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Record W3092124859

La modelación e interpretación del enfriamiento en libros de texto de matemática para secundaria y universidad: unas consideraciones críticas

2019· article· es· W3092124859 on OpenAlexaboutno aff
Honorina Ruiz Estrada, Wendy Loraine De León Zamora, Josip Sliško, Juan Nieto Frausto

Bibliographic record

VenueLatin American journal of physics education · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicEducational Outcomes and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)HumanitiesPhilosophyGeography
DOInot available

Abstract

fetched live from OpenAlex

espanolEn este trabajo se analiza el uso de los cambios de temperatura (enfriamiento) en problemas matematicos de libros de texto del nivel secundario (Mexico) y universitario (Estados Unidos de America y Canada). Se presenta una evidencia experimental que pone en entredicho las supuestas situaciones reales que se exponen en aquellos documentos, evidenciando que el uso inapropiado del fenomeno de enfriamiento no es un sindrome mexicano sino que podria ser una “cultura global” que requiere mas atencion de la comunidad internacional dedicada a la educacion matematica. Se incluye una discusion de las implicaciones negativas que pueden llegar a tener el uso inapropiado de este contexto en la ensenanza y el aprendizaje de la matematica EnglishThis paper analyzes the use of temperature changes (cooling) in mathematical problems of textbooks of the secondary level (Mexico) and university level (United States of America and Canada). An experimental evidence is presented that calls into question the supposed real situations that are exposed in those documents, showing that the inappropriate use of the cooling phenomenon is not a Mexican syndrome but it could be a “global culture” that requires more attention from the international community dedicated to education mathematics. A discussion of the negative implications that may have the inappropriate use of this context in the teaching and learning of mathematics is included

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.358
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
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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