Human Interpretation, AI Support: A Workflow for Thematic Analysis using Large Language Models in Co-design

Authors

  • Crystal Silver 1st Department of Sociological and Psychological Sciences, Abertay University, Dundee, United Kingdom
  • Diane Morrow 1st Department of Sociological and Psychological Sciences, Abertay University, Dundee, United Kingdom
  • Stefano De Paoli 1st Department of Sociological and Psychological Sciences, Abertay University, Dundee, United Kingdom

DOI:

https://doi.org/10.23726/cij.2026.1827

Keywords:

co-design, thematic analysis, LLM, qualitative analysis

Abstract

This methodological note describes a workflow for thematic analysis in which Large Language Models (LLMs) are used to support specific analytic tasks on Co-creation and Co-design user data. LLMs are advanced artificial intelligence systems trained on large volumes of textual data that can generate articulated textual responses when prompted. The primary benefit of this workflow is the streamlining of time-intensive analytic tasks, enabling Co-creation and Co-design teams to maintain methodological rigour in qualitative analysis while working under tight time constraints.

References

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Published

2026-09-16

How to Cite

Silver, C., Morrow, D., & De Paoli, S. (2026). Human Interpretation, AI Support: A Workflow for Thematic Analysis using Large Language Models in Co-design. CERN IdeaSquare Journal of Experimental Innovation, 10(2), 141–143. https://doi.org/10.23726/cij.2026.1827

Issue

Section

Part 3: Co-Creating with Machines

Categories