All entries for October 2018
October 14, 2018
I am in no doubt that after the previous reading session it is difficult to pigeon hole my approach. Even the development of the coding scheme, I am finding that my approach consists of ideas from, though not limited to, inductive reasoning, thematic analysis and grounded theory. There is another idea that I have been working on for quite a while but now am in a position where I can make significant progress in this idea. Still plenty to do, but I am thinking that this research will become a multimodal project. It’s really a case of thinking about the way that is best to present this idea in the thesis, and to think more about the way in which the coding scheme relates to this idea. Now that the coding scheme is improving and I feel is beginning to take the form I want it to take, it is expected that there shall be some significant movement in developing this other idea in the coming weeks.
Along with that, another key current task is to continue to rework the coding scheme: reread the data segments, recheck the coding, and drop codes or amend them as necessary as well as combining data segments to present a complete meaning if I feel that I have divided them a bit too much. The idea also is to continue to go through the rest of the data and recode the data as necessary to reflect new meanings and new insights I am making whilst editing on paper, which is also a continuous process.
The process of rechecking everything, as just mentioned, is being carried out on paper. I have used computer software various times to amend the coding and to think about the data in various ways but sometimes for some objectives, it is best to simply use pen and paper. Print out all of your coding, relevant theoretical memos and other relevant documents and go through everything by hand. This approach I feel is especially relevant to mine because I am comparing a lot of data, within and across data sets, in order to develop the categories and themes, and also to develop an understanding of the behaviour of the phenomenon. This is not to suggest that there is no value in computer based analysis and I plan on using that further in the future.
I am pleased that I made the choice to do this, because I have found new insights and ideas that were not at all obvious when staring at the computer screen. Being at the computer screen and being concerned with navigating the software in order to find relevant pieces of data sometimes distracts you from your objectives and can cause you miss out on important insights. Simply doing things by hand sometimes can really help you find new insights that perhaps were not so obvious before. That being said however when I was editing everything on the computer following the edits by hand, there were some insights I made on paper that actually did not make sense when I really thought about what the particular pieces of data actually meant. It’s like a constant battle between colliding thoughts inside your mind with regards to the meaning of the data and what any particular data represents, but my experiences tell me that sometimes using pen and paper is best.
When you have these colliding thoughts and when you are able to perceive and interpret any date segment or segments in various different ways, remember to think about the context within which the segment is situated and remember that whatever you observe and interpret must be relevant to your research questions.
Regardless of what methods are used to explore the data, as always the key idea is to keep asking questions about the data. Remember that the data is a representation of the phenomenon of interest, and what you observe and place meaning upon might not be the same between multiple researchers. Here, you have to try to make sure that what you observe and what you interpret is as close to the data and as close to some sense of objectivity as is possible, if that is a desire of your research. Therefore, I am continuously asking questions about the data and also about my own observations and interpretations, and the quality of those observations and interpretations.
The only way you can progress is to ask questions. Making an observation or an interpretation of something within the data is fine, but you have to be sure of what it is you are really observing or interpreting. This is a process that I am only just scratching the surface of describing the process here (seriously, it’s taking up pages of my research design chapter!), but it is a process that is worth investment and engagement with. You need to make time and effort in ensuring that your observations and interpretations are as sound as possible, regardless of their ultimate subjective nature.
Just keep asking questions about the data and your own interpretations. You learn and develop only through asking, rechecking, reconfirming, and asking again! And when you are sure you are done with everything and have all the answers (quite frankly, I doubt claims of this sort), then ask more questions again!
Keep asking questions and keep going!
‘till next time!
During the first couple of weeks of returning to my Ph.D. following a summer break, marking the fifth and final year of the Ph.D., I engaged with qualitative methodological literature and continued to develop my philosophical beliefs and methodological approach. After a couple of weeks of reading through appropriate chapters of qualitative methodological textbooks, I have been inspired and fascinated by the fact that I am better able to understand qualitative research concepts and contexts presented compared to three or four years ago. This awareness has enabled me to better explain and argue the relevance of qualitative research for my Ph.D. project and indeed for the general research context and type of data I am exploring. As ever, as always, there is always a lot more to say and what can be said, but I do believe I am at the point where I can produce methodological arguments regarding the relationship between qualitative concepts and the general research context. These ideas can only be further improved and developed as I continue to write the research design chapter.
What is interesting is my developing understanding has occurred not necessarily through constant rereading of the qualitative textbook literature, which can help, but through active engagement with the data, through testing out various methodologies and methods, and documenting their effectiveness and comparisons in their effectiveness and usefulness in exploring the phenomena of interest. Perhaps more specifically and importantly, what has impacted my understanding the most is the active engagement through coding and really exploring the data: breaking data down into segments and giving them meaning (codes) and being able to visualise links between these segments. This has really helped me to understand more what my data is about; to think about the nature and context of the data and its characteristics; to think about the way in which the data represents the phenomenon of interest, and, therefore, has assisted in developing my understanding of the relevance of qualitative methodologies particularly the approach I am developing. It’s not just about active data engagement: you have to be able to provide methodological and philosophical reasoning and justifications of your approach and it has to make logical and reasonable sense. This is what I am continuing to strive and achieve. Not an easy task by all means, it can take a long, long time, but it can happen and you can achieve. You just have to believe!
