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dc.contributor.authorLekkas, Zachariasen
dc.contributor.authorTsianos, Nikosen
dc.contributor.authorGermanakos, Panagiotisen
dc.contributor.authorMourlas, Constantinosen
dc.contributor.authorSamaras, George S.en
dc.creatorLekkas, Zachariasen
dc.creatorTsianos, Nikosen
dc.creatorGermanakos, Panagiotisen
dc.creatorMourlas, Constantinosen
dc.creatorSamaras, George S.en
dc.date.accessioned2019-11-13T10:40:57Z
dc.date.available2019-11-13T10:40:57Z
dc.date.issued2009
dc.identifier.isbn978-0-7695-3711-5
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54377
dc.description.abstractResearch on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. The basic objective of this paper is to analyse the way that individuals process their emotions and how they interact with other elements of their information-processing system. It will further underpin their significance taking into consideration the notion of emotion regulation, based on which users expect to receive the most apt personalized provider's content. Special emphasis will be given in dispositional trait affect that serves as an overall estimation of an individual's affective state and statistical evidence will be provided which suggest that affect can have both informational and processing effects on cognition © 2009 IEEE.en
dc.sourceProceedings - 2009 9th IEEE International Conference on Advanced Learning Technologies, ICALT 2009en
dc.source2009 9th IEEE International Conference on Advanced Learning Technologies, ICALT 2009en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-70449397591&doi=10.1109%2fICALT.2009.203&partnerID=40&md5=ad2ba39f8fb6c3d4616c01347d237e17
dc.subjectEducationen
dc.subjectPersonalized learningen
dc.subjectAffective factorsen
dc.subjectAffective stateen
dc.subjectOverall estimationen
dc.subjectPhysiological activityen
dc.subjectProcessing effectsen
dc.subjectProcessing systemsen
dc.subjectSpecial effectsen
dc.subjectStatistical evidenceen
dc.titleThe role of affect in personalized learningen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/ICALT.2009.203
dc.description.startingpage629
dc.description.endingpage633
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: IEEE Computer Societyen
dc.description.notesIEEE Technical Committee on Learning Technologyen
dc.description.notesConference code: 78349</p>en
dc.contributor.orcidLekkas, Zacharias [0000-0003-2049-8187]
dc.gnosis.orcid0000-0003-2049-8187


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