dc.contributor.author | Sáiz Manzanares, María Consuelo | |
dc.contributor.author | Marticorena Sánchez, Raúl | |
dc.contributor.author | Martín Antón, Luis Jorge | |
dc.contributor.author | González Díez, Irene | |
dc.contributor.author | Carbonero Martín, Miguel Ángel | |
dc.date.accessioned | 2023-07-12T10:17:37Z | |
dc.date.available | 2023-07-12T10:17:37Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 1044-7318 | |
dc.identifier.uri | http://hdl.handle.net/10259/7755 | |
dc.description.abstract | Monitoring 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.sponsorship | his 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.mimetype | application/pdf | |
dc.language.iso | eng | es |
dc.publisher | Taylor & Francis | es |
dc.relation.ispartof | International Journal of Human–Computer Interaction. 2023 | en |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Self-regulated learning | en |
dc.subject | Cognitive load | en |
dc.subject | Eye tracking | en |
dc.subject | Machine learning | en |
dc.subject | Effective learning | en |
dc.subject.other | Enseñanza superior | es |
dc.subject.other | Education, Higher | en |
dc.subject.other | Psicología | es |
dc.subject.other | Psychology | en |
dc.subject.other | Tecnología | es |
dc.subject.other | Technology | en |
dc.title | Using Eye Tracking Technology to Analyse Cognitive Load in Multichannel Activities in University Students | en |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.relation.publisherversion | https://doi.org/10.1080/10447318.2023.2188532 | es |
dc.identifier.doi | 10.1080/10447318.2023.2188532 | |
dc.relation.projectID | info: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.essn | 1532-7590 | |
dc.journal.title | International Journal of Human–Computer Interaction | es |
dc.page.initial | 1 | es |
dc.page.final | 19 | es |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es |
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