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A Tecnologia na Formação Inicial do Professor: um olhar para as práticas formativas

2023· article· pt· W4389729896 on OpenAlexaff
João Batista de Menezes Bittencourt, Márcia Maria Previato de Souza, Gisele Rodrigues, Cristiane Gonçalves de Aguiar Bonnici, Kelen Amaral

Bibliographic record

VenueApresentações Trabalhos Científicos · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Com a vasta inserção da tecnologia na sociedade conectada, principalmente, no âmbito educacional, o ensino a distância ganha força e expressividade. Assim, pretendemos realizar uma pesquisa bibliográfica entre formação inicial do professor e a tecnologia. Tal intento terá o objetivo de analisar o processo de formação inicial do professor para o uso da tecnologia, a fim de verificar se a formação docente está sendo promovida para atender às demandas da sociedade na atualidade. Por meio de atividades denominada MAPA (Material de Avaliação Prática de Aprendizagem), os docentes universitários do curso de Pedagogia da UniCesumar, utilizam estratégias inovadoras, tecnológicas e imersivas, que leva o aluno a experimentar e vivenciar a sua prática formativa.

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)0.022
metaresearch head score (Gemma)0.046
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0120.022
Scholarly communication0.0280.026
Open science0.0030.011
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0180.005

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 head0.115
GPT teacher head0.404
Teacher spread0.289 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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