Current State Of Play: Thesis Structure

I have altered the thesis structure several times relative to the research design. I have come to understand over the years that research design is not driven by the thesis: the thesis, its structure, its content and layout is guided by the research design. Quantitative, Mixed Methods and Qualitative research designs all influence the structure and ordering of the thesis in various ways.

I have thought about Mixed Methods and Qualitative theses given that I have been fascinated by both research designs. But now I am focussed on qualitative as the main component of the research, with quantitative analysis involved as deemed necessary, but as a smaller component that complements the qualitative.

It could almost be argued that in some way, quantitative data shall be embedded in a bigger qualitative project in order to provide a broader and more detailed picture of what is happening with the phenomenon of interest within the research context. I am not sure if this could be classed as mixed methods though. I would call it multi-method, because the collected data would serve both quantitative and qualitative and the quantitative analysis would be based on qualitative findings. Multi-method means multiple methods of, for example, data analysis used in the same methodological paradigm, in this case qualitative. It could still be a mixed methods approach but an embedded approach, but I shall have to think about this more. That said though, Mixed Methods is a continuously evolving methodological field with continuous potential for new contributions of creativity, innovation, possibility and lots of debates. Either way, the qualitative provides the framework within which the thesis is being developed, given that the qualitative side of the Ph.D. is considered the largest aspect.

Anyway, the the following thesis structure is now in place:

Introduction: this is going to be a chapter that shall be formally written last. This chapter shall simply introduce the research problem, research context, research issues, the need and value of the research, the research questions, research aims and objectives, research outcomes, and who the research is intending to benefit.

Literature Review, Setting The Scene: this chapter sets the scene and the key outcome of this chapter is to justify why a particular technological context is being used relative to the problems, questions etc. introduced in the introductory chapter. This involves evaluating and comparing each context relative to the phenomenon of interest. I am also attempting to engage with discussion and debate about terminology, and to provide my own definitions of different terms relative to the technological context, and attempt to address ambiguity and conflation.

Methodology Literature Review: this is a critical and analytical evaluation and comparison of different philosophies, theories, coding schemes, methodologies, and methods used to explore the phenomenon of interest within contexts very similar to the Ph.D. research. Additionally, the chapter shall report on the testing, evaluation, comparisons and critiques of different research methods in order to justify the most suitable approach to the research project. The actual approach used for the research project shall be described, explained, evaluated, critiqued and tested in the research design chapter.

Research Design: provides a full elaboration the research design phases including full details on the philosophies, methodology, methods and approaches that made up the design. The chapter shall also consist of design evaluations and shall comprehensively relate every part of the design to the research context, issues, problems, outcomes and questions. There shall also be a full discussion on the way in which the coding scheme and the themes were developed, tested, verified, clarified and validated.

Following the design there shall be chapters dedicated to discussing the coding scheme in more detail, as well as discussing identified categories and themes, and their interrelationships. Also as and where necessary there shall be chapters associated with thematic maps, and any quantitative analysis that takes place. It’s difficult to plan these chapters out though, because the chapter structure and content emerges from the data and not emerge from pre-existing theories and models. Hence, the structure and content of these later chapters are continuously emerging from the data analysis. There shall also be a chapter or a section of a chapter revolving around the application of theory in practice.

That’s the thesis at this time! Next are blog posts that cover a couple of the initial thesis chapters: the literature reviews.

Alex Darracott : 05 Sep 2018 21:39 |  Tags: Design Qualitative Reflections Thesis Thesis Structure |  Comments (0) |  Close comments |  Report a problem

Current State Of Play: General Observations

Literature Review

Since writing the previous blog post back in early August, I have focussed on restructuring and rewriting the literature review sections, and have adjusted the scope of the literature as well as collected and analysed further literature. Thoughts and arguments within the literature review have been reconstructed and extended.

The literature review now has a beginning, middle and concluding structure, and this is the structure I intend to use for each chapter though written in a way that the introduction connects with the conclusion of the previous chapter, and the conclusion section leads into the introduction of the next chapter. All the sections in the literature review are interconnected: they might refer to different topics, but these topics are related in a way that logically, coherently, consistently and cohesively constructs thoughts, ideas, arguments and perspectives.

