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Educational Data Mining with Focus on Dropout Rates


Rosangela Villwock, Andressa Appio and Aldioni Adaiani Andreta


Vol. 15  No. 3  pp. 17-23


High dropout rates in higher education may be motivated by social, economic or personal factors and it is a reality in the Mathematics Major at Universidade Estadual do Oeste do Paran? - Cascavel. Thus, the aim of this study was to identify the factors that may have been influencing this reality through Data Mining (Classification). The study investigated the academic background and socioeconomic factors. Higher dropout rates were identified in the first year of this Major in which the course 'Differential and Integral Calculus I' was the one that most contributed for that. As for the socioeconomic factor, full-time working necessity was the one that was the most responsible for dropouts. Although trivial, the rules found endorse what by socializing with academics involved in the research was expected. It is hoped that this work may contribute to the elaboration of policies aimed at meeting the needs of the students, therefore ensuring their permanency at the University.


Process of Knowledge Discovery in Databases Classification Socioeconomic Patterns Patterns of Courses.