Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/10440
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dc.contributor.authorΧάλαρης, Μανώληςell
dc.contributor.authorΓκρίτζαλης, Στέφανοςell
dc.contributor.authorΜαραγκουδάκης, Μανώληςell
dc.contributor.authorΣγουροπούλου, Κλειώ Ε.ell
dc.contributor.authorΤσολακίδης, Αναστάσιοςell
dc.date.accessioned2015-05-15T10:05:49Z-
dc.date.available2015-05-15T10:05:49Z-
dc.date.issued2015-05-15-
dc.date.issued2014-
dc.identifier.citationChalaris, M., Gritzalis, S., Maragoudakis, M., Sgouropoulou, C. and Tsolakidis, A. (2014) Improving quality of educational processes providing new knowledge using data mining techniques. Procedia- Social and behavioral sciences, (147). pp.390-397.eng
dc.identifier.urihttp://hdl.handle.net/11400/10440-
dc.description.abstractOne of the biggest challenges that Higher Education Institutions (HEI) faces is to improve the quality of their educational processes. Thus, it is crucial for the administration of the institutions to set new strategies and plans for a better management of the current processes. Furthermore, the managerial decision is becoming more difficult as the complexity of educational entities increase. The purpose of this study is to suggest a way to support the administration of a HEI by providing new knowledge related to the educational processes using data mining techniques. This knowledge can be extracted among other from educational data that derive from the evaluation processes that each department of a HEI conducts. These data can be found in educational databases, in students’ questionnaires or in faculty members’ records. This paper presents the capabilities of data mining in the context of a Higher Education Institute and tries to discover new explicit knowledge by applying data mining techniques to educational data of Technological Educational Institute of Athens. The data used for this study come from students’ questionnaires distributed in the classes within the evaluation process of each department of the Institute.eng
dc.language.isoeng-
dc.publisherElseviereng
dc.rightsΑναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourcehttp://www.elsevier.com/en
dc.subjectΤεχνικές εξόρυξης δεδομένων-
dc.subjectΑνώτατα Εκπαιδευτικά Ιδρύματα-
dc.subjectΕκπαιδευτικό πρόγραμμα-
dc.subjectΕκπαιδευτική εξόρυξη δεδομένων-
dc.subjectΑπόφαση στήριξης-
dc.subjectΜεθοδολογία CRISPDM-
dc.subjectData mining techniques-
dc.subjectHigher Education Institutes-
dc.subjectEducational Processes-
dc.subjectEducational Data Mining-
dc.subjectDecision support-
dc.subjectCRISPDM methodology-
dc.titleImproving quality of educational processes providing new knowledge using data mining techniqueseng
dc.typeΔημοσίευση σε περιοδικό-
heal.classificationComputer science-
heal.classificationTechnology-
heal.classificationΠληροφορική-
heal.classificationΤεχνολογία-
heal.classificationURIhttp://skos.um.es/unescothes/C00750-
heal.classificationURIhttp://zbw.eu/stw/descriptor/10470-6-
heal.classificationURI**N/A**-Πληροφορική-
heal.classificationURI**N/A**-Τεχνολογία-
heal.accessfree-
heal.recordProviderΤεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Tμήμα Μηχανικών Πληροφορικής Τ.Ε.ell
heal.journalNameProcedia- Social and behavioral scienceseng
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilitytrue-
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