Unsurprisingly, as with everything at postgraduate level it is not quite black and white. With all Ph.D. theses, every chapter should also be referencing the first chapter: the introduction, where the research context, issues, problems and questions shall be presented and discussed. Referencing the first chapter gives each chapter situatedness, context, a framework for the chapter discussions, and a guide whilst allowing for open mindedness, flexibility, originality, creativity and innovation. Each chapter, therefore, needs to state the way in which it addresses research problems, context, purposes or questions, or a mixture if necessary.

With qualitative research where themes are to be developed, each chapter is related to each identified theme. The theme chapters are expected to adopt some sort of network structure where every chapter relates to and cross references each other. I shall probably discuss this more at a later time.

Effectively, the literature review has been completed for now! The next round of edits shall take place before Christmas or at some point early next year.

Thesis Structure

The thesis has been structured to an extent. I say to an extent because it is impossible to plan chapters related to findings within a qualitative research project because essentially the structure and content of these chapters are led by observations in the data and the framework and themes that emerge from the data. The structure leans toward the qualitative nature of thesis structure production, as shall be discussed more in a future blog post.

Research Design

Unchanged at the philosophical level (essentially, moderate realism ontology with an interpretivist epistemology), though the methodology has changed from mixed methods, to grounded theory, and to now more general qualitative methodology with the potential for some quantitative data to be embedded within it. The quantitative data would be used to complement and support the qualitative and perhaps be used to further evidence some of the claims made from the qualitative observations and thematic development.

Regardless of the quantitative, it is the qualitative that drives and dictates the research and, therefore, drives and dictates the structure of the thesis.

Data analysis appears to be leaning towards a mixture of concepts and processes from thematic analysis (particularly the aspect on developing themes), grounded theory (such as constant comparisons, maximising variance, open coding features, and theoretical sampling), and retroductive / abductive reasoning. The relationship between these approaches and the way they have been and are going to be used shall be explained in the thesis and discussed on here when appropriate.

Alex Darracott : 05 Sep 2018 21:24 |  Tags: Design Litreview Reflections Research Design Thesis |  Comments (0) |  Close comments |  Report a problem

Ph.D Update: Thoughts About The Literature Review And Thesis

My gosh, that was a manic week! Focussed on the rewriting and restructuring of the literature review and the thesis more generally. Through the chaos and deep thinking of the new role of the literature review, and dealing with the, at times, feelings of being overwhelmed (trust me, I’d rather be overwhelmed with ideas than be underwhelmed with no ideas), clarity has just started to come through.

I feel more confident and happier now with the new and continuously developing structure of the literature review and the thesis more generally. I feel that now I am beginning to structure the thesis that reflects the nature of a thematic research design, and my Ph.D. experience so far in general. I have discussed the thematic research design in some detail in previous blog posts.

If I were to offer a single word that characterises the new structure of the thesis, it would be: “comparisons.”

I have learnt that to attempt to write as a high calibre thesis as possible, it is not just about critiques, reflections, situating your own research, presenting and evaluating research design and presenting and discussing findings and their applications (in a nutshell) but it’s also about comparisons. By this, I mean, using my experiences of thinking about different philosophies, of using different methodologies and methods as a basis of writing reflective, reflexive and critical comparisons that build towards philosophical and methodological arguments for the research design.

Use the comparisons as a basis upon which critical and reflective thought can be developed, along with where you can clearly evidence, present, demonstrate and show progress in your understanding and deepening knowledge and skills as a researcher.

This is something that has struck me a while ago, particularly when I understood the value of comparing different methods and methodologies. The value lies in using the thesis as a means of charting, highlighting and documenting the development of how my understanding has developed over the years.

A thesis in this sense might, among its many roles, play the role of a historical document. It could be considered a document that guides the reader through how you have come to your philosophical, methodological, and methods selections, and the justifications and arguments that you present, through examining and analysing the comparisons that have taken place.

