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Predictor of School Failure of students enrolled in elementary and junior high school in the municipal education network of Rio de Janeiro
Parceria: Prefeitura Municipal do Rio de Janeiro - ACT nº 105/2024
Development of parametric models, using statistical and data science techniques, such as machine learning to estimate the probability of failure of students enrolled in elementary and junior school at the end of the 2024 and 2025 school years. Variables from the dimensions of the student’s life will be incorporated, such as: school, family, teachers, attendance and evaluations. The study foresees, as a by-product, an analysis of the students’ attendance patterns, based on daily school attendance data.