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 (jorge.cavalcanti@univasf.edu.br)1, Ricardo Euller Dantas e Silva (riceuller@gmail.com)1, João Carlos Sedraz Silva (jsedraz@gmail.com)1, Rodrigo Lins Rodrigues (rlr@cin.ufpe.br)2, Alex Sandro Gomes (asg@cin.ufpe.br)3


1Universidade Federal do Vale do São Francisco
2Universidade Federal Rural de Pernambuco
3Universidade Federal de Pernambuco

This paper appears in: Revista IEEE América Latina

Publication Date: Aug. 2016
Volume: 14,   Issue: 8 
ISSN: 1548-0992


Abstract:
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.

Index Terms:
Educational Data Mining, EDM, Clustering Hierarchical method, Clustering Non-hierarchical method, distance education   


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