Paper writing IV: analysing data

One of the trickiest areas for researchers working with data – either primary or secondary (data you have generated in ‘the field’, or that gleaned from texts etc) – is the analysis of that data. It can be a significant challenge to move from redescribing findings, observations or results, to showing the reader what these mean in the context of the argument that is being made, and the field into which the research fits. There are a few moves that need to be made in constructing an analysis, and these will be unpacked in this post.

Often, in empirical research, we make our contribution to knowledge in our field through the data we generate, and analyse. Especially in the social sciences, we take well-known theories and established methodologies and use these to look at new cases – adding incrementally to the body of knowledge in our field. Thus, analysis is a really important thing to get right: if all we do is describe our data, without indicating how it adds to knowledge in useful ways, what kind of contribution will we be making? How will our research really benefit peers and fellow researchers? After all, we don’t write papers just to get published. We conduct research and publish it so that our work can influence and shape the work of others, even in small ways. We write and publish to join a productive conversation about the research we are doing, and to connect our research with other research, and knowledge.

data 1

How to make a contribution to knowledge that really counts, though?

First things first, you can’t use all your data in one paper (or even in one thesis). You will need to choose the most relevant data and use it to further illustrate and consolidate your argument. But how do you make this choice – what data should you use, and why? The key tool used to make all the choices in a paper (or thesis) – from relevant literature, to methodology and methods, to data for analysis – is the argument you are making. You need to have, in one or two sentences, a very clear argument (sometimes referred to as a problem statement, or a main claim). In essence, whatever you call it, this is the central point of your paper. To make this point, succinctly and persuasively, you need to craft, section by section, support for this argument, so that you reader believes it to be valid and worth engaging with.

So, you have worked out your argument in succinct form, and have chosen relevant section of data that you feel best make or illustrate that argument. Now what? In the analysis section, you are making your data mean something quite specific: you are not just telling us what the data says (we can probably work that out from reading the quotes or excerpts you are including in the paper). To make meaning through analysis, you need to connect the specific with the general. By this I mean that your data is specific – to your research problem and your consequent choice of case study, or experiment, or archival search and so on. It tells us something about a small slice of the world. But, if all we did in our papers was describe small slices of the world, we would all be doing rather isolated or disconnected research. This would defeat the aim of research to build knowledge, and forge connections between fields, countries, studies and so on. Thus, we have to use our specific data to speak back to a more general or broader phenomenon or conversation.

data 2

The best, and most accepted way, of making meaning of your data is through theorising. To begin theorising your data, you need to start by asking yourself: What does this data mean? Are these meanings valid, and why? There are different kinds of theory, of course, and too many to go into here, but the main thing to consider in ‘theorising’ your data is that you need a point of reference against which to critically think about and discuss your data: you need to be able to connect the specifics of your data with a relevant general phenomenon, explanation, frame of reference, etc. You don’t necessarily need a big theory, like constructivism or social realism; you could simply have a few connected concepts, like ‘reflection’, ‘learning’ and ‘practice’ for example; but you do need a way of lifting your discussion out of the common sense, descriptive realm into the critical, analytical realm that shows that reader why and how the data support your argument, and add knowledge to your field.

Analysis and theorising data is an iterative process, whether you are working qualitatively or quantitatively. It can be difficult, confusing, and take time. This is par for the course: a strong, well-supported analysis should take time. Don’t worry if you can’t make the chosen data make sense in the first go: you may well need to read, and re-read your data, and write several drafts of this section of the paper (preferably with critical feedback) before you can be confident of your analysis. But don’t settle for the quick-fix, thin analysis that draft one might produce. Keep at it, and strive for a stronger, more influential contribution to your field. In the long run, it’ll be worth more to you,to your peers, and to your field.

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Paper writing: opening with a strong abstract, title and keywords

The first thing fellow researchers read when they find your paper are the title and the abstract. They find your paper, often, by typing keywords into a database or search engine that match words in your title, abstract or keyword list. It is thus really important to spend time crafting these aspects of your paper carefully, as time spent getting them right pays dividends in the visibility of your work in keyword searches within your field.

Titles and keywords

To begin with, your paper needs a clear, descriptive and relevant title. Usually you have about 15-20 words for a title (check with the author guidelines of the journal you have targeted), and about 4-6 key words.

A first, useful, rule of thumb is to use all of these words strategically: don’t repeat words you use in the title in the list of keywords, and avoid acronyms, even well-known ones. Use the keywords to highlight elements of your argument or paper not referenced in the title. So, you really have a maximum of about 25-30 words to play with.

To begin with the title, a good starting place is to look at the title of papers you are referencing, and have enjoyed reading. What about the title caught your attention? The better paper titles indicate both what the paper is about, and something of the contribution the paper is making to the field. They are, therefore, relatively descriptive. They should be, really, because titles that are obscure, or only obliquely connected to the content of the paper will put readers off. Further, titles that try to be too catchy or clever may not contain the kinds of words researchers will type into search engines, resulting in your work being too far down the list (be honest, how often do you search past page 4 of Google Scholar?). Your work will be missed, and that would be a great shame considering all the work that went into publishing it.

