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Record W4404737832 · doi:10.22456/1982-8918.127202

Formação de treinadores(as) no contexto universitário

2023· article· pt· W4404737832 on OpenAlexaff
Yura Yuka Sato dos Santos, Diane M. Culver, Larissa Rafaela Galatti

Bibliographic record

VenueMovimento (Porto Alegre) · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicEducational Practices and Policies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste estudo foi investigar o desenvolvimento inicial do ensino centrado no(a) aprendiz (ECA) na disciplina “Treinador Desportivo”, do curso de Ciências do Esporte da Universidade Estadual de Campinas (UNICAMP). Seguindo uma abordagem qualitativa e procedimentos da pesquisa-ação, apresentamos o planejamento, implementação e avaliação do ECA na disciplina por meio do programa e plano institucional, planos de aula e diário de bordo; a perspectiva das docentes por conversas crítico-reflexivas e registros em diário de bordo; as opiniões de estudantes-treinadores(as) por questionários e grupo focal. Utilizamos a técnica de análise temática. O ECA se mostrou complexo, especialmente pela apropriação dos princípios e desenvolvimento enquanto abordagem. Os(as) estudantes-treinadores(as) perceberam uma aproximação da disciplina à realidade prática do(a) treinador(a), contribuindo com a motivação e aprendizagem significativa. Enfatizamos a necessidade de formação de docentes acerca do ECA e aproximação com o papel de formadores(as) de treinadores(as) na formação inicial universitária.

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)0.019
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.034
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0110.007
Scholarly communication0.0190.009
Open science0.0020.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.101
GPT teacher head0.420
Teacher spread0.320 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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