1. Qualitative Analysis Martyn Hammersley
Emeritus Professor of Educational and Social Research, FELS
Personal website:
CREET Workshop, March 2016

2. Distinctive features of qualitative analysis
Unstructured data: fieldnotes, audio- or video- recordings, photographs, documents, artefacts.
The research usually starts from an interest in some topic, setting, or type of people, and tentative questions about these, rather than from specific hypotheses to test.
The task is to develop a conceptual framework – a set of categories or a form of interpretation that eventually allows inference from the data to conclusions about evolving research questions.

3. The production of data
Data are not simply ‘collected’. In one way or another, they are produced.
At the very least they have to be ‘worked’ into a form that allows analysis. In particular:
- Fieldnotes ‘jotted’ in the field must be written up in full later.
- Audio- or video-recordings must usually be transcribed.
These are time-consuming activities. And what is required will depend upon the sort of analysis that is to be done.

4. There is no recipe for analysis
While the process can be described in broad terms, and advice given about how to approach it and what strategies may be useful, analyzing qualitative data cannot be specified in terms of a set of procedures.
What is required in the analysis will vary somewhat depending on the nature of the data being used, the research problems that are of interest, and the assumptions made about the phenomena being investigated and how they can be understood.

5. Analysis: an uncertain process
The formulation and reformulation of research questions
Research design as a continual process, often involving revised plans as regards what data to collect and how to analyse it.
Much of the time there is uncertainty about what is being investigated, what the product will be, and what its value might be.
Advice: Don’t panic!

6. Where do we get concepts from?
Do they emerge out of the data?
Should we take over participants’ terms, or commonsense terms more generally?
Should concepts be brought in from the research literature? If so, does this mean adopting a whole framework developed by a theorist?
How can we determine what are and are not fruitful concepts?

7. Emergence
The idea that the concepts needed for the analysis emerge out of the data captures an important aspect of the process, but is at the same time fundamentally misleading.
Concepts emerge through the interrogation of the data, and the simultaneous interrogation of existing commonsense and theoretical concepts drawn from the literature.

8. Building up resources
It is usually not possible, or at least not desirable, simply to impose some set of concepts borrowed from the literature.
However, it is important to familiarise yourself with a range of theoretical ideas, both those developed in other relevant or related empirical studies and those in widely used theoretical approaches.
These are tools or resources that you may be able to use in your analysis.

9. What is analysis? Two basic aspects:
Developing interpretations of the data – new concepts or refinements of existing ones – that contribute towards answering research questions; or serve to clarify, improve or reformulate those questions.
Checking the reliability of assumptions, interpretations, and conclusions through searching for and examining evidence.
I will focus here on the first of these aspects.

10. Variation in the form of analysis
There are clearly differences relating to the kind of data employed:
a) Textual data: fieldnotes, documents, audio-recordings
b) Images and artefacts: drawings/ paintings, maps, photographs, video-recordings.
I will concentrate here on the analysis of text.

11. Discourse analysis – Theme analysis
Discourse analysis: concerned with discursive patterns and practices, with these perhaps seen as constitutive of social phenomena.
Theme analysis is concerned with identifying patterns among the orientations of actors, their actions and environments. This is characteristic of most ethnography, grounded theorising (Glaser and Strauss 1969), and of a great deal of qualitative research more generally.

12. Discourse analysis
Involves detailed attention to specific textual features, with a view to understanding their mutual relations, functions, etc.
Often it requires identifying sociolinguistic strategies, or the framework of assumptions, that generates particular kinds of social practice or institution: viewing these as textual constructions
Tends often to focus on one particular type or source of data: documents; recordings of naturally occurring talk; or, sometimes, interview data.

13. Some types of discourse analysis
Narrative analysis
Conversation analysis
Discursive psychology
Linguistic discourse analysis
Critical discourse analysis
Bakhtinian analysis
Post-structuralist discourse analysis
(See Hammersley 2003; Wetherell et al 2001a and b)

14. Divisions within discourse analysis
Some versions of DA treat discursive strategies as objects in the world that have material effects, and that are themselves products of socio-cultural and material factors, such as Power, Capitalism, etc.
Other versions treat discursive practices as constituting the phenomena to which they refer; and the analytic task is to document those practices.
Finally, there are versions that treat all discourse as constituting the world that it refers to, including the accounts of social scientists themselves.
Which stance is adopted will profoundly affect the process of analysis.