These comparisons could be at the philosophical level, methodological level, methods level, data source level, and also comparing different types of findings the same phenomena within different types of literature.

It is no wonder I’ve been feeling a little overwhelmed……..

But that’s the way a Ph.D. is and that’s the way I like to progress!

What of the thesis now? I have now divided the thesis into two main parts. The first part deals with the introduction chapter and the literature review chapter and combined I am allocating around 30,000 words. My literature review, when all the notes I have dotted around are combined, comes to about 20,000 words but this is in the process of being completely rewritten and restructured with a new purpose and new functions for my research project. This is work in progress and I will probably talk a little more about this soon. It suffices to say that in order to make way for a lot of new ideas and inclusions I am dropping a fair number of planned discussions that I consider are no longer relevant or needed for understanding my research.

During the past week, and shall be continued for a while, I have been going through the literature review chapters and notes dotted around to decide what I am going to keep, to decided what is to be kept and amended, and to restructure in order to add in new, relevant discussion points.

Sometimes when writing the literature review it is just a case of trying out different presentation approaches e.g., tables, in order to save space. Tables are really useful because they can help to cut down on repeatable information and can help present information more concisely but with the same meaning; or even enhanced, depending on the way the table is constructed.

The other 50,000 words of the thesis represent the real meat and beast of the thesis. I have expanded this section by about 15,000 words in order to accommodate new chapter ideas. Working out the structure, and obviously the content, is work in progress. Currently though, the idea is to write: a methodology based literature review (this would involve the comparison and critique of different coding schemes and approaches the phenomenon of interest ); the comparisons between different approaches to analysing the same type of data at the philosophical, methodological and methods level; the Ph.D. research design itself, and then chapters and sections referring to different themes, the coding scheme itself, and its application in learning contexts. Not to mention the inclusion of more critiques of literature within certain parts in order to verify and validate the developing themes and to discuss the way that existing published themes can be developed further.

This big section of the thesis came about from many reasons, some of which occurred as I began to write about my methodology. These reason include: the need to be reflexive, the need to fully and elaborately document the way in which the new coding scheme is being developed, the way in which phenomenon data can be explored, and also the need to include methods of verifying and validating themes. There are many other reasons but these are the core reasons. I shall talk about each of them in time!

Everything is a work in progress. Sometimes you might feel completely overwhelmed but as I said earlier it is better to be overwhelmed with continuingly new, developing ideas than be underwhelmed with no ideas at all. Keep writing, keep experimenting, keep thinking, and keep going!

‘till next time!

Alex Darracott : 10 Aug 2018 22:30 |  Tags: Litreview Reflections Thesis Writing |  Comments (2) |  Close comments |  Report a problem

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!

Alex Darracott : 03 Aug 2018 21:25 |  Tags: Categories Coding Design Methodology Thematic Analysis Themes Thesis |  Comments (0) |  Close comments |  Report a problem

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!

Alex Darracott : 22 Jul 2018 19:43 |  Tags: Design Methodology Reflections Thematic Analysis Themes Thesis |  Comments (0) |  Close comments |  Report a problem

Ph.D Update: Thoughts on Themes and Categories

I have managed to code through the entire data corpus, involving the development and assignment of codes to relevant data segments; codes that capture the meaning of the assigned data segments, along with embedded theoretical memos within the data. These memos explain the nature, function, context and meaning of the code and the segment’s content and any other relevant thoughts, hypotheses and theories related to the content. However, as I was thinking about the next stage I stated to doubt myself and asked myself the main questions:

What is the real meaning of a theme?

How is a theme really constructed?

What type of theme should I be constructing?

These questions reflected the doubts that I had at the time of my understanding of what a theme really is, and the depth and breadth of which I should involve myself with theme analysis and development for the purposes of my research. These questions are continuously asked but I appear to have some clarity in my rereadings and exploration of the literature. I knew at the time the process of making themes but there was something that bought doubt into my mind: is there really no step between developing codes and developing themes? I wasn’t convinced, and hence the formation of the questions and the subsequent reading of literature. Doubt in this case has been used as a means, a process, of developing questions and of endeavouring to explore topics further.

