Pixel International Conferences

The present study investigated the extent to which the student-student dimension of the Relational Factors for the Risk of School Dropout Scale [1] was able to track students at higher risk of dropping out of school based on their relationships with each other and how class, race, and gender markers [2] were determinant for risk analysis and prevention over the course of a year Synthetic data was generated using the Gaussian Copula technique, which estimates new responses based on the correlation between the observed variables in the real dataset, reproducing its relationships. Due to ethical considerations and compliance with Brazilian data protection legislation (LGPD), this study relies on synthetic, anonymized data, however, a nationwide data collection using real-world data is currently being conducted in Brazil. This approach was considered due to the General Law of Data Protection (LGPD). Results reflect that the use of interventions based on Psychology and Critical Pedagogy have an effect on reducing the risk of school dropout as well as promoting well-being [3] in this environment and quality for the teaching and learning process as showed in the state case [4]. In the end, it is proposed to link the measure to its intersectional analyses, which consider racism, sexism and ableism as important tools in the fight against school dropout when we think of a country of continental proportions and as diverse in numerous factors as is the case of Brazil.