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April 17, 2019

Research Design Chapter Philosophical Section: How Much Is Too Much? Part A

When writing the research design chapter, and indeed when engaging with postgraduate research, a key issue is Philosophy. Philosophical issues relating to the phenomenon of interest and the research context have to be acknowledged, identified, documented, critiqued, reflected upon, and strongly associated with the research methodology. Philosophy drives methodology, and the methodology provides the framework that guides the research methods and procedures. It is imperative to ensure that strong links, cohesiveness and cohesion exist between philosophy, methodology, methods and procedures of the research within your writings so that the design can stand up to academic scrutiny, and to ensure that findings are consistent, correct, appropriate, and suitable for the context and the main research objectives.


Those are separate topics for another time, but referring to writing the Philosophical section of the research design of a thesis a key question is, how much is too much? This is an interesting question that I continuously have asked myself when writing the philosophical section of the research design. I am of the firm belief that nothing is ever, and should ever, be wasted. Nothing you write on the Ph.D. is ever wasted as something can be turned into something else, even a publishable form of something else.


During my time on the Ph.D. I have written extensive notes on paper and in digital form about numerous philosophical, both ontological and epistemological, positions. Even back at this time I was questioning how I could apply what I was exploring to the methodology, how each position affected my perspective of the phenomenon, and the way I could best record and express the positions in the thesis. Whether you are writing in pre-draft form on paper or in digital form, don’t be afraid to ask yourself questions early, but don’t restrict your creativity and inquiry. Allow your thoughts to come out, to develop, and to become as complex as they are required to be. You know how complex your ideas should be, and you know how complex you want them to be to fit the context. But again, don’t reject anything. I have been writing the draft form of the research design chapter for quite a while. The Philosophical aspect has experienced a number of rewrites as my pre-draft form ideas matured further and as I engaged with more philosophical ideas and different philosophical authors.


Where to begin with this minefield? I began fairly early in thinking about research design to read the theses of other post graduates. It did not take long to find a stumbling block: there is no universal law or standard that appears to guide how much is too much or too little. The problem, and difficulty, is that theses, although they might focus on the same methodology, differ widely in their philosophical coverage. Some theses make a passing suggestion towards philosophy and include it in a discussion about methodology, whilst other theses provide more detail and include a separate Philosophical section followed by a discussion of methodology. Even the Philosophical section, however, differs with some making short references to ideas about reality and knowledge, whilst others talk about knowledge without referring to any sense of reality even though they reference an ontological position.


What is important to remember is that despite the diverse range of philosophical coverage, there is some sort of expectancy to ensure cohesiveness and consistency in your approach. You cannot, for example, say that you’re adopting constructivist ontology and an objectivist epistemology supporting an experimental methodology. You cannot, in my view, talk about epistemology and pay lip service to ontology if you’re making explicit statements about how you come to understand reality. If you are talking about reality, then you’re talking about ontology. If you’re talking about the nature, structure, limits and origins of your knowledge and of coming to know this reality, then that’s epistemology. If you’re talking about how you are to gain knowledge about reality, that’s methodology. It’s important to remember this.


Is it worth reading though these theses? Yes, it is. Engaging with other theses enables us to become more acquainted with the self or being as a researcher. It makes us question how we should present our philosophical stance, and to wonder why such diversity in Philosophical coverage exists.


Engaging with these theses has in party contributed to increasing the value and importance of acknowledging, recognising, critiquing and engaging with my own philosophical stance, and the way my stance could be communicated. There is no particularly strict guide, and it’s important to explore and experiment in order to find what is best. This takes many redrafts. I’m sure many of the longer term readers of this blog have followed my Philosophical battles as I oscillated between different positions in order to situate or locate my views of reality within the extended literature. One needs to be careful to not pigeon-hole their beliefs or to ‘stuff’ their beliefs within a particular position just to tick a box. Your beliefs need to be engaged with critically and reflectively. They need to be intellectualised, and to be intellectually engaged with, so that they can logically be applied to your research, be integrated cohesively within your research design, and communicated consistently within your writings.


How much is too much or too little? It simply depends on what is right for your research, and how you relate your philosophical position to your research, and how valuable discussing ontological and epistemological issues are in relation to your research, research question, and phenomena of interest.


I shall cover this more in the next blog post where I discuss and explain further my experiences so far!


