Demystifying qualitative data analysis
It’s that time of year when many of you are in the thick of analysing qualitative data. If you’re feeling a bit lost as to what’s involved, be assured that you’re likely not the only one! I’ve been busy facilitating NVivo courses recently and have been asked a lot of questions that relate more widely to qualitative analysis. Often people feel like they’re asking “stupid” questions, but I firmly believe it’s only a stupid question if you don’t ask it! In case you’ve been too shy to ask – here’s a round up of some of the common questions beginners ask me about qualitative data analysis.
What is coding?
Coding is a central process in all qualitative methodologies, although researchers use the term in different ways. At a very simple level, codes are just labels. The process of coding involves sifting through your data and identifying topics, ideas, concepts, terms, phrases or keywords. Each piece of text is marked with a label, which means that you can easily retrieve all the text that relates to that label – think of a recipe index that helps you easily find the cake recipes versus the soup recipes. The text that you code could be single words, phrases, sentences or paragraphs. Note that the purpose of being able to retrieve this data is not necessarily so that you can “count it”, but to allow you to identify patterns and interpret ideas.
What’s the difference between a code and a theme?
Codes are defined above – they’re usually a smaller unit of analysis. Themes generally represent bigger picture findings that emerge from your coding. Braun and Clarke define a theme by saying it "captures something important about the data in relation to the research question, and represents some level of patterned response or meaning within the data set" (2006, p. 10). In their book Successful Qualitative Research (2013), Braun and Clarke use an analogy of a brick wall where a code is an individual brick, while a theme is the actual wall. So – think of codes as the building blocks of your larger themes.
What’s a “coding framework” and why do I need one?
A coding framework is a list of all the codes or labels that you’ll use in your analysis. It’s sometimes referred to by other names such as a codebook or analysis framework.
Having a clear coding framework is important as codes are often quite abstract/fuzzy concepts. If you don’t define codes clearly, later down the track you may either completely forget what they mean, or your understanding may shift which may introduce inconsistent coding. They’re particularly important if you’re working in a qualitative team – if multiple people are coding on a project, they all need to have the exact same understanding of the codes being used – otherwise the analysis will just be a disaster!
If you’re new to the idea of a coding framework, you might like to read DeCuir-Gunby, Marshall and McCulloch’s (2010) article on developing and using a codebook for the analysis of interview data.
Do I have to use software for my qualitative analysis?
Definitely not – while I generally recommend the use of qualitative software such as NVivo, it’s not necessarily the best choice for every project. If you have a very small project for example, it may not be worth the time investment to learn something like NVivo, and you should be able to manage the data using highlighter pens or cutting out chunks of text with a good old-fashioned pair of scissors. It’s also worth considering that you don’t need to use specialist qualitative software. On a smaller project, Microsoft Word or Excel can be surprisingly effective.
Just a note though – if you’re considering not using software because you’ve heard from others that it’s difficult to use or distances you from the data, have a chat to other researchers who do use it. There are a lot of misconceptions out there about the use of software in qualitative research, so don’t believe the first person that tells you not to use it!
If you enjoyed the above tips, you might find our upcoming Research Accelerator useful. This is a time-efficient and cost-effective way for you to access research training – if you can't attend the event live, you'll receive on-demand access so that you can watch the sessions at your convenience.