Workshop 3: Generative AI for Qualitative Research

We begin by demystifying Large Language Models (LLMs) - understanding how they work, their intricacies, and the ethical considerations they raise. This foundational knowledge will empower you to make informed decisions about using generative AI tools and critically evaluate their outcomes. Building on this groundwork, you’ll gain practical experience with two tools:

• MAXQDA, a leading qualitative data analysis (QDA) software that integrates generative AI into its robust framework.
• QInsights, a cutting-edge tool designed specifically for generative AI-powered qualitative research.

Through guided workflows tailored to various methodological frameworks, you’ll explore how to use these tools effectively. The workflows will be customized to the projects and descriptions participants submit before the workshop, ensuring a personalized learning experience that addresses your specific research needs.

This workshop is ideal for researchers who:

• Have collected or started analysing qualitative data and are ready to dive deeper.
• Are curious about incorporating AI into their research, whether as beginners or experienced users.

It is not mandatory to have prior experience with MAXQDA. However, completing the recommended video tutorials before the workshop will greatly enhance your learning experience and allow you to get the most out of the sessions. After your registration is confirmed and your participation in the workshop is accepted, we will provide you with links to the recommended tutorials.

By the end of the workshop, you will:

• Gain a clear understanding of how AI can transform qualitative research and data analysis.
• Learn to use AI tools to enhance research efficiency, rigor, and integrity.
• Navigate ethical considerations in the use of AI for research.
• Apply AI tools directly to your current and future qualitative research projects.

Participants will receive comprehensive materials to support continued exploration after the workshop. You are encouraged to bring your own data for practical, hands-on sessions tailored to your research needs.
This workshop is a must for anyone looking to integrate AI effectively and responsibly into their qualitative research practices, combining theoretical insights with practical application to help you take your research to the next level.

• Adduesselam, M. S. (2023). Qualitative data analysis in the age of artificial general intelligence. Journal of Advanced Research in Qualitative Data Analysis, 1(1), 10-25.
• Anis, S. and French L. A. (2023), Efficient, Explicatory, and Equitable: Why Qualitative Researchers Should Embrace AI, but Cautiously. Business and Society, volume 62( 6). https://journals.sagepub.com/doi/full/10.1177/00076503231163286
• Christou, P. (2023a). How to Use Artificial Intelligence (AI) as a Resource, Methodological and Analysis Tool in Qualitative Research? The Qualitative Report, 28(7), 1968-1980. https://doi.org/10.46743/2160-3715/2023.6406
• Friese, S. (2025). Generative AI: A Catalyst for Paradigmatic Change in Qualitative Data Analysis. In Christou A. Prokopis (Ed.) Artificial Intelligence (AI) in Social Research, Chapter 7. CAB International, Wallingford, UK.
• Kuckartz, U. & Rädiker, S. (2024, November). Integrating artificial intelligence (AI) in qualitative content analysis. https://qca-method.net/documents/kuckartz-raediker-2024-integrating-ai-inqualitative-content-analysis.pdf
• Thominet, L., Amorim, J., Acosta, K., & Sohan, V. K. (2024). Role Play: Conversational Roles as a Framework for Reflexive Practice in AI-Assisted Qualitative Research. Journal of Technical Writing and Communication, 0(0). https://doi.org/10.1177/00472816241260044
• Resnik, D.B., Hosseini, M. The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool. AI Ethics (2024). https://doi.org/10.1007/s43681-024-00493-8

In order to receive credits for active participation (for details see the information concerning „Course certificate“ under „Registration“), you are required to submit a report by September 15^th, 2025 to Susanne.friese@qeludra.com. Please include the following:

