Some practical solutions you can use to help break through the initial overwhelm of having a lot of qualitative data to analyse, and get close to your data in record time.

The more data you have, the less likely it is you'll have the time to analyse all of it, especially with looming university deadlines in mind.

Compared with the GameCube version I enjoyed so much growing up, the New Horizons villagers seem less ‘genuine’. How does that balance affect your relationship with the characters? To find out, I completed some qualitative analysis.

The constant comparison method isn't restricted to Grounded Theory, and is a frequently applied approach to analysing and exploring qualitative data. It's essentially a really common-sense approach for examining qualitative data...

There are many different ways of coding qualitative data. Two of the most frequently mentioned are in vivo coding, in which participants’ actual words become codes while the researcher is coding, and a priori coding, in which the researcher has defined codes before beginning to analyze the data.

Sometimes content analysis is applied as a blanket term for looking to see what qualitative data is about (ie the content) and from there many approaches can be applied.

Qualitative researchers often try to understand the world by listening to how people talk, but it can be really revealing to look at not just what people say, but how. This is how discourse analysis (DA) can be used to examine qualitative data.

Many forms of grounded theory adopt a variant of open, axial and selective coding as their key steps in qualitative analysis. Usually these follow the description in Strauss and Corbin (1990), but others such as Glaser (1978) defined similar procedures

How do you actually analyse qualitative data? How do you start to digest a rich qualitative data set, and begin to pull together the strands that will show insights from the data? If you've ever written a book report in high school, some of the basic concepts are

There are large number of options for free and open-source software tools for qualitative data analysis. They can help you explore, analyse and manage qualitative data, but each have their own strengths and weaknesses.

There are a huge variety of ways we can analyse qualitative data, but perhaps the most commonly applied is known as Thematic Analysis. This is an approach classically described by Braun and Clarke (2006) but is straightforward and intuitive