From Manual Coding to Machine Insight: Comparing Traditional Thematic Analysis With ChatGPT and NVivo in Qualitative Research
Copyright: © 2026
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Pages: 28
DOI: 10.4018/979-8-3373-7640-0.ch010
Abstract
This chapter examines the methodological shift in qualitative research from traditional manual thematic analysis to technology-assisted approaches using NVivo and AI-supported tools such as ChatGPT. Manual coding enables interpretive depth and reflexivity but is time-consuming and difficult to scale. NVivo strengthens analytical rigor through systematic coding and transparency while remaining dependent on researcher interpretation. ChatGPT supports exploratory analysis through summarization, preliminary coding, and reflexive questioning, yet raises methodological, epistemological, and ethical concerns related to validity, contextual sensitivity, bias, and data privacy. Rather than treating these approaches as competing methods, the chapter proposes a hybrid, reflexive framework that integrates human interpretive authority with digital and AI-based support tools, offering practical guidance for responsible and rigorous qualitative analysis.
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