DBPapers
DOI:10.5593/SGEM2013/BB2.V1/S07.010

DATA-MINING AND THE QUALITY OF DISTANCE-EDUCATION IMPROVEMENT

M. Mensik, J. Gerlich
Monday 5 August 2013 by Libadmin2013

References: 13th SGEM GeoConference on Informatics, Geoinformatics And Remote Sensing, www.sgem.org, SGEM2013 Conference Proceedings, ISBN 978-954-91818-9-0 / ISSN 1314-2704, June 16-22, 2013, Vol. 1, 77 - 84 pp

ABSTRACT

Using LMS (Learning Management System) has become a common practice in the universities in which a large number of students are enrolled in particular courses. The LMS systems make it possible to store data that contain pieces of hidden information that may appear to be valuable and yield interesting results. In this paper we introduce the eLogika system and describe data-mining methods that make it possible to make that implicit information explicit. We describe the way of storing those data that are invisible to users but they contain interesting pieces of information on teaching logic, like students’ abilities, typical mistakes and so on. The methods of preprocessing these data are described so that then we can apply data-mining methods in order to improve the quality of teaching process. We focus in particular on association rules and clustering methods.

Keywords: data-mining, association rules, clustering methods

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