Analysis of Learning Styles for Adaptive E-Learning

Autor:	Ondřej Takács, Jana Šarmanová, Kateřina Kostolányová
Rok vydání:	2011
Předmět:	Learning styles Process (engineering) Need to know Computer science E-learning (theory) Decision tree Mathematics education Adaptive learning Adaptation (computer science) Cluster analysis
Zdroj:	Digital Information Processing and Communications ISBN: 9783642223884 ICDIPC (1)
DOI:	10.1007/978-3-642-22389-1_33
Popis:	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 questionnaire was 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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a5a78b1c47778a5c40cbd31d227fdd27 https://doi.org/10.1007/978-3-642-22389-1_33 Zobrazit plný text záznamu