Integrating AI in the Qualitative Research Workflow Appropriately

About

Workshop contents and objectives

This course provides PhD students with a comprehensive understanding of the landscape of Artificial Intelligence (AI) with respect to the qualitative research process, covering the principles, practices and ethics 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 students have the opportunity to experiment with a selection of them, using sample data and their own research materials, if appropriate.

The emphasis of the course is to critically reflect on the potential role and appropriate use of AI-driven tools in qualitative research. Ethical issues are central, along with how to document the use of AI transparently, and best practices for integrating AI with human interpretation in qualitative studies. We also discuss the future of qualitative research in the generative-AI world, reflecting on the impact on methods of these technologies.

Students 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 their own 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 rigor 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?

**The Summer School cannot grant credits. We only deliver a Certificate of Participation, i.e. we certify your attendance.**

If you consider using Summer School workshops to obtain credits (ECTS), you will have to investigate at your home institution (contact the person/institute responsible for your degree) to find out whether they recognise the Summer School, how many credits can be earned from a workshop/course with roughly 35 hours of teaching, no graded work, and no exams.

Make sure to investigate this matter before registering if this is important to you

Course leader

Dr Christina Silver is an Associate Professor (Teaching) and a Director of CAQDAS Networking Project based at the University of Surrey, UK

Target group

graduate students, doctoral researchers, early career researchers

Fee info