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The Analysis of the Length of Studies in Higher Education based on Clustering and the Extraction of Association Rules

2014; Elsevier BV; Volume: 147; Linguagem: Inglês

10.1016/j.sbspro.2014.07.159

1877-0428

Petros Belsis, Ioannis Chalaris, Manolis Chalaris, Christos Skourlas, Anastasios Tsolakidis,

Data Mining Algorithms and Applications

Abstract The length of studies of the students who “linger” in Higher Education has not been justified in many countries, and the Higher Education Institutes try to solve the problem using various methods. The problem of students who “linger” in their Departments beyond the six or seven years is seen as complex one, in the Greek Higher Education. Two main alternative methods have been discussed: Giving the students who “linger” a low priority for registration in the laboratory classes, and limiting the number of times of attending laboratory based courses. Eventually, according to the new legislation the Greek Higher Education Institutes must cut off access to the students who “linger” too long. This study focuses on this hard problem. Clustering techniques and the mining of Association rules are used. The results of clustering and the generation of the association rules are based on students’ questionnaires collected in the laboratory classes. Various interesting results and rules are extracted and discussed.