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Record W2542893391

Formação Continuada para Docentes: uma Proposta de Especialização Em Educação Tecnológica

2016· article· pt· W2542893391 on OpenAlexvenueno aff
Maria Esther Provenzano, Simone Regina de Oliveira Ribeiro

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsContinuing educationHumanitiesSociologyPhilosophyMedicineMedical education
DOInot available

Abstract

fetched live from OpenAlex

Esta comunicacao trata das possibilidades da formacao continuada para docentes da Educacao Basica. Tem como referencia o Curso de Especializacao Lato Sensu em Educacao Tecnologica, desenvolvido de forma semipresencial pelo Centro Federal de Educacao Tecnologica Celso Suckow da Fonseca do Rio de Janeiro/CEFET/RJ em parceria com a Fundacao Centro de Ciencias e Educacao Superior a Distância do Estado do Rio de Janeiro/CEDERJ, no âmbito da Universidade Aberta do Brasil (UAB/MEC/CAPES). Foram investigados possibilidades e desafios da formacao de professores-cursistas, no ambiente de aprendizagem Moodle, utilizando-se como referenciais teoricos autores que formulam concepcoes no campo da comunicacao, dialogicidade e interatividade em uma perspectiva critica. Devido a suas especificidades, optamos pela metodologia descritiva, na perspectiva qualitativa. Trata-se de um estudo bibliografico. Os resultados da pesquisa apontam para a necessidade de formacao continua dos professores, bem como para a importância da Educacao a Distância, sobretudo, como forma de interiorizar o acesso aos docentes que atuam fora do centro do Estado do Rio de Janeiro. Concluimos que a formacao do professor por meio das Tecnologias da Informacao e Comunicacao (TICs) vem sendo uma possibilidade de melhoria do ensino e de acesso a niveis mais elevados da carreira.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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 score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.007
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.143
GPT teacher head0.429
Teacher spread0.286 · 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
Published2016
Admission routes1
Has abstractyes

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