Concepts and theory: constructing a ‘gaze’ for your study

I have been thinking a great deal lately about theory, and the role it has to play in research. There are a couple of contexts in which this thinking has been taking place: I reviewed a paper recently that didn’t quite hang together, and after a second reading I worked out that I was missing the significance of the research, largely because the findings were not theorised, even implicitly. I then reviewed an MA proposal in which the student hinted at a particular body of theory in her literature review, but didn’t follow through with an explicit theoretical framework that she then connected to her proposed methodology and mode of analysis. I have also been reading and commenting on a student’s ‘theory chapter’ and have been thinking about how to help her build this theoryology so that it is fit for purpose as she moves into her data, and the analysis of it.

What is theory for?

All of these different ways in which theory, or concepts that are part of theories, have (or have not) been used in all this reading have brought me to one basic conclusion: the thing that theory does in our research is enable us to see the thing we are researching in a new, and hopefully more illuminated light. It enables us to lift ourselves out of the minutiae of what we are researching – the words our participants say, or write in documents, or the issues we are engrossed in while generating and coding data – and see patterns, and bigger contexts and questions. It also helps us to connect our research findings more clearly with the field we are researching in. Without any kind of theoretical or conceptual ‘gaze’ or way of seeing, I wonder if we can do research that adds to knowledge in our field in useful, clear and significant ways.

I do not think that all research needs to employ high-brow, complex or fancy theory – we don’t all need to be Foucauldian scholars, or read Heidegger, Deleuze or Bourdieu in their entirety (thank goodness!). I have worked with many postgraduate and undergraduate students who are scared of theory, because they conflate theory with complexity, and therefore with work that is too difficult and abstract to make sense of. This is a mistake, because theory is actually both useful, and necessary, in research. ‘Theoretical’ research is the wrong term, I think (unless we are actually doing the work of theory-building or theory-creating, which few of us are). What we are aiming for is ‘theorised’ research; research that does more than just describe what it sees, but goes beyond that to consider implications, significance and field-building.

Building the framework we need

Building-BlocksWe need, as researchers, to build a theoretical framework that will hold and guide our research, and that will help us to choose the most suitable methodology, data organisation and coding tools, and analytical tools as well. This is the foundation, in many ways, for our research. We need, within these frameworks, to select and connect concepts that help us (and our readers) to understand the part of the world we are researching clearly, and in a way that coheres both epistemologically and ontologically. In other words, we need to build, out of our chosen concepts, theoretical frameworks that make sense in the context of the study we are engaged in, and that help us to see more clearly the things we are researching, and say something new, interesting and useful about them. But we cannot just cherry-pick many shiny concepts that look and sound interesting, trendy or clever. We need to select carefully, to ensure, at a deeper level where we consider what we conceptualise as knowledge or truth and how that comes to be known, that we have agreement between the component parts we are building our framework with.

If you are, for example, an epistemic constructivist in terms of your understanding of what the world and knowledge about it entail and how we can come to know anything, you would not choose concepts for your framework from a critical or social realist school of thought, because at a deeper ontological and epistemological level, there would be disagreements that would be difficult to reconcile. Thus, you need to build your framework with a view to the epistemological and ontological underpinnings of the theories and concepts you are reading about and considering.

You also need to choose parsimoniously: how many concepts do you really need to build your framework? How much theory is enough for your problem, and your readers? Often, you can’t really know the answer until you have generated and analysed your data, so the theoryology you start off writing may be larger and more complex than you actually need it to be to tell the story of your research, its findings and their significance. You can and may well cut your theoryology post-analysis, trimming it to be as concise, clear and relevant as it needs to be within the context of your completed research.

However, even though your initial theory chapter draft is by no means final, try not to simply lump all the concepts you find interesting and helpful together in a long list, summarised and synthesised together. As you are writing this part of your thesis, think about the work the concepts you have chosen are doing for you. How do they connect with your research problem, and what relevance do they potentially have in this study? Your reader needs to be written into your theoretical gaze, so that when they come to read your methodology, and the findings and discussion thereof, they can see the theory coming through, and shaping and informing choices made and analyses offered.

etsy specsThere are, of course, different kinds of levels of theory – substantive, meta, applied and so on. I’m not sure I really understand all the differences, to be honest, but I think, regardless of the kind of theoretical framework you are building for the specific research problem you are investigating, it’s useful to remember that the role of theory is to provide you with principled insight: insight into the problem and context you are engaged in that helps you lift out of the murky mess of details, case studies or quantitative data and ask, for example:  ‘Why is this particular thing happening in this way? What could be causing this? How could this be addressed or solved or thought about in a new way? How could we address it, and what would the implications be? Theory gives you the means to go beyond your small research problem and think about it in a more principled, generalised way, so that rather than producing many small scale studies that cannot speak beyond specificities, we can produce research that uses local, smaller scale cases or data to build our collective knowledge about the issues, problems and solutions that have relevance within our spheres of interest, research and praxis.

