Estimating the School Dropout Trend by Using Data Mining Methods

Abstract

The knowledge discovery in the education and training process is very important in terms of raising the quality of the education and training activities. Nowadays, there are a number of applications in the field of education and training that enable giving high-dimensional data such as questionnaires, exam results and guidance tests. It is easier to improve the education and training processes by analyzing data from these large data sets. In this study, a software with graphical interface that can be used in the problem of educational data mining is designed. In addition, this software has been used to estimate the school failure by using data mining methods and to compare the performance of these methods on a data set from the UCI data warehouse.