Management of Inter-municipal Consortia for Brazilian Basic Education System using School Census data and Artificial Intelligence algorithms

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Abstract

The aim is to integrate data from the INEP School Census and Python algorithms in the shared management of inter-municipal consortia for Brazilian basic education system. Variables from the School Census pertaining to schools, students, and management activities were utilized, leveraging them to forecast future scenarios. The outcomes encompassed Python algorithms for decision-making concerning the planning of school network expansion and distribution, optimized allocation of human resources, as well as strategies for preventing school dropout, along with future scenarios for each algorithm category generated.

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Institutions
  • 1 Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.
  • 2 Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto
  • 3 FEA/RP-USP
Track
  • WG 22 Experiences and challenges of Artificial Intelligence in the Public Sector
Keywords
inter-municipal consortia
basic education
school census
python
ai