AI and Computer Assistance in Qualitative Software: The Case of QDA Miner

Location: Jagiellonian University, Collegium Wróblewskiego

In recent years, the integration of generative AI features into qualitative analysis software has sparked both excitement and concern within the research community. However, the implementation of artificial intelligence and machine learning (ML) techniques in qualitative software is not a recent phenomenon. As early as 2007, QDA Miner 3.0 introduced the first AI-driven feature with the Query-by-Example search tool. This was followed in 2011 with QDA Miner 4.0, which incorporated Cluster Extraction and the Code Similarity search features—both leveraging machine learning to help qualitative researchers manage larger datasets and achieve faster, more consistent coding.

This workshop will explore how these AI features were thoughtfully designed to assist rather than replace the researcher, aligning with methodological traditions in qualitative research. More advanced automation techniques, aimed at reducing manual intervention, were intentionally reserved for QDA Miner’s companion software, WordStat. This design approach recognizes the various epistemological positions and the varied needs of researchers working with different data types and research objectives.

During the session, we will:

• Demonstrate existing AI features in QDA Miner and discuss their practical applications.
• Discuss how these tools balance automation and researcher control, respecting qualitative traditions.
• Preview upcoming AI-driven features currently under development for QDA Miner.
• Engage participants in a dialogue about the role of AI in qualitative software, addressing opportunities, limitations, and ethical considerations.