Spinning the ‘golden thread’ that can sew your PhD together

When I was doing my PhD, someone at some stage asked me (probably in response to my ramblings about what my PhD was about): ‘what is your “golden thread”?’ This stumped me. My what? I hadn’t really heard that term before, although my supervisor has talked about it since, as have other colleagues who all supervise students – it seems to be a fairly common notion then, this notion of a ‘golden thread’ with which you can ‘sew’ your PhD thesis together. But what, indeed, is a golden thread, where do you get one, and how do you work out how to sew your PhD together?

To begin with what it is: the golden thread is, for want of a better explanation, the central argument that pulls through your whole thesis, and creates coherence across the literature review, the research questions, the theoretical and conceptual framework, the methodology, and finally the analysis and organisation of the data and the conclusions you are able to draw (on the basis of that argument you set out to make). It sounds quite straightforward when it is put like this, but in my experience (and in the experience of many other PhD students) it is really difficult to find and hold onto over the long course of researching and writing a PhD thesis. Another way of thinking about it would be to keep reminding yourself about what the point of your PhD is. What is it actually about – what are you trying to say here? A friend of mine types her main research question into the header of each page she works on in each of her chapters, so that she is not tempted to go off track in her writing and thinking; another friend wrote a haiku about the main point her PhD was making, and stuck it in a place she could see it when she was writing; another wrote her research questions on several sticky notes and put them above her desk at work and her desk at home, so that she had them in front of her whenever she was working on the thesis. I kept a fairly faithful research journal, and re-read it often, to remind myself what I was actually making my argument about.

So, how do you get one? Sadly, you cannot go to and order one; you have to make or build one, and this takes time and is really challenging. I think of it a bit like Rumpelstiltskin turning all the straw into golden thread (except without all the creepiness). What you have when you start a PhD is straw – ideas, concepts, theory, methods, questions, literature you have read – and you have to pull the right pieces of straw together to make a strong, shiny length of golden thread that you can then use to sew a beautifully coherent and persuasive PhD thesis. Like theoretical frameworks, analytical frameworks, literature reviews, an argument is built part by part and always in relation to the main question it is being made to answer. There are key parts of the thesis that you need to put into place as you go to help you create strong and coherent sub-arguments that build towards the overall, central argument your PhD will make.

You need to scope your field well, and find a gap into which your research could fit – this helps you to start asking more refined questions, which can turn into research questions. You need to move from this reading into tougher theoretical and conceptual territory – you need to find your theoryology, and with it, further refinement and focus of your research questions. You need then to consider how you will answer these questions: what data will you need? How will you find it? What will you do with it in order to make sense out of it, and select what is relevant to analyse in relation to your research questions? Then you need to further consider the research questions you are trying to answer as you connect the theory with the data in the process of analysing it, and using it to tell the story that answers your questions, and explains why both the questions and the answers are important to your readers, and your research community or field. Following a logical and coherent process, and pulling each part of the process through with you into the subsequent stage or part of the process, really helps. In other words, don’t leave all your theory and research questions behind when you plan out your methodology and generate your data. Don’t forget the scoping of the field you have done, the research questions you are asking, and your theoretical framework and conceptual tools when you organise and begin to analyse that data in order to build your strong, shiny argument.

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The argument, in the end, is the thing with the PhD. You cannot have your readers get to the end of it wondering: ‘So what? Why did I just read all of that? What was the point?’ The golden thread is just that: the answer to the ‘so what’ question; the point of the research; the central argument you have made on the basis of the research you have done. Without it you don’t have a PhD thesis; you have parts of a whole that has not been realised or pulled together. In order to sew those parts into something that represents what Trafford and Leshem have termed ‘doctorateness’, you need to channel Rumpelstiltskin, and start turning all your straw into your own golden thread, so that you can sew the parts of your research into a coherent, persuasive, strong PhD thesis.

