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AVALIANDO O CONHECIMENTO DE PROPRIEDADES DA MEDIANA E MÉDIA DE ALUNOS DO SEGUNDO ANO DO ENSINO MÉDIO NO BRASIL

2022· article· pt· W4308705922 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

VenueEducação Matemática em Revista - RS · 2022
Typearticle
Languagept
FieldSocial Sciences
TopicScience and Education Research
Canadian institutionsNoNO (Canada)
Fundersnot available
KeywordsHumanitiesMedicinePhilosophyPsychology

Abstract

fetched live from OpenAlex

No presente artigo estuda-se o conhecimento de alunos brasileiros do Ensino Médio sobre propriedades da mediana e da média que derivam de transformações dos dados ou de afirmações enunciadas. Implementou-se um estudo quantitativo, de tipo descritivo, em que participaram 116 alunos do 2º ano do Ensino Médio de uma escola pública do município de São Paulo. Perguntou-se sobre a alteração da mediana e da média ao adicionar-se um valor constante a todos os dados, sobre se a mediana diminui/aumenta/mantém-se ao acrescentar um ou dois dados em certas condições e se certas afirmações eram verdadeiras ou falsas. Em termos de resultados, em geral, os alunos revelaram muitas dificuldades nos itens abertos, enquanto nos itens fechados os alunos tiveram um melhor desempenho. Conclui-se que os alunos têm um conhecimento conceitual da mediana e da média limitado, devendo ser-lhe dada mais atenção no ensino.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0430.004

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 head0.064
GPT teacher head0.382
Teacher spread0.318 · 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