Academic Evasion

Dropout is one of the most intriguing and crucial problems in education. This problem permeates the various levels and modalities of education and generates social economic political academic and financial losses for all those involved in the educational process. Therefore it is essential to develop efficient methods to predict the risk of student dropout allowing institutions to adopt proactive actions to minimize the situation. Thus the objective of this paper is to present a knowledge discovery approach using a database to identify groups of students at risk of dropping out of in-class courses of higher education.