Constructing the Template
Authors of this page:Dawn Clarke and Graham R. Gibbs
Affiliation: University of Huddersfield
Date written: 20th November 2008
- Learn about the role of the template as a means of organising codes or themes.
- Understand how to arrange themes into a hierarchy and why this is done.
- Appreciate that themes can be generated before data analysis or during data analysis
The term "Template Analysis" refers to a particular way of thematically analysing qualitative data. The data involved are usually interview transcripts, but may be any kind of textual data. Template analysis involves the development of a coding "template", which summarises themes identified by the researcher(s) as important in a data set, and organises them in a meaningful and useful manner. Hierarchical coding is emphasised; that is to say, broad themes encompass successively narrower, more specific ones. Analysis often, though not always, starts with some a priori codes, which identify themes strongly expected to be relevant to the analysis. However, these codes may be modified or dispensed with altogether if they do not prove to be useful or appropriate to the actual data examined.
The template itself is a way or arranging the themes or codes that the researcher is using or has discovered in the data. Major, or more general themes appear near the top of a hierarchy of themes and gathered below them (as sub themes) are other themes that exemplify different aspects, types, or interpretations of the major themes. Sub-themes can themselves have sub-themes and so on to give potentially many levels of themes - though the research does not have to use all levels. In Grounded Theory, all the codes are discovered in the data (or developed from the data). In that sense the coding is 'grounded' in the data. In contrast, in Template Analysis codes or themes can be identified or developed before the data are examined - what are called a priori codes - alongside developing codes by reading and examining the data.
The resources on this site by Graham R Gibbs, Dawn Clarke, Celia Taylor, Christina Silver and Ann Lewins are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.