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Record W4281907121 · doi:10.51891/rease.v8i5.5600

HISTÓRIA EM QUADRINHOS NA APRENDIZAGEM DAS SÉRIES INICIAIS

2022· article· pt· W4281907121 on OpenAlexaff
Andréa Cristina Teixeira da Silva, Carlos Henrique da Silva Santos, Fabiana Angelo, Lorraine Rossmann Gonçalves, Maria Olívia dos Reis

Bibliographic record

VenueRevista Ibero-Americana de Humanidades, Ciências e Educação · 2022
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Os processos de alfabetização e letramento oportunizam os caminhos de desenvolvimento da leitura, que se aprofunda com diversos textos no processo de ensino-aprendizagem das séries iniciais. Na aprendizagem das séries iniciais, a história em quadrinhos se potencializa como um recurso didático que facilita o desenvolvimento da leitura. O objetivo geral deste estudo é discutir as potencialidades da história em quadrinhos como recurso didático no desenvolvimento da leitura nos alunos das séries iniciais. Este estudo se qualifica como uma pesquisa bibliográfica. A relevância deste estudo consiste na importância de se buscar práticas pedagógicas e recursos didáticos que facilitem o desenvolvimento da leitura no processo de ensino-aprendizagem. A utilização da história em quadrinhos como recurso didático no processo de ensino-aprendizagem da Língua Portuguesa nas séries iniciais contempla práticas pedagógicas que aproximam a aprendizagem escolar do mundo vivenciado pelas crianças, por isso demanda-se observar a didática e a ludicidade nas estratégias de ensino.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0080.007
Scholarly communication0.0090.007
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0260.002

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 head0.057
GPT teacher head0.353
Teacher spread0.296 · 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
Published2022
Admission routes1
Has abstractyes

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