Introduction to Grouned Theory (Analysis)
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The workshop on grounded theory analysis introduces participants to its basic principles, including open coding, axial coding, and selective coding. It emphasizes the importance of systematic engagement with data to generate meaningful theoretical insights while also encouraging reflexivity among researchers. Attendees will gain practical experience in applying these procedures and reflecting on their personal engagement with the research process.
Introduction to Grouned Theory (Analysis)
- 1. KARL-FRANZENS-UNIVERSITÄT GRAZ UNIVERSITY OF GRAZ Introduction to Grounded Theory Analysis Achilleas Kostoulas, PhD
- 2. Objectives of this workshop By the end of this workshop, you… … will be familiar with the basic principles and procedures of Grounded Theory analysis. … will understand the procedures used in open coding … will have had practical experience applying the procedures used in open coding. … will have reflected on the question of reflexivity.
- 3. Structure of this workshop
- 4. Overview AIMS, PRINCIPLES & PROCEDURES RobertG NL @ Flickr
- 5. What is Grounded Theory? Grounded Theory is an inductive, theory-generating approach to conducting research. It is a method (not a theory!) It involves systematic, rigorous engagement with the data, following specific procedures, and it aims to generate a theoretical understanding of some phenomenon. This understanding should be sufficiently abstract, so that it is theoretically useful, but must remain connected to the data from which it was derived.
- 6. Key publications 1967 •Glaser, B. & Strauss, A. (1967). Discovery of Grounded Theory. Chicago, IL: Aldine. 1978 •Strauss, A. (1978). Theoretical Sensitivity. Mill Valley, CA: The Sociology Press. 1987 •Strauss, A. (1987). Qualitative Analysis for Social Scientists. Cambridge: CUP. 1990 •Strauss, A. & Corbin, J. (1990). Basics of Qualitative Research: Grounded Theory Procedures & Techniques. Thousand Oaks, CA: SAGE. 1992 •Glaser, B. (1992). Emergence vs. Forcing: Basics of Grounded Theory Analyses. Mill Valley, CA: The Sociology Press. 2006 •Charmaz, K. (2006). Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. Thousand Oaks, CA: SAGE.
- 7. Developing a theory Theoretical Sampling Constant comparison Constant comparison Constant comparisonResearch problem Theory Case Case Case Image credit: Karina Fernandez
- 8. Procedures of Grounded Theory analysis Open coding: involves ‘breaking open’ the data, and generating a (relatively large) number of theoretical categories. Axial coding: (or categorical coding) involves making connections between the previously identified categories. Selective coding: involves identifying a core theoretical category and coding data with reference to it. Open coding Axial Coding Selective coding
- 9. “ ” The published word is not the final one, but only a pause in the never- ending process of generating theory. Glaser & Strauss (1967, p. 40)
- 10. Open coding GETTING A FEEL OF THE DATA J. Mark Bertrand
- 11. Open coding First level of conceptual engagement with the data Involves assigning substantive codes to instances of data. Codes should not merely describe the data – they correspond to more abstract categories of which the data are indicators. Initially, codes should be “detailed, specific and numerous” (Gilbert, 2008, p. 87) The purpose of open coding is to open up the theoretical possibilities that are suggested by the data.
- 13. Open coding Break the data into cognitively manageable segments. Natural breaks in the data can be helpful, as they frequently denote shifts in topic. Explore the segments for ideas that they might contain. Read the data multiple times (phrase-by-phrase; sentence-by-sentence, entire text) Be on the look out for ‘rich’ moments, which will have to be micro- analysed Work analytically, nor descriptively. There can be multiple codes assigned to each data segment. Record your thoughts in memos. Assign names to the ideas you have identified. These may be suggested by the text (in vivo) or the literature.
- 14. In-depth engagement with the data To avoid shallow or uninteresting findings, ‘interrogate’ the data: Who? (Who is involved? In what capacity?) What? (What was the event? What were the consequences?) When? (At what point in time? How often? Before and after what? At what rate? For how long?) Where? Why? (What was the proximal cause? What was the distal cause? What was the intention? How were causes and intentions perceived?) How? (How much? How many? With what instrument? With what strategy? With what feeling?)
- 15. 1 My formal language education began at age 10 in secondary school when I started having 2 English lessons. It was only much later that I realized my history of being taught had already 3 started much earlier. Though there was no systematic teaching my nursery and primary 4 school teachers used to play a lot of easy English games and sing English songs with us. I did 5 not learn grammar, writing or talking that way but it helped me develop a feeling for the 6 sound and rhythm of the language. Furthermore, as my parents owned a hostel that was 7 being frequented by a lot of foreign travellers I grew up in an environment where a lot of 8 languages were used. For me, different languages were never something isolated and 9 distant but part of my everyday life.
- 17. Keep comparing! Constant comparison: Compare instantiations of each code / category in the data. How is each code / category manifested in each case? Consider revising categories (splitting, merging or renaming) Theoretical comparison: Think about the abstract properties of each category. Do you feel that you know enough about the category? Should you generate more data about it? Do other possibilities suggest themselves?
- 18. Reflexivity THINKING ABOUT THE RESEARCHER Creative Ignition
- 19. Discussion questions Compare your codes with a partner. To what extent do your codes overlap? What are some salient differences? How might we account for these differences?
- 20. “ ” How does it make a difference that it is me (rather than someone else) engaging with the data? Beliefs Emotions Past experiences Research interests
- 21. Thank you for your participation! ACHILLEFS.KOSTOULAS@UNI-GRAZ.AT