One of the questions I’m often asked by researchers and course organisers is ‘When is the best time to be trained in NVivo?’ Is it during your research skills training? Is it at the start of a new project? Is it part-way through a project, when you’ve collected your data and want to move on to analysis?
NVivo is designed to be the environment in which you carry out your research from start to finish, so that your NVivo project contains your whole research project, from initial, tentative thoughts to thoroughly developed arguments. If you take this approach, you clearly need training in NVivo as early as possible – preferably right at the beginning of your research, or even before you begin.
However, although NVivo can be used in this way, it doesn’t have to be. Many people prefer to write and develop research ideas in other ways (when it comes to creativity there’s a lot to be said for the humble pencil and paper). Research projects aren’t always neat and easily contained – they might be off-shoots of or integrated with other projects, or they might develop through interactions of several people. For most people, NVivo remains firmly in the category of Computer-Assisted Qualitative Data Analysis Software, to be used primarily or solely for data analysis.
If you’re not planning to start using NVivo until you’ve collected your data, you may wish to delay training until that point. A big advantage of this is that you can learn and experiment using your own data with training focused on your specific analytical requirements, as well as practised immediately instead of languishing in the back of your mind for several months. The moment new users see the software applied to their own data is the moment it all makes sense.
On the other hand, it can be helpful to gain an understanding of NVivo early on in the life of your research project in order to envisage and plan your analysis – particularly important when working in a team. Not all research has an easily defined moment when analysis begins, as developing research questions, collecting data and analysing them may occur simultaneously. There are also some features of NVivo that require early preparation such as pre-formatting interview schedules and transcripts. Knowing what your analysis tool can and can’t deal with is essential to deciding what you’re going to put into it – and you might find that the pre-analysis functions are useful as well.
The most effective way to learn NVivo is to split your training. As early as possible – for students this might be before you even know what you’re going to research – take an introductory course to get to know what the software looks like and what it can do. At this point don’t worry too much about learning how to do things, unless you want to use NVivo to develop your project from scratch. This might be enough for you – when the time comes to start using the program you may find sufficient assistance in the help files and online tutorials. If not, when your research is beginning to take shape and you have some data, attend an advanced workshop or arrange a practical, focused session for yourself and/or your research group to learn how to apply NVivo relevantly and effectively.
Explore and experiment. Happy learning!