Writing spaces are one of the most valuable features of dedicated CAQDAS packages. But I often see projects that make little use of them. Here’s why they are so potentially powerful.
Access to analytic insights
I've previously written about how using CAQDAS packages is all about access. As soon as you start using a dedicated CAQDAS package the increased access to your materials is obvious - all project materials are right there to view and work with as soon as you open the CAQDAS project file. Once you start conceptualizing what is interesting and meaningful in the data your access to all these ideas is easy, quick, and reliable - however they are represented in the software. The same can be true of your all-important reflections on every aspect of the analysis. But you have to use the available writing spaces in the best way to reap their full potential.
Insights get lost if left in your head
We all have important analytic reflections when working with our research materials. This is true in every phase of a research project - from problem formulation and research design, through reviewing the literature, collecting and transcribing data, setting-up an analytic framework, exploring, conceptualising and retrieving data, to visualizing, interrogating and reporting our findings. These insights during moments of contact with the data need to be captured in order to be built upon. If you leave them in your heads they will be lost. You might expect to remember them, and we remember some of them. But the detailed nuances of our thoughts will inevitably be lost if we don't capture them when we have them.
Writing reflections on paper does record them, but they are hard to reliably find when needed unless they are particularly well structured and systematic – but who has time for that when noting down a fleeting insight? Storing reflections electronically significantly increases our access to them. We can search for the key terms we know we wrote - even if we can't remember exactly where. This is of course true whatever software we use for writing.
Linking our reflections to what promoted them is powerful
There are many dedicated note-taking programs with specifically designed writing tools – three popular programs are Scrivener, Evernote and Onenote. But potentially much more powerful is to capture analytic reflections in the same software that is being used for an analysis because our reflections can be linked to the data that prompted them. This means we can integrate our reflections with our data, and then retrieve both together, continue reflecting, and start building an account.
From long experience I cannot overstate the value of doing this.
Several writing spaces to choose from
Each CAQDAS package has different writing tools but most provide several writing spaces (see Chapters 3 and 10 of Silver & Lewins 2014 for an overview and discussion). It is usually possible to select a segment of data - perhaps a sentence or paragraph in a textual transcript, a selection of a still image, or a clip in a video or audio file - and annotate it.
These writing spaces are similar to footnoting or commenting tools in word processing programs. But in CAQDAS packages they are automatically linked to the data that prompted them and can usually be viewed in several different ways, searched, and outputted alongside coded data.
In addition, dedicated CAQDAS programs have centralised memos in which anything can be written. Memos are larger spaces than annotations – they are essentially like word processing files that can be named and (usually) formatted. But they can also be linked to other components in the software project - for example data files, codes, segments of data. Or they can be left free-standing when their content is not directly related to any specific components of the software project. They can also be organised, for example, groups of memos can usually be created to differentiate different types of writing within each group. This is another way of integrating reflections with research materials.
Some packages - for example MAXQDA and NVivo - also provide tabular spaces linked to coded data in which summaries of those data can be written. These writing spaces can be harnessed for a range of purposes but the tabular view enables a matrix or grid of summarised data to be displayed, analysed and outputted.
Most CAQDAS packages also allow textual data files themselves to be edited. This means that data can be transcribed within the program and altered or appended as time goes by.
Treating your reflections as data
Integrating reflective writing with other aspects of research work is the core benefit of using CAQDAS writing spaces. Writing is always an analytic act - crafting a sentence or a paragraph makes us think about our arguments in a precise and concrete way, and what those arguments entail often ends up different from what we planned when we started writing. This is most pronounced when we treat our own reflective writing as data, which in some methodologies can take an analysis a whole step further. In a literature review I always say that a peer-reviewed article is text, just like an interview transcript is text, or a set of fieldnotes is text, so items of literature in a literature review can be treated as data. The same is true of the analytic reflections we capture when writing about our analysis.
Flexibility in choice
The range of writing spaces available in dedicated CAQDAS packages provides enormous flexibility for capturing thoughts as they occur throughout the iterative and emergent process of qualitative analysis. But the appropriateness of each writing space depends on the needs of individual analytic tasks.
Our forthcoming books on implementing the Five-Level QDA method in ATLAS.ti, MAXQDA and NVivo discuss the writing spaces in these programs, and illustrate how to choose appropriate writing tools for the needs of specific analytic tasks.
As well as writing spaces, most CAQDAS packages also include mapping or networking tools - spaces to visually represent ideas and their connection to one another. Similar to writing spaces, maps and networks can be harnessed to ensure analytic reflections are captured in the moment, but that's a subject for another time...