January 25, 2019

A year In Reflection, Part B: Methodological Changes

The relationship between our philosophical beliefs and methodological approach to our research is, as far as I am concerned, a complex relationship. Not only can there be a sense of fluidity between the ontological and epistemological beliefs, but also fluidity between the philosophical beliefs and the methodological approach. As I have spoken about on this blog, what I found during the year was a shift in my conceptualisation of the phenomenon of interest, which led to a change in what I wanted to explore in the data, and, therefore, changes to the directions of my research interest. The changes to the conceptualisations, concepts, and directions of what I wanted to explore and why I think they are important led to me changing methodological approach.


Over time I came to realise that Grounded Theory was no longer working for me for various reasons that I shall explain in the thesis. I came to realise that, out of the various analytical approaches I was then experimenting with (grounded theory, discourse analysis, content analysis, and thematic analysis) thematic analysis revealed itself to be the most appropriate. The type of thematic analysis of most use appears to be a mix of Braun and Clarke’s version along with Guest’s Applied Thematic Analysis approach, with some concepts and ideas loosely based on aspects of Grounded Theory. All this shall of course be explained in the thesis.


Those are the changes made in a nutshell: if you want to know more about these changes feel free to read through my previous blog posts and also read the thesis when it’s written!


Upon reflection, what can be learnt from qualitative research is that it is near enough impossible to know what you are going to be exploring at the very beginning. This is relevant claim to qualitative research that adopts an inductive approach to exploring data, where you are essentially allowing your interpretations and observations of the data to guide your thinking and the directions that you take.


All changes to the research have been recorded with great detail. It is important to record everything. Even the smallest, slightest change to your philosophical beliefs, methodological approaches and the way you perceive and interact with the data can lead to even bigger changes in the future, so it is important to record these small changes and reflect upon their implications, impacts, and meanings to your research. Record them either through your own blog, through theoretical memos that you right as part of your data analysis, or even on a scrap piece of paper that is stored correctly for easy retrieval later.


All these observations and interpretations that you record can be logically ordered, expanded, discussed and reflected upon at a later time as you write your thesis. Remember that a qualitative thesis is a reflexive exercise and you as the researcher become part of the data analysis, so do ensure that you record appropriately, store as logically as you can, and reflect deeply and comprehensively during your thesis write up as part of telling the story of the way in which you approached your research, why, and what changes were made.


Record and detail absolutely everything!


November 19, 2018

Ph.D Update: Up To Mid November 2018, Part B: Continuing To Write Extensively

Writing is a continuous, ongoing task in qualitative research but the question is, what do you write? Obviously, many qualitative methodological textbooks and my own experiences suggest that it is very important to document what you observe and begin to interpret very early in the qualitative process. Typically, quantitative research is fairly set in nature and the writing of the research findings usually take place following the analysis phase. With qualitative research, you begin to write about your findings and interpretations at the very beginning of the analytical process. Your writings, interpretations and coding schemes, etc. all change and evolve over time, and it is always wise to write about these changes as they occur.


Reflect on these changes and alternatives, explain the way in which these changes have impacted your research, compare the changed approach to the previous approach, and evaluate these changes. All these reflections shall form a part of your analysis and overall production of the research design chapter and later thesis chapters.


Typically in qualitative research, data analysis and writing of the interpretations and findings occur simultaneously. What I am finding that is in addition to the norm is that I am writing about the research design as I go through each data analysis stage and phase. I have found that my analytical lens and general analytical approach have changed as I have progressed through the data analysis and as I have reread the data several times. With this, I am not just writing and contributing towards the findings and discussion related chapters simultaneous to data analysis, but also various aspects of the research design chapter.


Trust me, this can be quite mind boggling. But for me, it’s an approach that works as I have always viewed little sense in writing the research design chapter before the data analysis began. I did attempt this before, but as I progressed through the data analysis I found that what I found was challenging what I thought, and continues to do so. It made sense for me from that point to write about the design as I progressed through the data analysis.


It was more than a couple of years or so ago that I started the qualitative journey after moving away from mixed methods approaches to investigating the phenomenon of interest. I suppose back then I was aware of the need for writing about the data itself and what I was to observe, but I had no idea that at the time I would effectively be writing about the research design AND the data observations and thematic development simultaneously but this is the way that my research appears to have been worked out.


