Streamlining Field Note Analysis: Leveraging GPT for Further Insights

• In Event: Qualitative Research and AI

Abstract

Field notes are essential for assessing the transferability of findings, guiding future data collection, and supporting ongoing analysis. However, their interpretation presents significant challenges.
This study offers a preliminary investigation into the potential of generative AI, to assist researchers with the interpretation of field data through a deductive coding approach.
With a relatively low agreement accuracy of 29.95% between a researcher and generative AI, we investigated the reasons for the disagreements. We found that GPT-4o can replicate some aspects of human coding, provide insights on specific codes, and challenge researchers' interpretations with counter-responses. The study demonstrates that while achieving complete trustworthiness with AI remains challenging, appropriate validation can effectively leverage AI to enhance qualitative analysis.

Authors

• Umar Shehzad, Utah State University

• Saríah López-Fierro, Utah State University

• Alireza Zandi, Utah State University

• Jody E. Clarke-Midura, Utah State University

• Mimi M. Recker, Utah State University