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Record W7036002095

Análisis de las páginas web de los centros educativos de Navarra

2019· dissertation· es· W7036002095 on OpenAlexfundno aff

Bibliographic record

VenueAcademica-e (Universidad Pública de Navarra) · 2019
Typedissertation
Languagees
FieldComputer Science
TopicEducational Technology in Learning
Canadian institutionsnot available
FundersIndependent Electricity System Operator
KeywordsWeb siteWeb technologyWeb testingInformation center
DOInot available

Abstract

fetched live from OpenAlex

El objetivo de este trabajo es analizar las páginas web de los centros educativos de Navarra. El análisis incluye un detallado estudio centrado en aspectos relacionados con el contenido de las páginas, las redes sociales y la comunicación , y aspectos técnicos y de diseño que transmiten las instituciones educativas a través de Internet. La incorporación de las nuevas Tecnologías de la Información y Comunicaciones ha provocado que las instituciones educativas se hayan visto comprometidas en gestionar las páginas web de los centros para mostrarse ante la sociedad. Además, la información que transmiten las páginas web debe estar dirigida a alumnos, padres y profesores que tratan de buscar información útil acerca del centro. Tras realizar la investigación se realiza una comparación del estado de las páginas web de los centros públicos frente a los concertados de Navarra. Los resultados muestran que hay una deficiencia clara en cuanto a contenidos publicados, y aspectos técnicos y de diseño que deben mejorar. Al finalizar, se efectúa una propuesta para diseñar una página web institucional con contenido considerado como útil y diseño atractivo.

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)0.012
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 score0.205
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.013
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.010
GPT teacher head0.298
Teacher spread0.287 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueAcademica-e (Universidad Pública de Navarra)Same topicEducational Technology in LearningFrench-language works237,207