AI and Qualitative Data Analysis in Education Research: Familiarization and Exploration of Interview Transcripts Enhanced with ChatGPT

Abstract

This study investigates the efficacy of ChatGPT in enhancing the initial phases of Qualitative Data Analysis (QDA), particularly in data familiarization and exploration in education research. Analyzing interview data from young adults in Lima, Peru, the research explores how AI can complement traditional methods by speeding up the generation of relevant statements, case-cluster summaries, and initial codes. Despite ChatGPT’s ability to rapidly process data, the study highlights the need for human oversight to ensure the specificity and relevance of AI-generated outputs. Furthermore, while AI can enhance the reflexivity of researchers by providing alternative analyses, it does not substitute the nuanced judgment required in qualitative research. The findings suggest that while AI can significantly aid the research process, it must be used judiciously, with careful consideration of its limitations and potential biases. This research contributes to a deeper understanding of AI’s role in QDA, proposing that it be used as a supportive tool in the initial phases rather than a replacement for human expertise in education research.