A useful tool for crafting a title that balances a bit of catchiness with relevance and contribution is the subtitle. For example: ‘When arts meets enterprise: Transdisciplinarity, student identities, and EAP’ or ‘Chloroform fumigation and the release of soil nitrogen: A rapid direct extraction method to measure microbial biomass nitrogen in soil’. The first title marries a bit of fun with a focus on what the paper is about; the second uses the subtitle to indicate a method that the researchers are using to explore the phenomenon mentioned before the colon. Subtitles can also be used to sharpen the focus of your title, to create a limit or boundary to your research, to add additional context, or to expand on the scope of your research (See this article, and this one, for useful advice on title creation).

Use your list of keywords to add to the title: mention, for example, a key methodological tool (e.g. action research, or regression analysis) that researchers might be interested on, or the theory you have used (e.g. constructivism, or social realism), or key thinkers you draw on (e.g. Karl Marx, or John Rawls), and finally on the parts of your field the paper references that the title doesn’t mention (e.g. disability studies, or political theory). This should ensure good visibility for your published paper.

The abstract

The abstract, after the title, is the first thing researchers read of your paper. Often, given the current system of paywalls and needing access to databases or your library’s holding to find the full paper, it is the only thing people can read to decide whether they want to pay for it, or search harder for the free version. So, it is really important to craft a clear, persuasive abstract that makes them want to read more.

Barbara Kamler and Pat Thomson helpfully refer to the abstract as ‘the Tiny Text’: all of the relevant parts of your paper have to be in your abstract, in much abbreviated form, i.e. the focus of your paper, the argument it makes, the methodology, the main findings and the significance of those findings for your field. This is a tough ask when you often have only around 150-200 words for the average abstract.

A useful tool I learnt at a workshop from Lucia Thesen, and now use with postgraduate writers in my courses, is ‘the fairytale’. It goes like this, with you taking two sentences or so to complete each line.

  • Once upon a time people thought that…
  • But then I/we thought that…
  • So what I/we did was…
  • And what I/we found was…
  • This may change the way people think about…

This helps you create a gentle, narrative story about your paper, covering the main aspects of the abstract – the area of research you are locating your study within, the gap you have located, the way in which your research was conducted, your major findings, and what contribution your research could make to your field (related to the problem you are responding to).

Then you can recraft this into a more formal abstract, using Pat Thomson’s basic structure as a guide:

• ….. is now a significant issue (in/for).. because…. . ( Expand by up to one sentence if necessary)
• In this paper I focus on …..
• The paper draws on ( I draw on) findings from a study of… which used…… in order to show that….. (expand through additional sentences)
• The paper argues that….
• It concludes (I conclude) by suggesting that…

A useful thing to do is to read carefully the abstracts of the papers you are citing, and critique them against this basic guide: do you understand why this research has been done, and what it aims to achieve? Do you understand how it has been done and what the main findings are? Do you have a sense of what the research contributes to the field? It is interesting, and well-written? If any of these elements are missing, consider how the abstract could have been better written for you, as the reader/researcher. Then apply this reflection to your own abstract. Think about your readers carefully, and what they need to know to understand what your paper is arguing, where this argument fits into the field of research it is concerned with, how the research was conducted and what it found, and why the research matters. (See this article for useful advice on abstracts).

You should start your paper writing process with drafts of your title and abstract, to give you focus and a direction for the paper as a whole. But these drafts should be carefully revised again at the end, when your paper is finalised, to ensure that they are connected, and that the title, abstract and added keywords best reflect your research, and get it noticed, read, and hopefully cited.

Iterativity in postgraduate writing: making peace with the mess

Lovely husband and I were talking recently about a workshop we both attended on postgraduate study, and our respective conversations with our own postgraduate students about what postgraduate study involves them in, specifically the over-and-over again nature of the reading, writing and thinking. Iterativity, we concluded, is the name of the game at this level, and in post-doctoral academic research; yet, it is an aspect of working at this level that produces much frustration, self-doubt and struggle.

Ernest Hemingway famously said: ‘The first draft of anything is shit’. He was, certainly in my experience, right. If you look up writing advice on Pinterest, you will find many soundbites to inspire you; for example: ‘First drafts  don’t have to be perfect. They just have to be written’, ‘A crappy first draft is worth more than a non-existent one’, and writing first drafts as being like ‘shoveling sand into a box so that later [you] can build sandcastles’.  There is truth in all of these inspirational tips: first drafts are messy things: often incoherent in parts, full of both useful and useless information, lacking a proper focus. But, they are where we start any writing, and the key word here is ‘start’: writing is a non-linear, often chaotic, process, where we learn as we write, and our thinking develops with each round of feedback and revision.