1. Project Overview
Provide a brief description of your project, including its aim and research questions.
2. Methodology Description
Outline the methodology you are using or plan to use. Address the following questions:
• Who are your respondents? What type of data are you collecting?
• Add interview guide if appropriate.
• What stage are you at in your data collection process?
• Are the data transcribed and anonymized?
• Have you addressed the potential use of AI in your confidentiality agreements? Refer to the provided templates:
• AI-Focused Confidentiality and Consent Agreement Template
• Vorlage: Vertraulichkeitserklärung für Forschungsteilnehmende bei KI Nutzung
3. Data Analysis Plan and Challenges
• Describe in detail how you are analysing or planning to analyse your data.
• Highlight any current challenges you are facing.
4. Proficiency with AI Tools
• Share your level of experience with AI tools (it’s fine to state if you’re a beginner).
• If you’ve been using generative AI:
• Describe what you’ve used it for and your experiences.
• Identify tasks where AI has been useful or not useful.
• Highlight any challenges you faced and questions you’d like to address during the course.
5. If you are using qualitative data analysis (QDA) software:
• Submit your project file if sharing is permitted.
• If sharing the entire project is not possible, export your code system in Excel format and share only the code system.

This report will help us tailor the workshop to your needs and ensure a productive learning experience. In addition, the report will serve as the foundation for reflecting on and further developing your individual data analysis approach during the workshop. No additional proof of performance is required beyond this preparation; instead, the goal is for you to leave the workshop with a concrete analysis strategy tailored to your project.

Dr. Susanne Friese is a distinguished expert in qualitative research, renowned for her extensive experience and contributions to the field. With over 30 years of active involvement in the evolution of computer-assisted qualitative data analysis software (QDAS), she has become a leading figure in the qualitative research community and an emerging thought leader in the integration of AI into qualitative methodologies. Dr. Friese is the author of the landmark book on conducting qualitative analysis with ATLAS.ti and has contributed chapters to numerous influential publications, including the SAGE handbook: Current Developments in Grounded Theory. Her latest project, co-edited with David Morgan, focuses on the use of AI in qualitative research and is set to be published by SAGE in 2026. As an educator, Dr. Friese combines her deep domain expertise with a passion for teaching, offering practical insights and guidance to researchers navigating the intersection of traditional qualitative methods and AI technologies.

• Friese, S. and Morgan, D. (eds.) (2026). Qualitative Data Analysis with Artificial Intelligence: Theory, Methods and Practice. SAGE publications. Forthcoming June 2026.
• Friese, S. (2026). Qualitative content analysis in the context of generative artificial intelligence. In Margrit Schreier and Nicole Weydmann (Eds.) Handbook of Qualitative Content Analysis, chapter 43. Edward Elgar Publishing Ltd. Forthcoming 2026.
• Friese, S. (2025). Generative AI: A Catalyst for Paradigmatic Change in Qualitative Data Analysis. In Christou A. Prokopis (Ed.) Artificial Intelligence (AI) in Social Research, Chapter 7. CAB International, Wallingford, UK. Forthcoming in March 2025.
• Friese, S. (2025). Computergestützte Analyse: Auswertung narrativer Interviews mit QDAS und KI. In Pentzold, Christian; Bischof, Andreas & Heise, Nele (Hrsg.) Praxis Grounded Theory. Theoriegenerierendes empirisches Forschen in medienbezogenen Lebenswelten. Ein Lehr- und Arbeitsbuch, 2ed. Wiesbaden: Springer VS, forthcoming in 2025.
• Friese, S. and Unterpertinger, E. (2025). Using the CAQDAS Software ATLAS.ti with the Grounded Theory Method: A Step-by-Step Guide. In Gregory Hadley and Antony Bryant (eds.) Grounded Theory in Action: Voices from the Field. Edward Elgar, forthcoming in 2025.
• Friese, S. (2023). How QDAS (Qualitative Data Analysis Software) can support the analysis of social media brand communities and consumer engagement. In George Rosollatos (ed). Advances in Brand Semiotics & Discourse Analysis, 91-116. Wilmington, DC, Vernon Press.
• Friese, S. (2022). Role and Impact of CAQDAS Software for Designs in Qualitative Research. In Uwe Flick (ed). The SAGE Handbook of Qualitative Research Design. Chapter 19. London: SAGE.
• Friese, S. (2021). Grounded Theory Analysis and CAQDAS: A happy pairing or remodeling GT to QDA? In: Antony Bryant and Kathy Charmaz (eds.). The SAGE Handbook of Current Developments in Grounded Theory, 282-313. London: SAGE.