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Learning Analytics for GenAI Augmented Collaborative and Dialogic Educational Approaches: A Generativity Theory Perspective

Research output: Contribution to journal › Conference article › peer-review

Abstract

Generative AI (GenAI) is increasingly used to support collaborative, discursive, and dialogic pedagogy. We explore ways to use learning analytics (LA) to make these hybrid human-GenAI practices visible and actionable. Borrowing from management and information systems research, we use a generativity theory perspective and treat GenAI-augmented classrooms as generative socio-technical systems. Using Thomas and Tee’s seven components (architecture, community, governance, fit, combinatorial innovation, outcomes, feedback) to define categories of learning analytics, we demonstrate how generativity-informed LA can help distinguish generative from degenerative patterns of human-GenAI collaboration.

Bibliographical note

Publisher Copyright:
© 2026 Copyright for this paper by its authors.

Keywords

  • Generative AI
  • generativity theory
  • learning analytics

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