Research problems: too big, too small or just right?

I have been working, in recent weeks, with two groups of postgraduate students working on research proposals. These workshops were planned specifically to assist these students with clarifying their research problem, research questions and potential argument. This is turning out to be a little tougher than I thought it would be. There seem, right now, to be two reasons for this: the first is that focusing on just one small, manageable project is difficult when there are so many possible things that could be researched and written about. The second is more about experience, and learning to trust that if one follows a research process and a supervisor, the results will be positive in the end.

Size and scope: finding a research problem you can solve

The first place you start with any research project is with the problem that needs to be solved. Sometimes, as postgraduate students (especially at more junior levels, like Honours and Masters) you may be guided quite firmly to a research problem by your supervisor, perhaps connected to their own research. Most of the time, hopefully, you are able to find one that excites and interests you, and that you really want to find out more about. In the first case, it may be easier to focus on a problem of manageable size and scope, because that may well be part of the process of guiding you to that problem. But most of the time, you will need to work out, through a process of reading, writing and working with supervisor feedback, what the right size and scope of your project is.



This is not necessarily an easy or even quick process, and finding your way to the research problem that is neither too big, nor too small, can be frustrating. I started my own PhD sending my supervisor an email outlining my research problem, thinking – here we go! She emailed back a week later outlining the four or five (!!) PhD theses I could actually be researching based on that email. She helpfully outlined them all as she saw them, and then asked me which one I wanted  pursue. This, of course, was partly very helpful and exciting, and partly anxiety-inducing. Surely just that one seemingly small problem was in no way big enough for a whole PhD? I had to trust her experience and wisdom on this, and I am so glad I did because that problem was indeed big enough, and if I had fought her and tried to think I knew better, I may have had a much more frustrating time researching and writing my thesis.

I think, based on my conversations with these students in my workshops, and my own experience, that part of the anxiety is that we make the project too big in our heads. We make it everything about ourselves and our work as students at that particular level. We try to write ALL the PhDs and MAs and Honours mini-theses in our one small project. Part of this urge to do ALL the research may stem from a fear that if we just make one small, but clear, argument we won’t be doing enough to prove we are worthy of the degree being awarded, or what comes after. Part of it may stem from an unwillingness to choose, because it means closing doors on other ideas and projects that also interest us.


What I had to learn, and what all postgraduate students and researchers need to learn, is to manage one project at a time, and to resist turning the PhD (or MA or Honours project) into everything. Especially at PhD level, which often leads to a career based on academic research, writing and possibly also teaching, the PhD is the door-opener to that career, not the career itself. It is the stepping stone to other and further research and writing, not the best and brightest piece of research you will ever do. As lovely husband kept telling me: ‘It’s a project. You have to manage it well and move on’.

What this means for finding and defining your research problem is that you need to firstly, trust your supervisor when they caution you about aiming too high and going too big. They’ve done this before you, they have learned some of the lessons already, and their advice comes from their desire for you to succeed and not spend months and years floundering on a project you cannot realistically manage or complete. Secondly, you need to be brave enough to close doors to other shiny and interesting ideas and projects and keep them closed until your PhD or MA is finished. They’re not barred forever – there are many problems to solve, and many ways to solve them and if you’re signing up for academia, you’ll have time to reopen doors and revisit ideas you’ve had to put on hold while working on the PhD or MA.

revolving doorhotel-corridor

Continuing to read, look for theory, change methodologies, look for new and more data, and so on will likely pull you in too many different directions, and will slow your progress on the project in front of you. Moreover, it may actually lead you to feeling that the project you are actually working on is holding you back from and making you give up on other cool projects and possibilities, creating a potentially negative and fractious relationship with it. It is worth remembering that this project – PhD, MA or Honours – is actually going to open doors for you to many other exciting opportunities for work and research, but it can only do that if you finish it, and get your degree, and have the skills, knowledge and abilities to move on to whatever comes next.

A first step is finding one small, defined and focused research problem that you can actually follow up on in the timeframe you have, and with the resources at your disposal. Focusing on one thing, while this does mean at least temporarily pushing other things into the background, will give you the space and time to do what a postgraduate degree is really trying to do: help you develop your capacity for more independent thinking, reading, writing and argumentation.


Researching your own ‘backyard’: on bias and ethical dilemmas

This is a post particularly for those in the social sciences and humanities who may be doing a form of ethnographic research within the context in which they work or study – in other words, doing ‘insider research’ to use Paul Trowler’s term. Researching a context with which one is intimately familiar and in which one has a vested interest can create possible bias and ethical dilemmas which need to be considered by researchers in these situations. The last thing you want, in presenting your completed research, is for your findings to be called into question or invalidated because you have not accounted clearly enough for issues of insider bias, and your own vested interests.