Qualitative research is nuanced and there really is no set path towards the way you are to write your qualitative thesis! Plus do remember that it is an ongoing process: you cannot write about an observation once and then leave it. It’s a long running, complex, detailed, deep process of understanding and comprehending what it is you are observing.


'till next time, keep applying that pen to paper! Or hands to keyboard! Or both!


Ph.D Update: Up To Mid November 2018, Part A: Refining Coding Scheme

As mentioned in the previous blog post I am pretty much there with the coding scheme. That’s not to suggests that revisions and adjustments are not going to occur, but it is to suggest that I am in a happier place with the coding; I feel that the coding scheme now better represents the aims and objectives of the research. New codes and adjustments of the existing codes are likely to occur as I continue with the development of categories and themes and their verification and validation. Never ever hold anything as absolute and complete especially when you are engaged with qualitative research.


Along with refining the codes, etc. another task I am involved with is the rechecking of the coding of data characteristics. By this I mean, ensuring that the data segments have been interpreted consistently according to their characteristics, and coded accurately. There is a relationship here between interpreting consistently and coding accurately, because accurate coding can only arguably occur with consistent interpreting. A deeper question here, however, is to ask about the accuracy of interpretation, or, in what way data segments could be interpreted accurately and this is a challenging question, which I suspect is related to validation and verification. A part of this involves ensuring that the segments have been coded using the most appropriate code that best describes the activity expressed in the data segment.


I am also double checking what I call the “code memos.” These are theoretical memos, a concept from Grounded Theory, which documents my approach to developing the code, and explaining the meaning of the code, and why the code is most appropriate for each recorded data segment. All coded segments are placed in the code’s appropriate memo, and this assists with observing and documenting the capturing of variation within the code, and therefore, assists with understanding the variation of themes. These memos, therefore, shall come part of the identification and development of themes.


I have identified initial sets of themes and these themes have been / are continuing to be refined but this is a continuous process and will be for the foreseeable future.


The key is, it is my belief that my core ideas of the coding scheme are in place: I just need to validate and refine the codes as necessary. The refinement and checking of the coding scheme as explained in the previous blog post is ongoing.


October 14, 2018

Ph.D Update: Late September till 5th October

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!


September 06, 2018

Currrent State Of Play: The Research Design Chapter

This is the chapter that shall describe, explain, evaluate and critique the development of my new approach (coding scheme) of exploring the phenomenon of interest. The chapter shall also describe and explain the development and application phases of the coding scheme and the way in which categorical and thematic development took place. Therefore, the chapter prior to this deals with a variety of research designs that were tested, whilst this research design chapter deals with the research design that was actually used in the Ph.D. project.


This chapter is a continuous, ongoing and progressive document because it is being written at the same time as data is being analysed. With a quantitative research project the typical process is to write the research design chapter first before carrying out data analysis, but with the qualitative analysis I am finding that I am writing the research design chapter and performing data analysis concurrently. It depends on preferences: some people might like to write their methodological chapters before carrying out the research whilst others might write their chapters afterwards. But with me, I’m writing the chapter as I progress through the phases and stages of data analysis. For me, it makes sense to write about each stage and phase as I encounter each of them because, as I would be engaging with that phase or stage at the time, I can fully elaborate and explain the processes I used within that particular phase or stage.


Because the chapter is work in progress, the structure of the chapter has not been finalised although I have a rough outline of the chapter in place. These include sections that discusses, evaluates, critiques and explores my philosophical beliefs and my personal background (interests, beliefs, experiences, knowledge prior to the Ph.D., etc.), and their possible impact on the development of the coding scheme and categorical and theme development (a process called ‘Researcher Reflexivity’). The outline also includes sections that discuss the methodology and the data collection and analysis methods.


I feel that I have made fair progress with this chapter. I have written lots and lots of notes about my beliefs, experiences, philosophies, my critiques and use of methodology, methods etc. and continue to do so. It’s becoming a matter soon to simply knit these sections together to form the chapter, and work out what I need to develop next. What I am focussing on currently, however, is comprehensively detailing and explaining how I am analysing the data; the phases and stages of data analysis that shall result in the new coding scheme and the identification and development of themes. The writing of this section, obviously, shall continue for as long as data analysis continues.


Lots of editing and rewriting to do, obviously, but I think on the whole I have wrote a considerable amount but shall need to knit the sections together after the data analysis process. That way, I can observe where I need to go next with the research design chapter. Writing the chapter especially the specific data analysis section at the same time as carrying out the data analysis has, however, helped tremendously with documenting with precision and accuracy exactly what I am doing, where, when, how, and why.


