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Record W4403884851

La concepción de la naturaleza de la ciencia (CNC) de un grupo de docentes inmersos en un programa de formación profesional

2004· article· es· W4403884851 on OpenAlexaff
César Barona Ríos, Janet Paul de Verjovsky, Marcela Moreno Ruiz, Claude Lessard

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2004
Typearticle
Languagees
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMathematics educationImmersion (mathematics)Group (periodic table)Science educationTraining (meteorology)PsychologyMathematicsChemistryPhysicsPure mathematicsOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Este trabajo muestra cómo un grupo de docentes del área de ciencias inmersos en un programa de formación –la Maestría en Enseñanza de las Ciencias (MEC) de una universidad estatal mexicana– modificaron sus perfiles iniciales acerca de la concepción de la naturaleza de la ciencia (CNC). La información empírica, recogida en diferentes momentos de los dos años de duración de la MEC, proviene de un grupo único de 11 docentes, quienes enseñan materias científicas, principalmente, en escuelas de educación media superior. Los resultados en este primer recorte de investigación, muestran que la MEC mejora los perfiles iniciales incoherentes de la CNC del grupo de docentes, al adoptar un patrón de grupo que tiende hacia el relativismo. Se discuten las dificultades de reducir la CNC a un modelo técnico de la organización del contenido. Se aborda también una línea de interpretación que se refiere a la alfabetización científica de los docentes.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.004
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.164
GPT teacher head0.616
Teacher spread0.451 · 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.

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
Published2004
Admission routes1
Has abstractyes

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