Qualitative data analysis is a MethodSpace focus for April. One topic is the use of software to aid the process. See a post on Qual Data Analysis with Software, and the entire series of posts about qualitative data analysis.
You’ve collected documents and images, you have recordings and piles of interview transcripts…now what? NVivo and Atlas ti are popular software options for analyzing diverse types of data for qualitative research. Two important books that guide researchers who want to use these CAQDAS are newly updated. In this post Kristi Jackson, co-author with Pat Bazeley, discusses Qualitative Data Analysis with NVivo. In the next post we will hear from Susanne Friese, author of Qualitative Data Analysis with ATLAS.ti.
JS. The new edition of your book, Qualitative Data Analysis with NVivo, is now available. Can you tell us briefly what you’ve updated in the third edition?
KJ. Thanks to the use of a different font color in the book, we have visually differentiated universal instructions, Mac instructions, and Windows instructions, which means that Mac and Windows users can even be in the same training, following the same instructions. Our standardized reorganization of each chapter allows readers easily dip in and out of relevant sections seamlessly, allowing for a customized experience by each user. Finally, our addition of a Takeaways section at the end of each chapter includes – in addition to other material – practice questions that instructors can use in their qualitative methods courses. This is truly a completely reworked edition.
JS. What features of NVivo are difficult to learn and use, and how will your book help researchers to move forward with their data analysis?
KJ. I think it’s always been the Classification system and the Queries. We provide a lot of examples and ideas for both, really pushing the book beyond what you see in Help files. To augment the reader’s exploration of Queries, we include at least one Query in context in each chapter (providing a practical application without information overload). In addition, the chapter on Queries provides extensive visuals and comparisons among them. The goal is to provide different ways to access and think about Queries to help meet different learning styles.
JS. Can NVivo help qualitative researchers who are using Big Data? What about visual data, online data, media, physical artifacts?
KJ: I wouldn’t say the use of Big Data is one of the strengths of NVivo, but it is getting better all the time and I suspect NVivo will continue to allow for more functionality with Big Data. The really exciting development in the current version is the ease of analyzing on-line communication and interaction that occurs on Twitter, Facebook, YouTube, and even email! Users can very easily capture some social media data or link to it (subject, of course, to the restrictions established by the platform). Physical artifacts can be represented via video or images/pictures, along with descriptions of these artifacts such as their size, texture or location. So, even if you can’t import something into a Project, you can still find a mode to represent it (like a photograph) and further handle/analyze it.
JS. What research experience prepared you to develop this comprehensive guide?
KJ. Years and years of working with a lot of qualitative researchers in different contexts. Pat and I have a rare vantage by working in so many contexts, instead of a career of working in the same kind of data for a handful of institutions/organizations. I’ve always been a bit of an explorer and a risk-taker, so the journey has been full of diving into unfamiliar contexts and figuring things out! That’s one of the things I love about doing qualitative research and meeting qualitative researchers.
JS. You offer lots of steps and takeaways in your book. How do you suggest readers who are new to data analysis use them?
KJ. This is one of my favorite new parts of the book. The goal is to use a range of strategies for different kinds of learners. Some people want to explicitly hear our intended priorities in each chapter and others want to know what on-line resources they can access. For people who want to make sure they can apply the information in the chapter to their research, we provide a variety of questions that help them consider the tools and activities as they apply to their own context. There’s something for everyone in the Takeaways section at the end of each chapter.
JS. Is there anything else you would like to add about NVivo or the new edition of your book?
KJ. The book benefited greatly from another innovative aspect to this third edition: Seventeen NVivo Platinum Trainers around the world who reviewed our materials, provided suggestions, and pushed us to think about how we articulated various tools. We provide contact information for these contributors in the book and hope to work with all of them in the future!