Current State Of Play: The Methodology Literature Review

A Ph.D. is a continuous journey of exploration, critique, evaluation and questioning. It is a critical, reflective, evaluative, and analytical engagement with reality, with self-knowledge and understanding, and the knowledge that exists in published literature. If you take the Ph.D. and your research seriously enough, these intellectual investigations can extend beyond the Ph.D.


The key fact to remember is that a Ph.D. does not represent the conclusion of your research, but represents the beginning: it lays the groundwork of your publishing interests, and the disciplinary fields within which you desire to explore and contribute further. It involves the contribution or invention of something new, with potential opportunities to expand upon this contribution and invention through post-doctoral opportunities. Whatever is created during the Ph.D., for example a theory or model, can be situated within different philosophical, theoretical and technological contexts with a variety of different participants. This would lead to evidencing the authenticity, validity, verifiability, transportability, and usefulness of the theory or model. Subsequent explorations beyond the Ph.D. can even lead to amendments and adjustments to your theory or model, and even extensions and specific versions designed for particular contexts and circumstances. This existing journey of research and development is a nuanced experience and you cannot really, fully predict where it shall go with any sense of certainty and accuracy.


With qualitative research in particular, questions and research directions related to the phenomenon of interest can and do change, therefore it can take a long time before you are settled on a particular set of questions and directions. This could be misconceived or misinterpreted as you not knowing what you are doing or that you keep changing your mind flippantly. This is a complete misconception of qualitative research, because when a qualitative researcher changes direction they do so intellectually.


Change to directions and questions come not as a result of hunches or emotions, but as a result of an intellectual engagement with the data, with interpretations of this data, and literature. It takes time to really understand the “layered” existence of data and the many ways in which data could be observed and perceived, and should be observed and perceived in a way that aligns with your broader, general research interests and objectives.


The very essence of engaging with qualitative research is that directions and questions change over time, and if this is intellectually justified, elaborated and explained with each change then you are evidencing and tracking your learning and development. These changes can be justified through these reflections and observations in the thesis. Intellectual justifications, elaborations and explanations are constructed as you deepen your understanding and appreciation of the complexity of the reality that the data represents.


Deepening your understanding of the data arguably occurs if you are given the time to investigate various ways in which data can be analysed and not simply accept the first approach you come across as most suitable just because it has been used most often used in existing empirical literature. The most often used methodology, approach, etc. is not always the most suitable for your own research context. Invest your time in thinking about what is really correct, what isn’t correct, and if any sense of correctness could actually be achieved (without your research project collapsing in on itself and fall into relativism!).


It is through what has been discussed so far that eventually led to the construction of the methodological literature review.


Essentially, this chapter is the narrative of how my research has evolved over the four or five years of thinking about the research issues, experimenting with different analytical methods, experimenting with different philosophical theories, and contemplating and reflecting deeply upon different methodologies. Questions related to these issues are ongoing and will no doubt stretch beyond the Ph.D. (might be important to note unanswered questions in your thesis: that way you can address them at the VIVA examination and also show ambition and commitment to post-doctoral opportunities).


But as it is, this chapter begins to tell the narrative of the development of my approach, the way that my approach differs from others relative to the objectives of research explorations of the phenomenon of interest, and the way that my approach could possibly complement other approaches.


The approach that I am developing did not come to me immediately, nor was the approach based on the first set of ideas and answers that I had when attempting to align research design with research issues and initial research questions. It has taken years of reading existing literature, of comparing and evaluating existing theories and models, of understanding how and where these theories and models have been applied, and of understanding the general context of their application and of critiques that exist regarding their effectiveness and usefulness. Reading and evaluation of these theories are ongoing though more now with the aim of justifying and evidencing the need for the new approach to exploring the phenomenon of interest.


The feature of this chapter is the exploration, comparison, evaluation, and critiquing of the philosophies, methodologies and analytical methods that I have tested against the data, research issues and evolving research questions in order to find the most suitable approach to exploring the phenomenon of interest. Philosophies include realism, constructivism, relativism, interpretivism, and constructionism. Methodologies to be included are mixed methods and qualitative. Analytical methods include a variety of discourse analyses, grounded theory approaches, content analysis, and thematic analysis. From these evaluations and critiques, a picture begins to build that explains the way that my approach to exploring the phenomenon of interest has been constructed. Full elaboration of my approach shall take place in the Research Design chapter.


