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Record W2781567868

Leitura para estudantes surdos: um recurso para o aprendizado da Língua Portuguesa

2017· article· pt· W2781567868 on OpenAlexvenueno aff
Daniela Alves Ferreira, Ana Paula Pacheco Moraes Maturana

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2017
Typearticle
Languagept
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesLingua francaArtPsychologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

A leitura para estudantes surdos e um recurso primordial para o aprendizado da Lingua Portuguesa na modalidade escrita. O objetivo desta pesquisa foi analisar como os professores desenvolvem a rotina de leitura atraves da Libras para os alunos surdos nos primeiros anos iniciais do Ensino Fundamental I. As participantes foram 14 professoras de tres Escolas Municipais de Educacao Bilingue para Surdos (EMEBS), de diretorias da regiao de Sao Paulo, capital.  A coleta de dados foi realizada por meio de um questionario com 9 (nove) questoes abertas e fechadas. A analise de dados resultou em categorias relacionadas as praticas de leitura e apresentacao de diferentes generos textuais aos estudantes surdos: (1) Apreciacao da leitura por parte dos estudantes com DA/Surdez, (2) Adaptacoes realizadas nas atividades para os alunos com DA/Surdez, (3) Exemplos de atividades na rotina de leitura e (4) A leitura como um recurso eficaz para o aprendizado da Lingua Portuguesa. As professoras envolvidas nesse estudo entendem a importância da leitura para o aprendizado da Lingua Portuguesa, como segunda lingua, bem como para a insercao do estudante surdo no mundo letrado, na perspectiva de uma educacao bilingue.

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)0.007
metaresearch head score (Gemma)0.001
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0060.005
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.238
GPT teacher head0.470
Teacher spread0.232 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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