DOI: 10.5593/sgem2017/21/S07.079


M. Mensik, P. Drazdilova, J. Kermaschek
Wednesday 13 September 2017 by Libadmin2017

References: 17th International Multidisciplinary Scientific GeoConference SGEM 2017, www.sgem.org, SGEM2017 Conference Proceedings, ISBN 978-619-7408-01-0 / ISSN 1314-2704, 29 June - 5 July, 2017, Vol. 17, Issue 21, 617-624 pp, DOI: 10.5593/sgem2017/21/S07.079


The e-learning system eLogika serves for teaching logic. In the system there are study materials at students’ disposal, but it also provides online tests and promotes all the activities in which the students can obtain their credits. The system collects data about users who are logged in, e.g. time spent on a particular activity, the number of activities performed by particular students, what data is a student interested in, etc.
The goal of this paper is to describe the application of many-valued formal concept analysis (FCA) in order to discover typical patterns of students’ behavior. The concepts retrieved by this method represent groups of students with a common behavior in the learning process. These concepts are further used in the e-learning system in order to inform students about their positive/negative tendencies with respect to their course results. Another way of utilizing these patterns is their application in order to improve the system to be more user-friendly. Since the data stored in the eLogika system are numerical we need to categorize them in order to be used in the many-valued FCA method. In the paper we describe two ways of data categorization that proved to be applicable in the FCA method with promising results.

Keywords: E-learning, logic, log files, FCA, behavior pattern

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