The data analysis on-line learning programme at the University of the West of England (Faculty of Health and Social Care) contains some good examples of both the analysis of texts and of images. (Probably written by J M Cobby & M. Gilchrist)
Analysis process & keeping the data tidy
To be completed
How to code and analyse
Qualitative data sets tend to be large, complex and detailed. The task of keeping on top of such a mountain of data so that each part is given a fair, balanced and equally thorough analysis should not be underestimated. There are techniques and procedures that can help with that.
Working to create theory
Do you need to explore a theory or create one, or add ideas to an existing theory? Tom Richards (Richards and Richards, 1994) neatly captures the potential processes in developing theory from data
“We often get going by finding little things that relate in some meaningful way – perhaps, if our interest is in stress, that certain topics get discussed in anxious ways (and that is something that good coding and retrieval can find for us). So then we start looking for components in those topics that might cause anxiety, often by studying the text, finding or guessing the components and coding for them, recalling situational facts not in the text and looking for suggestive co-occurrences of codes. We might on a hunch start looking at text passages on people’s personal security and how they arrange it (research on background theory here, and lots of coding again), to see if there is some possible connection between components occurring in the anxiety topics and security arrangements. If we find one, the theory is still thin, so we embark on a search for others, and thereby look for a pattern. The result of this is a little group of chunked-together coded text, ideas and hypotheses that, provided they can be kept and accessed as a chunk, can become an ingredient in further more abstracted or wide-ranging explorations. This chunk is said to be of larger “grain size” than its component codings, and it may in turn become an ingredient of a later theorizing of larger grain size still that is built out of existing chunks. (Big fleas are made out of smaller fleas.)
And so the web – of code, explore, relate, study the text – grows, resulting in little explorations, little tests, little ideas hardly worth calling theories but that need to be hung onto as wholes, to be further data for further study. Together they link together with other theories and make the story, the understanding of the text. The strength of this growing interpretation lies to a considerable extent in the fine grain size and tight inter-knittedness of all these steps; and the job of qualitative data handling (and software) is to help in the development of such growing interpretations”
Richards T. and Richards, L. (1994) Using Computers in Qualitative Analysis. In: Denzin and Lincoln (eds) Handbook of Qualitative Research, Sage Publications, Thousand Oaks, California. p. 448
