人机协作开展主题分析，AI辅助流程但解读权归研究者。
Human-AI Collaborative Inductive Thematic Analysis: AI Guided Analysis and Human Interpretive Authority
- 用定制AI工具按反思性分析原则自动引导编码与主题构建。
- 三名研究者在加纳教师教育数据上完成分析，流程透明可审计。
- 人类保留解释权，通过修改、删除等操作主导最终结论。
生成式人工智能在质性研究中的应用引发对分析实践与解释权威的关切。本研究考察研究人员如何使用专为归纳主题分析设计的ITA-GPT工具，该工具通过符合反思性主题分析与原文编码原则的结构化半自动化提示，支持熟悉资料、原话编码、动词化描述编码及主题发展。基于人机协同归纳主题分析（HACITA）框架，研究聚焦分析过程而非具体发现。三位经验丰富的质性研究者在加纳教师教育语境下的访谈资料上使用ITA-GPT进行分析。工具支持熟悉资料、原话在生编码、动词基描述编码与主题建构，同时确保文本溯源完整性、覆盖检查与可审计性。数据来源包括交互日志、AI生成表格、研究者修订、删改、插入、评论及反思备忘录。结果显示，ITA-GPT作为程序性支架，规范了分析流程并提升了透明度；但解释权威始终保留在人类研究者手中，其通过反复的修改、删除、拒绝、插入与评论等分析行动行使判断。研究证明，归纳主题分析可通过负责任的人机协作实现。
原文摘要 · Abstract (English)
The increasing use of generative artificial intelligence (GenAI) in qualitative research raises important questions about analytic practice and interpretive authority. This study examines how researchers interact with an Inductive Thematic Analysis GPT (ITA-GPT), a purpose-built AI tool designed to support inductive thematic analysis through structured, semi-automated prompts aligned with reflexive thematic analysis and verbatim coding principles. Guided by a Human-Artificial Intelligence Collaborative Inductive Thematic Analysis (HACITA) framework, the study focuses on analytic process rather than substantive findings. Three experienced qualitative researchers conducted ITA-GPT assisted analyses of interview transcripts from education research in the Ghanaian teacher education context. The tool supported familiarization, verbatim in vivo coding, gerund-based descriptive coding, and theme development, while enforcing trace to text integrity, coverage checks, and auditability. Data sources included interaction logs, AI-generated tables, researcher revisions, deletions, insertions, comments, and reflexive memos. Findings show that ITA-GPT functioned as a procedural scaffold that structured analytic workflow and enhanced transparency. However, interpretive authority remained with human researchers, who exercised judgment through recurrent analytic actions including modification, deletion, rejection, insertion, and commenting. The study demonstrates how inductive thematic analysis is enacted through responsible human AI collaboration.
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