Blog Posts

Making Qualitative Research Happen provides a rigorous, methodologically grounded framework for the entire research lifecycle. This text moves beyond basic software tutorials to examine the critical intersections of theory, ethics, and digital tools. By addressing contemporary challenges—including AI integration, the decolonisation of methodology, and the nuances of CAQDAS—it serves as a foundational resource for researchers committed to achieving transparency and depth in th

On the 17th March I was invited to give a keynote at the MAXDAYS 2026 Europe virtual conference. I was grateful for the opportunity to talk about the relationship between methodology and technology, which is something I’ve spent much of my career thinking about . Here's what I said. You can also watch the recording here. Image Source: Bart Fish & Power Tools of AI / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/ To get straight to the point,

On Thursday 21st August 2025 I was invited to give the plenary talk to open a debate about Generative-AI for qualitative research at the Summer School in Social Science Methods at the Università della Svizzera italiana in Lugano, Switzerland. All week I'd been teaching my course on Integrating AI into the qualitative workflow, and had been enjoying the discussions with my students who were engaged, thoughtful, and prepared to critically engage with when AI is not appropriate

Christina Silver, 25th July 2025 (posted simultaneously on the CAQDAS blog) I got a bunch of interesting comments on my LinkedIn post asking who'd be interested in what I think about AI in qualitative research, and why, so here goes.... There are 6 sections. I could actually write a post the length of this one on each topic, but instead I’ve prioritised some “headlines” as I currently see them under these headings: Background: from whence my thoughts derive What I think of

Last week I spoke at the AQR's ’s second AI Hackathon having been asked to talk about getting the most out of GenAI tools for qualitative analysis. View my slides here Following Mike Stevens' talk that mapped what's changed in the AI for research space in 2025, I began putting Generative-AI capabilities for qualitative data analysis (QDA) in context by commenting on “traditional-AI” tools, such as topic modelling, sentiment analysis, automatic document classification, and so