Por que os estudantes usam a Inteligência Artificial Generativa na edição de ensaios: uma perspectiva baseada em métodos configuracionais e na Escala Ética Multidimensional
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Palavras-chave

Inteligência Artificial Generativa (IAG)
Escrita de Ensaios
Escala Multidimensional de Ética (MES)
Análise Configuracional
Análise Qualitativa Comparativa De Conjuntos Fuzzy (FSQCA)

Como Citar

Andrés-Sánchez, J. de, Pérez-Portabella, A., Arias-Oliva, M., & Padilla-Castillo, G. (2026). Por que os estudantes usam a Inteligência Artificial Generativa na edição de ensaios: uma perspectiva baseada em métodos configuracionais e na Escala Ética Multidimensional . Review of Artificial Intelligence in Education, 7(i), e01122. https://doi.org/10.37497/rev.artif.intell.educ.v7ii.1122

Resumo

Contexto: A rápida emergência da inteligência artificial generativa (IAG) está a ter um impacto substancial em numerosas áreas do ensino superior, incluindo a escrita académica. A sua utilização como assistente linguístico ocupa uma posição eticamente ambígua entre o apoio académico legítimo e práticas que podem fomentar a dependência tecnológica ou comprometer a integridade académica.

Objetivo: Examinar a utilização da IAG por estudantes universitários num cenário académico específico: a sua utilização como assistente linguístico para melhorar a qualidade da escrita e a clareza de ensaios previamente elaborados pelo estudante, sem alterar substancialmente o seu conteúdo. O objetivo é analisar de que modo diferentes juízos éticos moldam a adoção desta prática pelos estudantes, que ocupa uma posição intermédia entre o apoio académico legítimo e os potenciais riscos de dependência tecnológica ou fraude académica.

Métodos: O estudo baseia-se na Escala Multidimensional de Ética, considerando quatro dimensões morais: justiça, relativismo, consequencialismo e deontologia. Incorpora também variáveis sociodemográficas e académicas, incluindo género, situação laboral e desempenho académico percebido. Metodologicamente, aplica-se a análise qualitativa comparativa de conjuntos fuzzy (fsQCA) para identificar configurações causais associadas tanto à utilização como à não utilização da IAG.

Resultados: A aceitação não depende de uma única dimensão ética, mas de combinações específicas de juízos morais. O consequencialismo emerge como a condição mais relevante nas trajetórias que conduzem à utilização e surge frequentemente combinado com perceções favoráveis de justiça e relativismo. Em contraste, a rejeição apresenta uma estrutura mais fragmentada e uma menor cobertura explicativa, particularmente quando avaliações éticas desfavoráveis, especialmente avaliações consequencialistas, se combinam com fatores sociodemográficos.

Conclusão: A aceitação e a rejeição, por parte dos estudantes, da edição de ensaios apoiada pela IAG seguem lógicas configuracionais assimétricas, mostrando como diferentes juízos éticos se combinam para explicar a utilização de tecnologia académica num contexto moralmente ambíguo. Os resultados destacam a necessidade de regras institucionais claras, formação ética e critérios transparentes para a utilização académica da IAG. As universidades devem distinguir entre apoio linguístico aceitável e práticas que possam comprometer a integridade académica, ajudando simultaneamente os estudantes a desenvolver utilizações responsáveis e reflexivas da IAG.

https://doi.org/10.37497/rev.artif.intell.educ.v7ii.1122
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