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Record W4391450023 · doi:10.5007/2175-795x.2024.e93184

Desenvolvimento profissional e estágios supervisionados na formação inicial docente: pontos de vista de futuros professores do ensino secundário

2024· article· pt· W4391450023 on OpenAlexaffabout
Anderson Araújo‐Oliveira, Karine Vanessa Perez, Carla Barroso da Costa, Salem Amamou

Bibliographic record

VenuePerspectiva · 2024
Typearticle
Languagept
FieldComputer Science
TopicDigital literacy in education
Canadian institutionsUniversité de SherbrookeUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsProfessional developmentPedagogyPsychologyMathematics education

Abstract

fetched live from OpenAlex

O artigo tem por objetivo apresentar os pontos de vista de futuros professores relativos às contribuições dos estágios supervisionados (formação prática) no desenvolvimento profissional docente. A partir da articulação teórica entre o conceito de desenvolvimento profissional e as competências profissionais prescritas para a formação de professores no Quebec (Canadá), organizou-se um grupo focal com a participação de futuros professores oriundos de um programa de formação inicial docente para ensino secundário. Por intermédio de uma análise de conteúdo, destacou-se como resultados que a formação prática desempenha um papel essencial, pois promove vivências do real do trabalho docente, permite o aprimoramento das competências pretendidas e possibilita a construção da identidade docente. Neste sentido, o aprofundamento das reflexões em torno do desenvolvimento profissional que requer um acompanhamento adequado dos professores, não somente durante a formação inicial, mas também em contexto de inserção profissional e ao longo da carreira, constitui uma pista importante a ser explorada.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.564

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.004
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.017
GPT teacher head0.327
Teacher spread0.310 · 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 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
Published2024
Admission routes2
Has abstractyes

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