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dc.contributor.authorSáiz Manzanares, María Consuelo 
dc.contributor.authorMarticorena Sánchez, Raúl 
dc.contributor.authorMartín Antón, Luis Jorge
dc.contributor.authorGonzález Díez, Irene 
dc.contributor.authorCarbonero Martín, Miguel Ángel
dc.date.accessioned2023-07-12T10:17:37Z
dc.date.available2023-07-12T10:17:37Z
dc.date.issued2023
dc.identifier.issn1044-7318
dc.identifier.urihttp://hdl.handle.net/10259/7755
dc.description.abstractMonitoring through the use of eye-tracking technology helps in understanding the cognitive load learners experience when doing tasks. This data gives the teacher and the student important information for improving learning outcomes. This study examined whether students’ participation in a learning virtual laboratory, with a self-regulated video monitored with eye-tracking, would influence their learning outcomes. It also examined whether students’ prior knowledge affected their learning outcomes. Lastly, the study identified clusters related to cognitive load in relevant Areas of Interest vs. non-relevant Areas of Interest. The sample comprised 42 university students of health sciences. The results indicate that participation in the virtual laboratory was related to better learning outcomes. In addition, prior knowledge did not affect cognitive load. A number of different clusters were found related to indicators of cognitive load in relevant and non-relevant AOIs. More applied studies are needed about the effects of monitoring on learning outcomes and on what it means for individualization of learning.en
dc.description.sponsorshiphis work was supported by the Ministerio de Ciencia e Innovación de España. Proyectos de I + D+i-RTI Tipo B under Grant number [PID2020-117111RB-I00].en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherTaylor & Francises
dc.relation.ispartofInternational Journal of Human–Computer Interaction. 2023en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSelf-regulated learningen
dc.subjectCognitive loaden
dc.subjectEye trackingen
dc.subjectMachine learningen
dc.subjectEffective learningen
dc.subject.otherEnseñanza superiores
dc.subject.otherEducation, Higheren
dc.subject.otherPsicologíaes
dc.subject.otherPsychologyen
dc.subject.otherTecnologíaes
dc.subject.otherTechnologyen
dc.titleUsing Eye Tracking Technology to Analyse Cognitive Load in Multichannel Activities in University Studentsen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1080/10447318.2023.2188532es
dc.identifier.doi10.1080/10447318.2023.2188532
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117111RB-I00/ES/ASISTENTES DE VOZ E INTELIGENCIA ARTIFICIAL EN MOODLE: UN CAMINO HACIA UNA UNIVERSIDAD INTELIGENTE/es
dc.identifier.essn1532-7590
dc.journal.titleInternational Journal of Human–Computer Interactiones
dc.page.initial1es
dc.page.final19es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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