August 18, 2016
A new term is just beginning, so many lecturers, professors and TAs are looking at their teaching schedule for the next year. Some will be creating new courses, or revising existing modules, wondering what to include and what’s new. So why not include qualitative analysis software (also known as CAQDAS or QDA software)?
There’s a common misconception that software for qualitative research takes too long to teach, and
August 11, 2016
In the analysis of qualitative data, it can be easy to fall in the habit of creating either very descriptive, or very general theoretical codes. It’s often a good idea to take a step back, and examine your coding framework, challenging yourself to look at the data in a fresh way. There are some more suggestions for how to do this in a blog post article about turning coding strategies on their head. But while in Delhi recently to
August 4, 2016
Writing up and publishing research based on qualitative or mixed methods data is one thing, but most researchers will want to go beyond this, and engage with the wider public and decision makers. This requires a different style of publication, and a different style of writing. We are not talking about journal articles, funders reports, book chapters or a thesis here, but creating short, engaging and impactful summaries of your research that
July 28, 2016
Studies and surveys seem to show that the amount of qualitative research is growing, and that more and more people are using software to help with their qualitative analysis (Woods et al. 2015). However, these studies also highlight that users report problems with learning qualitative software, and that universities sometimes struggle to provide enough expertise to teach and troubleshoot them (Gibbs 2014).
Quirkos was specifically designed
July 21, 2016
A common question from newcomers to qualitative research is, what’s the right sample size? How many people do I need to have in my project to get a good answer for my research questions? For research based on quantitative data, there is usually a definitive answer: you can decide ahead of time what sample size is needed to gain a significant result for a particular test or method.
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