Nivelación inteligente: estrategia de aprendizaje adaptativo con IA en educación superior
DOI:
https://doi.org/10.5944/ried.45482Palavras-chave:
Nivelamento, Inteligência Artificial, Aprendizagem Adaptativa, Educação SuperiorResumo
Este estudo avalia a implementação de uma Estratégia de Aprendizagem Adaptativa voltada para a nivelamento de conhecimentos prévios em estudantes do primeiro ano de diversos programas universitários. A estratégia se diferencia das abordagens remediais tradicionais ao oferecer uma experiência de aprendizagem flexível e centrada no estudante, por meio da incorporação de breves módulos adaptativos integrados aos cursos regulares. Esses módulos utilizam uma plataforma com inteligência artificial para gerar trajetórias personalizadas de aprendizagem, adaptar conteúdos, produzir análises e apoiar a tomada de decisões docentes. A Estratégia de Aprendizagem Adaptativa foi desenvolvida com uma abordagem sistêmica que inclui o design de conteúdos, um modelo didático específico e a redefinição do papel do docente. Para a pesquisa, foi empregado um enfoque metodológico misto, do tipo Quant > qual, com grupos controle e experimental. Os cursos envolvidos na intervenção foram: Pensamento Computacional e Modelagem Matemática Fundamental da Escola de Engenharia e Ciências, Raciocínio Matemático da Escola de Negócios e Pensamento Matemático da Escola de Ciências Sociais e Governo de uma universidade privada no México. Os resultados evidenciam que uma estratégia de aprendizagem adaptativa concebida de forma integral, mediada por uma plataforma tecnológica e impulsionada por inteligência artificial, melhora significativamente o desempenho acadêmico, o nivelamento de conhecimentos e a percepção positiva de estudantes e docentes.
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Direitos de Autor (c) 2026 Patricia Aldape-Valdés, Elvira G Rincón-Flores, Leticia Castaño, Sadie Guerrero
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