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Integrating Learning Styles and Personality Traits into an Affective Model to Support Learner’s Learning

dc.contributor.authorLeontidis, Makis
dc.contributor.authorHalatsis, Constantin
dc.description.abstractThe aim of this paper is to present a model in order to integrate the learning style and the personality traits of a learner into an enhanced Affective Style which is stored in the learner’s model. This model which can deal with the cognitive abilities as well as the affective preferences of the learner is called Learner Affective Model (LAM). The LAM is used to retain learner’s knowledge and activities during his interaction with a Web-based learning environment and also to provide him with the appropriate pedagogical guidance. The proposed model makes use of an ontological approach in combination with the Bayesian Network model and contributes to the efficient management of the LAM in an Affective Module.en_UK
dc.publisherSpringer International Publishingen_UK
dc.relation.ispartofseriesLecture Notes in Computer Science;Vol. 5686
dc.rights© Springer International Publishing AGen_UK
dc.subjectUser Modelingen_UK
dc.subjectAffective Computingen_UK
dc.subjectAffective Modelen_UK
dc.titleIntegrating Learning Styles and Personality Traits into an Affective Model to Support Learner’s Learningen_UK
dc.typeBook chapteren_UK

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