Análse comparativa de algoritmos de aprendizagem de máquina: um estudo de caso na área educacional

Abstract

In the educational area, the application of machine algorithms allows define strategies that help students to improve their performance to progress in learning, assist teachers and researchers to discover new ways to improve themselves, predict the risk of student evasion, evaluate the performance of students acting in the educational environment, among others. This work applied data mining tools using machine learning algorithms on a database referring to the opinion of higher education students about remote education in the pandemic period. The data mining step aimed to infer rules and patterns that can model students' profile in relation to distance learning methodology. The results found show different characteristics for groups of students with varying opinions on the application of distance learning. The algorithms showed satisfactory results in relation to accuracy and it was possible to analyze the profiles of these students through the rules defined by them.