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    A Ubiquitous Model of Emotional Tracking in Virtual Classes: From Simple Emotions to Learning Action Tendency

    Autor: 
    Arias T., Susana A.
    ;
    Moreno-Ger, Pablo
    ;
    Verdú, Elena
    Fecha: 
    2022
    Palabra clave: 
    Faces; behavioral sciences; videos; education; software; emotion recognition; semantics; Scopus; WOS
    Revista / editorial: 
    IEEE Latin America Transactions
    Citación: 
    S. A. Arias T., P. Moreno-Ger and E. Verdú, "A Ubiquitous Model of Emotional Tracking in Virtual Classes: From Simple Emotions to Learning Action Tendency," in IEEE Latin America Transactions, vol. 21, no. 8, pp. 889-896, Aug. 2023, doi: 10.1109/TLA.2023.10246345. keywords: {Faces;Behavioral sciences;Videos;Education;Software;Emotion recognition;Semantics},
    Tipo de Ítem: 
    Articulo Revista Indexada
    URI: 
    https://reunir.unir.net/handle/123456789/16841
    DOI: 
    https://doi.org/10.1109/TLA.2023.10246345
    Dirección web: 
    https://ieeexplore.ieee.org/document/10246345/authors#authors
    Resumen:
    Researchers in the field of ubiquitous learning assert that emotional presence management leads to promising results in the teaching-learning process. However, are there predominant emotions in virtual classes How can emotional clusters be created Is it possible to obtain action tendencies in virtual classes In response to these questions, we propose a ubiquitous emotional model for virtual classes, recording the simple emotions from participants faces, checking whether these emotions can produce emotional clusters, and using these clusters to infer action tendencies within the context of virtual classes. The experimentation was carried out in a real virtual class. To evaluate the model, the experts verified the results of the ubiquitous model, and it is confirmed that the action tendency obtained by the model coincides with the criteria of the experts. Inferring these action tendencies are very important, since the teacher, unlike a face-to-face model, has difficulty observing all the students with the use of cameras in virtual classes, making it difficult to understand the students behavior online.
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