A Mixed Method for Assessing the Reliability of Shared Knowledge in Mass Collaborative Learning Community

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The recent trends in open, informal, and collective education have gradually been shaping an innovative approach to learning called “mass collaborative learning” where large and limitless number of scattered but interested people (with different backgrounds and levels of knowledge) join a networked community aiming to learn new things interactively. Even though the potential benefits of mass collaborative learning for learners are enormous, the process is by nature prone to be harmed by sharing unhealthy materials within the community. In order to minimize the dissemination of disinformation and promote the quality of shared contents in mass collaborative learning communities, this study, as a contribution in this context, proposes a mixed method that can help involved learners to assess the reliability and quality of shared knowledge or information through a multi-user and multilevel evaluation approach. Preliminary findings of this research work are discussed.

Original languageEnglish
Title of host publicationTechnological Innovation for Applied AI Systems - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Proceedings
EditorsLuis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito
Place of PublicationCham
PublisherSpringer
Pages24-36
Number of pages13
ISBN (Electronic)978-3-030-78288-7
ISBN (Print)978-3-030-78287-0
DOIs
Publication statusPublished - 1 Jul 2021
Event12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 - Costa de Caparica and Online, Portugal
Duration: 7 Jul 20219 Jul 2021

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume626
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
Country/TerritoryPortugal
CityCosta de Caparica and Online
Period7/07/219/07/21

Keywords

  • Assessment
  • Content
  • Information
  • Knowledge
  • Mass Collaborative Learning (MCL)
  • Mixed method
  • Reliability

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