Here for NVivo? Let’s talk analysis first.

I’ve had the pleasure of engaging with lovely people on twitter, especially over the last few months. So, for my first post of the year, I wanted to share a little about myself. Namely, what I have learned through my time as a certified NVivo trainer.

I have been a researcher for over 15 years and got my doctorate in 2011. Towards the end of my PhD, I was lucky enough to teach research methods. At the same time, I started working as a trainer for NVivo (a qualitative research software program). I’ve continued to research and train in NVivo over the years, and I can honestly say I love my work.

In the first few years of NVivo training, I thought that people were primarily coming to the workshops or one-on-one sessions to learn how to use the software, so did they. This was only partly correct. I soon realised that people were coming to workshops not only to learn how to use NVivo, but also because they wanted to understand how to analyse data.

Some people think that the software does this for you (or that the software should do this for you), but fortunately (yes, I said fortunately) it doesn’t. It assists with the analysis and can help you to see the data from different perspectives, but ultimately the researcher needs to ‘do’ the analysis.

So I find that a decent chunk of my time goes into helping researchers understand how to approach the analysis of their data. While this should be based on their methodology, often the researchers that see me, don’t know what methodological approach they are using.

The students easiest to work with, and the ones who get the most out of my time, are those who are honest about what they don’t know and are willing to be reflexive. These students are the ones that learn the fastest, and in my experience, ultimately produce the best work. I once had a student who said they had no idea why they were conducting interviews. We worked through the research question and sub-questions and were able to see how the interviews added value. I’ve also had students tell me they know what they are doing, but clearly have no idea. It is difficult to help them make the connections and guide them with analysis when they don’t understand the fundamentals.

My role also involves taking researchers through the basics of understanding qualitative research. One of the key things I have learnt from my decade of training is that beginners in qualitative research often need simplified language, and need help understanding what to actually “do”. I try to avoid using jargon or buzz words. I hear students and fellow researchers tell me they need to look at their data “In-depth”, “find the meaning”, or find the “emerging themes”, but have no idea how to do this. This terminology has little meaning for them when staring at a piece of paper with a transcript on it for the first time. I like to focus on how researchers can do these things. This often means helping them clarify the research question, identify their methodology, and then move into techniques for analysis.

With my job, care needs to be taken to ensure researchers new to qualitative methods are taught with simplicity and an attitude of inclusivity. My fear is that if it is too complex to start, they will be scared off. This could mean that researchers either continue with qualitative work but do it badly, or get scared off completely and start to be critical of it. This will simply re-enforce widely held criticisms of qualitative work.

I do occasionally think I might be over-simplifying things. However, as years of attending qualitative interest groups with senior and experienced researchers have taught me, there is no one “right” approach. It all depends on the research question and to some extent the researcher. My job is to ensure the process of “doing” the analysis is accessible and understood.

This of course, is half of what I do. The other half is all about showing how NVivo can help researchers with analysis. I find that people pick up how to use NVivo fairly quickly. Once the process of how to analyse data is understood, NVivo is simple to explain. There are tools that help researchers with the thinking and analysis process. There are some great tools within NVivo that help researchers see their data from a different perspective, find patterns, and even “check” to see if their assumptions are correct. I’ll be posting throughout the year on some of my favourite NVivo features, and how they can be used. As well as other caqdas software II’ve committed to learning.

I’m interested to hear your thoughts and experience with qualitative research. Looking forward to positive and interesting conversations and discussions in 2020.