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MAMIPEC - Affective modeling in inclusive personalized educational scenarios

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dc.contributor.authorSantos, Olga C.
dc.contributor.authorGonzález Boticario, Jesús
dc.contributor.authorArevalillo Herráez, Miguel
dc.contributor.authorSaneiro Silva, María del Mar
dc.contributor.authorCabestrero Alonso, Raúl
dc.contributor.authorCampo Adrián, María del Campo
dc.contributor.authorManjarrés Riesco, Ángeles
dc.contributor.authorMoreno Clarí, Paloma
dc.contributor.authorQuirós Expósito, Pilar
dc.contributor.authorSalmeron Majadas, Sergio
dc.date.accessioned2025-09-12T08:16:35Z
dc.date.available2025-09-12T08:16:35Z
dc.date.issued2012
dc.descriptionThe registered version of this article, first published in "Bulletin of the Technical Committee on Learning Technology 14 - 4, pp. 35 - 38", is available online at the publisher's website: https://tc.computer.org/tclt/wp-content/uploads/sites/5/2018/01/SantosEtAl.pdf
dc.descriptionLa versión registrada de este artículo, publicado por primera vez en "Bulletin of the Technical Committee on Learning Technology 14 - 4, pp. 35 - 38", está disponible en línea en el sitio web del editor: https://tc.computer.org/tclt/wp-content/uploads/sites/5/2018/01/SantosEtAl.pdf
dc.description.abstractThere is agreement in the literature that affect influences learning. In turn, addressing affective issues in the recommendation process has shown their ability to increase the performance of recommender systems in non-educational scenarios. In our work, we combine both research lines and describe the SAERS approach to model affective educational recommendations. This affective recommendation model has been initially validated with the application of the TORMES methodology to specific educational settings. We report 29 recommendations elicited in 12 scenarios by applying this methodology. Moreover, a UML formalized version of the recommendations model which can describe the recommendations elicited is presented in the paper.en
dc.description.provenanceMade available in DSpace on 2025-09-12T08:16:35Z (GMT). No. of bitstreams: 1 Santos et al_2012_MAMIPEC Affective Modeling_JESUS GONZALEZ BOTIC.pdf: 183981 bytes, checksum: d3c79c415191b71617bc23c01981e251 (MD5) Previous issue date: 2012en
dc.description.versionversión publicada
dc.identifier.citationOlga C. Santos, Jesus G. Boticario, Miguel Arevalillo-Herráez, Mar Saneiro, Raul Cabestrero, Elena del Campo, Angeles Manjarres; Paloma Moreno, Pilar Quiros, Sergio Salmerón (2012). MAMIPEC - Affective Modeling in Inclusive Personalized Educational Scenarios. Bulletin of the Technical Committee on Learning Technology. Special Issue Articles: Technology-Augmented Physical Educational Spaces. 14 - 4, pp. 35 - 38. IEEE Technical Committee on Learning Technology, 2012. https://tc.computer.org/tclt/wp-content/uploads/sites/5/2018/01/SantosEtAl.pdf
dc.identifier.issn2306-0212
dc.identifier.urihttps://hdl.handle.net/20.500.14468/30010
dc.journal.issue2
dc.journal.titleBulletin of the Technical Committee on Learning Technology
dc.journal.volume14
dc.language.isoen
dc.page.final38
dc.page.initial35
dc.publisherIEEE Technical Committee on Learning Technology,
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentInteligencia Artificial
dc.relation.projectidinfo:eu-repo/grantAgreement/MICINN/Programa Nacional de Investigación Fundamental/TIN2011-29221-C03-01/ES/ENFOQUES MULTIMODALES PARA EL MODELADO DE ASPECTOS EMOCIONALES EN ESCENARIOS DE EDUCACION PERSONALIZADOS E INCLUSIVOS EN CONTEXTOS INTELIGENTES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject3304 Tecnología de los ordenadores
dc.subject.keywordsAffective computingen
dc.subject.keywordsEducational recommender systemsen
dc.subject.keywordsRecommendation modelen
dc.subject.keywordsSemantic affective educational recommender systemsen
dc.titleMAMIPEC - Affective modeling in inclusive personalized educational scenariosen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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