Mineração de dados educacionais baseada em grafos: uma análise em cursos de computação com alto índice de retenção - Oliveira, João Lucas dos Santos (2021)
Student evasion and retention is a recurring problem in all areas of education. In Area ssuch as Educational Data Mining (MDE) have been used to mitigate such problems. In particular, the area of Graph-based Educational Data Mining (G-EDM) uses unconventional data mining techniques to represent student behavior. This analysis of students can be done both in physical and virtual environments, through complex networks and graphs. The students’ behavior shown by the graphs can express dimensional patterns that would not be expressed by tabular and statistical analyzes. The present work investigated three different techniques of representing student history to investigate the possible causes of retention and dropout in computer courses. The results show that it is possible to identify retention problems in curriculum and that the modeling of the curriculum in the form of agraph can show patterns that would not be possible to describe in tabular representation.