Automated Formal Register Scoring of Student Narrative Essays Written in Portuguese

This paper develops and evaluates machine learning models for automatically scoring formal register (grammar, vocabulary, language proficiency) in narrative essays written by K-12 students in Portuguese, comparing automated scores against human annotators. The study creates a dataset of 327 annotated student narrative essays and tests various ML algorithms to predict human ratings.

Automated essay scoring (AES) is the task of automatically assigning scores (i.e., grades) to written texts. Although AES has been widely studied in the literature (e.g., informational and argumentative essays), specific types of texts still need more attention. Narrative essays are characterized by texts describing personal experiences and stories, either real or fictional. In this work, we describe a study on scoring student essays written in Portuguese under the aspect of Formal Register, whi

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