From what I can understand of the literature, there is varying terminology to refer to the same type of theme but for the sake of brevity I shall focus on a couple of authors who are becoming key writers for my understanding and application of thematic analysis.

Braun and Clarke (2006) define the themes as semantic or latent. Semantic refers to theme development based on just the surface level meaning of the data; essentially, the researcher is not interested in anything beyond what is said literally within the text. There is therefore, from what I can understand, no attempt at understanding context, nuances, variety, diversity and deeper meaning at the semantic level. Semantic level is essentially considered to be a descriptive level of meaning.

At the latent level of theme development, however, there are attempts at going beyond the semantic level and into the realm of interpretation, assumptions, concepts, conceptualisations, meaning making, hypothesis making and theorisation. From what I can understand, Braun and Clarke (2006) describe theme analysis and development as a progress from the descriptive level to the level of interpretation and theorisation. What is identified at the semantic level is taken beyond the obvious and observable to what can be known and understood through theories and interpretations. The latent level, however, is not grounded on hairy fairly assumptions as the latent level assumptions and theorisation processes are grounded in the semantic level. Therefore, what I find or observe at the semantic level I can theorise, hypothesise, assume, and make meaning of their existence, functionality, purpose and context.

This actually makes sense, because how can I possibly stop at just a simple observation? How can I simply consider the existence and meaning of something at only the semantic level and not at the latent level? It doesn’t make any sense to me just to observe and know something at the semantic level: I am immediately drawn to theories, well grounded assumptions, hypotheses, and meaning behind existence and function. Is that because I have an academic mind? Can I perceive beyond the observable? Can I understand meaning and function beyond what is right in front of me and clearly observable? Surely I can if I am drawn to this level of understanding?

Moving forwards, I have this understanding now of semantic and latent themes so surely it is common sense that thematic analysis consists of both themes? That my research would involve the construction of both? According to the approach to thematic analysis by Braun and Clarke (2006), I would be correct.

But wait, there’s more!

Category or Theme? Should we consider both?

After spending a long time pouring over methodological papers about thematic analysis and the idea of theme development, I had more questions than answers. I came across literature that was not only encouraging me to doubt and question what to do in the next stage (I shall discuss this more in a future blog post), but also encouraged me to question my own understanding of what a theme is, and also what a category is. Is it not true that categories are an integral part of grounded theory and therefore I should not worry about them? If only our attempts at understanding the world, of social reality and all the components of social reality were that easy!

Methodological authors differ in their description and discussion of the theme development level and of the definition of categories and themes. After a long while of reading however, I am beginning to lean towards discussions around the likes of Vaismoradi et al (2016), who suggested that the thematic analyst considers both the category and theme, where the category represents the semantic content whilst the theme overarch the category and represents therefore latent data.

What is interesting here therefore is that a theme could consist of multiple categories although some authors name categories as sub-themes. Categories or sub-themes themselves are constructed through the grouping of codes; categories therefore describe and functionalise a group of codes and describe their general meaning. From what I understand of the literature and particularly Braun and Clarke (2006) is that categories (or sub-themes) are constructed first before they are them grouped into themes. But it’s not as clear cut as that, because I’ve just recently read another paper and the author suggests that there is no need for theme development and automatically considered their codes to be themes………..

It is a minefield, but the way my mind works I like the idea of progressing from codes to categories to themes (and, therefore, from semantic or manifest data, different authors label them differently, to latent data; from observation to interpretation and theorisation).

What did I learn from that process? That the whole idea of building themes is to move from semantic or manifest level to the level of interpretation and theorising and this makes a lot more sense to me now and comes to me really as quite obvious. Also reflecting back on the process I have used so far this is something that I have always done, I just wasn’t familiar with the terminology! Also, categories themselves are complex and used in different contexts. Previously I thought categories were terms and features exclusive to grounded theory, but categories are general terms but it appears to me that categories are used differently depending on the research method used. Within grounded theory, they are used to build towards a theory whilst in thematic analysis they are used as part of building understanding and not a theory.

