| Stage |
Explanation |
| Stage 1: Familiarising oneself with the dataset |
Read and re-read and note down initial ideas. The initial ideas are most likely to be initial categories (or codes) of information being classified. |
| Stage 2: Coding the data |
Generating initial codes to organize the data, with full and equal attention given to each data set - Labelling and organizing data items into meaningful group |
| Stage 3: Generating themes |
Involve the process of sorting out the codes into initial themes and also identifying the meaning of and relationship between initial codes - writing themes and their defining properties. |
| Stage 4: Reviewing themes |
Identifying coherent patterns at the level of the coded data. This stage involves reviewing the entire data set as a whole - ensuring there is enough data to support a theme, collapsing overlapping themes and re-working and refining codes and themes. |
| Stage 5:Defining and naming themes |
Identifying the story of each identified theme and fitting the broader story of the data set to respond to the research questions - cycling between the data and the identified themes in order to organize the story |
| Stage 6:Producing themes |
Presenting a concise and interesting account of the story told by the data, both within and across themes - writing a compelling argument that addresses the research question. This stage requires writing beyond the simple description of the themes. |
