2026-06-29T21:02:27Zhttps://riubu.ubu.es/oai/request
oai:riubu.ubu.es:10259/62472023-08-28T12:06:49Zcom_10259.4_2503com_10259_5086com_10259_2604com_10259_4219com_10259_5841col_10259.4_2504col_10259_4220col_10259_5842
Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques Sáiz Manzanares, María Consuelo Rodríguez Diez, Juan José Marticorena Sánchez, Raúl Zaparaín Yáñez, Mª José Cerezo Menéndez, Rebeca Advanced learning technologies Lifelong learning Sustainability education Eye tracking Data mining techniques 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. 2021-11-29 2021-11-29 2020-03 info:eu-repo/semantics/article 2071-1050 http://hdl.handle.net/10259/6247 10.3390/su12051970 eng Sustainability. 2020, V. 12, n. 5, 1970 https://doi.org/10.3390/su12051970 info:eu-repo/grantAgreement/EC/Erasmus+/2019-1-ES01-KA204-065615/EU/SELF-REGULATED LEARNING IN SMARTART http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional MDPI