Students' Behavior Patterns in LMS eLogika Detected by FCA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10235980" target="_blank" >RIV/61989100:27240/17:10235980 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5593/sgem2017/21/S07.079" target="_blank" >http://dx.doi.org/10.5593/sgem2017/21/S07.079</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5593/sgem2017/21/S07.079" target="_blank" >10.5593/sgem2017/21/S07.079</a>
Alternative languages
Result language
angličtina
Original language name
Students' Behavior Patterns in LMS eLogika Detected by FCA
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA15-13277S" target="_blank" >GA15-13277S: Hyperintensional logic for natural language analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
17th International Multidisciplinary Scientific GeoConference: SGEM 2017 : conference proceedings : 29 June-5 July, 2017, Albena, Bulgaria. Volume 17. Issue 21
ISBN
978-619-7408-01-0
ISSN
1314-2704
e-ISSN
neuvedeno
Number of pages
8
Pages from-to
617-624
Publisher name
STEF92 Technology Ltd.
Place of publication
Sofia
Event location
Albena
Event date
Jun 29, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—