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Record W4398165642 · doi:10.55905/cuadv16n5-072

O impacto da produção de material autoral digital educacional na aprendizagem de estudantes do ensino médio sobre fisiologia humana

2024· article· pt· W4398165642 on OpenAlexaff
Ivna Bezerra Da Silva, Luciana de Lima, Robson Carlos Loureiro

Bibliographic record

VenueCuadernos de Educación y Desarrollo · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicScience and Education Research
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

A abordagem fragmentada dos Sistemas sobre Fisiologia Humana no Ensino Médio (EM) culmina em problemas de aprendizagem em Biologia. O objetivo é comparar o processo de aprendizagem de estudantes do 3º ano (EM) produtores de Materiais Autorais Digitais Educacionais (MADEs) em relação aos que assistiram aos MADEs em formato de vídeo sobre Fisiologia Humana. A pesquisa é qualitativa e quantitativa. A coleta de dados ocorre com a aplicação do Questionário Inicial, da Sequência Didática e do Questionário Final junto a 11 estudantes. A análise de dados é interpretativa com uso de triangulação metodológica e Estatística Básica. Os participantes que produziram os vídeos apresentaram desempenho superior em seu processo de aprendizagem quando comparados aos participantes que apenas assistiram-nos.

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)0.010
metaresearch head score (Gemma)0.032
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.061
GPT teacher head0.379
Teacher spread0.318 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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