Granular mining of student's learning behavior in learning management system using rough set technique

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86092840" target="_blank" >RIV/61989100:27240/10:86092840 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-642-11224-9_5" target="_blank" >http://dx.doi.org/10.1007/978-3-642-11224-9_5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-11224-9_5" target="_blank" >10.1007/978-3-642-11224-9_5</a>

Result language

angličtina

Original language name

Granular mining of student's learning behavior in learning management system using rough set technique

Original language description

Pattern multiplicity of user interaction in learning management system can be intelligently examined to diagnose students' learning style. Such patterns include the way the user navigate, the choice of the link provided in the system, the preferences oftype of learning material, and the usage of the tool provided in the system. In this study, we propose mapping development of student characteristics into Integrated Felder Silverman (IFS) learning style dimensions. Four learning dimensions in Felder Silverman model are incorporated to map the student characteristics into sixteen learning styles. Subsequently, by employing rough set technique, twenty attributes have been selected for mapping principle. However, rough set generates a large number of rules that might have redundancy and irrelevant. Hence, in this study, we assess and mining the most significant IFS rules for user behavior by filtering these irrelevant rules. The assessments of the rules are executed by evaluating the rule

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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Project

<a href="/en/project/GA201%2F09%2F0990" target="_blank" >GA201/09/0990: XML data processing</a><br>

Continuities

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

Publication year

2010

Confidentiality

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

Name of the periodical

Studies in Computational Intelligence

ISSN

1860-949X

e-ISSN

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Volume of the periodical

273

Issue of the periodical within the volume

1

Country of publishing house

DE - GERMANY

Number of pages

26

Pages from-to

99-124

UT code for WoS article

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EID of the result in the Scopus database

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