Articles producció científica> Pedagogia

Classroom Emotion Monitoring Based on Image Processing

  • Datos identificativos

    Identificador: imarina:9351841
    Handle: http://hdl.handle.net/20.500.11797/imarina9351841
  • Autores:

    Llurba C
    Fretes G
    Palau R
  • Otros:

    Autor según el artículo: Llurba C; Fretes G; Palau R
    Departamento: Pedagogia
    Autor/es de la URV: Palau Martin, Ramon Felix
    Palabras clave: Academic performance Emotion recognition Image processing Py-feat Secondary school students Students’ emotions Students’ well-being
    Resumen: One challenge of teaching and learning the lack of information during these processes, including information about students’ emotions. Emotions play a role in learning and processing information, impacting accurate comprehension. Furthermore, emotions affect students’ academic engagement and performance. Consideration of students’ emotions, and therefore their well-being, contributes to building a more sustainable society. A new way of obtaining such information is by monitoring students’ facial emotions. Accordingly, the purpose of this study was to explore whether the use of such advanced technologies can assist the teaching–learning process while ensuring the emotional well-being of secondary school students. A model of Emotional Recognition (ER) was designed for use in a classroom. The model employs a custom code, recorded videos, and images to identify faces, follow action units (AUs), and classify the students’ emotions displayed on screen. We then analysed the classified emotions according to the academic year, subject, and moment in the lesson. The results revealed a range of emotions in the classroom, both pleasant and unpleasant. We observed significant variations in the presence of certain emotions based on the beginning or end of the class, subject, and academic year, although no clear patterns emerged. Our discussion focuses on the relationship between emotions, academic performance, and sustainability. We recommend that future research prioritise the study of how teachers can use ER-based tools to improve both the well-being and performance of students.
    Áreas temáticas: Arquitetura e urbanismo Arquitetura, urbanismo e design Biodiversidade Biotecnología Building and construction Ciências agrárias i Computer networks and communications Computer science (miscellaneous) Education Energy engineering and power technology Enfermagem Engenharias i Engenharias ii Engenharias iii Ensino Environmental science (miscellaneous) Environmental sciences Environmental studies Geociências Geografía Geography, planning and development Green & sustainable science & technology Hardware and architecture Historia Interdisciplinar Management, monitoring, policy and law Medicina i Renewable energy, sustainability and the environment Zootecnia / recursos pesqueiros
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: ramon.palau@urv.cat
    Identificador del autor: 0000-0002-9843-3116
    Fecha de alta del registro: 2024-02-10
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/2071-1050/16/2/916
    Referencia al articulo segun fuente origial: Sustainability. 16 (2):
    Referencia de l'ítem segons les normes APA: Llurba C; Fretes G; Palau R (2024). Classroom Emotion Monitoring Based on Image Processing. Sustainability, 16(2), -. DOI: 10.3390/su16020916
    URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
    DOI del artículo: 10.3390/su16020916
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2024
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computer Networks and Communications,Education,Energy Engineering and Power Technology,Environmental Science (Miscellaneous),Environmental Sciences,Environmental Studies,Geography, Planning and Development,Green & Sustainable Science & Technology,Hardware and Architecture,Management, Monitoring, Policy and Law,Renewable Energy, Sustainabil
    Academic performance
    Emotion recognition
    Image processing
    Py-feat
    Secondary school students
    Students’ emotions
    Students’ well-being
    Arquitetura e urbanismo
    Arquitetura, urbanismo e design
    Biodiversidade
    Biotecnología
    Building and construction
    Ciências agrárias i
    Computer networks and communications
    Computer science (miscellaneous)
    Education
    Energy engineering and power technology
    Enfermagem
    Engenharias i
    Engenharias ii
    Engenharias iii
    Ensino
    Environmental science (miscellaneous)
    Environmental sciences
    Environmental studies
    Geociências
    Geografía
    Geography, planning and development
    Green & sustainable science & technology
    Hardware and architecture
    Historia
    Interdisciplinar
    Management, monitoring, policy and law
    Medicina i
    Renewable energy, sustainability and the environment
    Zootecnia / recursos pesqueiros
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