Uso da inteligência artificial generativa na avaliação da aprendizagem universitária: uma revisão sistemática da literatura (2024-2025)
DOI:
https://doi.org/10.22458/ie.v28i45.6535Palavras-chave:
competência digital, ensino superior, ética, avaliação, inteligência artificialResumo
Este estudo apresenta uma revisão sistemática da literatura internacional sobre o uso da inteligência artificial (IA) na avaliação da aprendizagem universitária, realizada segundo o marco metodológico PRISMA 2020. O objetivo é analisar como a IA, especialmente a inteligência artificial generativa (IAG), vem transformando os processos avaliativos no ensino superior, além de identificar os principais dilemas éticos, desafios pedagógicos e estratégias institucionais emergentes na literatura publicada entre 2024 e 2025. Para isso, realizou-se uma busca em bases de dados indexadas (Scopus, Web of Science, EBSCOhost e ERIC), com aplicação de critérios rigorosos de inclusão e exclusão e codificação temática dos estudos selecionados. Os resultados foram organizados em seis eixos: transformação da avaliação da aprendizagem por meio da inteligência artificial; implicações éticas; dilemas emergentes associados ao uso da IA; letramento em inteligência artificial; desenvolvimento de competências digitais; e governança institucional e políticas para a implementação responsável da IA. Os achados indicam uma tendência crescente à promoção de uma avaliação ética, formativa e humanista, baseada no equilíbrio entre inovação tecnológica e integridade acadêmica. Também evidenciam que o letramento em IA é essencial para o uso responsável dessas ferramentas e que as universidades devem criar marcos de governança e programas de formação docente. Assim, o desafio não está em proibir a IA, mas em integrá-la de forma ética, crítica e pedagogicamente coerente com os princípios de justiça, equidade e transparência educacional.
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