It is engaging with the data and the phenomenon at an embedded, detailed level that has assisted with that understanding of qualitative concepts and methodology. It is like an evolving relationship: you read the methodology textbooks, you actively engage with the code for a period, and that in turn increases your understanding of the methodological textbooks. Additionally, being actively engaged with the data increases your understanding of the data and the way in which the data represents the phenomenon of interest. I realised that my engagement with the data increased my understanding of the data and its representation, but finding out that it helped significantly in developing my understanding of qualitative textbooks is an interesting observation. It’s impossible to claim to know everything, that is not possible, but in the thesis I can detail the way in which engaging with the data has enabled me to better understand the purposes and objectives of qualitative data, and the way that I can argue that qualitative data could serve another purpose relative to the data and context of my research. Fascinating!
The key message to take away from this blog is, sometimes you just have to jump in and engage with the data. If it takes weeks or months to really understand the data as it has done with me, it doesn’t really matter. What matters is that you are able to return to the textbooks and be able to better understand the concepts of qualitative research and be able to begin to argue the concepts most relevant to your own research, whilst being able to argue which are not, and perhaps attempt to extend the scope and definitions of qualitative research.
It’s a journey, and it’s a journey of continuous improvement.
Keep going! You can get there! Believe in yourself and your capacity and capability to produce your thesis and promote your research!
October 06, 2018
The fifth and final year of the Ph.D. is now underway! All plans lead towards the submission of the thesis next September, the VIVA defence a few weeks or months following the submission, and the production of more research papers. I have every desire to publish my work following the thesis and where possible, before the submission of the thesis. I have every desire as well to develop a book proposal and have this accepted by an academic publisher: I’m leaning towards the idea of converting my thesis into a book format. I have ideas of what I might like to cover.
I look forward to the coming year, a year that shall academically challenge, excite, scare, and push me and develop me further as an academic researcher. There is always much more to learn, but I am excited because after the many months of experimenting with different analytical approaches to the data, I feel that I am starting to put together a workable plan of data analysis. I feel excited because I can observe continuous development of my understanding of the phenomenon and the data that represents it. This has been achieved through continuous detailing and elaborating of my ontological and epistemological beliefs, and continuous elaborations of the way in which these link with the methodological approach and the methods of data analysis. As I begin to further develop my approach to analysing the data, these elaborations shall no doubt become more detailed and comprehensive.
But I also feel challenged and slightly nervous at the fact that this is the final year and I still feel like I have a lot of analytical work to do, even though I feel like I have already completed a significant amount. Another concern is the simple consideration of the workability of what I shall ultimately develop, and whether or not I’ll actually get the Ph.D. but those thoughts are probably common among a large number of people working towards their Ph.Ds. That said, I do feel more confident with the approaches that I am developing compared to what I was trying to achieve a couple of years ago and even a few months ago.
My understanding of my own epistemology and the way that my beliefs link with methodological approaches and the data analysis methods have altered over the years of thinking about them and experimenting with them. The significant time spent thinking about different philosophical orientations, methodological approaches and experimenting with different analytical methods have been beneficial. This is leading to a thesis chapter that shall include comparisons between different epistemological orientations, methodological concerns and data analysis methods, where they shall be critiqued and evaluated with regards to their effectiveness of exploring the particular type of data in relation to the research questions. It gives me the opportunity not only to write a thesis that provides new knowledge pertaining to the understanding of the phenomena, but also new knowledge with regards to methods and approaches that can be used to explore the phenomena represented as a particular type of text.
Despite these alterations there have been a couple of constants that have remained throughout the research so far: the idea that there is something real independent of our conceptions and beliefs about that something in the social world, and also the appreciation of and desire to adopt a coding and categorisation approach. Coding and categorisation of the data leads to the development of categories and themes, which can be used for further analysis depending on the aims and objectives of the research. Coding and categorising are considered to be the fundamental aspects of qualitative research, and can be a key element of mixed methods research. Qualitative research is dominated by text based resources of different forms and types, which, I am going to argue, can provide different types of knowledge and understanding of a phenomenon. Depending on one’s theoretical and philosophical orientation, one shall perceive the texts in different ways, and place different emphases and meanings upon the text in order to understand the text in various ways related to the phenomena in order to answer the research questions. Coding and categorising, as well as thematic analysing, the data is the key means of capturing the meaning of particular events, actions, and activities either implicitly or explicitly stated in the text. That is essentially qualitative research in a nutshell though, obviously, qualitative research is much more complex than that.
It is a journey, and it’s a journey of constant wonder, awe, inspiration, development, innovation and invention. It’s a journey of challenges, excitement, of emotion, of being inspired, of inspiring others, and it’s a journey that is unique to you and to you alone.
It has been an incredible journey, and it’s nowhere near finished yet! Sometimes I feel that I am really only just beginning: that a real “end” does not necessarily exist, therefore, this idea of “finishing” a Ph.D. is quite an interesting concept. What is it you are actually finishing? Are you finishing the Ph.D. research course? Yes, you are! But are you actually finishing your research? Is that it? Is it done? What about all the ideas that you have developed during the time on your Ph.D. that you had not had the time to implement or develop further? Or what was considered irrelevant at the time but you might be able to think of contexts where they are more relevant? Does your thesis really represent all that your research could be, has been, might be, and should be? You might complete the Ph.D. course, but in reality your own research has only just begun!
Thanks for reading!
‘Till next time!