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.

本文提出了一种新颖的面向巴西全国高等教育入学考试（ENEM）中葡语作文的自动评分（AES）算法，解决了传统人工评分系统中的挑战。该方法利用先进的深度学习技术，紧密对齐人工评分标准，以评估大量学生作文的效率和可扩展性为目标。该研究不仅解决了巴西教育评估中手动评分的物流和财务约束，还承诺在评分中提高公平性和一致性，是应用 AES 在大规模学术环境中迈出的重要一步。