‘Retrofitting’ your PhD: when you get your data before your theory

I gave a workshop recently to two different groups of students at the same university on building a theoretical framework for a PhD. The two groups of students comprised scholars at very different points in their PhDs, some just starting to think about theory, some sitting with data and trying to get the theory to talk to the data, and others trying to rethink the theory after having analysed their data. One interesting question emerged: what if you have your data before you really have a theoretical framework in place? How do you build a theoretical framework in that case?

I started my PhD with theory, and spent a year working out what my ‘gaze’ was. I believed, and was told, that this was the best way to go about it: to get my gaze and then get my data. In my field, and with my study, this really seemed like the only way to progress. All I had starting out was my own anecdotal issues, problems and questions I wanted answers to, and I needed to try and understand not just what the rest of my field had already done to try and find answers, but what I could do to find my own answers. I needed to have a sense of what kinds of research were possible and what these might entail. I had no idea what data to generate or what to do with it, and could not have started there with my PhD. So I moved from reading the field, to reading the theory, to building an internal language of description, to generating data, to organising and analysing it using the theory to guide me, to reaching conclusions that spoke back to the theory and the field – a closed circle if you will. This seems, to me certainly, the most logical way to do a PhD.

But, I have colleagues and friends who haven’t necessarily followed this path. In their line of work, they have had opportunities to amass small mountains of data: interview transcripts, documents, observation field notes, student essays, exam transcripts and so forth. They have gathered and collected all of these data, and have then tried to find a PhD in the midst of all of it. They are, in other words, trying to ‘retrofit’ a PhD by looking to the data to suggest a question or questions and through these, a path towards a theoryology.

Many people start their doctoral study in my field – education studies – to find answers to very practical or practice-based questions. Like: ‘What kinds of teaching practice would better enable students to learn cumulatively?’ (a version of my own research question) Or: ‘What kinds of feedback practices better enable students to grow as writers in the Sciences?’ And so on. If you are working as a lecturer, facilitator, tutor, writing-respondent, staff advisor or similar, you may have many opportunities to generate or gather data: workshop inputs, feedback questionnaires, your own field notes and reports, student essays and exam submissions, and so on. After a while, you may look at this mountain of data and wonder: ‘Could there be a thesis in all of this? Maybe I need to start thinking about making some order and sense out of all of this’. You may then register for a PhD, searching for and finding a research question in your data, and then begin the process of retrofitting your PhD with substantive theory and a theoryology to help you work back again towards the data so as to tell its story in a coherent way that adds something to your field’s understanding or knowledge of the issues you are concerned with.

The question that emerged in these workshops was: ‘Can you create a theoretical framework if you have worked so far like this, and if so, how?’ I think the answer must be ‘yes’, but the how is the challenging thing. How do you ask your data the right kinds of questions? A good starting point might be to map out your data in some kind of order. Create mind-maps or visual pictures of what data you have and what interests you in that data. Do a basic thematic analysis – what keeps coming up or emerging for you that is a ‘conceptual itch’ or something you really feel you want or need to answer or explore further? Follow this ‘itch’ – can you formulate a question that could be honed into a research question? Once you have a basic research question, you can then move towards reading: what research is being or has been done on this one issue that you have pulled from your data? What methodologies and what theory are the authors doing this research using? What tools have they found helpful? Then, much as you would in a more ‘traditional’ way, you can begin to move from more substantive research and theory towards an ontological or more meta-theoretical level that will enable you to build a holding structure and fit lenses to your theory glasses, such that you have a way of looking at your data and questions that will enable you to see possible answers.

Then you can go back to your data, with a fresh pair of eyes using their theory glasses and re-look at your data, finding perhaps things you expect to see, but also hopefully being surprised and seeing new things that you missed or overlooked before you had the additional dimension or gaze offered by your theoretical or conceptual framing. But working in this ‘retrofitted’ way is potentially tricky: if you have been looking and looking at this data without a firm(ish) theoretically-informed or shaped gaze, can you be surprised by it? Can you approach your research with the curious, tentative ‘I don’t know the answers, but let’s explore this issue to find out’ kind of attitude that a PhD requires? I think, if you do decide to do or are doing a PhD in what I would regard as a middle-to-front sort of way, with data at the middle, then you need to be aware of your own already-established ideas of what is or isn’t ‘real’ or ‘true’, and your own biases informed by your own experience and immersion in your field and your data. You may need to work harder at pulling yourself back, so that you can look at your data afresh, and consider things you may be been blind to, or overlooked before; so that you can create a useful and illuminating conversation between your data and your theory that contributes something to your field.

