AI for Thematic Analysis in Qualitative Research - Claire Moran

Описание: This session demonstrates how generative AI can be used to support thematic analysis while preserving the interpretive depth central to qualitative research. Participants will learn to design structured prompts that work with their analytic approach, use AI to assist with organising and mapping data, and distinguish between surface‑level pattern detection and deeper thematic interpretation.

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The emphasis is on using AI as an organisational and thinking partner — one that scaffolds the analytic process but does not replace the researcher’s critical and reflexive engagement. Practical demonstrations will show how AI can help generate provisional code lists, group data extracts, and support theme development, all under the researcher’s methodological guidance.

Participants will also apply a short decision checklist to ensure AI is used in ways that align with their research paradigm, epistemological stance, and the type of thematic analysis they are conducting. Potential risks, such as over‑simplification, loss of nuance, and epistemic dominance, will be discussed alongside strategies for preserving participant voice, rigour, and reflexivity.

By the end of the session, participants will have a clear, adaptable workflow for integrating AI into thematic analysis ethically and effectively.