I was right to doubt, because I was able to realise and recognise where I have to build my own understanding. This is an ongoing process, but the more I use thematic analysis and read the relevant literature the more I can understand the way in which it relates to the coding process I am carrying out, and the way in which themes can be used for the next stage of the research.

‘Till next time!

References:

Braun, V., Clarke, V (2006): Using Thematic Analysis in Psychology, Qualitative Research in Psychology, 3 (2), 77 - 101

Vaismoradi, M., Jones, J., Turunen, Shelgrove, S (2016): Theme Development in Qualitative Content Analysis and Thematic Analysis, Journal of Nursing Education and Practice, 6 (5), 100 - 110

Alex Darracott : 07 Jul 2018 21:15 |  Tags: Categories Data Analysis Reflections Thematic Analysis Themes |  Comments (0) |  Close comments |  Report a problem

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!

Alex Darracott : 02 Jul 2018 23:36 |  Tags: Coding Methodology Methodology Chapter Methods Reflections Thematic Analysis |  Comments (0) |  Close comments |  Report a problem

Ph.D Update: Venturing Back To Data Analysis

Since the previous blog post I have returned to data analysis: I have reanalysed previously analysed data, managed to organise my data corpus and where I can find more data to analyse if need be, and have begun to identify potential themes and their potential relationships with each other based on the observations made of the data and coding completed so far. These themes, once determined to actually exist through further analysis, shall then become the core themes of the phenomenon of interest and, therefore, become objects of further data analysis in the phase following thematic analysis. Because more coding needs to be completed I cannot say with any solid certainty that these themes will manifest into core themes that become the focus of the rest of the analysis process; however, I have made enough observations to potentially suggest that the identified themes will be the main themes and any other themes are likely to be sub themes. An open mind, however, is still required and as I code through the data and enter the next stage of thematic analysis, I could potentially identify more core themes.

What have I done in order to reach the current point of coding? The very first step before even coding the data is to become familiar with your data. This has been a journey in itself as I battled with different philosophical perspectives and the most efficient and effective lens from which the particular kind of text should be analysed. I am more or less settled with this now and in the thesis it is a case of detailing what my philosophical beliefs are, the way in which these impact the way in which I perceive, engage with, and interpret the data, and the way in which they relate to the research problem and research questions, and fit in with the rest of the research design.

Away from Philosophy however and onto the data level, becoming familiar with the data makes sense as this gives you the widest scope and the widest sense of the nature of the data. It is through familiarising yourself with the data that you can begin to view high level, abstract structures, potential hierarchies and forms of organisation within the data. The participants might not have intended their interactions with you as a researcher directly or with each other to produce such structures, but those structures do exist in an external reality and can be reflected unconsciously within certain parts of the data at certain times. The nature and composition of these structures, hierarchies and organisations however depend on the type of text being analysed: interview transcripts, for example, shall differ completely compared with group learning transcripts. What I am finding and have found however is that data familiarity can continue past this familiarity phase and onto the coding phase. From my own experiences, as I code through the data I found myself exploring the date closely and begin to be able to view these hierarchies, structures etc at a closer level. These realisations and characteristics of the data were not revealed immediately however, it has taken several rereads and several rounds of coding in order to fully understand the nature of the data (or at least begin to understand the nature of the data) and to therefore begin to understand the constructs and structures of the data’s particular nature. This is something I shall be talking about to a more indepth level in the thesis. It’s important to state that I am not necessarily observing both “macro” and “micro” structures as what I am following is a micro level analysis set within a particular context. It really depends on what you can observe in the data and it depends on the type of text you are analysing, and the purpose of your research. Sometimes interactions can be theologically and politically influenced, for example, and this can be reflected in the data. It’s arguably simply a matter of working through the data and carefully and comprehensively thinking about what it is you are observing.