Retrofitting a PhD is not impossible – there is usually more than one path to take in reaching a goal (especially if you are a social scientist!) – but I would posit that this way has challenges that need to be carefully considered, not least in terms of the extra time the PhD may take, and the additional need to create critical distance from data and ‘findings’ you may already be very attached to.

Building a theoretical framework for your study

I am presenting a seminar tomorrow to PhD students on how I developed my PhD’s theoretical framework. When I agreed to do this workshop last year, I thought this would be fairly easy to do. However, I am finding it difficult to articulate the differences between substantive theory and what I think of as ‘framework theory’, and how to use both in different ways to contextualise your study and build a framework for it. This was, for me, the first and biggest ‘threshold’ (to use Meyer and Land’s term) that I crossed in my own PhD, and it’s a very important one.

There are two main places you tend to use theory in a social sciences PhD (I’d be really interested to hear about the differences between these and PhDs in the natural sciences): in your literature review where you contextualise your study and the rationale for it, and in your theoryology, as I call it, which works at a more ‘meta’ level to discuss how you understand the questions you are researching, how you plan to approach the research, and how you will move from theory to methodology and methods, and on to analysis. You come back to the theory in your conclusion, connecting it to your findings, but it needs to be laid out ahead of this in the earlier chapters.

I have written about writing a literature review, and using the research in the field in a more substantive way to build the context and rationale for your own study, and situate it within your field, so I won’t focus too much on that in this post. Here, I would rather focus on the more difficult-to-articulate issue: the theoretical framework. The reading PhD students almost always start with is the substantive ‘theory’ and research. You need to know what research has been done in your field, what the key issues and questions are, where the field is heading, and where you, coming into that field, can place your own research. But you may well find, if you spend long enough reading the substantive theory and research, that you start going in circles, confirming what you have already found out and slowly getting stuck. This is when you need to take a break. If you know what the lie of the land is, and you have a grasp of the trends, issues and research problems that are being or have been researched, and where the gaps you, you now need to find your question, your project. You should find the topic you want to research, and the focus, from your substantive reading, but you need to hone this to turn it into a lightning rod for all the other research and reading you will do to cling to. In my (albeit limited) experience, moving on to the ‘meta’ stuff at this point helped me to do this.

What do I mean by ‘meta’ stuff? The Free Dictionary defines metatheory as ‘a formal system that describes the structure of some other system, and ‘a theory devised to analyse theoretical systems’. Slightly obscure definitions on their own – theories that can analyse theories sounds like more going round in circles. But I’m going to concentrate on the words ‘formal system’, ‘structure’, and ‘analyse’ because this, for me, is what a theoryology hinges on. What comes after you  have focused on one research question your study can explore and answer? You need to design a methodology, and then use appropriate research methods to generate data, and then employ an analytical framework to organise that data. Thereafter, you need tools of analysis to make sense of the data in relation to the theoretical structure you have put together, and the field in which your research is located. All of this is nigh on impossible to do in any coherent, structured and organised way without an organising structure that can hold the project in place and on course. You need, then, a formal system, a structure, that can inform the methods you use, your data generation plans and strategies, and the ways in which you then organise and analyse the data to answer your research question. This formal system is your theoretical or conceptual framework (your theoryology).

But how do you build one? What kind of theory is theoryology-worthy? Theory is a weird word here, and it is often misused. I am sure I misuse it all the time. Often, when we say ‘theory’ we mean ‘other research that has been done in the field that informs how I think about my own research and/or practice’. By metatheory is meant something that, while derived from empirical research and data, is raised a bit further above the empirical to create a more generalised or abstract set of principles that can be applied as a formal organising or structural system in a range of studies. Theoretical frameworks are built out of this kind of theory. You need an abstract, generalised set of principles that you can adapt and apply to your own study, and that will inform what data you choose to generate, and how you then can organise that data and decide on methods of analysis. A helpful way of finding your way to this kind of theory that might be right for your study is to look at what kinds of frameworks or conceptual tools other researchers are using in your field or allied fields.

Finding a framework for your study is essential in the social sciences, certainly. Without an overarching metatheory to organise and analyse your project you may end up generating a mountain of data that you just get lost in because you’re not sure what is important or what is not; you may end up with the wrong kinds of data; or you may write a ‘findings’ chapter that describes rather than analyses the data in relation to the field itself, and the question your are answering, which would leave you in a precarious position, given the pressure on PhDs to make new contributions to knowledge. Don’t be too worried if this process of developing your own framework takes time (I spent most of my second year on mine). In my experience, if you have a solid framework that is chosen well and clear to you, what follows is generally more organised and less fraught on the whole*.

