Università della Svizzera italiana
Summer School in Social Sciences Methods
Università della Svizzera italiana
Summer School in Social Sciences Methods
6-21 August 2026

Integrating AI in the Qualitative Research Workflow Appropriately

Lecturer: Christina Silver

Modality: In presence

Week 2: 17-21 August 2026

 

Workshop contents and objectives

This course provides PhD students and researchers with a comprehensive understanding of the contemporary landscape of Artificial Intelligence (AI) in qualitative research. Grounded by ethical considerations and current methodological debates,  the course considers the principles and practices of using these technologies throughout the analytic workflow. A range of tools designed to facilitate qualitative research that harness AI in different ways are introduced and participants have the opportunity to experiment with a selection of them, using sample data and their own research materials, as appropriate.

The emphasis of the course is to critically reflect on the potential role and appropriate use of AI-driven tools in qualitative research, and to compare their utility with other tools and human-driven processes. Ethical issues are central, along with how to document the use of tools (whether AI or otherwise) transparently. This includes best practices for integrating AI with human interpretation in qualitative studies, and consideration of when the use of AI is not appropriate. We also discuss the future of qualitative research in the Generative-AI world, reflecting on the impact on methods of these technologies.

Participants will leave the course with a clear understanding of the implications of employing AI in qualitative studies and with practical experience of several tools. The qualitative AI space is evolving quickly, so the tools focused on during this course are subject to change, depending on what is available at the time of the course, but will include tools from across the qualitative-AI space. Students will have free access to all the tools used for the purpose of the course, and will be provided access ahead of the first sessions.

 

Workshop design

A mix of lectures, demonstrations and discussions, group work, practical exercises with AI tools, individual work with research data, student presentations, and other in-class activities. Students will spend approximately 50% of the course time on practical exercises with research data.

 

Detailed lecture plan (daily schedule)

Day 1 – Orientation to AI in the Qualitative Research Workflow
  • The history of Computer-Assisted Qualitative Data AnalysiS (CAQDAS)
  • Genres of computer-assistance in the context of qualitative methodologies
  • Types of AI tool for qualitative research: what do they actually do?
  • The Generative-AI explosion and its impact on qualitative research practice
  • Balancing human interpretation with computer-assistance
  • The ethics of using AI for qualitative research
  • Independent work: Student planning for own projects
  • Student reflections: why consider the use of AI for qualitative research?
Day 2 – AI for Qualitative research Design, Reviewing Literature and Data Collection
  • Integrating the use of AI into the qualitative workflow responsibly
  • Using Generative-AI for ideation
  • Reviewing literature with the assistance of AI
  • Independent work: Student work on own research data
  • Student reflections: how might the use of AI impact critical reading and thinking?
  • AI-assisted data collection – when is this appropriate?
  • Student experiences: being on the other side of AI-assisted data collection
Day 3 – Using AI for qualitative data analysis, part 1
  • Tools for AI-assisted qualitative analysis
  • Generative-AI capabilities in qualitative analysis
  • Planning for the use of AI in a qualitative analysis
  • AI-driven transcription – what we gain and what we lose
  • Data familiarisation with and without the use of AI
  • Independent work: Student work on own research data
  • Student reflections: role of AI to explore and conceptualise qualitative data
Day 4 – Using AI for qualitative data analysis, part 2
  • Qualitative coding with and without the use of AI
  • AI-assisted querying to find patterns
  • Independent work: Student work on own research data
  • Reflection and reflexivity when using AI in qualitative analysis
  • Student reflections: is it really my work if I use AI?
  • Keeping the human in the loop: AI as assistant not replacement
  • Student presentations: what ethical use of AI looks like in my project
Day 5 – Working qualitatively in the world of AI
  • Transparency and rigour in the AI-assisted qualitative workflow
  • Aligning the use of AI with the values of qualitative research
  • Considering the use of AI across the methodological spectrum
  • Is AI just another tool?
  • Communicating the use of AI in qualitative research projects
  • Student presentations: integrating AI into my project – research plans
  • Final reflections: where do we go from here?

 

Course materials

All materials will be provided online.

Prerequisites

None.

What our participants appreciated most

"The workshop met my expectations since it provided the ethical and methods reasoning attached to using IA in qualitative research (or not) as well as an overview of some ofthe tools available. It was well balanced between workshops and "hands on" activities and theoretical inputs/presentation of the instructor. The instructor was great in creating an open discussion in the group, giving some of her views but above all fostering each participants’ own reflective positions. Thank you for the engagement and willingness to share knowledge on this complex topic."

"I'm very happy | attended this class. | think it helped.me answer some of the questions | had surrounding the concerns we might have as researchers. l'm very satisfied with the professors approach, we not only saw its use and methods but she was very open to reflect on what this might mean to our research. So thank you!"

Christina Silver

Department of Sociology, University of Surrey, UK

Christina is Associate Professor (Teaching) in the Department of Sociology at the University of Surrey, UK. She is Director of the CAQDAS Networking Project, which provides information, advice and training in a range of digital tools designed to facilitate the analysis of qualitative data. She is also co-founder of Qualitative Data Analysis Services (QDAS), providing customised consultancy services for individuals and groups. Christina’s interests are in the relationship between technology and methodology (including AI) and the teaching of computer-assisted analysis, and she has published many articles, blogs and textbooks on these topics. She has experience in using all of the leading CAQDAS packages for a range of project types, across academic disciplines, and in applied, government and commercial contexts.

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