As for the coding process I am a certain way through the coding phase. I have identified the data corpus and about halfway through the coding phase. The approach to coding I have adopted is what I call a segment by segment analysis. Some argue for a line by line analysis or a sentence by sentence analysis but I am going to be arguing the ineffectiveness of these analytical approaches within the context of my research. Sometimes, a single line or a single sentence is not enough to capture the event or action that you are observing in the data: sometimes you can observe events and actions within half a sentence or half a line, sometimes they can be observed at a greater level than a sentence or a line. Segment by segment analysis based on the interpretation or observation of meaningful events or actions is a more flexible and pragmatic approach for my research: it enables me to break up each block of data into meaningful segments that can be below or above sentence level. I define a segment as meaningful because that segment contains an event or action that is expressed, described, or in some way engaged with that holds a particular meaning for my research purposes. A single sentence, therefore, could contain multiple meaningful events and activities that would be missed by sentence by sentence and line by line analytical approaches.

I have assigned each of these meaningful segments a code, which represents or encapsulates the general meaning or description of the event or activity that is contained within that segment. Again what this event or activity or action is depends on what you perceive, of what’s important to you and your research, of what relates to your research question and research problem, and what the nature of the transcript is. Previously when I used Grounded Theory I generated many codes and as I went through the previously coded transcript I altered some of the codes, dropped a few, and added new codes in. This time of coding more than ever I feel that I have been able to capture the pure essence of each segment that before I did not capture; I can perceive and observe events and activities in the data and view relationships between segments that I had not been able to previously recognise or identify. This has helped during the coding of further transcripts and even then, I have been observing new occurrences, happenings, events and actions within the data that I had not previously observed in the previous transcripts. Unsurprisingly, I have generated many codes.

The more you read through your data and become familiar with it, the more you learn about your data and therefore, with each reading session, new properties, events, dimensions and even higher level relationships and structures reveal themselves. There is much debate however as to whether or not these observations really do exist in the data, or if it is just what we perceive or observe in the data. This is a complex yet fascinating area of debate and shall be something I shall engage with in the thesis.

As I have been coding I have been writing short theoretical memos. The memos that are written at this stage serve the purpose of documenting continuous and evolving process of thinking and theorising about the codes and the data. The memos describe and explain the motivations, intentions, meanings, production, and context of the meaningful segments as well as the meaning of the code itself, and any other thoughts, hunches, ideas, observations and potential hypotheses, questions and predictions relevant to the research. These memos are very important as they ultimately form a substantial part of the chapters related to research findings and discussions, and, they assist you (along with any journals that you might have) with documenting your analytical and theoretical journey.

Your thinking, theorising, comprehension and understanding develops and progresses as you code through the data, and as you identify similar characteristics and the differences between them as well as, therefore, the similarities and differences between similarly coded data segments and, which can form the starting point of identifying and developing your themes, but that’s another aspect of the analysis to cover in another blog post!

Alex Darracott : 29 Jun 2018 22:32 |  Tags: Methodology Chapter Philosophy Reflections Thematic Analysis Thesis |  Comments (0) |  Close comments |  Report a problem

Ph.D Update: Research Methods

Since my previous update, I have been reading more about thematic analysis and discourse analysis, as well as beginning to recode and reanalyse the previously coded data, a process at the time influenced by Grounded Theory.

The reading has illuminated text analysis to be a complex area and therefore, there is no clear or shared consensus of the way in which a specific type of text can be or should be analysed. Different methods and methodological ideas lean towards different type of texts to achieve different purposes and different outcomes; at least, that’s what is perceived from the research methodology textbooks. I think it’s more complex than even that because since I have ideas about methodological fluidity (check earlier blog posts) I think potentially any analytical method can be used for any type of text. The key to all this is to understand your data within the context of the research problem, research questions, research discipline, and your own philosophical beliefs and the extent to which you are consciously aware of the values and importance that your beliefs bring to your research. Within the context of my current thinking about my philosophical beliefs, the research problem and questions, etc. there actually isn’t a single individual approach that convinces me to be the absolute way to analyse data that achieves what I want to know.

