RT Conference Proceedings
T1 Analysis of School Dropout Rate in Paraguay Using a Machine Learning Approach
A1 Insfrán-Coronel, Diego R.
A1 Enrique-Sánchez, Enzo M.
A1 Beck, Federico
A1 López Fernández, Aurelio
A1 García Torres, Miguel
K1 Data mining
K1 Machine learning
K1 Statistical learning
AB This study investigates the school dropout rates in Paraguay, focusing on the transition from ninth grade to the first year of secondary school in the Concepción department. Using an extract, transform, and load (ETL) process, data from the Paraguayan Ministry of Education and Science and the National Institute of Statistics were analyzed. The research employs clustering techniques, particularly K-means, to identify patterns and risk profiles among students. The findings highlight the significant impact of socio-economic factors, such as poverty and child labor, on school dropout rates. These insights aim to inform targeted interventions to improve educational outcomes and reduce dropout rates in Paraguay.
PB Springer
YR 2024
FD 2024-11-16
LK https://hdl.handle.net/10433/25237
UL https://hdl.handle.net/10433/25237
LA en
NO Insfrán-Coronel, D.R., Enrique-Sánchez, E.M., Beck, F., López-Fernández, A., García-Torres, M. (2024). Analysis of School Dropout Rate in Paraguay Using a Machine Learning Approach. In: Quintián, H., et al. International Joint Conferences. ICEUTE CISIS 2024 2024. Lecture Notes in Networks and Systems, vol 957. Springer, Cham. https://doi.org/10.1007/978-3-031-75016-8_29
NO Departamento de Deporte e Informática, Área de Lenguajes y Sistemas Informáticos
DS RIO
RD Apr 23, 2026