Sistema inteligente para a predição de grupo de risco de evasão discente

School dropout is one of the most complex and crucial problems in the field of education. It permeates and afflicts the several levels and teaching modalities, besides hurting the principle of human dignity. In relation to higher education, internationally, the phenomenon is an object of attention and care, aiming to increase the indexes of permanence and completion rate of the undergraduate students and minimize social, economic, political and financial damage caused to all involved in the educational process. In this context, it is fundamental to develop efficient and effective methods and instruments for prediction, assessment and monitoring of the students at risk of dropping out, making the planning and the adoption of proactive actions possible for the improvement of the situation. Thus, this study aims to present the potentialities of an intelligent system able to identify, in a proactive, continued and accurate way, the student dropout risk group in higher education classroom courses. In the development of this system one of the artificial intelligence techniques was used, the Artificial Neural Networks, more specifically, the Fuzzy-ARTMAP Neural network, a neural network of the ART (Adaptive Resonance Theory) family which makes the continued learning of the system possible. For the training and test of the Neural Network and, later, the validation of the system proposed the socio-economic and academic records of the students enrolled in the technology courses of the Federal Institute of Mato Grosso – IFMT were used. The data that constituted the input vectors of the system were extracted from two database of the IFMT information system, respectively, the Q-selection and the Q-Academic. This system classifies the input patterns in school dropout propensity. The consistence of the results, showing a success rate of the dropout group around 95% and 100% and the overall mean accuracy around 95%, shows the reliability, validity, accuracy and efficiency of the FuzzyARTMAP-Fuzzy neural system proposed, when making the prediction of the group of students more likely to dropout. It is an instituting experience permeated by the practice of alterity, allowing adoption of measures and individualized actions to meet the needs of each student and help them to overcome difficulties and remain in the institution, thus, being useful to society. Given that, with a proactive action, to make a student with potential to evade, be