Articles producció científica> Pedagogia

Gender-sensitive sentiment analysis for estimating the emotional climate in online teacher education

  • Datos identificativos

    Identificador: imarina:9244658
    Autores:
    Usart, MireiaGrimalt-Alvaro, CarmeIglesias-Estrade, Adolf Maria
    Resumen:
    Teacher training takes place in distance education to a large extent. Within these contexts, trainers should make use of all the information available to adapt and refine their instructional methods during the training process. Sentiment analysis (SA) can give immediate feedback of the emotions expressed and help in the training process, although it has been used infrequently in educational settings, slow to assess, and bound to interpretative issues, such as gender bias. This research aimed to design and evaluate a SA gender-sensitive method as a proxy to characterize the emotional climate of teacher trainees in an online course. An explanatory case study with mixed methods was implemented among students of the Interuniversity Master of Educational Technologies (N = 48). Participants' messages were analyzed and correlated with learning achievement and, along with a qualitative study of participants' satisfaction with the Master's degree, to validate the effectiveness of the method. Results show that sentiment expression cannot be used to exactly predict participants' achievement, but it can guide trainers to foresee how participants will broadly act in a learning task and, in consequence, use SA results for tuning and improving the quality of the guidance during the course. Gender differences found in our study support gendered patterns related to the emotional climate, with female participants posting more negative messages than their counterparts. Last but not least, the design of well-adjusted teaching-learning sequences with appropriate scaffolding can contribute to building a positive climate in the online learning environment.
  • Otros:

    Autor según el artículo: Usart, Mireia; Grimalt-Alvaro, Carme; Iglesias-Estrade, Adolf Maria
    Departamento: Pedagogia
    Autor/es de la URV: Grimalt Alvaro, Maria del Carme / Usart Rodríguez, Mireia
    Palabras clave: Virtual learning environments Teacher training Sentiment analysis Online learning Gender Formative assessment Feedback Experience Attitudes
    Resumen: Teacher training takes place in distance education to a large extent. Within these contexts, trainers should make use of all the information available to adapt and refine their instructional methods during the training process. Sentiment analysis (SA) can give immediate feedback of the emotions expressed and help in the training process, although it has been used infrequently in educational settings, slow to assess, and bound to interpretative issues, such as gender bias. This research aimed to design and evaluate a SA gender-sensitive method as a proxy to characterize the emotional climate of teacher trainees in an online course. An explanatory case study with mixed methods was implemented among students of the Interuniversity Master of Educational Technologies (N = 48). Participants' messages were analyzed and correlated with learning achievement and, along with a qualitative study of participants' satisfaction with the Master's degree, to validate the effectiveness of the method. Results show that sentiment expression cannot be used to exactly predict participants' achievement, but it can guide trainers to foresee how participants will broadly act in a learning task and, in consequence, use SA results for tuning and improving the quality of the guidance during the course. Gender differences found in our study support gendered patterns related to the emotional climate, with female participants posting more negative messages than their counterparts. Last but not least, the design of well-adjusted teaching-learning sequences with appropriate scaffolding can contribute to building a positive climate in the online learning environment.
    Áreas temáticas: Psicología Pedagogical & educational research Información y documentación Education & educational research Education Educació E-learning Developmental and educational psychology Communication Ciencias sociales
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: mireia.usart@urv.cat carme.grimalt@urv.cat
    Identificador del autor: 0000-0003-4372-9312 0000-0002-5314-7706
    Fecha de alta del registro: 2024-08-10
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://link.springer.com/article/10.1007/s10984-022-09405-1
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Learning Environments Research. 26 (1): 77-96
    Referencia de l'ítem segons les normes APA: Usart, Mireia; Grimalt-Alvaro, Carme; Iglesias-Estrade, Adolf Maria (2023). Gender-sensitive sentiment analysis for estimating the emotional climate in online teacher education. Learning Environments Research, 26(1), 77-96. DOI: 10.1007/s10984-022-09405-1
    DOI del artículo: 10.1007/s10984-022-09405-1
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2023
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Communication,Developmental and Educational Psychology,E-Learning,Education,Education & Educational Research
    Virtual learning environments
    Teacher training
    Sentiment analysis
    Online learning
    Gender
    Formative assessment
    Feedback
    Experience
    Attitudes
    Psicología
    Pedagogical & educational research
    Información y documentación
    Education & educational research
    Education
    Educació
    E-learning
    Developmental and educational psychology
    Communication
    Ciencias sociales
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