Insider bias and vested interests

In the article cited in this post, Trowler considers issues of bias in data generation. Bias in research can be defined as having only part of the ‘truth’ in your data but treating that part as a whole, ignoring other possibilities or answers because you are prejudiced towards the ones that best represent your interests or investment. If you are working in a context with which you are familiar, especially your own department or faculty, or an organisation in which you have worked or do work, you will have a vested interest in that context. Either you want everyone and everything to look amazing, or perhaps you are unhappy about certain aspects of the ways in which they work and you want your research to show problems and struggles so you have a basis for your unhappiness. Either way, you have to acknowledge going in that you cannot be anything but biased about this research.

bias blindspot

However, acknowledging that you are biased, and detailing what that bias might entail for readers and examiners, does not undermine your position as researcher. By making yourself aware of potential blindspots in your research design – for example the participants you have chosen, or the cases you are including and excluding from your dataset (and why) – you can better head off possible challenges to the validity of your data later on, and you can strengthen your research design choices. Be honest with yourself: there is a balance to strike here between being pragmatic and strategic in choosing research participants, sites, or cases that will be accessible and that will yield the data you need to make your argument, and between choosing too neatly and risking one-sided or myopic data generation. Why these participants, these cases, these sites? Are there others that you know less well that you could include to balance out the familiarity, and increase the validity of your eventual findings? If not, how might you maintain awareness of your ‘insiderness’ and account for this in analysis and discussion later on?

You need to account for these decisions and questions in your methodology, and discuss what it means for your study that you are doing insider research, and that this does imply particular forms of bias. I don’t think you can get away from being biased in these cases, but you can think through how this may affect your data generation processes, and your analysis as well, and share this thinking with your readers frankly and reflexively.

Insider bias and ‘intuitive analysis’

Another point Trowler makes concerns insider ‘intuition’ when analysing the data you have generated and selected for your study. You may be analysing a policy process you were part of, or meetings you sat in on, or projects you were involved in. You have insider knowledge of what was said, the tone of the conversations, background knowledge (and perhaps even gossip) about participants – in other words, you have a kind of cultivated ‘intuition’ about your data set that you reader will not be privy too. Accounting for bias here is crucial, because if you cannot see it, you may rely too much on this insider intuition in analysing your data, and too much of the language of description you are using to convey your theorised findings will be tacit and hidden from the reader. They will then struggle to understand fully on what basis you are claiming that X is an example of poor management, or that Y means that the department is doing well in these particular areas.


It is thus vital that you get feedback here on whether it is clear to your reader why you are making particular claims, and whether they can see and understand the basis on which you are making such claims. Do they understand your ‘external language of description’ or ‘translation device’ to use Bernstein’s and Maton’s terms respectively? If they do not, you may be relying too much on your insider view of your case or participants, and may need to find a way to step back, and try to see the data you are looking at as more strange and less familiar. Getting help from a supervisor or critical friend who can ask you questions, and expose and critique possible points of bias is a useful way to re-interrogate your data with fresher eyes.

Ethical dilemmas

An ethical dilemma is defined as ‘a choice between two options, both of which will bring a negative result based on society and personal guidelines’. In research, this definition could be nuanced to suggest that an ethical dilemma presents itself when you have to make a decision to protect the interests of your research or the interests of your participants or study site. For example, in an interview with a senior manager you learn information that may be better off staying private and confidential, yet would also add an important and insightful dimension to your findings. What do you do? A participant in your study asks you for help, but to help might be to prejudice that participant’s responses in a later survey or interview, possibly skewing your data. Yet it is your job to help them. Study first, or job first? These are the kinds of dilemmas that can arise when you do research in the same spaces in which you work, and with people you work with and have other responsibilities to outside of your research.


As researchers we have a duty to be as truthful and ethical in our research as possible. We are working to create and add to knowledge, not to simply maintain the status quo. In your study this may mean being carefully but resolutely critical, reflective and challenging, rather than only saying the palatable or easy things to say. This work is always going to present difficulties and dilemmas, but accounting as far as possible for your own bias and vested interests, and for your own relevant insider knowledge, can create space in your study for the development of your own reflexivity as a researcher, and can bolster rather than undermine the validity and veracity of your findings.

Trowler, P. (2011) Researching your own institution: Higher Education, British Educational Research Association online resource. Available online at []

Slogging away, slouching and sailing: developing a research work ethic

Recently I read a post on one of my favourite blogs written by Susan Carter on managing emotion in doctoral supervision, and in doctoral writing. What stood out for me were her comments on managing emotions around producing written work for comment and feedback. She comments that she no longer gets emotional about her writing; as an experienced academic she knows it is part of her job, and something she just has to do (and likes doing). She comments that students and academics would be helped by having a ‘workerly’ approach to writing, and also by learning to manage emotions that can lead to writing blocks or paralysis.

