O uso de estimativas de conhecimento do aluno em programação de computadores em modelos de detecção da emoção confusão livres de sensores

  • Tiago R. Kautzmann Universidade do Vale do Rio dos Sinos
  • Gabriel de O. Ramos Universidade do Vale do Rio dos Sinos
  • Patrícia A. Jaques Universidade Federal do Paraná http://orcid.org/0000-0002-2933-1052

Resumo


Detectar a confusão do aluno permite ao ambiente computacional de aprendizagem realizar ações que ajudem o aluno a regular sua confusão e a se beneficiar dela. O artigo apresenta evidências sobre os efeitos de usar dados sobre estimativas de conhecimento do aluno, além de dados sobre a interação dele com o ambiente, no desempenho de modelos de detecção da confusão do aluno livres de sensores em tarefas de programação de computadores. Modelos de aprendizado de máquina foram treinados com amostras compostas por dados coletados de 62 alunos, durante cinco meses, em turmas de programação. Os resultados apresentaram evidências positivas que suportam a abordagem do estudo. O artigo também descreve cenários onde a abordagem é mais vantajosa.
Palavras-chave: Programação de computadores, Confusão, Detecção de emoção, Modelo livres de sensores

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Publicado
16/11/2022
KAUTZMANN, Tiago R.; RAMOS, Gabriel de O.; JAQUES, Patrícia A.. O uso de estimativas de conhecimento do aluno em programação de computadores em modelos de detecção da emoção confusão livres de sensores. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 1196-1208. DOI: https://doi.org/10.5753/sbie.2022.225768.