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dc.contributor.authorSáiz Manzanares, María Consuelo 
dc.contributor.authorRodríguez Diez, Juan José 
dc.contributor.authorMarticorena Sánchez, Raúl 
dc.contributor.authorZaparaín Yáñez, Mª José 
dc.contributor.authorCerezo Menéndez, Rebeca
dc.date.accessioned2021-11-29T08:57:40Z
dc.date.available2021-11-29T08:57:40Z
dc.date.issued2020-03
dc.identifier.issn2071-1050
dc.identifier.urihttp://hdl.handle.net/10259/6247
dc.description.abstractThe use of learning environments that apply Advanced Learning Technologies (ALTs) and Self-Regulated Learning (SRL) is increasingly frequent. In this study, eye-tracking technology was used to analyze scan-path differences in a History of Art learning task. The study involved 36 participants (students versus university teachers with and without previous knowledge). The scan-paths were registered during the viewing of video based on SRL. Subsequently, the participants were asked to solve a crossword puzzle, and relevant vs. non-relevant Areas of Interest (AOI) were defined. Conventional statistical techniques (ANCOVA) and data mining techniques (string-edit methods and k-means clustering) were applied. The former only detected differences for the crossword puzzle. However, the latter, with the Uniform Distance model, detected the participants with the most effective scan-path. The use of this technique successfully predicted 64.9% of the variance in learning results. The contribution of this study is to analyze the teaching–learning process with resources that allow a personalized response to each learner, understanding education as a right throughout life from a sustainable perspective.en
dc.description.sponsorshipuropean Project “Self-Regulated Learning in SmartArt” 2019-1-ES01-KA204-065615 and the Research Funding Program (Funding of dissemination of research results, 2020) of the Vice-Rectorate for Research and Knowledge Transfer of the University of Burgos to the Recognized Investigation Group DATAHES.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSustainability. 2020, V. 12, n. 5, 1970es
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectAdvanced learning technologiesen
dc.subjectLifelong learningen
dc.subjectSustainability educationen
dc.subjectEye trackingen
dc.subjectData mining techniquesen
dc.subject.otherEnseñanza superiores
dc.subject.otherEducation, Higheren
dc.subject.otherPsicologíaes
dc.subject.otherPsychologyen
dc.subject.otherInformáticaes
dc.subject.otherComputer scienceen
dc.titleLifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniquesen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.3390/su12051970es
dc.identifier.doi10.3390/su12051970
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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