Students' Behavior Patterns in LMS eLogika Detected by FCA

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Students' Behavior Patterns in LMS eLogika Detected by FCA

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Students' Behavior Patterns in LMS eLogika Detected by FCA

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA15-13277S" target="_blank" >GA15-13277S: Hyperintensionální logika pro analýzu přirozeného jazyka</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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

Počet stran výsledku

8

Strana od-do

617-624

Název nakladatele

STEF92 Technology Ltd.

Místo vydání

Sofia

Místo konání akce

Albena

Datum konání akce

29. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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