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Adaptive eLearning based on individual learning styles – Performance and emotional factors

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dc.contributor.authorBeckmann, Jenniferde_DE
dc.contributor.authorBertel, Svende_DE
dc.contributor.authorZander, Steffide_DE
dc.contributor.editorButz, Andreasde_DE
dc.contributor.editorKoch, Michaelde_DE
dc.contributor.editorSchlichter, Johannde_DE
dc.date.accessioned2017-11-22T14:55:41Z
dc.date.available2017-11-22T14:55:41Z
dc.date.issued2014
dc.description.abstractAdaptive eLearning systems are able to adjust to a user’s learning needs, usually by user modeling or tracking progress. Such learner-adaptive behavior has rapidly become a hot topic for eLearning. This contribution presents original research on using differ-ences in individual learning styles. Factors related to performance, motivation, satisfac-tion, and previous knowledge were targeted and used to assess the effectiveness of the approach.de_DE
dc.identifier.isbn978-3-11-034448-6de_DE
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/7544
dc.language.isoende_DE
dc.publisherDe Gruyter Oldenbourgde_DE
dc.relation.ispartofMensch & Computer 2014 - Tagungsbandde_DE
dc.subjecteLearning Platformsde_DE
dc.subjectUser Motivationde_DE
dc.subjectUser Satisfactionde_DE
dc.subjectInter-Individual Differencesde_DE
dc.subjectLearning Stylesde_DE
dc.subjectAdaptivität und Benutzermodellierungde_DE
dc.subjectGender und Diversity im Designde_DE
dc.titleAdaptive eLearning based on individual learning styles – Performance and emotional factorsde_DE
dc.typeText/Workshop Paperde_DE
gi.citation.endPage290
gi.citation.publisherPlaceBerlinde_DE
gi.citation.startPage287de_DE
gi.conference.sessiontitlePoster Sessionde_DE
gi.document.qualitydigidocde_DE

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Tagungsband MuC 2014