This notion of a ‘workerly’ approach to academic writing has been floating around in my head since I read her post a few months ago. I think I have developed a more workerly approach to writing in the last two years especially; I have chosen an academic career and I do know that producing publishable writing is something I need to do as part of this career. I like writing, and while I don’t enjoy all the kinds of writing and reading I have to do, on the whole I derive pleasure from these scholarly activities.

But I still get emotional about my own writing; I still get stuck, and down, and worry about whether and how I will get up again. I do, however, get up. This being down and getting up and carrying on has to do with being resilient, and part of this is developing and maintaining a work ethic about research and writing. By this, I specifically mean working more consciously on what Susan Carter speaks about in her post: learning to manage emotions so that they do not block your progress, and being a little more ‘workerly’ about your writing.

Waiting for the mojo (can leave you waiting a long time)

I, like many writers, have what I think of as my ‘writing mojo’. I am sure many of you have experienced the mojo when it is strong – the ideas flow and the words come and the sentences hang together, and you sail through a morning’s writing that leaves you with a pretty brilliant piece of work to send to a supervisor, or build on tomorrow. These mornings are what keep me going, sometimes – knowing that on the days when the mojo seems weaker, days of sunny sailing through writing are still possible, and will come again.

The reality is that most mornings or days of writing are not necessarily like this. They see me slogging away at a measly 100 words, slouched over my computer, getting up every ten minutes because I can’t concentrate for longer, or find the right word, or figure out what I want to say. I agonise over synonyms, and wonder if I have used ‘like’ too many times. I edit, more than I create. It is hard, painful work. It makes me feel frustrated, and inadequate, and slow.

This is me when I am working on my writing, metaphorical quill in hand, completely idealistic task list mocking me gently

These emotions are difficult to manage. But manage them I must, otherwise the mojo may not return. I am learning that all that slogging is necessary for the brief bright mornings of sailing through my writing to be possible. If I spent all my writing time waiting for the mojo to be strong, and the ideas to flow, I might be waiting a very long time, and I’m not sure I’d get much writing done at all. This, then, is when I need to be workerly in my approach to my writing.

Planning and pragmatism

Being workerly, to me, means being pragmatic, and planning my time as carefully and realistically as I can. It means instead of messing around on email, I need to make myself sit down for two or three pomodoros to read two or three relevant papers and make notes. It means setting myself one task for a morning or a day: writing an introduction, or coding a small set of data, and holding myself to that task until it is done. This, for me, is slogging. It is the work of being an academic writer that is often boring, and tedious (especially coding and transcribing data), and it feels like trudging through treacle because I’m not actually producing something tangible to show for my time spent at my desk (yet).

Yet, in the midst of this slogging is where my work ethic is formed and strengthened. The ability to push through the tedium, boredom, frustration and anxiety and continue to do the small tasks that make the mojo stronger and make sailing through the writing possible is part of what it is to be an academic writer. It requires fortitude; sometimes it probably feels like you are being unkind to yourself when you have to make yourself work on part of your paper or PhD on a Saturday morning when the week has been long, and you are tired. But all those little tasks, especially the difficult ones, build your work ethic and your researcher resilience, and they move you forward.

mojo giftThere are no easy answers to building and strengthening a work ethic, especially when you are a part-time student with many other demands on your time and headspace. But it helps me to remember that the mojo isn’t magic: it’s created over time through many small, seemingly unconnected tasks that all add up to a finished project if I sit up straight and slog away.

Building ‘researcher resilience’

In my other work life, when I am not being a writer at home with my cats and endless cups of tea, I run workshops with academic lecturers and students, mostly focused on academic writing and research. Recently, I spent a productive day with an academic department at my former university helping them think about improving postgraduate supervision and scholarship in their growing Honours, MA and PhD programme. One of the most interesting points that kept coming up was the need to help their students develop a kind of ‘researcher resilience’. In this post I’d like to flesh out what this kind of resilience could mean, and how you could build it in your own research or supervision spaces.

What does it mean to be resilient?

Resilience is generally defined as having the ability to recover from or overcome misfortunes or struggles. Essentially, life or work or relationships will knock us down, and our ability to get back up ad keep moving forward, hopefully reflecting and on learning from the experiences that have knocked us, is resilience.

One of the issues the supervisors and lecturers I worked with recently commented several times that their students don’t have sufficient ability to recover from struggles in their research and writing, and when they are knocked down, they struggle to get up and keep moving forward. This obviously impacts on their supervisory relationships, as well as on their attitude towards their research and writing, and their ability to keep making progress towards completion. Developing researcher resilience is thus important to being a successful postgraduate student, and researcher.

