So, step 10 is data processing and analysis, and again this is dictated very much by the
methodological approach that you are using, in the philosophical approach of your research and
the methods of data collection that you've used. So I use semi structured interviews,
and as a result generated transcripts from those interviews. Observation, and through observation,
as a researcher you write field notes. So you have a book that you scribble on in terms of writing
your observations down. And then documentary analysis. I have the documents as well as my notes
about the documents, in terms of what's observed and how they were different between documents.
So moving forward with processing and analyzing that data, I've got three separate forms of data
that I'm needing to synthesize together to be able to analyze. So I took an iterative and inductive
approach, which meant that it was quite fluid, and also I had minimal assumptions about what
I was about to find. And the overall approach was something called 'constant comparative analysis'.
And what that essentially means is right from the start, you're comparing the data that you get and
analyzing your data as you go. So my analysis started right from the first day of an interview
that are transcribed. So I read and reread that first interview, and part of the initial coding,
er the initial analysis process is coding. So I coded that first transcript according to what
the participants had said. So I had already started analysis right at the very beginning,
and I started to do that also with documentary analysis and with observations. So starting to
build a picture right from the beginning of the research, so then with the second interview again,
I reread that interview numerous times and assigned codes to that interview. So then
what I did was went back to interview one to see whether the codes that were in interview one were
similar to interview two, and whether any new codes had been generated in interview two that
maybe I'd missed in interview one - so you're comparing the interviews all of the time. And
I did that for subsequent interviews. So you can see that it is a quite a time-consuming process,
and the more interviews you've got, and you're going back to previous interviews,
it can be quite time-consuming. But you're living and breathing the data, so you do
begin to understand it a lot more by using that process, and you can sometimes highlight more
codes as you go on identifying where you've missed things with in previous interviews that
have been highlighted by others. So I said earlier that I wanted to speak to doctors and midwives,
so I actually coded the interviews for doctors and midwives separately. So I was generating
specific codes for midwives and specific codes for doctors. And once I'd achieved what we call 'data
saturation' then then I stopped. Data saturation is where you - with the last interview that
you've done -you generate no new codes, and that interview is not telling you anything new to what
other interviews have told you. And then at that point you can deem that you've achieved what we
call 'data saturation' and you are well within your rights at that point to stop sampling,
so you don't need to gather any more information from anybody so you do not need to sample any
more individuals. So as I said alongside this I was also coding observational field notes
and notes from documentary analysis, and I was using that information alongside the codes of
the interviews that I'd gathered so that I could gain, you know, quite a big picture about what I
was trying to do. And there is a picture that you can see about my data analysis for a PhD,
and you can see on this picture that there were different orders that I took, and this does follow
usual qualitative data analysis. A recommendation I would make is that you actually use a reputable
author in terms of their recommendation for data analysis, and state that you will follow that
particular approach. But usually they do follow in different orders where you are ultimately trying
to make sense of a large amount of data. So you can see first order coding is quite significant,
and that was done with midwifery and the medical profession separately, before moving on and
combining them at a later stage. So first order coding is about making sense and coding large
amounts of raw data to be able to make sense of it, and you can see that as I said I did
that separately in terms of first order coding to move through themes and generate categories
for each of the different professions. Then I moved on to second order coding,
again using the professions separately, but here I wanted to generate concepts so you focus in those
themes and categories to generate concepts,- so to generate bigger ideas about what the data
is actually telling you. And then I moved on to third order coding. And moving on to third order
coding is where I actually started to combine all of this data that I'd looked at separately.
So combining doctors with midwives, with thinking about what was happening within the organization
to try and generate some third order coding. And what you generate then from third order code is
something called 'theoretical concepts'. So as part of a higher degree, particularly a PhD,
you are needing to demonstrate something called 'theoretical contribution', so you are aiming
to add knowledge to existing theory. So moving forward for theoretical concepts, it is where you
can start to demonstrate where your theoretical contribution is and where you can really start
to hang your data on existing theory. Okay, some points to remember for data analysis. Your data
analysis strategy does need to be congruent with your research approach. So it does need to fit
with your research aim and your methodology. You also need to use a reputable author in terms of
what strategy you're going to use in terms of the process, so that it helps you to justify
the approach that you're taking. And also, there are numerous tools that you can use in terms of
software and other manual tools that you can use to help you make sense of your data through data
analysis. I use NVIVO for first-order coding but then moved on to manual mind mapping techniques
for second and third order coding. So you do need to have some kind of strategy in mind as to
how you'll move forward with using those tools to make sure sure that your data analysis is robust.