1. Familiarizing yourself with your data: |
Transcribing data (if necessary), reading and re-reading the data, noting down initial ideas. |
2. Generating initial codes: |
Coding interesting features of the data in a systematic fashion across the entire data set, collating data relevant to each code. |
3. Searching for themes: |
Collating codes in potential themes, gathering all data relevant to each potential theme. |
4. Reviewing themes: |
Checking if the themes work in relation to the coded extracts (Level 1) and the entire data set (Level 2), generating a thematic ‘map’ of the analysis. |
5. Defining and naming themes: |
Ongoing analysis to refine the specifics of each theme, and the overall story the analysis tells, generating clear definitions and names for each theme. |
6. Producing the report |
The final opportunity for analysis. Selection of vivid, compelling extract examples, final analysis of selected extracts, relating back of the analysis to the research question and literature, producing a scholarly report of the analysis. |