Paper writing IV: analysing data

One of the trickiest areas for researchers working with data – either primary or secondary (data you have generated in ‘the field’, or that gleaned from texts etc) – is the analysis of that data. It can be a significant challenge to move from redescribing findings, observations or results, to showing the reader what these mean in the context of the argument that is being made, and the field into which the research fits. There are a few moves that need to be made in constructing an analysis, and these will be unpacked in this post.

Often, in empirical research, we make our contribution to knowledge in our field through the data we generate, and analyse. Especially in the social sciences, we take well-known theories and established methodologies and use these to look at new cases – adding incrementally to the body of knowledge in our field. Thus, analysis is a really important thing to get right: if all we do is describe our data, without indicating how it adds to knowledge in useful ways, what kind of contribution will we be making? How will our research really benefit peers and fellow researchers? After all, we don’t write papers just to get published. We conduct research and publish it so that our work can influence and shape the work of others, even in small ways. We write and publish to join a productive conversation about the research we are doing, and to connect our research with other research, and knowledge.

data 1

How to make a contribution to knowledge that really counts, though?

First things first, you can’t use all your data in one paper (or even in one thesis). You will need to choose the most relevant data and use it to further illustrate and consolidate your argument. But how do you make this choice – what data should you use, and why? The key tool used to make all the choices in a paper (or thesis) – from relevant literature, to methodology and methods, to data for analysis – is the argument you are making. You need to have, in one or two sentences, a very clear argument (sometimes referred to as a problem statement, or a main claim). In essence, whatever you call it, this is the central point of your paper. To make this point, succinctly and persuasively, you need to craft, section by section, support for this argument, so that you reader believes it to be valid and worth engaging with.

So, you have worked out your argument in succinct form, and have chosen relevant section of data that you feel best make or illustrate that argument. Now what? In the analysis section, you are making your data mean something quite specific: you are not just telling us what the data says (we can probably work that out from reading the quotes or excerpts you are including in the paper). To make meaning through analysis, you need to connect the specific with the general. By this I mean that your data is specific – to your research problem and your consequent choice of case study, or experiment, or archival search and so on. It tells us something about a small slice of the world. But, if all we did in our papers was describe small slices of the world, we would all be doing rather isolated or disconnected research. This would defeat the aim of research to build knowledge, and forge connections between fields, countries, studies and so on. Thus, we have to use our specific data to speak back to a more general or broader phenomenon or conversation.

data 2

The best, and most accepted way, of making meaning of your data is through theorising. To begin theorising your data, you need to start by asking yourself: What does this data mean? Are these meanings valid, and why? There are different kinds of theory, of course, and too many to go into here, but the main thing to consider in ‘theorising’ your data is that you need a point of reference against which to critically think about and discuss your data: you need to be able to connect the specifics of your data with a relevant general phenomenon, explanation, frame of reference, etc. You don’t necessarily need a big theory, like constructivism or social realism; you could simply have a few connected concepts, like ‘reflection’, ‘learning’ and ‘practice’ for example; but you do need a way of lifting your discussion out of the common sense, descriptive realm into the critical, analytical realm that shows that reader why and how the data support your argument, and add knowledge to your field.

Analysis and theorising data is an iterative process, whether you are working qualitatively or quantitatively. It can be difficult, confusing, and take time. This is par for the course: a strong, well-supported analysis should take time. Don’t worry if you can’t make the chosen data make sense in the first go: you may well need to read, and re-read your data, and write several drafts of this section of the paper (preferably with critical feedback) before you can be confident of your analysis. But don’t settle for the quick-fix, thin analysis that draft one might produce. Keep at it, and strive for a stronger, more influential contribution to your field. In the long run, it’ll be worth more to you,to your peers, and to your field.

The relationship between your research question and your argument

In the last post I wrote about research problems, and working out one that is the right size and shape for the scope of your project and level of study. In this post, I want to go a step further, and reflect a little on research questions, and the relationship between your research questions and your argument, and how to think about building your argument from the start.

In the workshops I have been facilitating with postgraduate students, all of whom are in the early stages of their projects, it has become clear that they have research problems, and questions, but are still struggling to a) pin these down into a manageable project the right shape and size for their level of study and time available; and b) separate (yet also connect) their research questions from their proposed argument.

(b) is a tricky thing to do early on in an MA or PhD – how do you really know what your argument is if you haven’t even done the research yet? I didn’t really know clearly what my argument actually was until I had finished the research – generated and analysed the data and considered what kinds of answers I had found in response to my research questions. But I had a sense of where I was trying to go. Working out a basic, ‘holding’ line of argument, and clear research questions that can reasonably be answered within your proposed timeframe and project scope is important to work on at this early stage for two main reasons.

Clear strategy and leadership solutionsThe first is so that you have a track to stay on when you start  reading, sharing your work, getting feedback and so on. Having a sense of the point of your project can limit the risks of  being pulled in different, potentially confusing directions, especially by reading and other people’s responses to your early thinking. This track may shift and change shape a bit, but you need to try and argue for what your proposal says you will argue for, so having a basic idea of what that argument could be, even if it starts off a little more fuzzy and ill-defined than it will be at the end, is helpful.

golden-threadThe second reason for creating a line of argument refers to the golden thread I have written about here. The questions you ask, and the argument that you propose as the answer to these questions, will guide the rest of the work you do on your thesis. You choose conceptual tools and build your theoryology in order to create a framework within which the argument can be built; you create a methodology, and choose a research design and methods in line with the theoryology and the research questions and proposed argument; and you analyse your data within the bounds set by these frameworks, so that you can actually refine and strengthen your overall argument. Thus, having a fairly clear sense of what this golden thread will comprise, and how it will pull through the different parts of your argument-building process, is also important.

Your argument is your original contribution to knowledge in your field, at PhD more than an MA level. It is the answer, more or less, to your research questions. It is the most important part of your research. You may well find that it is difficult to pin down in a concise few sentences, in your proposal or early on, exactly what your argument is. You may only find this emerging from your research as it progresses, and your thinking deepens. If you have followed a more linear research process (theory, then methods, then data, then analysis, then pulling it all together) you might find it easier to see your argument, your contribution, from early on. If you have started somewhere in the middle, with data, and are moving back and forth to build your theoryology and methodology around the data, your argument might be more fuzzy and difficult to pin down.

The point is, though, that your argument is there, and that pulling it out and jotting it down, at various points, is a useful exercise. Ask yourself: ‘What is the point of my research? What am I trying to say here?‘ Write down what you think the point of your research is on post-its and stick them up where you work. Rewrite these every few months and update them, even if the changes seem small.  A workshop I went to during my PhD encouraged us to come up with a haiku to capture the contribution we thought our research could be making (this was actually pretty spot on, and fun to do, so it’s worth a try). Keep a research journal, and make a point of checking in every few months on what claims you are making, and how these might be slowly becoming more refined, sharper, and possibly changed.

At the end of your research project, at whatever level you are working, and whether you are writing a paper, a book or a dissertation, you need to have found an answer to the question that started the research process in the first place. This answer is your argument, and it is what will make that contribution to your field, whether bigger or smaller. This is your voice, joining the conversation, and you want it to be a loud, and clear, and relevant as possible. Taking some time, throughout your research process, to make notes on what that argument is shaping up to be is a useful way of keeping yourself on track with your research aims, and spinning that golden thread as you go.