The analysis of the legth of studies in higher education based on clustering and the extraction of association rules

dc.contributor.author	Μπέλσης, Πέτρος	el
dc.contributor.author	Χάλαρης, Ιωάννης	el
dc.contributor.author	Χάλαρης, Μανώλης	el
dc.contributor.author	Σκουρλάς, Χρήστος Π.	el
dc.contributor.author	Τσολακίδης, Αναστάσιος	el
dc.date.accessioned	2015-05-15T16:37:55Z
dc.date.available	2015-05-15T16:37:55Z
dc.date.issued	2015-05-15
dc.identifier.uri	http://hdl.handle.net/11400/10465
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.elsevier.com/	en
dc.subject	Κανόνες συσχέτισης
dc.subject	Τριτοβάθμια εκπαίδευση
dc.subject	Φοιτητική διατήρηση
dc.subject	Φοιτητική παρέμβαση
dc.subject	Εξόρυξη κανόνων
dc.subject	Association rules
dc.subject	Higher education
dc.subject	Student retention
dc.subject	Student intervention
dc.subject	Rules’ extraction
dc.title	The analysis of the legth of studies in higher education based on clustering and the extraction of association rules	en
heal.type	journalArticle
heal.classification	Computer science
heal.classification	Higher education
heal.classification	Πληροφορική
heal.classification	Τριτοβάθμια εκπαίδευση
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://skos.um.es/unescothes/C01791
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Τριτοβάθμια εκπαίδευση
heal.language	en
heal.access	free
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Tμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2014-08-25
heal.bibliographicCitation	Belsis, P., Chalaris, I., Chalaris, M., Skourlas, C. and Tsolakidis, A. (2014) The analysis of the legth of studies in higher education based on clustering and the extraction of association rules. Procedia- Social and behavioral sciences, (147). pp.567-575.	el
heal.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.	en
heal.publisher	Elsevier	en
heal.journalName	Procedia- Social and behavioral sciences	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true