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On the use of case-based planning for e-learning personalization

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On the use of case-based planning for e-learning personalization

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dc.contributor.author Garrido Tejero, Antonio es_ES
dc.contributor.author Morales, Lluvia es_ES
dc.contributor.author Serina, Iván es_ES
dc.date.accessioned 2017-04-03T09:06:58Z
dc.date.available 2017-04-03T09:06:58Z
dc.date.issued 2016-10-30
dc.identifier.issn 0957-4174
dc.identifier.uri http://hdl.handle.net/10251/79349
dc.description This is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, 60, 1-15, 2016. DOI:10.1016/j.eswa.2016.04.030 es_ES
dc.description.abstract In this paper we propose myPTutor, a general and effective approach which uses AI planning techniques to create fully tailored learning routes, as sequences of Learning Objects (LOs) that fit the pedagogical and students’ requirements. myPTutor has a potential applicability to support e-learning personalization by producing, and automatically solving, a planning model from (and to) e-learning standards in a vast number of real scenarios, from small to medium/large e-learning communities. Our experiments demonstrate that we can solve scenarios with large courses and a high number of students. Therefore, it is perfectly valid for schools, high schools and universities, especially if they already use Moodle, on top of which we have implemented myPTutor. It is also of practical significance for repairing unexpected discrepancies (while the students are executing their learning routes) by using a Case-Based Planning adaptation process that reduces the differences between the original and the new route, thus enhancing the learning process. © 2016 Elsevier Ltd. All rights reserved. es_ES
dc.description.sponsorship This work has been partially funded by the Consolider AT project CSD2007-0022 INGENIO 2010 of the Spanish Ministry of Science and Innovation, the MICINN project TIN2011-27652-C03-01, the MINECO and FEDER project TIN2014-55637-C2-2-R, the Mexican National Council of Science and Technology, the Valencian Prometeo project II/2013/019 and the BW5053 research project of the Free University of Bozen-Bolzano. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Expert Systems with Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject E-learning es_ES
dc.subject Learning route personalization es_ES
dc.subject Planning es_ES
dc.subject Plan adaptation es_ES
dc.subject Case base planning es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title On the use of case-based planning for e-learning personalization es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.eswa.2016.04.030
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00022/ES/Agreement Technologies/ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2011-27652-C03-01/ES/INTERACCION MULTIAGENTE PARA PLANIFICACION/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2014-55637-C2-2-R/ES/GESTION DE METAS PARA AUTONOMIA A LARGO PLAZO EN CIUDADES INTELIGENTES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2013%2F019/ES/HUMBACE: HUMAN-LIKE COMPUTATIONAL MODELS FOR AGENT-BASED COMPUTATIONAL ECONOMICS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UNIBZ//BW5053/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Garrido Tejero, A.; Morales, L.; Serina, I. (2016). On the use of case-based planning for e-learning personalization. Expert Systems with Applications. 60:1-15. https://doi.org/10.1016/j.eswa.2016.04.030 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.eswa.2016.04.030 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 15 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 60 es_ES
dc.relation.senia 311995 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Educación y Ciencia es_ES
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México es_ES
dc.contributor.funder Libera Università di Bolzano


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