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.
| Original language | English |
|---|---|
| Pages (from-to) | 77-80 |
| Number of pages | 4 |
| Journal | CEUR Workshop Proceedings |
| Volume | 4268 |
| State | Published - 2026 |
| Event | 3rd International Workshop on Generative AI and Learning Analytics, 2nd Workshop on Hybrid Intelligence in Learning Analytics, and 1st International Workshop on Advancing AI Literacy with Learning Analytics, LAK-WS 2026 - Bergen, Norway Duration: 27 Apr 2026 → 1 May 2026 |
Bibliographical note
Publisher Copyright:© 2026 Copyright for this paper by its authors.
Keywords
- Generative AI
- generativity theory
- learning analytics
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