Data Scaling by Differential Evolution for FCA over Data from LMS eLogika
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The e-learning system eLogika serves for teaching logic. The system collects data about users who arelogged in, e.g. time spent on a particular activity, the number of activities performed by particular students, whatdata is a student interested in, etc. The goal of this paper is to describe the application of many-valued formalconcept analysis (FCA) in order to discover typical patterns of students behavior. Since the data stored in theeLogika system are numerical we need to categorize them in order to be used in the many-valued FCA method.In the paper we describe a way of data categorization by di erential evolution that proved to be applicable in theFCA method with promising results.
KeywordsE-learning, log files, many-valued FCA, data scaling, differential evolution, behavior pattern
Document typePeer reviewed
Document versionFinal PDF
SourceMendel. 2017 vol. 23, č. 1, s. 15-20. ISSN 1803-3814
- Vol. 23, No. 1