Ph.D Update: Data Analysis Is The Dominating Task!
Data analysis has dominated the past couple of weeks, although, whilst engaging with data analysis, I have been continuously engaged with other areas of thought and practice:
· The characteristics of the phenomenon of interest
· The nature, complexity, nuances, and functionality of the specific data source, including comparisons with other sources
· The nature and functions of the social learning context in comparison with other contexts
· Evaluation, critiques and reflections of thematic analysis so far, and comparative observations with other methodologies and methods
Essentially this encompasses four levels of thinking: the phenomenon itself, the data source, the more general learning context, and the research design. All thoughts and processes of evaluations, etc. are situated not just within the research context but also within the context of my philosophical beliefs.
Everything is a work in progress. As I progress through the data analysis phase, my thoughts, interpretations, observations, hypotheses and questions shall be continuously refined in order to more effectively reflect the true reality (remember, I am a realist) of what is occurring in the data. Coding is always a work in progress and all that I am thinking about, observing, hypothesising, questioning etc has developed from earlier coding efforts in the Ph.D.
As I shall be explaining more in the thesis, coding is not just a mechanistic act of labelling meanings and activities in the data, but is an active, engaging, dynamic, nuanced, flexible and adaptable method for analysing qualitative data that (I shall argue) plays a part in understanding the truth of what is happening in the data.
Currently, therefore, I am progressing through the “opening” stage of the analysis phase. This “opening” stage is based on the coding and reanalysis of the data corpus. I am continuously revisiting what I have coded before, and continuously reanalysing and recoding, in order to ensure that the codes are as reflective of the nature and function of the data segments as possible. This shall then help to develop themes that, although constructed on a more theoretical plane, are as close to the data as possible.
I am breaking the context of the data corpus down stage by stage. In the first stage that has been ongoing for a few months on and off, I coded all the way through the data corpus without much thought for nuances and context. It was simply a matter of initially understanding the meanings and functions of the data segments though if nuances and contextual influences were immediately obvious then these would be considered.
What I am doing currently is the next level: I am breaking the data corpus down and really exploring the context and nuances of each data segment, along with developing an understanding of the way in which these segments logically connect with and relate to each other on various levels and various purposes. Additionally, this level involves the rechecking of codes to ensure they reflect the reality of what is being expressed in the segment, and to alter the codes if necessary. This deeper approach to understanding the data is in my view more relative to the research questions.
The study of the nuances and contexts is based on what I have observed during my time of using grounded theory, and which led to moving away from grounded theory as has been documented on this blog and which is being documented in the thesis methodology chapter. It is all ultimately based on what I perceive and interpret within the data, but this is not a subjective, relativist approach. As a part of the theme development I shall be exploring the codes and segments again and test all that I observe. E.g., just because I have coded a segment to represent a particular feature or activity does not mean that I am objectively correct: this correctness, perhaps, comes from repeatable observations of similar data characteristics. This idea is taken from the abductive reasoning method. This shall be discussed further at the time of theme development.
Along with the coding, I have been writing theoretical memos (an aspect of Grounded Theory I have liked, so have included it in my own approach), which serve the purpose of documenting and recording all my thinking, observations, thoughts, hypotheses and questions about each data segment, and also of the meaning, nature, function and representativeness of each code.
This coding level is ongoing and work in progress, but there are already some interesting insights and points of discussion. Nevertheless, my understanding of the relationship between segments, the impact of contextual and situated conditions, and the emergence or development of meaning and activities shall continue to develop and refine as I progress through this analytical phase.
All this shall lead onto the development of themes, which operate and are constructed at the latent level and are constructed through combining, in some way, multiple, different, though similar codes (as discussed in the previous post: I shall be talking more about the development of themes soon). My understanding of themes so far is leading me to think of a theme as a core aspect of a phenomenon of interest that describes and explains the phenomenon’s behaviour and helps to characterise its theoretical existence. Thematic theoretical insights are drawn from the data, and tested against the data.
Speaking of themes, I have made enough observations in the data to tentatively suggest the existence of two themes, and the way in which these themes could relate to each other. At a push I could suggest I have observed four themes, but I am not convinced or at least not as certain about two of the themes as I am with the first two themes I came to observe. These themes, and possibly more, shall be identified, defined, developed, and established following this coding phase. At the moment I have put the thoughts of these themes aside as I do not want to restrict my thinking and open mindedness during the rest of the coding phase. There is a danger that if I did become too fixated in the idea of exploring to prove these themes, I might miss out on something that might be obscure but is equally as important.
That’s over a thousand words and I haven’t scratched the surface!
I intend on writing some more posts during the week related to the four points made at the beginning of the post, but honestly, I’d rather focus on data analysis. But when I get the chance I shall post up more posts!
‘Till next time!