*Of course, all sorts of things can and do go wrong in a PhD, and this is just my experience, but colleagues who have followed this route have found similarly that the data generation and analysis process has been less stressful if they have a clearer sense of what they are looking for, why, and how to look at it.

Disciple or pathmaker? Critiquing your theoretical ‘gurus’

I recently enjoyed an amazing week at the University of Sydney, where I spent time talking about my work with the researcher who developed the conceptual tools I used to frame my theoryology and methodology, as well as with PhD scholars and researchers who are also using these tools in their own research. Two of my friends asked me whether the week with my ‘guru’ was a good one, and these comments coupled with a recent seminar I attended on data and theory gave me pause for thought. I do not think of this person as my ‘guru’, although I find the tools truly brilliant, and I am so enjoying working with them in my research and practice. I think (I hope) I am capable of putting aside my admiration for both him and this conceptual toolkit to offer critique and questions, and to find ways in which I can contribute to this field of research and practice with my own work. But, when you are new to a particular theoretical or conceptual approach, or new to a significant piece of research like a PhD which requires so much deep and extended engagement with theory, it can be really difficult to do this. I certainly found it difficult to be critical of the concepts when I was working with them during the PhD. This ability I now feel I have to critique the tools and the theory is very much a post-PhD thing.

Why are we so tempted to make ‘gurus’ out of our favourite theorists? Why is it hard to be critical of the theories we have chosen to use to provide the foundation and analytical tools for our research, especially in a PhD? I think, for me, the answer was quite simple: because I needed them to be right. I really wanted to have answers to my questions, and I really needed the theory and the tools to provide me with those answers. I suppose, too, I was afraid that pointing out gaps, holes and areas where the theory was still fuzzy would ultimately weaken my stance and my arguments. I opted, without quite realising it at the time, for being a bit of a theory disciple. This was in big part due to what I have just said, but it was also due to the fact that I was so excited about the ways in which the theory opened my eyes to things in the environments I was researching that I had not been able to see otherwise, or in quite those ways, that I got a bit carried away by just how thrilling my research actually was for me when I got into the data  and started finding tentative answers to my questions.

One of my thesis examiners suggested to me in the report I received that I should exercise caution in getting too excited and too carried away. Part of the role of a good researcher is to be able to stand back a bit from the thing we are looking at, or the lenses we are looking through or with, and wonder if we are seeing the right sorts of things, or asking the right sorts of questions. We need to be able to see gaps, holes, inconsistencies, not just to avoid being accused of having a weak argument and having no defence in your viva or examination, but more importantly to show that you are clear enough on what theory you are using, as well as why and how you are using it, that you can show that although there may be questions you cannot yet answer, or things you cannot yet see, you know that the answers you have are good ones, even though they are always partial and fallible. You aren’t answering all the questions in your PhD – you are just answering one – but you need to be able to show not just all the reasons why your theoretical framework and tools are right for answering this question; you also need to be able to be critical and careful, so that you anticipate and can stand up to critique of your own work and answer back to the critics.

Rather than being theory disciples, I think we should be aiming to be research pathmakers. Theory on its own is a bit pointless. Your research will bring any of the theory you use to life in a range of ways depending on how you draw the framework, and also what data you choose to generate, analyse and interpret using the theory. You can be a pathmaker, even if the bit of path you are chipping out for others to walk on is small or short. But, this is not easy. I think you have to be well-read and brave to be critical, and you also need to know your theoryology well. It is almost impossible to offer a sound and useful (but not too damning) critique of your own theoretical framework unless you really know it well. In chipping out your piece of path, you will be following the paths of those who have gone there before you, and you’ll hopefully be either extending the paths they have created, or branching off in slightly new and unexplored directions, rather than simply smoothing out their already-trod path or pruning the bushes on either side of it :). It’s hard to be this kind of pathmaking researcher if you are not going to be brave enough to take your ‘gurus’ off the pedestals you could tend to place them on when you start your PhDs, and offer thoughtful, relevant and useful critique that shows your readers just how well you do know your own field, and that adds depth and credibility to your own researcher’s voice.

I have learned that I don’t need the theory or my answers to be ‘right’ (if they even can be); but I do need them to be credible, productive and interesting, and being able to both believe in and offer measured critique of the theoryology that serves my research well will certainly help me to find my ways to the kinds of answers I am seeking.