Um Estudo Comparativo entre Métodos de Agrupamento em Mineração de Dados Educacionais
(A Comparative Study between Clustering Methods in Educational Data Mining)
Jorge Luis Cavalcanti Ramos (firstname.lastname@example.org)1, Ricardo Euller Dantas e Silva (email@example.com)1, João Carlos Sedraz Silva (firstname.lastname@example.org)1, Rodrigo Lins Rodrigues (email@example.com)2, Alex Sandro Gomes (firstname.lastname@example.org)3
1Universidade Federal do Vale do São Francisco2Universidade Federal Rural de Pernambuco3Universidade Federal de Pernambuco
This paper appears in: Revista IEEE América Latina
Publication Date: Aug. 2016
Volume: 14, Issue: 8
This paper aims to describe the analysis of data from the Moodle's database of a beginner class in Distance Education of a Federal University using distinct educational data mining clustering methods. We carried out clustering using hierarchical and non-hierarchical methods in different groups of students, according to their interaction and performance characteristics. In the analysis, it was possible to perceive the groups obtained, a similarity between the results of each method used, confirming the acquired knowledge from the clustering and demonstrating that the choice of method in this study had little influence on the knowledge obtained from interactions and students performance on the course.
Educational Data Mining, EDM, Clustering Hierarchical method, Clustering Non-hierarchical method, distance education
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