15. Theme analysis
Seeks to describe particular patterns of belief or action, and to explain why they occur, or why they result in particular outcomes; usually with a view to identifying general patterns.
May involve integrating data of multiple kinds (observations, interviews, documents, etc).

16. Taking account of data production
While the task in theme analysis is to answer substantive research questions, it is important to remember how the sorts of data being employed were produced, and to think about what the implications of this may be for how we should interpret them.
For example, there could be a difference between what people say ‘spontaneously’ and what they say in response to an interview question; or between what is said in a group interview versus in an individual interview.

17. Stages of theme analysis
‘Coding the data’: generating categories ‘from’ the data. Initially, involves backgrounding research questions and trying to find what is ‘in’ the data, particularly as regards the perspectives and practices of participants, distinctive features of these and of the settings in which they operate, and so on.
Constant comparative method: comparing data placed in the same conceptual category, in order to clarify and develop ideas about the categories and how they are interrelated.
Checking interpretations and conclusions.

18. Generating categories
Suspend as far as possible your initial ideas about your research topic.
Carefully read the data line by line, looking out for anything that is surprising, puzzling, interesting, etc.
Look out for unusual words and phrases, or for repetition, since these can sometimes indicate issues that are important for the people speaking.
Categories may be banal or speculative.
Data may be put in multiple categories or none.
sa,mpling. Analytic memos

19. A data analysis activity
The best way to learn more about qualitative data analysis is to try it out! The data provided are historical. While you know nothing of the background to how they were collected, this is no barrier. The task is analyse these data with a view to documenting the perspective of the headteacher: about his role, his school, and education more generally.

20. Critical Questions
How do we know that the informant is telling the truth? How do we know what he says corresponds to what he does?
How do we know that the attitudes he expresses in the interview are stable over time and across contexts, rather than simply being a product of the interview situation, including the particular questions asked?
What counts as well-grounded versus speculative interpretation? Can this distinction be defended?

21. Constant comparative method
Examine the data you have assigned to a particular category: Does it all belong in one category? Are there any subcategories? Can the meaning of the category be clarified on the basis of the data?
Are there links amongst particular categories? Do these suggest a kind of model or story that can be developed to make sense of the data, and of the phenomena you are interested in understanding?

22. Storing and retrieving data
In order to carry out the constant comparative method, it is necessary to employ a retrieval system that will allow you to access all of the data you have coded under a particular category.
In the past this was done by photocopying data sheets and putting them into folders.
But today a word processing program or specialist software is generally used.

23. CAQDAS Computer assisted qualitative data analysis.
Does not do the analysis, but facilitates the coding, storage, and retrieval of data for analysis.
Is it worth it? Yes if dealing with a large amount of data and using theme analysis.
Which program? (see, for example, Silver and Lewins 2014)

24. Conclusion
Qualitative research today takes a variety of forms, some of them sharply discrepant.
However, the basic process is often some version of theme analysis, of the kind we have just attempted, some sort of discourse analysis, or a combination of the two.
What is involved is essentially an interpretive process, but it requires conceptual clarity and empirical testing.

25. Bibliography
Glaser, B. and Strauss, A. (1967) The Discovery of Grounded Theory, Chicago, Aldine.
Hammersley, M. (2003) Discourse Analysis: bibliographical guide. Available at: bib.pdf
Hammersley, M. and Atkinson, P. (2007) Ethnography: principles in practice, London, Routledge.
Silver, C. and Lewins, A. (2014) Using Qualitative Software: a step-by-step guide, Second edition, London, Sage.
Wetherell, M., Taylor, S. and Yates, S. (eds.) (2001a) Discourse as Data, London, Sage; and (2001b) Discourse Theory and Practice - A Reader, London, Sage.
You will find a bibliographical guide to qualitative data analysis under the heading ‘other resources’ on my website: