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Record W3199915179 · doi:10.35699/2238-037x.2021.25380

ATIVIDADES DIDÁTICAS IMPEDIDAS E DILEMAS DE ENSINO NAS AULAS DE EDUCAÇÃO FÍSICA

2021· article· pt· W3199915179 on OpenAlexaff
Marcos Roberto Godoi, Cécilia Borges, Yannick Lémonie

Bibliographic record

VenueTrabalho & Educação · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicPhysical Education and Sports Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyPsychology

Abstract

fetched live from OpenAlex

Partindo do pressuposto de que a atividade realizada pelos professores emerge de conflitos psíquicos subjacentes, esta pesquisa analisa as atividades didáticas impedidas ou suspendidas, bem como os dilemas de ensino na educação física. A pesquisa mobiliza um estudo multi-casos com quatro professores, no qual o método da autoconfrontação simples foi utilizado, baseando-se no referencial da Clínica da Atividade. As atividades suspendidas ou impedidas estão vinculadas à riscos conjunturais externos relativamente independentes do ensino como a fenômenos relacionados à interação entre o professor e os alunos. Assim, as atividades impedidas ou suspendidas são causadas por restrições de tempo ou de materiais, fatores climáticos, quantidade de alunos, mas também por eventos analisados pelos professores como falhas nos procedimentos didáticos empregados. Dois dilemas de ensino foram particularmente evidenciados: 1) oferecer tarefas atrativas ou tarefas efetivas para o aprendizado; e 2) dividir equipes de futebol mistas ou separadas por gênero. Além disso, os resultados mostram que a abordagem metodológica utilizada nesta pesquisa favorece a compreensão das atividades didáticas impedidas e dos dilemas do ensino pelos professores contribui com o desenvolvimento profissional e permite expandir o poder de agir dos 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)0.005
metaresearch head score (Gemma)0.020
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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.049
GPT teacher head0.381
Teacher spread0.332 · 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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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