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Find the story in your data

For many kinds of research, the main work of interpretation cannot be done until most of the data has been collected and analysed. For others, the data already exists (in the form of archival documents or literary texts, for example), and the work of interpreting it begins much earlier in the research process.

Whatever kind of research you are doing, there comes a moment when your head is full of ideas that have emerged from your analysis. Ideally, you will have written them down as they came to you. Now you have to convert that mass of material and ideas into a written text that will make sense to a reader, and do justice to your findings.

Which aspects will you focus on? What's important, what's interesting?

How will you decide?

It is useful to remind yourself what the task of writing up research is all about:

…the major task of writing [about our research] involves working out how to make contextually grounded theoretical points that are viewed as a contribution by the relevant professional community of readers.

That is, in your thesis you need to make points that are

  • contextually grounded (based on your data)
  • theoretical (related to relevant theory)
  • viewed as a contribution by the relevant professional community of readers (they add something to the current body of research or theory)

These points must fit into a framework that makes a coherent story of your findings.

What have you learnt from your data?

The first step is to clarify for yourself what you know now, as a result of your research. David Evans and Paul Gruba (2002, p.112) remind us that our minds continue to work on problems when we aren't thinking about them consciously. So it is worth finding out what conclusions your brain has reached while you were collecting and analysing your data. Here are two techniques you can use:

  1. Evans and Gruba suggest you do this:
    1. Write down all the things you know now that you didn't know when you started the research. Use a single sentence for each item. (At this point, don't worry about whether they relate to your aims or research questions)
    2. Sort the sentences into groups. Give each group a heading. Now check the headings against your research question(s). Do all the headings relate to the research question(s)? Do the questions need refining?
    3. Use these groups and headings to make a plan of the points you want to make in your discussion.
  2. Making lists works well for some people, but not for others. Another technique you can use to unlock your unconscious thought processes is freewriting.
  3. Freewriting on a topic means taking a fresh piece of paper and writing anything that comes into your head on that topic for a limited time-it must be in whole sentences and you must not stop. If you have nothing to write, write 'I have nothing to write'. This is writing to think. It has no value in itself except as a step to something else.

    Try doing it now.

    Write about your data for 5 minutes. You don't have to show what you write to anyone.

    Stop. Now read over what you've written. Have you learnt anything? Is there anything there you want to develop further?

Three kinds of story: macrostructures for a thesis

The way you present the analysis and interpretation of your data can be thought of as a story (this is adapted from Silverman 2005, pp. 242-43):

  • the hypothesis story (this is the standard framework for theses in the empirical sciences)
    • state your hypotheses
    • test them
    • discuss the implications
  • the analytic story (a common framework for theses in the social sciences)
    • What are the key concepts I have used in this study?
    • How do my 'findings' shed light on these concepts and, through them, on the substantive topics I studied?
    • What, therefore, has become of my original research problem and the literature regarding it?
  • the mystery story (Silverman comments that this framework is the most difficult to use successfully)
    • starts from empirical examples
    • develops the questions by discussing them
    • gradually leads the reader to interpretations of the material and to more general implications of the results

The big picture

The challenge for every thesis writer is to hold the detail of the data in focus without losing sight of the big picture of the research. This is why reporting data analysis is not enough; you need to

  • establish the connections between the patterns that emerge from your analysis and your research questions
  • relate those connections to the existing research and theory

in order to make clear your contribution to knowledge in the field.

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