Automatic Essay Scoring in a Brazilian Scenario
Felipe Akio Matsuoka
This paper presents a novel Automatic Essay Scoring (AES) algorithm tailored
for the Portuguese-language essays of Brazil's Exame Nacional do Ensino M\'edio
(ENEM), addressing the challenges in traditional human grading systems. Our
approach leverages advanced deep learning techniques to align closely with
human grading criteria, targeting efficiency and scalability in evaluating
large volumes of student essays. This research not only responds to the
logistical and financial constraints of manual grading in Brazilian educational
assessments but also promises to enhance fairness and consistency in scoring,
marking a significant step forward in the application of AES in large-scale
academic settings.