RT info:eu-repo/semantics/article
T1 Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques
A1 Sáiz Manzanares, María Consuelo
A1 Rodríguez Diez, Juan José
A1 Marticorena Sánchez, Raúl
A1 Zaparaín Yáñez, Mª José
A1 Cerezo Menéndez, Rebeca
K1 Advanced learning technologies
K1 Lifelong learning
K1 Sustainability education
K1 Eye tracking
K1 Data mining techniques
K1 Enseñanza superior
K1 Education, Higher
K1 Psicología
K1 Psychology
K1 Informática
K1 Computer science
AB The 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.
PB MDPI
SN 2071-1050
YR 2020
FD 2020-03
LK http://hdl.handle.net/10259/6247
UL http://hdl.handle.net/10259/6247
LA eng
NO European 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.
DS Repositorio Institucional de la Universidad de Burgos
RD 23-nov-2024