It’s been a long time coming, but the latest version of Quirkos is now available, and as always it’s a free update for everyone, released simultaneously on Mac, Windows and Linux with all the new goodies! The focus of this update has been speed. You won’t see a lot of visible differences in the software, but behind the scenes we have rewritten a lot of Quirkos to make sure it copes better with large qualitative sources and

We've now got more than 70 posts on the official Quirkos blog, on lots of different aspects of qualitative research and using Quirkos in different fields. But it's now getting a bit difficult to navigate, so I wanted to do a quick recap with the 10 most popular articles, based on the number of hits over the last two years.   Tools for critical appraisal of qualitative research A review of tools that can be used to assess the quality of

  I’ve written a little about this before, but I really love participant diaries! In qualitative research, you are often trying to understand the lives, experiences and motivations of other people. Through methods like interviews and focus groups, you can get a one-off insight into people’s own descriptions of themselves. If you want to measure change over a period, you need to schedule a series of meetings, and each of which

Once you’ve coded, explored and analysed your qualitative data, it’s time to share it with the world. For students, the first step will be supervisors, for researchers it might be peers or the wider research community, and for market research firms, it will be their clients. Regardless of who the end user of your research is, Quirkos offers a lot of different ways to get your hard earned coding out into the real world.   Share

I've mentioned before how the general public are very quantitatively literate: we are used to dealing with news containing graphs, percentages, growth rates, and big numbers, and they are common enough that people rarely have trouble engaging with them.   In many fields of studies this is also true for researchers and those who use evidence professionally. They become accustomed to p-values, common statistical tests, and plot charts. Lots