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Utilização do Instagram no ensino de Paleontologia

2022· article· pt· W4286603390 on OpenAlexaff
Denilson Almeida Da Silva, Luciano Artemio Leal

Bibliographic record

VenueRevista Insignare Scientia - RIS · 2022
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsCamosun College
Fundersnot available
KeywordsHumanitiesPhilosophyPhysics

Abstract

fetched live from OpenAlex

O avanço acelerado das tecnologias tem provocado mudanças na sociedade e na educação. A internet está se tornando uma das ferramentas mais utilizadas dentro do ambiente acadêmico. Com o surgimento das Tecnologias de Informação e Comunicação (TICs), novos ambientes de aprendizagem foram desenvolvidos. O uso das redes sociais tem crescido bastante entre os estudantes e essa ferramenta tem um grande potencial para contribuir no processo educacional. Nesse cenário encontra-se o professor, que enfrenta o desafio de conseguir a atenção dos alunos e realizar sua prática pedagógica com qualidade. Diante disso, o objetivo deste trabalho é analisar as contribuições de uma proposta pedagógica baseada no uso do Instagram como uma ferramenta para o ensino da disciplina Paleontologia por meio de publicações com imagens, vídeos e textos com o objetivo de chamar a atenção dos alunos durante o período letivo e avaliar suas contribuições no aprendizado dos mesmos. Concluiu-se que o uso do Instagram direcionado aos conteúdos da disciplina teve bons resultados em relação ao aprendizado dos alunos e contribuiu de forma significativa para a construção de conhecimento durante o semestre letivo.

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)0.002
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.004
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.060
GPT teacher head0.341
Teacher spread0.281 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueRevista Insignare Scientia - RISSame topicEducation and Digital TechnologiesFrench-language works237,207