This is a challenge because how can I possibly analyse data if I do not know which analytical method is best?

The answer comes from releasing your mind; from allowing your mind to be chained to this idea that a specific analytical method is required to becoming open and sensitive to the data; to allow yourself to become sensitised and to allow the data to speak to you. Obviously I am being guided by the research questions and I have a very general approach to what I am looking for based on the previous readings and analysis of the data via grounded theory, and identifying aspects of the data that grounded theory in my opinion is not able to capture (check previous blog posts). Beyond that I am allowing the text data to “speak” instead of me trying to apply any frameworks to it.

This is challenging, but my thinking is that I shall eventually arrive at either a specific analytical approach beyond the initial stage of thematic analysis, or I shall be able to pragmatically combine different aspects and ideas of different analytical methods in order to enable me to explore the data fully and therefore, enable me to achieve what I want to achieve with the research.

I have read through a variety of different analytical approaches, and what I am finding is there are aspects of these approaches that I think are relevant and aspects that are not. It is from these readings that I am leaning towards the possibility of adopting some sort of pragmatic, functional approach to analysing the data. This would involve the combination of different elements and aspects of different approaches, as long as what I do is relevant to the research purpose and questions, and aligns with my philosophical beliefs. What I will have to do in the thesis is to very carefully, reflectively, critically and analytically describe, critique, evaluate and explain what I am doing, how I am doing things, why I am doing things the way I am doing them, and also evaluate, critique, contrast and compare my approach with other approaches relevant to the analysis of the phenomenon of interest.

I could probably write eighty thousand words for the methodology chapter, nevermind the entire thesis………

This is effectively where I am with the data analysis! I have recoded the data that I have previously coded now under the thinking of thematic analysis instead of grounded theory, and I view no problem so far with the transition of thinking. The current task is simply to recode the data, meaning that I have dropped some of the previous codes and created new codes in order to better represent what is going on in the data. This has come from an increased understanding and awareness of the subject content and the way in which the content can be expressed. And also, I’m going beyond the data: I am beginning to visualise, theorise and conceptualise relationships and patterns within the data, which shall contribute towards theme development as the next part of the thematic analysis as well as the phase beyond thematic analysis. But before I get to that point I shall have to analyse more data than previously as I have changed the scope of data collection and data sampling procedures but I can discuss that another time and more specifically in the thesis.

As I code through the data, develop the themes and then begin to go deeper into the data and explore the contexts and expressions of these themes I shall be able to understand which analytical method is best used for the particular type of text (again, in the context of the research problem, research questions, and my own philosophical beliefs), or which aspects of relevant analytical approaches are best combined in a more pragmatic sense.

This is challenging but fascinating area of research and exploration!

‘till next time!

Alex Darracott : 22 Jun 2018 21:33 |  Tags: Design Methodology Methods Philosophy Reflections Thesis |  Comments (0) |  Close comments |  Report a problem

Previous Week's Update Part B: New Research Design

I have now settled on a new research design. The philosophical and epistemological perspectives remain the same (ontological realist; epistemologically, presently, a mix of interpretivism and constructionism but this needs further elaboration) and the methodological approach is the same (qualitative, possibly moving onto mixed methods methodology though should the need arise). But I have changed methods from a qualitative grounded theory set of methods to a qualitative multi- modal approach that incorporates both thematic analysis and discourse analysis. As a side note, multi-modal is different to a mixed methods: multi-modal is the utalisation of different analytical methods set within the same methodological approach, which in this case of my research the methodological approach is qualitative. A mixed methods methodology would include both qualitative and quantitative analytical methods. The reason for this change, as has been mentioned in previous blog posts, is because the data characteristics that I became interested are, what I argue to be, difficult if not impossible for grounded theory to capture and integrate into a theory of the phenomenon of interest.

