All entries for Monday 02 July 2018

July 02, 2018

Thoughts On The Coding Process: Implications Of New Insights

Like a toddler running back and forth into the arms of those that love that child, ideas and visions that were previously considered irrelevant or perhaps not suitable for this project but might be for another project have been running back to me like that happy little toddler. Everyone say aww……..


(Oh by the way, I’m not at all suggesting that toddlers are irrelevant! Even if they turn into screaming delightful door slamming teenagers…………..)


The day has been a productive coding session. As I have been coding the data and observing patterns and meanings within the data, I have come to realise that certain patterns and meanings that were once considered irrelevant are now becoming more relevant and, also, I have observed new patterns and meanings that I had not previously observed when previous sets of data were coded. Or at least, new patterns and meanings that have not made themselves obvious till now, even though I might have observed them before but had not consciously acknowledged them, for whatever reason. I think this is a psychological thing: the more you become sensitised to a particular pattern or meaning you start to think later in the coding process that you have observed similar before in different contexts and then you start to identify the bigger picture or wider pattern of behaviour. It’s a very interesting and a very involving process. What I have found during the day is making me rethink what I have coded previously, and the way in which I have interpreted and perceived what is occurring in the data, which might lead to recoding the data again as I go through a more deeper coding phase as I go further into building an understanding of the phenomenon of interest. I’ll be talking more about this in another post later this week.


In the meantime however it is clearer to me now more than ever, and what might be good practice for other Ph.D. candidates to adopt, not to throw away any old ideas and visions that were previously considered irrelevant. This is an approach that I have adopted from the beginning of the Ph.D., as I have folders upon folders of books and research papers and thesis related documents and notes, and a fair percentage has been sent back and forth between the archive folders and the working folders as they were continuously examined for relevance at particular times of the project so far.


Now some of the oldest ideas and visions I had right at the earlier stages of the Ph.D. are becoming more relevant for answering my research questions and addressing the research problems. But more than that: what I was writing about earlier in a theoretical memo that documented my thinking of what I was observing was an attempt at building upon those earlier visions. It’s really interesting when you have built your earliest visions upon a section of existing literature and then to observe what you thought was irrelevant within the data brings back home the thinking that nothing is really impossible. There is a slight problem, however.


It is a fair way into the reanalysis and coding phase that these older ideas and visions have occurred, so this leaves me with a couple of questions. Do I carry on with the coding and analysis and simply suggest at what point I observed a new aspect of a phenomenon to be relevant? Or, do I reanalyse the data again and code for these additional observations that I made later in the coding?


Methodological literature that I have come across so far has not been clear on this subject although it is a subject I shall read more about. I have come across a paper that did suggest that you don’t have to reanalyse the data to code any new observations but this from what I remember was associated with grounded theory based Open Coding, where you are basically coding to build a theory and not coding to identify and relate themes. I am leaning towards yes, I would have to recode the data to code for more instances and examples of what I have observed in order to validate and authenticate the existence of what it is I have been observing.


Of course this then leads onto other philosophical questions such as does repeatability really represent truth? If you observe something often enough does it really exist in an external reality or does it exist within our own interpretations? What about if others are not able to perceive or observe what a researcher finds observable? In what way can I tell that something might exist in an external reality? In what way can I possibly know what I know to be true? These, and more, are challenging questions, but the key I think is to keep everything grounded in the data and make sure that arguments and observations are built from the data. You cannot build from existing theory; you can, however, build from a relationship between data observations and existing theory, but I shall cover that point at a later time.


With all that in mind, what I am thinking about is to analyse the data but keep the original copy of the data and embed evidence of a change in perspective or the observation of a potentially key new theme. This would be in the form of a theoretical note embedded within the data that would mark precisely the point that I began to observe the importance and relevance of an event or meaning that could form a part of a theme. This would show and evidence the progression of thinking and the way in which my thinking and thought pattern progressed to the point that I began to observe the importance and relevance of what it was I was observing. I am not really sure what the literature says on this subject, but I am becoming convinced that this might be the best approach.


The key lesson here really is, don’t throw out your old ideas. Whether that idea is represented as a few lines of writing on a scrappy piece of paper or rushed serious of paragraphs on the word processor, keep it! Archive it or put it in some relevant folder or whatever storage system you have so that you can refer back to those ideas in the future if they prove to be relevant. Another lesson is don’t focus your mind exclusively on what you found previously.


In other words, don’t code one set of data and then focus the next set of data on what you have discovered before (I know this is rather a contentious point in academic discussion from what I can understand about coding approaches and debates) (another contentious point is whether or not anything is actually discovered at all, but is actually interpreted), but keep an open mind. Of course what you find whilst you are coding and thinking about the data is exciting, overwhelmingly exciting, but keep a level head, keep an open mind, and don’t be distracted by what you have observed previously. If you become too focussed on what you have observed previously you’ll begin to lose the meaning of innovation and originality, and become potentially enslaved by previous observations. Keep an open mind and keep coding for original insights and meanings, and think and plan carefully to determine if there is a real need to reanalyse the data when you find something new a fair way into your data analysis process. This really depends on your research questions, research problem, and the way in which what you have observed relates to explaining the phenomenon of interest.


‘till next time!


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