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Record W4391597694 · doi:10.36238/2359-5787.2024.023

O DESENVOLVIMENTO DA ALFABETIZAÇÃO DIGITAL NAS ESCOLAS

2024· article· pt· W4391597694 on OpenAlexaff
José Carlos Guimarães, Leticia Ferreira Conti, Joana Josiane Andriotte Oliveira Lima Nyland, Carlos Alberto Feitosa dos Santos, Diego de Figueiredo Santos, Domingas Regiane Oliveira Ribeiro, Tânia Lúcia Viana de Souza

Bibliographic record

VenueRevista Acadêmica Online · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsSaint Paul University
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

A alfabetização digital tornou-se imperativa na educação contemporânea, visando capacitar os alunos para a era digital. Este resumo aborda a importância crescente da alfabetização digital, os desafios de sua implementação e estratégias eficazes. Fundamentada em habilidades técnicas, pensamento crítico e ética digital, a alfabetização digital enfrenta obstáculos como a falta de recursos e resistência à mudança. Estratégias abrangentes, como formação contínua para educadores e integração curricular, são essenciais para superar esses desafios. A incorporação de tecnologias emergentes, como realidade aumentada e aprendizagem adaptativa, enriquece a experiência de aprendizagem. Estudos de caso exemplares destacam melhorias mensuráveis no desempenho acadêmico e preparação eficaz dos alunos. Contudo, a alfabetização digital também exige abordagens éticas, promovendo responsabilidade digital e cidadania ética. Em síntese, a alfabetização digital não apenas fortalece o desenvolvimento acadêmico, mas também prepara os alunos para enfrentar os desafios e oportunidades do futuro digital com confiança e responsabilidade

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.007
Scholarly communication0.0130.009
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.004

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 head0.076
GPT teacher head0.391
Teacher spread0.314 · 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 designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

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