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Record W4390688225 · doi:10.18050/eduser.v9n2a4

Rúbrica de evaluación en la satisfacción del estudiante en una universidad peruana

2022· article· es· W4390688225 on OpenAlex
Julio Ernesto Rojas Galarza

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

VenueREVISTA EDUSER · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicDiverse Applied Research Studies
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPhysicsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

El estudio tuvo como propósito determinar el impacto del uso de las rúbricas de evaluación para lograr medir niveles de satisfacción de estudiantes universitarios en el Perú. El método pertenece a la ruta cuantitativa, de nivel correlacional causal, no experimental, método hipotético deductivo, el grupo de estudio estuvo representado por 83 estudiantes universitarios. Los cuestionarios de recolección de información se delinearon para cada variable empleando la escala Likert, se realizó por medio de la técnica de la encuesta virtual a través del Google forms. Los resultados obtenidos demostraron un valor de Wald de 9,541 alejado del 0 lo que señala que existe efecto entre las variables con un p valor = 0.002 mínimo a 0.05 el resultado se objeta a la suposición nula y se admite la suposición alterna. Se concluye que la aplicación de las rúbricas de evaluación impacta significativamente en la complacencia de los universitarios como agentes del servicio.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.363
Teacher spread0.346 · 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