A Brief Review about Educational Data Mining applied to Predict Student’s Dropout

  • G. A. S. Santos PPCC - CEFET/RJ
  • A. L. Bordignon Instituto de Matemática - Universidade Federal Fluminense
  • S. L. G. Oliveira Universidade Federal de Lavras
  • D. B. Haddad PPCC - CEFET/RJ
  • D. N. Brandão PPCC - CEFET/RJ
  • K. T. Belloze PPCC - CEFET/RJ

Resumo


Educational Data Mining (EDM) may be a very useful technique as much to understand student behavior as to plan and manage government investments in education. EDM helps to analyzes and to expose the hidden information of educational data. Particularly, an important application of EDM is to predict or analyze the students’ dropout. This problem affects several educational institutions in Brazil and the world, and identify its origin has been a relevant research motivator. This paper presents a brief introduction about EDM applied to predict students’ dropout and analyzes some important articles during the period from 2013 to 2018.
Publicado
24/10/2018
SANTOS, G. A. S. ; BORDIGNON, A. L.; OLIVEIRA, S. L. G.; HADDAD, D. B.; BRANDÃO, D. N.; BELLOZE, K. T.. A Brief Review about Educational Data Mining applied to Predict Student’s Dropout. In: ESCOLA REGIONAL DE SISTEMAS DE INFORMAÇÃO DO RIO DE JANEIRO (ERSI-RJ), 5. , 2018, Nova Friburgo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 86 - 91. DOI: https://doi.org/10.5753/ersirj.2018.4660.