú. El modelo educativo virtual se soporta en cuatro pilares de calidad, constituidos por: calidad de formación, calidad de servicio, calidad de sistema y calidad de información. Desde el plano metodológico, se planteó una investigación de orden descriptivo y proyectivo, que detalla componentes como infraestructura tecnológica, materiales digitales, conocimientos tecnológicos de los usuarios, integración de las Tecnologías de Información y Comunicación. Se concibe un aula virtual con cinco componentes: Informativa, formativa, experiencial, comunicativa e investigativa que cumplen con el aprendizaje significativo en entornos virtuales de aprendizaje. Se concluye que los elementos del modelo utilizado como referencia y basado en una mejora continua, se adaptaron perfectamente a los entornos virtuales de la Universidad de San Martín de Porres.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.316
Teacher spread0.300 · 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 teacher head, not a consensus.

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

Citations3
Published2021
Admission routes1
Has abstractyes

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