Palavras-chave
IA na educação
Redes bayesianas
Modelo de estudante
Como Citar
Resumo
Práticas pedagógicas apoiadas por recursos computacionais, especialmente aquelas que incorporam técnicas de Inteligência Artificial, podem auxiliar na predição do nível de conhecimento de estudantes em ambientes virtuais de aprendizagem. Nesse contexto, este artigo apresenta uma abordagem híbrida, baseada em Redes Bayesianas e ontologias, para tratar informações sobre o nível de conhecimento e comportamento dos estudantes e, assim, medir seu desempenho. Foi criado um modelo de estudante dinâmico, probabilístico, independente de domínio, extensível e reutilizável. Também foi apresentada uma extensão do modelo para permitir a visualização das capacidades e limitações dos estudantes. Como estudo de caso, o modelo proposto foi integrado a uma plataforma educacional, servindo de base para validação e experimentação da abordagem.
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