RT info:eu-repo/semantics/article
T1 Using Eye Tracking Technology to Analyse Cognitive Load in Multichannel Activities in University Students
A1 Sáiz Manzanares, María Consuelo
A1 Marticorena Sánchez, Raúl
A1 Martín Antón, Luis Jorge
A1 González Díez, Irene
A1 Carbonero Martín, Miguel Ángel
K1 Self-regulated learning
K1 Cognitive load
K1 Eye tracking
K1 Machine learning
K1 Effective learning
K1 Enseñanza superior
K1 Education, Higher
K1 Psicología
K1 Psychology
K1 Tecnología
K1 Technology
AB 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.
PB Taylor & Francis
SN 1044-7318
YR 2023
FD 2023
LK http://hdl.handle.net/10259/7755
UL http://hdl.handle.net/10259/7755
LA eng
NO 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].
DS Repositorio Institucional de la Universidad de Burgos
RD 09-may-2024