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Evaluación educacional a las tecnologías de información y comunicación con modelos estadísticos

2020· article· es· W3096784347 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.

venuePublished in a venue whose home country is Canada.
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

VenueConcienciaDigital · 2020
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

El artículo pretende exponer la evaluación de impacto realizada para determinar el nivel de incidencia de las Tecnologías de Información y Comunicación, y los resultados alcanzados en el rendimiento académico con el estudio piloto “Sistema de Tutoría Cognitiva para educación secundaria en Ecuador”, proyecto implementado por la Escuela Superior Politécnica del Litoral. Para su desarrollo, se especifica el modelo estadístico y los resultados alcanzados a lo largo de un estudio de diseño cuasiexperimental. Los resultados permiten establecer su efecto sobre el rendimiento académico en la asignatura de matemática en estudiantes de octavo de educación básica de Unidades Educativas ubicadas en zonas urbano-marginales de la ciudad de Guayaquil que colaboraron en el estudio piloto. En conclusión, estudio piloto Sistema de Tutor Cognitivo tiene un impacto de 0,54 puntos en la nota promedio de la asignatura de matemática, logrando disminuir al menos en la muestra estudiada la brecha de conocimiento en los estudiantes del grupo de tratamiento.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
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 head0.045
GPT teacher head0.315
Teacher spread0.270 · 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