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Record W3093087170 · doi:10.18616/rsp.v4i3.6203

OS DESAFIOS DOS GESTORES AO ORIENTAR OS PROFESSORES NOS PROCESSOS AVALIATIVOS DA EDUCAÇÃO INFANTIL

2020· article· pt· W3093087170 on OpenAlexaff
Franciele Waschinevski Marcello, Zélia Medeiros Silveira

Bibliographic record

VenueRevista Saberes Pedagógicos · 2020
Typearticle
Languagept
FieldSocial Sciences
TopicAcademic Research in Diverse Fields
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

O presente artigo é o resultado de uma pesquisa que buscou analisar os desafios dos gestores ao orientar sobre o processo avaliativo em instituições pública e privada da Educação Infantil. Como procedimento metodológico, a investigação utilizou-se da pesquisa de campo de caráter qualitativo e descritivo, em que foram entrevistadas duas gestoras de redes pública e privada, localizadas no município de Criciúma – SC. Os resultados da pesquisa revelaram que os principais desafios das gestoras na orientação ao processo avaliativo na Educação Infantil referem-se à orientação constante dos procedimentos avaliativos para as professoras novas, devido à rotatividade, como também às dificuldades na orientação da escrita do registro avaliativo. Dentre esses, um dos maiores desafios consiste no modo de registrar as fragilidades da criança no parecer descritivo. Neste sentido, entende-se que o gestor, ao assumir a responsabilidade de sua função, deve adotar postura ética, essencial ao funcionamento da instituição, principalmente nas orientações pedagógica às professoras, pois a atuação docente revela a qualidade da educação da instituição e materializa o seu Projeto Político Pedagógico.Palavras-chave: Avaliação. Gestão. Educação Infantil.

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 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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient 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 score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0040.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.003

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 head0.159
GPT teacher head0.408
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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