Skip to main content

Research Repository

Advanced Search

The use of Generative AI in qualitative analysis: Inductive thematic analysis with ChatGPT

Perkins, Mike; Roe, Jasper

Authors

Mike Perkins



Abstract

This article describes a methodological innovation in the analysis of qualitative data using Generative AI (GenAI) tools alongside traditional research methodologies to conduct inductive thematic analysis. The case study employs an integrative method that comprises two researchers conducting simultaneous analysis: one using manual and traditional research approaches to coding, analysis, and interpretation, and the other conducting the same analysis but with the support and assistance of GenAI tools, namely, the premium version of ChatGPT (GPT-4).

The key strengths of this approach include the enhanced capacity for data processing and theme identification offered by GenAI, along with the nuanced understanding and interpretative depth provided by human analysis. This synergy allows for a richer and more complex understanding of the themes present in the data. The challenges encountered include managing the inconsistencies and hallucinations of GenAI outputs and the necessity for rigorous validation processes to maintain research validity. The findings indicate a complementary relationship between GenAI and human researchers, where the use of such tools can expedite the analytical process without diminishing the essential role of the researcher’s expertise and critical engagement.

Citation

Perkins, M., & Roe, J. (2024). The use of Generative AI in qualitative analysis: Inductive thematic analysis with ChatGPT. Journal of Applied Learning & Teaching, 7(1), 390-395. https://doi.org/10.37074/jalt.2024.7.1.22

Journal Article Type Article
Acceptance Date Feb 1, 2024
Online Publication Date Mar 5, 2024
Publication Date Jan 4, 2024
Deposit Date Jan 29, 2025
Journal Journal of Applied Learning & Teaching
Print ISSN 2591-801X
Peer Reviewed Peer Reviewed
Volume 7
Issue 1
Pages 390-395
DOI https://doi.org/10.37074/jalt.2024.7.1.22
Public URL https://durham-repository.worktribe.com/output/3355768