Analysis of learning styles for adaptive E-learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86080800" target="_blank" >RIV/61989100:27240/11:86080800 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-642-22389-1_33" target="_blank" >http://dx.doi.org/10.1007/978-3-642-22389-1_33</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-22389-1_33" target="_blank" >10.1007/978-3-642-22389-1_33</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of learning styles for adaptive E-learning

Popis výsledku v původním jazyce

In adaptive e-learning we try to make learning more efficient by adapting the process of learning to students' individual needs. To make this adaptation possible, we need to know key students characteristics - his motivation, group learning preferences,sensual type and various learning styles. One of the easiest ways to measure these characteristics is to use questionnaires. New questionnaire was created because there was no questionnaire to measure all these characteristics at once. This questionnairewas filled by 500 students from different fields of study. These results were analyzed using clustering, decision tree and principal component analysis. Several interesting dependencies between students' properties were discovered using this analysis.

Název v anglickém jazyce

Analysis of learning styles for adaptive E-learning

Popis výsledku anglicky

In adaptive e-learning we try to make learning more efficient by adapting the process of learning to students' individual needs. To make this adaptation possible, we need to know key students characteristics - his motivation, group learning preferences,sensual type and various learning styles. One of the easiest ways to measure these characteristics is to use questionnaires. New questionnaire was created because there was no questionnaire to measure all these characteristics at once. This questionnairewas filled by 500 students from different fields of study. These results were analyzed using clustering, decision tree and principal component analysis. Several interesting dependencies between students' properties were discovered using this analysis.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Communications in Computer and Information Science

ISSN

1865-0929

e-ISSN

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Svazek periodika

188

Číslo periodika v rámci svazku

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Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

8

Strana od-do

368-376

Kód UT WoS článku

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EID výsledku v databázi Scopus

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