Try these books first
We recommend that first you read Discovery, in a relaxed way, for an introduction to the ideas underpinning grounded theory. Then read Doing Grounded Theory more intentionally.
Start out ‘right’
It will make your life as a GT researcher much easier if you apply the basic principles of Grounded Theory to your study from the start. This entails making sure that the Grounded Theory method is right for you and your study, and that it will do the job that you want it to. Once you have identified your substantive area of interest and/or population, an early test of whether GT is the right method for you, is to ask yourself ‘Do I want to know:
- The main concern of my participants?
- How my participants resolve or process that concern?’
A ‘yes’ is encouraging, a ‘no’ is a warning!
‘Getting started’ also means making sure that you are able to collect your data in a way that is consistent with grounded theory and that from the beginning, you focus on conceptual analysis, rather than simply coding data.
For help getting started, consider our online and face-to-face Introductory Workshops and individual online sessions. The understanding you gain from these workshops/sessions can also inform your research proposal and your application for ethical review. For longer term support, consider a mentoring relationship.
Data collection tips
A grounded theory may use qualitative data, quantitative data (e.g. Glaser 1964 and Glaser 2008) or a mixture of the two. Thus data types include but are not restricted to:
- observations of the substantive area itself and activities occurring within the substantive area 2
- public or private record irrespective of form (e.g. photograph, diary, video, painting, sculpture, biography, television broadcast, news report, survey, government or organisational document, etc.)2
- conversations with individuals or a group of individuals, face-to-face or remotely, either synchronously (e.g chat, video or audio) or asynchronously (e.g. email or forum).
If interviewing, it can be helpful to:
- Make sure you organise your time so that you have plenty of time for analysis between interviews.
- Before you start coding your field notes of the interview, write a memo capturing the overview; what was the interview about, what were the key issues; what concepts stood out? Were there any links between concepts? Was a main concern stated? If so, what was it?
How do you interview people I asked? The reply came back ‘Just do it…. you’ve been listening to people all your life’.3
Once you have started collecting and analysing your data is a good time to read Theoretical Sensitivity.
Data analysis tips
Theoretical Sensitivity pages 56 -61, Chapter 7 in Basics of Grounded Theory and Chapter 9 in Doing Grounded Theory are must read sections, which tell you exactly how to open code. Remember that data collection and analysis are integrated activities thus the data collection stage and open coding stage occur simultaneously and continue until the core category is recognised/selected.
As you code it can be helpful to:
- Take care not to push professional interests. It is essential to identify what your professional interests are and be wary about following them. In our experience students who pursue the professional interest usually end up with a “superficial” analysis that does not go beyond what is known.
- Keep in close touch with your supervisor or grounded theory mentor. Analyse material together: code and write memos. In our experience student learns a lot by role modelling and the discussion that takes place around analysis. The grounded theory mentor can prompt the student to follow through on leads. The experienced grounded theory researcher raises awareness of concepts the student might not see, and asks questions about what is happening.
- Use grounded theory language from the beginning; talk concepts, categories, processes etc.
- Read and re-read the recommended texts; particularly read the chapters about your current stage in the grounded theory process. Try to follow through on what is advised in Barney’s books; some students like to run away with interviewing and think numbers are important whereas in grounded theory, analysis drives the data collection process.
- Look for patterns of behaviour. Having completed 6 interviews for example, are there processes evident? Do any of the processes seem as if they account for behaviour and the management of a the main concern?
- Practice conceptualisation from the beginning. Arrange concepts for similarities and differences. For example, if a participant talks about “knowing, attitudes and experience” each could be considered a concept in its own right. If they were grouped together could they form a category of “learning”? The analyst is comparing data for similarities and differences – arranging the data in chunks that are similar and chunks that are very different. For instance, if a participant discusses supports – what goes alongside that? Are they talking social supports? Emotional supports? Physical supports? Structural supports, cultural? What is the difference? Does it matter? Is this relevant to the management of the main concern? How? Why
- Stop coding to write memos as ideas about concepts arise. Memos are critically important as they track theory development.
- Be alert for the received view of the world, interpretations, and try to minimise their impact on your analysis. You may be aware of what the literature says because of work required for ethical review and university application procedures. Try and set these understanding aside and focus on conceptualising the data before you.
The open coding stage ends when the core category and the main concern become apparent; where the core category explains the behaviour in the substantive area, that is, it explains how the main concern is resolved or processed.
1XIE, S.L. (2009). Striking a Balance between Program Requirements and GT Principles: Writing a compromised GT proposal The Grounded Theory Review: An international journal, 8(2), 35 – 47. This paper might be helpful if you are currently writing your proposal.
2 If you have experience in analysing any of these data types that you are willing to share, please firstname.lastname@example.org and we will post with acknowledgement.
3 In conversation with Barney Glaser, GTI seminar, Malmo 2003.