Automatic Grading of Portuguese Short Answers Using a Machine Learning Approach

  • Lucas Galhardi UEL
  • Rodrigo C. Thom de Souza UFPR
  • Jacques Brancher UEL


Short answers are routinely used in learning environments for students’ assessment. Despite its importance, teachers find the task of assessing discursive answers very time-consuming. Aiming at assisting in this problem, this work explores the Automatic Short Answer Grading (ASAG) field using a machine learning approach. The literature was reviewed and 44 papers using different techniques were analyzed considering many aspects. A Portuguese dataset was build with more than 7000 short answers. Different approaches were experimented and a final model was created with their combination. The model’s effectiveness showed to be satisfactory, with kappa scores indicating moderate/substantial agreement between the model and human grading.
Palavras-chave: Machine Learning, Short answers, assessments


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GALHARDI, Lucas; DE SOUZA, Rodrigo C. Thom; BRANCHER, Jacques. Automatic Grading of Portuguese Short Answers Using a Machine Learning Approach. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 16. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 109-124. DOI: