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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/6247

    Título
    Lifelong Learning from Sustainable Education: An Analysis with Eye Tracking and Data Mining Techniques
    Autor
    Sáiz Manzanares, María ConsueloUBU authority Orcid
    Rodríguez Diez, Juan JoséUBU authority Orcid
    Marticorena Sánchez, RaúlUBU authority Orcid
    Zaparaín Yáñez, Mª José
    Cerezo Menéndez, Rebeca
    Publicado en
    Sustainability. 2020, V. 12, n. 5, 1970
    Editorial
    MDPI
    Fecha de publicación
    2020-03
    ISSN
    2071-1050
    DOI
    10.3390/su12051970
    Abstract
    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.
    Palabras clave
    Advanced learning technologies
    Lifelong learning
    Sustainability education
    Eye tracking
    Data mining techniques
    Materia
    Enseñanza superior
    Education, Higher
    Psicología
    Psychology
    Informática
    Computer science
    URI
    http://hdl.handle.net/10259/6247
    Versión del editor
    https://doi.org/10.3390/su12051970
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    Saiz-sustainability_2020.pdf
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