MétaCan
Menu
Back to cohort

Transformación Digital y su Impacto en la Educación Superior: Competencias Tecnológicas para Docentes y Estudiantes en la Universidad Internacional San Isidro Labrador, Costa Rica.

2024· article· es· W4398161433 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRevista El Labrador · 2024
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

La presente investigación explora la transformación digital en la Universidad Internacional San Isidro Labrador en Costa Rica, centrándose en su impacto en los procesos pedagógicos y administrativos, y en la necesidad de desarrollar competencias tecnológicas en docentes y estudiantes. El objetivo general es evaluar cómo la digitalización afecta la educación superior y proponer estrategias para una adaptación efectiva al entorno digital. Mediante un enfoque metodológico mixto, que combina técnicas cuantitativas y cualitativas, se recopiló y analizó la información. Los hallazgos revelan una brecha significativa en la adopción y uso de tecnologías digitales, destacando la importancia de competencias tecnológicas específicas. Las conclusiones subrayan la necesidad de mejorar la infraestructura tecnológica, la capacitación en competencias digitales y la promoción de una cultura de innovación. Se recomienda la implementación de programas de formación continua y la evaluación constante de estrategias de digitalización.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.294
Teacher spread0.283 · 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