Data mining in academic databases to detect behaviors of students related to school dropout and disapproval

Abstract

This work focuses on data mining in relational databases, aiming to detect behaviors related to school dropouts and disapproval by mapping the factors that influence this dropout. This work is relevant by the fact that the dropout and school disapproval are big factors of concern to all who care about education in Brasil. At the end of it, we intend to point out the need to implement solutions that enable access to results dynamically, thus allowing educators can early diagnose the causes of school dropout and disapproval, and allow for relevant pedagogical actions. This way, we intend to reduce the school dropout and school disapproval, towards a more efficient teaching and learning process at brazilian federal education institution named Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte - IFRN.