Training pre-service teachers to deal with cyberbullying: Collective intelligence as a mode of learning

Bautista Alcaine, Pablo (Universidad de Zaragoza) ; Vicente Sánchez, Eva (Universidad de Zaragoza) ; Orejudo Hernández, Santos (Universidad de Zaragoza) ; Cano Escoriaza, Jacobo (Universidad de Zaragoza)

Resumen: Collective intelligence is a theoretical construct that focuses on results stemming from a workgroup dealing with complex tasks. Our goal was to determine whether a group of pre-service teachers presented with a case of adolescent cyberbullying could improve their capacity for action. The experiment was carried out with 221 pre-service teachers at the University of Zaragoza, Spain, and using Collective Learning. The cyberbullying case we presented could be resolved via a series of questions in successive phases. Results showed an increase in learning throughout all phases, with a remarkable difference between the average score of the first phase and the last one. By the end of the experiment, the answers which had been most highly valued by the total set of participants turned out to be of considerable quality. We discuss the potential of collective intelligence as a tool for innovating and improving teaching-learning processes in university training.

Idioma: Inglés

DOI: 10.1016/j.compedu.2024.105123

Año: 2024

Publicado en: Computers and Education 220 (2024), 105123 [14 pp.]
ISSN: 0360-1315

Financiación: info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130302B-C21

Tipo y forma: Article (Published version)

Área (Departamento): Área Didáctica y Organiz. Esc. (Dpto. Ciencias de la Educación)
Área (Departamento): Área Psicolog.Evolut.Educac (Dpto. Psicología y Sociología)