During the previous week I have been reading more papers about thematic analysis and discourse analysis that consists mostly of the philosophical and methodological approaches to these methods. This has helped me to understand the way in which they align with my philosophical position, which is important in various ways. Firstly, from the philosophical level, it goes without saying that the use, value, understanding and application of research methods are situated within our understanding of the world, whether we are conscious or unconscious of our philosophical perspectives, and whether or not we make this explicit or implicit. More fundamental than the methods level however is the data level: our philosophical perspectives of the world highly influences the way we value and perceive different types and sources of data upon which we apply the research methods. Secondly, from a methodological perspective, the multi-modal approach has to consist of analytical methods that are used in a way that are compatible with and complements each other; where, for example, findings from each method either support each other, or extend or build upon each other in some way.

I shall be using thematic analysis and discourse analysis together in a way that findings are built upon each other. I am working this out though, and continuing to fine tune their utalisation and compatibility the more I read the literature and understand their application within the context of my philosophical beliefs, the methodological orientation, the wider purpose and objectives of research, and the type and source of data. There is a substantial need, therefore, to ensure that thematic analysis and discourse analysis are combined in a way that not only advocates a sense of unity and extended construction of findings, but also in a way that is methodologically rigorous, valid, authentic and sound. This is a huge topic that I shall engage with to a significant and detailed level in the methodology chapter (talking thousands of words and page after page after page after page after page…….you get the idea!) of the thesis with discussions posted on this blog. However in the meantime it suffices to say that I shall be carrying out a thematic analysis first, then a discourse analysis. It might be an idea, actually, and as recommended by some authors, to verify the products and results of a thematic analysis with existing published literature before engaging with discourse analysis. Either way, what is intended with thematic analysis is the generation of different themes of the phenomenon of interest through coding the data. Following this (and possible verification with published relevant literature), discourse analysis shall be utalised to analyse the discourse within and around these identified themes, leading possibly to a deeper and more substantial understanding of the way in which different social objects are used in certain learning contexts and also the way in which objects can relate to each other.

A reason why this topic is complex and vast is in part because there are various types of thematic analysis and various types of discourse analysis, aligning with differing philosophical and theoretical perspectives (a bit like Grounded Theory and near enough any other method) and therefore differing in process of analysis with each version. This is why methodological compatibility is important; that the variation of thematic analysis and discourse analysis are methodological compatible and are methodologically sound and valid, in part determined by whether or not they can capture and analyse the data characteristics of most interest regarding the phenomenon of interest.

Before I even get to this stage however, the very first task that I shall be engaging with during the coming week, along with the continuing to elaborate on my philosophical and theoretical thoughts and approaches to the research design, is to check the work that I have done so far. Because various authors have suggest that thematic analysis is similar in approach to the open coding aspect of grounded theory (both approaches use an initial coding phase), I have to check that the codes that I have used whilst using grounded theory are compatible or are in whatever way suitable for thematic analysis. From what I can currently understand, the only real difference between thematic analysis and grounded theory is that thematic analysis’ intention is not to develop a full theory but can contribute towards theorisation as a beginning phase of a multi-modal qualitative project. Also, I have to check that the codes I have created can be formed into themes, which are, from what I can currently understand, conceptually different to Grounded Theory categories. At the moment I cannot imagine there being any substantial differences in the coding engines of thematic coding and the initial stage of open coding, or initial coding as other grounded theory writers call it, but obviously this needs further checking.

I am just scratching the surface here with this blog post! It’s going to be a very busy summer with data analysis and the rewriting and further construction of the methodological chapter(s). It’s going to be challenging but exciting, and it helps that I am feeling more confident and happier with my approach compared to grounded theory.

It’s a challenging task alone to work out your research design and the methods to use especially in qualitative, emergent based research. But the best thing you can do is continue to be guided by your data. My research design is data driven: I have come away from grounded theory and onto a combined approach of thematic analysis and discourse analysis exactly because of what I have been observing in the data and coming to know that grounded theory is not able to capture what I really want to explore in the data.

Keep going!

Alex Darracott : 10 Jun 2018 21:02 |  Tags: Design Discourse Analysis Philosophy Realism Reflections Thematic Analysis |  Comments (0) |  Close comments |  Report a problem