Qualitative Data Analysis using MAXQDA: from coding to AI-assisted analysis

The fees for the Qualitative Data Analysis using MAXQDA: from coding to AI-assisted analysis short course are:

A certificate of attendance for those completing the course will be provided, endorsed by the University of Essex Department of Sociology & Criminology. 

Day 1: Principles of Qualitative Analysis and MAXQDA Fundamentals

The first session introduces the principles of qualitative analysis, including an overview of common analytic approaches such as thematic analysis and content analysis, and a discussion of how different logics of inquiry shape analytic choices. Participants will learn how to set up a MAXQDA project, import and prepare data, document decisions, and begin coding. Key functions such as memos, document variables, and visual tools will be demonstrated to show how analysis can be enhanced through these tactics.

Day 2: AI Assist and considerations when using generative AI tools

The second session focuses on MAXQDA’s ‘AI Assist’ feature and on the emerging role of generative AI in qualitative analysis. The session will provide guided demonstrations of what the AI tools can and cannot do and will discuss the practical and ethical considerations raised by automated support – such as transparency, data handling, and the risks of over-relying on machine-generated interpretations. Participants will have the opportunity to test AI Assist and reflect on how it might complement, challenge, or reshape their usual analytic practices.

By the end of the course, participants will be able to: 

• Describe key approaches to qualitative analysis, including thematic analysis and qualitative content analysis, and recognise how different analytical logics shape decisions throughout the research process.
• Use MAXQDA to undertake the early stages of qualitative analysis, including data import, familiarisation, initial coding, memoing, and iterative development of analytic ideas.
• Apply document variables and organisational tools to structure, compare, and explore qualitative material in relation to relevant attributes or case characteristics.
• Critically evaluate the role of generative AI tools in qualitative research concerns about data security, the uncertainty of how AI arrives at its suggestions, the risk of unreliable interpretations, and the ways these tools can change what work the researcher does.
• Assess the specific strengths and limitations of MAXQDA’s ‘AI Assist’ feature, and understand how to integrate (or intentionally resist) AI-supported outputs within a qualitative analysis.
• Develop greater confidence in their own qualitative data literacy, including the ability to judge when automated analytic support is appropriate, when human interpretation is indispensable, and how to combine both without compromising analytic quality.

This short course is open to anyone who works with, or intends to work with, qualitative data – whether in academic, public-sector, commercial, or third-sector settings. It is designed to be accessible to participants with varying levels of prior experience, including those who are new to digital qualitative analysis. 

Prerequisites:
The course is designed as a hands-on learning environment. No prior experience with MAXQDA or digital qualitative analysis is required for Day 1; those wishing to attend Day 2 only will need a basic working knowledge of MAXQDA (e.g., how to navigate the interface, import data, and undertake simple coding). Trial licences will be provided.

This course will be delivered online. Participants will need access to a laptop or desktop computer capable of running MAXQDA. Trial licences will be provided in advance of the course. Participants are responsible for downloading and installing MAXQDA before the first session. Those using University of Essex-managed devices (or other institution-managed machines) should ensure they have the necessary admin permissions or request IT support ahead of the course, as installation may require approval and cannot be completed during the session. 

A stable internet connection, access to Zoom, and the ability to share their screen during practical tasks are also recommended to support participation.

Session recordings will be made available to participants for a limited period after each session. 

Dr. Katy Wheeler is a Senior Lecturer in Sociology at The University of Essex. She has extensive experience of conducting interviews and analysing qualitative data from interviews, focus groups, surveys and documents. She is the co-author of the popular SAGE textbook How to do Qualitative Interviewing (2022) and is a MAXQDA Professional Trainer. Her research interests are in the fields of sustainability and consumption, and she has published widely within leading academic journals and two monographs, Fair-Trade and the Citizen-Consumer: Shopping for Justice (Palgrave, 2012) and Recycling and Consumption Work: Social and moral economies (Palgrave, 2015). She is currently pursuing a project on sustainability education.

Find out more about Dr Katy Wheeler by viewing her staff profile or LinkedIn page.