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Networked Learning Analytics: A Theoretically Informed Methodology for Analytics of Collaborative Learning

  • Carmel Kent
  • Amit Rechavi
  • Sheizaf Rafaeli
Chapter
Part of the Computer-Supported Collaborative Learning Series book series (CULS, volume 17)

Abstract

Online social learning is a prevalent pedagogical tool, enabling learners across all ages and cultures to learn together. Educators, policy-makers, and international organizations such as the Organization for Economic Cooperation and Development (OECD) stress the need to assess collaborative learning systematically. However, the systematic assessment of large online groups’ collaboration is still in its infancy. In this chapter, we suggest perceiving social learning through the lens of interaction networks between learners and content. Based on well-accepted learning theories, we demonstrate the harnessing of digital traces of online discussions to the assessment of social learning, at both the individual and the group levels. Practically, our contribution is to suggest a network analysis point of view for the assessment of the performance and design of learning communities. Our proposed methodology can be used by instructors to open-up the black box of collaborative learning, to be able to equip learners with twenty-first-century skill-set.

Keywords

Learning analytics Collaborative learning Online social learning Assessment Interaction networks Digital traces Online discussions Assessment of social learning Network analysis Assessment of learning communities 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Carmel Kent
    • 1
  • Amit Rechavi
    • 2
  • Sheizaf Rafaeli
    • 3
  1. 1.Institute of EducationUniversity College LondonLondonUK
  2. 2.Department of Business AdministrationRuppin Academic CenterMichmoretIsrael
  3. 3.Samuel Neaman Institute, Technion, and Faculty of ManagementUniversity of HaifaHaifaIsrael

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