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Record W4403769051 · doi:10.1590/1518-8345.7256.4348

Explorando o metaverso na educação de estudantes da saúde: revisão de escopo

2024· article· pt· W4403769051 on OpenAlexaff
Andréa Bernardes, Lucas Gardim, Agostinho Antônio Cruz Araújo, Rodrigo Jensen, Raquel Acciarito Motta, Denise Maria de Almeida, Roberta Rubia de Lima, Heloísa Helena Ciqueto Peres

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Objetivo: mapear a literatura a respeito da incorporação do metaverso na educação de estudantes de graduação na área da saúde. Método: revisão de escopo de acordo com as recomendações do JBI e Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), conduzida na Web of Science , Medical Literature Analysis and Retrieval System Online (MEDLINE) via PubMed, Embase, Scopus, Cumulative Index to Nursing and Allied Health (CINAHL), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS) e ProQuest. Resultados: foram incluídos 23 registros publicados de 2020 a 2023 e desenvolvidos em 10 países. O metaverso destaca-se por permitir a simulação de casos hipotéticos, tornando a educação interativa e atrativa. Apesar disso, enfrenta limitações, incluindo possibilidade de despersonalização dos estudantes, preocupações com segurança de dados e privacidade, além do custo elevado de implementação e manutenção de sua infraestrutura. Conclusão: o metaverso viabiliza o desenvolvimento de competências clínicas que subsidiam a construção da identidade profissional do estudante. Todavia, pode não ser equitativo, na medida em que demanda recursos e educadores com domínio para implementá-lo, contribuindo para acentuar a desigualdade na educação de estudantes.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.153
GPT teacher head0.452
Teacher spread0.299 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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