Data Scaling by Differential Evolution for FCA over Data from LMS eLogika

Abstract

The e-learning system eLogika serves for teaching logic. 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. 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 a way of data categorization by di erential evolution that proved to be applicable in the FCA method with promising results.