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

Kent, Carmel; Rechavi, A. and Rafaeli, S. (2019). Networked Learning Analytics: A Theoretically Informed Methodology for Analytics of Collaborative Learning. In: Kali, Y.; Baram-Tsabary, A. and Schejter, A. eds. Learning In a Networked Society. Computer-Supported Collaborative Learning Series, 17. Cham: Springer, pp. 145–175.



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.

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  • Item ORO ID
  • 80192
  • Item Type
  • Book Section
  • ISBN
  • 3-030-14609-X, 978-3-030-14609-2
  • 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
  • Academic Unit or School
  • Faculty of Wellbeing, Education and Language Studies (WELS)
  • Copyright Holders
  • © 2019 Springer Nature Switzerland AG
  • Depositing User
  • Carmel Kent