Preparing data sources for qualitative analysis

  How do you actually analyse qualitative data? How do you turn the results from your research into findings that can answer your research questions? Analysing qualitative data requires drawing meaning from it, and getting to some higher level of interpretation than reading the data at face value. This is the process that can seem difficult for newcomers to qualitative techniques, or those used to quantitative methods where the

If you are doing inductive coding or grounded theory, your coding framework can get complex, quickly. If you have hundreds of codes, they can become difficult to mangage which can slow down your coding - the part of your analysis you want as efficient and effective as possible so you can focus on identifying bigger trends.   Fortunately, this is what qualitative analysis software is best at - and whether you are using Nvivo, Atlas.ti or

  It’s easy to get seduced by the excitement of primary data collection, and plan your qualitative research around methods that give you rich data from face-to-face contact with participants. But some research questions may be better illustrated or even mostly answered by analysis of existing documents.   This ‘desk-based’ research often doesn’t seem as fun, but can provide a very important wider context that

Quirkos is now 3 years old! To celebrate, we’re taking a break from our regular programming of qualitative method posts to remind everyone why Quirkos is the best qualitative analysis software around...   1. All the colours! Obviously I’m going to start with the most important features first. Some qualitative analysis software restricts you to only 8 colours when customising your themes. Quirkos lets you choose from 16

  Qualitative software used to need you to format text files in very specific ways before they could be imported. These days the software is much more capable and means you can import nearly any kind of text data in any kind of formatting, which allows for a lot more flexibility. However, that easy-going nature can let you get away with some pretty lazy habits. You’ll probably find your analysis (and even data collection and