Pablo Bautista Alcaine , Eva Vicente Sánchez , Santos Orejudo Hernández , Jacobo Cano Escoriaza
{"title":"Training pre-service teachers to deal with cyberbullying: Collective intelligence as a mode of learning","authors":"Pablo Bautista Alcaine , Eva Vicente Sánchez , Santos Orejudo Hernández , Jacobo Cano Escoriaza","doi":"10.1016/j.compedu.2024.105123","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"220 ","pages":"Article 105123"},"PeriodicalIF":8.9000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0360131524001374/pdfft?md5=35bea9ed2e78f167e79994cbd9f86065&pid=1-s2.0-S0360131524001374-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360131524001374","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.