Análise dos Impactos da Gestão do Tempo no Desempenho Acadêmico Através da Mineração de Dados Educacionais

Abstract

With technological advances, new challenges were born. Amongst them is the problem of identifying factors that corroborate with the good academic performance of students of distance learning courses. This work aims to analyze the impacts of time management on the academic performance of the student. For this, the K-means technique was used to group students in relation to their academic performance, a neural network was used to classify these groups according to the time management variables, and the SHAP method was used to interpret the classes obtained in an efficient way. The construction of this research uses data from distance learning courses extracted from the moodle platform of a public university in the state of Pernambuco. As a conclusion, it was possible to observe which characteristics of time management impact the student's academic performance positively.