Utilização de Recursos Linguísticos para Classificação Automática de Mensagens de Feedback

  • Anderson Pinheiro Cavalcanti Universidade Federal de Pernambuco / SiDi http://orcid.org/0000-0002-5228-1583
  • Rafael Ferreira Mello Universidade Federal Rural de Pernambuco / Cesar School http://orcid.org/0000-0003-3548-9670
  • Péricles Miranda Universidade Federal Rural de Pernambuco
  • André Nascimento Universidade Federal Rural de Pernambuco
  • Fred Freitas Universidade Federal de Pernambuco

Resumo


O feedback possui um papel significativo no processo de aprendizagem de um aluno. Permite que os alunos identifiquem os pontos fracos e melhorem a autorregulação. No entanto, estudos mostram que esta é uma área de grande insatisfação no ensino superior. Com o número cada vez maior de participantes em cursos, fornecer feedback eficaz está se tornando uma tarefa cada vez mais desafiadora. Portanto, este artigo explora o uso da análise de conteúdo automatizada para examinar o feedback fornecido por instrutores com base em modelos conceituados da literatura que fornecem boas práticas e classificam os feedbacks em níveis diferentes. Para isso, foram treinados classificadores binários usando o algoritmo XGBoost em conjunto com recursos linguísticos que extraem características das mensagens de feedback. Os resultados indicam desempenho de classificação eficaz tanto para as boas práticas quanto para os níveis de feedback atingindo valores de até 0,89 de acurácia no conjunto de teste.

Palavras-chave: Feedback, Recursos Linguísticos, Classificação de Texto

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Publicado
22/11/2021
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CAVALCANTI, Anderson Pinheiro; MELLO, Rafael Ferreira; MIRANDA, Péricles; NASCIMENTO, André; FREITAS, Fred. Utilização de Recursos Linguísticos para Classificação Automática de Mensagens de Feedback. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO, 32. , 2021, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 861-872. DOI: https://doi.org/10.5753/sbie.2021.218481.