Educational Technologies for Multilingual Learners: A Systematic Review of AI-Based Human-Centered Design

Taraneh Yarahmadi; Zane Whitcomb

doi:10.37497/rev.artif.intell.educ.v7ii.1120

Autores

Taraneh Yarahmadi Politecnico di milano https://orcid.org/0009-0006-0112-5982
Zane Whitcomb California State University https://orcid.org/0009-0003-0457-2276

DOI:

https://doi.org/10.37497/rev.artif.intell.educ.v7ii.1120

Palavras-chave:

Design Centrado no Humano, Inteligência Artificial na Educação, Aprendizes Multilíngues, Viés Algorítmico, ISO 9241-210

Resumo

Contexto: Embora a inteligência artificial seja promovida como uma força transformadora na educação por meio de plataformas adaptativas e feedback em tempo real, sua implementação para aprendizes multilíngues frequentemente corre o risco de reforçar desigualdades educacionais. A literatura atual alerta que sistemas automatizados ainda apresentam dificuldades com nuances culturais e expressões idiomáticas, evidenciando a necessidade de abordagens de design que priorizem a equidade e a agência humana.

Objetivo: Esta revisão sistemática examina 10 estudos centrais por meio da lente do framework de Design Centrado no Humano ISO 9241-210. O objetivo é analisar como tecnologias educacionais baseadas em IA são projetadas e avaliadas para apoiar aprendizes multilíngues, com foco específico nas fases de "Contexto de Uso", "Requisitos do Usuário", "Soluções de Design" e "Avaliação".

Métodos: Por meio de busca sistemática em quatro bases de dados e subsequente técnica de snowballing, 10 artigos centrais foram selecionados para analisar como ferramentas de IA abordam a diversidade linguística e cultural.

Resultados: Nos estudos revisados, as melhorias relatadas variaram desde ganhos quantitativos, incluindo aumento de 25–31% na retenção de literacia e vocabulário e elevação das taxas de sucesso acadêmico para até 77,8%. Além disso, sistemas orientados por IA, quando alinhados aos princípios de DUH, foram associados a uma economia de até 41% do tempo dos educadores. No entanto, as avaliações revelaram "paradoxos sociotécnicos" críticos: os estudantes enfrentaram um dilema no qual revertiam para prompts em inglês devido ao viés algorítmico em línguas de baixos recursos, e riscos de "preguiça metacognitiva" emergiram da dependência excessiva de ferramentas automatizadas.

Conclusão: A integração bem-sucedida da IA em contextos multilíngues depende de uma mudança da geração de conteúdo para o scaffolding pedagógico. Designers devem priorizar modelos "Human-in-the-Loop" que equilibrem a eficiência computacional com a supervisão humana, de modo a proporcionar o engajamento emocional e a autenticidade cultural que a IA atualmente não é capaz de oferecer.

Biografia do Autor

Taraneh Yarahmadi, Politecnico di milano

Taraneh Yarahmadi is a Master of Science candidate in Digital and Interaction Design at Politecnico di Milano, Italy. Her work explores the intersection of Human-Computer Interaction (HCI) and Artificial Intelligence, with a focus on how Interaction Design can improve the usability and equity of automated systems. Drawing on her professional experience as a UX and Product Designer, she investigates how human-centered frameworks (such as ISO 9241-210) can be used to identify and solve user-experience gaps in complex, data-driven environments.

Zane Whitcomb , California State University

Zane Whitcomb is an independent researcher and writer focusing on intersectional sociology and social psychology. Based in California, his work examines the dynamics of institutional structures and individual agency. He is currently completing his undergraduate studies in Sociology.

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