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Record W2177178959 · doi:10.22458/ie.v17i22.1097

Estrategias para la evaluación en educación a distancia: un análisis de las opciones empleadas en el programa de educación general básica de la UNED

2015· article· es· W2177178959 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInnovaciones educativas · 2015
Typearticle
Languagees
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

El artículo expone algunos los hallazgos de la investigación que se llevó a cabo gracias al financiamiento de la Coordinación Educativa y Cultural Centroamericana (CECC/SICA); se analizaron las opciones empleadas en la evaluación de los aprendizajes de nueve asignaturas pertenecientes al Programa de Educación General Básica I y II Ciclos, de la Escuela Ciencias de la Educación en la Universidad Estatal a Distancia de Costa Rica (UNED). Se empleó una metodología de investigación mixta; en esta entrega se brindan los resultados correspondientes al primer objetivo de la investigación que responde a la etapa cuantitativa: “Identificar la índole de opciones evaluativas que se emplean en las asignaturas para recopilar las evidencias de aprendizaje del estudiantado”; se examinaron documentos pertenecientes a dos periodos académicos y se logró determinar que en la mayoría de los casos se evalúa por medio de pruebas escritas, tareas o proyectos que incluyen al menos un instrumento de evaluación como, por ejemplo, ensayo, entrevista, cuadro comparativo o reporte de observación.

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)0.006
metaresearch head score (Gemma)0.002
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 score0.720
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.001
Research integrity0.0010.002
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 head0.025
GPT teacher head0.369
Teacher spread0.344 · 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