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EVALUACIÓN ALTERNATIVA Y HERRAMIENTAS DE EVALUACIÓN EN LA ENSEÑANZA DEL CONCEPTO “RESPIRACIÓN”

2017· article· es· W2776171608 on OpenAlexaff
Juan Nicolás Velásquez, Karina Gisell Rey Pulido, David Fernando Villanueva Solano

Bibliographic record

VenueBio-grafía · 2017
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

El presente artículo muestra las implicaciones del uso de diferentes herramientas evaluativas durante el proceso de enseñanza-aprendizaje del concepto respiración en seres vivos. Para esto se diseñaron dos instrumentos de evaluación; uno de ellos el cual denominamos cuestionario estructurado, el cual ofrecía a los estudiantes una serie de preguntas cerradas, las cuales podían resolverse mediante el uso de bancos de respuestas obtenidos de medios externos (internet, literatura relacionada o indagación a terceros). El segundo instrumento es la elaboración de mapas conceptuales pues al ser una herramienta no limitante, permite una interacción más flexible entre conceptos lo cual refleja una clara observación de los posibles problemas en el proceso enseñanza-aprendizaje. Como principal resultado se evidencia que la herramienta evaluativa que más aporta en este tipo de evaluación son los mapas conceptuales.

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)0.036
metaresearch head score (Gemma)0.077
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.077
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.007
Scholarly communication0.0080.008
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.043
GPT teacher head0.392
Teacher spread0.349 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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