Creating referencing codes to identify each participant response enables us to do that.
This does not mean that we need to know exactly who any one participant is, so we can have participant anonymity, but we do need to be able to identify each unique dataset in our findings. Sometimes we only need identify a particular particpant group, where the behaviour is more useful in a cluster.
Creating referencing codes - or referencing systems if using a very large data set - for our particpants or particpant groups doesn't need to be complex. For example, if we interviewed a number of students and lecturers, we could simply use group codes such as "Level 7 Student, 2015" or "Lecturer, 2015". These would provide both ourselves and our readers useful insights into comments from interviewees, to enable us to shortcut long and repetitive explanations.
They are then referenced within our findings exactly as normal, for example "(Level 7 Student, 2015; Lecturer, 2015)".
If we needed to identify individual students, we could assign a name, or we could assign a number; eg, "Level 7 Student Amy, 2015" or "Level 7 Student 5, 2015". We simply need record what we decided to do and why within our methodology.
Putting a table of all codes that we decided on somewhere (eg, in our methodology or in an Appendix) then gives ourselves and our reader a map back to each source.
This in turn enables us to shortcut when linking between our Findings to our Literature Review within our Discussion section. We have effectively short-coded all our explanations.
In providing ourselves with this index, we have also reassured our readers that our work is well-planned, and well-thought through.
And it also means that both we and our reader can find things later, when our memories for the links has faded.
Sam
- References: Brickley, Dan (2011). 6230460521_1d5e97f15b_o. Retrieved 7 December 2015 from https://www.flickr.com/photos/danbri/6230460521/in/photostream/
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