Researcher resilience

If resilience in general is the ability to get up after being knocked down, metaphorically speaking, and keep going, then what is resilience in research? I would suggest, based on my own studies and research career thus far, and what my peers have shared with me, that it is the ability to manage disappointment and unexpected hurdles and keep making progress, encouraging and bolstering yourself along the way. These disappointments and hurdles may be many, but the ones that seem particularly significant to the supervisors I have been working with are: dealing with difficult and challenging feedback; finding relevant literature and resources; and grappling with complexity in research.

thewritingcampus.comFeedback:  I have written here and here about working with feedback. This is a tricky issue for writers, especially for writers who are postgraduate students anxious about doing well, pleasing supervisors and examiners, and earning their degree. It is often taken for granted that students, particularly at postgraduate level, will know how to decipher, make sense of, and then act on the feedback they are given. But, more often than not, students struggle to understand what their supervisor wants, either because of a lack of confidence, opaque and confusing feedback, too little feedback, or a combination of these and perhaps other factors. Feedback needs to be mediated to students, to enable them to learn how to make sense of it, claim ownership of it, and respond in ways that enable them to move forward with insight, and with increased confidence.

Too often feedback flattens students with feelings of inadequacy, shame and fear of failure. Learning to manage these feelings so that you can respond emotionally to feedback, but work through those responses to an intellectual response through further writing, research and revisions – this is what students need to learn how to do. While supervisors can learn how to write and speak their feedback more effectively, clearly and supportively, students also need to realise that everyone gets feedback that hurts, and demands more work, and that this is part of the writing process that they need to learn to manage more productively over time.

Finding resources: Another key issue raised, especially for ‘younger’ postgraduate students working on Masters degrees or very new to the PhD, was a lack of resilience around resource gathering. This referred to literature on their chosen research problem, as well as participants for empirical studies, archival materials, and other relevant research-related resources needed to make progress.

It isn’t always easy to find published research on your chosen research topic, especially if you are working in a smaller niche area, or in a new area where you are among only a few people doing your particular kind of research. However, it is pretty much never true that there are no relevant papers, articles, blogposts, newspaper articles, or published research of a credible kind on your research. With the internet growing bigger by the day, and more and more resources available to us, we need to be careful about what we choose to cite, and how credible our sources are, but we also have far more information and knowledge to access and learn from than ever before. Be creative: use reference lists written by authors of texts that are helpful. Contact corresponding authors of papers that you have found useful and introduce yourself politely. Briefly explain your research, and ask them if they can suggest useful reading to you. Get to know your librarian and enlist his or her help. Ask your supervisor to suggest key reading material if you get stuck. Play with your search terms and keep track of which ones yield better results. Go past page 3 of Google Scholar.

If you are struggling to find participants for an empirical qualitative study, or to respond to a survey, or to assist physically with your research, don’t give up. You need to be pragmatic. There is often a wishlist of research participants, and a real-world list. Sometimes you can be fortunate enough to have these lists match. Often, though, people will be busy, or on sabbatical, or traveling, or just won’t respond to your emails, requests and pleas. Draw on your networks, your peers’ networks and supervisors’ networks (if you can), and be practical. Try to start with participants who will respond and will be able to give you relevant data. Ask them to suggest other people to talk to – use different forms of purposive sampling or snowball sampling to select other participants. There is always a plan to be made; you may have to make 15 phone calls, or send several emails before you get a response, but you need to keep going.

Grappling with complexity: Finally, supervisors mentioned students’ need to become more resilient about grappling with complexity, and becoming okay with not knowing and being confused or a bit lost. Struggle is part of the journey, but too much struggle can be paralysing. So this is a challenge for supervisors and students alike. The reality is that no MA or PhD or journal article or book can answer every question, and there are so many ways of addressing research problems that there will always be someone who disagrees with you, or offers critique of your work.

The problems most of us research are complex, and multi-layered, and we often only work with a small slice of a problem and a possible solution or answer. But don’t mistake small slices for superficiality. Often, somewhat paradoxically, we need great depth of insight into our research problem to make it simple, accessible and knowable by our audience. Pushing away the papers that offer different angles, refusing to read the work of those with an opposing point of view – this doesn’t make your research simpler. It makes it less likely to have anticipated challenges and able to respond to these. As a mentor once said to me: you can’t pretend those who disagree aren’t out there; you need to engage with them and persuade them that your argument is stronger than theirs. This is perhaps the toughest area in which to build researcher resilience, but it’s the most important.

At the end of the day, to push through the rough patches, disappointments, lost data, absent supervisors and other myriad issues that can scupper even the most well-planned projects, researchers need to build resilience. This can be facilitated by supervision that makes visible students’ hurdles and struggles and makes space to talk about and deal with them productively. But it also is up to students to create and manage support systems that can bolster them as they progress, and to consciously work on becoming more research-resilient over time.

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.