Detecção de Emoções na Aprendizagem de Programação: Os Efeitos de Usar Estimativas de Conhecimento em Modelos Livres de Sensores que Detectam a Confusão do Aluno

Authors

DOI:

https://doi.org/10.5753/rbie.2024.3437

Keywords:

Detecção de confusão, Modelos livres de sensores, Aprendizado de máquina, Estimativas de conhecimento do aluno, Aprendizagem de programação de computadores, Regulação emocional na aprendizagem, Emoções na aprendizagem

Abstract

A confusão é uma emoção provável de ocorrer em tarefas de aprendizagem de conteúdos complexos, como na aprendizagem de programação de computadores. Quando não regulada pelo aluno, a confusão pode afetar negativamente o aprendizado. Quando regulada, pode levar a aprendizagem a níveis mais profundos. O estudo descrito neste artigo buscou melhorar o desempenho de modelos livres de sensores que detectam a confusão do aluno enquanto envolvido em tarefas de aprendizagem de programação. Estes modelos são interessantes quando integrados a ferramentas de programação porque, ao detectar a confusão do aluno durante a aprendizagem, a ferramenta poderia intervir e auxiliar o aluno na regulação dessa emoção. Trabalhos relacionados treinaram modelos de detecção de confusão usando dados de interação do aluno com o ambiente de programação, como dados sobre movimentos de teclado e mouse. Nosso estudo levantou a hipótese que incorporar dados sobre estimativas de conhecimento do aluno aos dados de interação poderia melhorar o desempenho dos modelos. Nós comparamos o desempenho de modelos de aprendizado de máquina treinados com a abordagem da hipótese com modelos treinados com a abordagem dos trabalhos relacionados. Os modelos foram treinados com dados coletados de 62 alunos em aulas de programação ao longo de cinco meses. Os resultados apresentaram evidências positivas que apoiam nossa hipótese. Também discutimos cenários onde nossa abordagem é vantajosa, como o tamanho adequado dos segmentos de dados, os algoritmos com melhor desempenho e o poder de generalização dos modelos para alunos de diferentes níveis de ensino.

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2024-10-31

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KAUTZMANN, T. R.; RAMOS, G. de O.; JAQUES, P. A. Detecção de Emoções na Aprendizagem de Programação: Os Efeitos de Usar Estimativas de Conhecimento em Modelos Livres de Sensores que Detectam a Confusão do Aluno. Revista Brasileira de Informática na Educação, [S. l.], v. 32, p. 642–678, 2024. DOI: 10.5753/rbie.2024.3437. Disponível em: https://journals-sol.sbc.org.br/index.php/rbie/article/view/3437. Acesso em: 21 dez. 2024.

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