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dc.contributor.authorDurães, Dalilapor
dc.contributor.authorBajo, Javierpor
dc.contributor.authorNovais, Paulopor
dc.date.accessioned2018-02-16T09:05:58Z-
dc.date.available2018-02-16T09:05:58Z-
dc.date.issued2017-
dc.identifier.citationDurães D., Bajo J., Novais P., Analysis learning styles though attentiveness, Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference, Springer - Advances in Intelligent Systems and Computing, Pierpaolo Vittorini et al.(Eds), Vol 617, ISSN 2194-5357, ISBN 978-3-319-60818-1, pp 90-97, 2017. https://doi.org/10.1007/978-3-319-60819-8_11.por
dc.identifier.isbn9783319608181por
dc.identifier.issn2194-5357-
dc.identifier.urihttps://hdl.handle.net/1822/50555-
dc.description.abstractAttention is one of the most widely misused and overgeneralized constructs found in the educational, learning, instructional, and psychological sciences. It would be convenient for teachers if they could grasp the attentiveness states of learners in their classes precisely so that they could try to improve the way to deliver the course material in a manner that could attract more learners. When students are doing learning activities using the news technologies is very hard for the teacher detected if each student her/his level of attentiveness. Furthermore, different student learn in different ways, each one preferring a different learning style. This paper presents an experience using different learning styles with a system that monitoring attention, with the aim of providing a nonintrusive and non-invasive way, reliable and easy tool that can be used freely in schools, without changing or interfering with the established working routines. Specifically, we look at desk students in learning activities, in which the student spends long time interacting with the computer.por
dc.description.sponsorshipThis work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationPOCI-01-0145-FEDER-007043por
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.rightsopenAccesspor
dc.subjectLearning stylepor
dc.subjectAttentionpor
dc.subjectBehavior biometricspor
dc.subjectTechnologies in learningpor
dc.subjectAmbient intelligent systempor
dc.titleAnalysis learning styles though attentivenesspor
dc.typeconferencePaperpor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-319-60819-8_11por
oaire.citationStartPage90por
oaire.citationEndPage97por
oaire.citationVolume617por
dc.identifier.doi10.1007/978-3-319-60819-8_11por
dc.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
sdum.journalAdvances in Intelligent Systems and Computingpor
sdum.conferencePublicationMethodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conferencepor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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