This is going to be a big chapter, and is a reason why the literature reviews had to be changed to make space!


August 03, 2018

Ph.D. Update: Research Design And Approach Now Certain!

The main output of my research shall now be a new coding scheme designed and developed to assist with the analysis of social learning processes, with the potential to move towards contributing thematic, conceptual and possible theoretical understanding of the phenomena of interest. The development process of this coding scheme (the data analysis process) has been inspired by writers of thematic analysis and grounded theory. The coding scheme’s development process (the actual development of the coding scheme) questions some aspects of existing ways in which to develop coding schemes. Sub stages of development are being proposed and shall possibly continue to be proposed as I go through the phases of analysis.


That, folks, is basically the nutshell take away conclusion of the past couple of weeks where I have completed another full round of coding the data and taking a break from coding in order to deeply reflect on my research purpose, objectives, direction, and research design. Phew! There is clarity in the world of organised chaos!


Reflecting on my journey of the Ph.D. so far, I have experimented with and thought about various types of analytical approaches related to exploring the phenomenon of interest, and have thought deeply about the type of data source from a philosophical perspective. E.g., what can I know about the phenomenon from this type of data source? In what way is this data source different to other data sources regarding what can be known? What knowledge can potentially be revealed about the phenomenon from this data source? What can I use to extract this knowledge from this data source? What are the differences between different methods of extracting knowledge both in general and related to the data source? What would different methodologies and methods tell me? What best fits the research questions, research problem, research objectives, and research context in general? In what way can my philosophical beliefs determine what I can know? What are the limits of my knowing? What limits are placed upon my knowing? Do I need to overcome these limits to know more? If so, in what way could this be achieved? And so on and so on.


All these questions have led to various different answers e.g., through comparing different methods and methodologies regarding the questions of what I can know, what can be known, and what can be known and revealed from the data source about the phenomenon of interest. And this I shall be explaining and exploring in great detail in the thesis!


When you are developing a coding scheme, establishing a time frame can be difficult. You might have identified the stages and sub stages of coding scheme development, but it’s fairly impossible to determine a time frame. This is because developing codes from the actual data, developing categories from the codes, developing themes from the categories (this is a broad, typical process of coding scheme development), and writing the methodology chapter are all performed pretty much concurrently.


As you are thinking about the codes that reflect different events and activities of your data, you are thinking about the ways in which similar coded data could be categorised. In turn, you begin to think more abstractly and more theoretically about the way in which categories can be related and placed defined into themes. Themes are the broadest, most abstract, and most theoretical constructions of the coding process, and they explain the data as a whole related to the phenomenon of interest and the way in which you want to explore the phenomenon of interest.


As you can therefore imagine, coding data with the intentions of developing categories and / or themes is not a linear process. Not to mention, every single stage involves writing lots of theoretical memos, which capture your thoughts, theories, assumptions, hypotheses, questions, queries and ponderings of the data, code, category, or theme (and relations within and between codes, categories, and themes).


As a result of all of what I have discussed, the focus of the thesis on the latter chapters (the methodology chapters and the subsequent chapters dealing with discussions of what has been found) is on the qualitative process of coding, category development, and thematic development. At a rough guess this might come anywhere between thirty thousand to forty thousand words of the thesis though perhaps more. I shall talk about the process of writing a qualitative thesis within the context of developing coding schemes in future blog posts.


The research, therefore, has moved away from generating a new theory (as was proposed originally via the use of Grounded Theory) towards developing a new coding scheme, with the intentions of developing and extending existing themes of understanding, and create where necessary new themes, regarding the phenomenon of interest.


The qualitative research field is additionally awash with limitless debates about the ontological, epistemological and methodological levels of interacting with qualitative methods and qualitative approaches. I am not kidding here: recently I have come across many different perspectives and arguments regarding a single approach to sampling for qualitative research, and have also come across many, many arguments for and against and perspectives on qualitative control criteria particularly around the terms “validity,” “reliability,” and, “generalisability.”


I intend on engaging with debates and discussions as every level and every stage of qualitative research.


And that, folks, is what happened in a nutshell during the past couple of weeks since the previous update!


‘till next time!


July 22, 2018

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!


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!


January 2020

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