This ‘logic of discovery’ is at odds, though, with the ‘logic of dissemination’ that we display in our finished thesis: the iterative process that produces the thesis is hidden from the view of the reader, as they are presented with our neat, polished, coherent argument. Many postgraduate students start their thesis process believing that these two logics are the same: that you start with Chapter 1, and the process unfolds neatly and logically from there. They become frustrated, then, when this turns out to be a lie:  when the truth is multiple drafts and mistakes, time spent writing paragraphs or pages of writing that have to be deleted when they are no longer relevant, and sometimes unexpected changes to your research questions, theory or methodology as the project evolves. This frustration can breed self-doubt if not carefully managed through supervision: many students believe that the more drafts you have to write, the worse you are as a writer; so many students I have met erroneously believe that the best writers don’t write that many drafts, and don’t make that many mistakes or revisions.

The opposite is the truth. The more successful writers, and postgraduate students, have learned to embrace the chaos and the frustration; they have learned to manage a balance between having a clear research plan and letting that process evolve so that they can still be surprised by what they find, or learn, as they write and work the data. This is a hard thing to do, live in a space where you know probably less than you don’t know, and where you have to be okay with the not-knowing, and move willingly between knowing and not-knowing over and over as your research moves forwards. This requires not just mental fortitude, but emotional resilience.

Researching and writing a thesis feels, at times, as if you are on a many-roaded route, trying to keep your eye on the GPS when it’s giving you more than one possible route and asking you to choose the best one to get you to your destination within minimal traffic and in good time. You may choose one route, and then find halfway you’ve made an error in judgement, and then choose to turnoff, and take a back road back to the main route you were on. There may be unexpected detours that the GPS didn’t know about and so couldn’t warn you of. You may feel like you are going around in circles at some points, and in a lovely, free-flowing straight line at others. A research degree, especially a PhD, represents a long road, with several possible routes to your destination. And it’s not a straight line. You may have to re-drive parts of the route at times, or try out different parts of the route than you expected to. But, if you try to trust the process, and make peace with taking your time and living with a bit of mess and non-linear chaos, you will hopefully get to your destination in one piece, and with a really good understanding of the area you’ve been driving around and around.

In research terms, this means getting more comfortable with the iterative nature of research, writing, and thinking. You cannot expect to write a chapter once, and be done. And you can’t expect to read something once and fully understand it, especially if it’s pivotal to your project, like theory. Writing multiple drafts, making mistakes, including knowledge and reading you don’t need along with that which you do, and making revisions that improve your writing, further your thinking and push your research forward is part and parcel of valuable, challenging postgraduate study that makes you a more capable researcher. Doing worthwhile research that pushes your field forward will require you to have a really firm understanding of that field, and the place your research can occupy within it. This means getting a bit lost sometimes, but having the means (through supervisors, peers, reading) to find your way onto your route again.

Terry Pratchett’s soundbite on first drafts is my favourite: ‘The first draft is just you telling yourself the story’. If you see your thesis as a story, evolving as the characters and plot take shape, and as the twists and turns reveal themselves through working with theory, methodology, data and analysis, it can be easier to embrace that uncertainty, and iterative rounds of writing, feedback, revision, and rewriting that push your research, and you as a researcher, forward. You start by telling yourself, and move to telling your supervisors, examiners and finally your wider audience – and you make a contribution that is valued and relevant. It won’t happen in a nice, linear way, but the depth of knowledge you gain, of your field and the research process, will be worth all the ‘driving’ in the end.

Paper writing: effective conclusions

This is the second post in the Paper Writing series: the first on Introductions is here. This post deals with the opposite end of the paper: conclusions. 

Conclusions, for me, are the hardest part of paper writing. I really struggle to pull all the strands of the paper together in a coherent, punchy closing paragraph or two. Part of this struggle, I think, stems from how I was taught to write conclusions in my undergraduate study. I was taught that you need to start with the phrase ‘To conclude/in conclusion/to sum up’ or similar, and then proceed to summarise the ‘body’ of the essay by restating the main claim and then the main ideas of each paragraph. Although most essays asked us to make an argument, we were not taught to consider the relevance or significance of that argument for our audience. In fact, I was never explicitly told to consider an audience for my work (beyond my tutor or lecturer) until I was a Masters student.

This ‘summarise and restate’ version of conclusion stays with many students as they move into postgraduate study, largely because of the dearth of focused writing education and support at postgraduate level; once students are registered for an MA, or PhD especially, we assume they can write effectively in these forms and at these levels. This obviously needs to change if we are going to graduate more successful postgraduate students, and at PhD level graduate more able researchers, writers and future supervisors.

The papers and dissertations we write at postgraduate level – PhD and postdoctoral in particular – have to make a contribution to knowledge in our fields; they have to say something relatively new, interesting and relevant to our audience. But, we can’t just leave it to that audience to work out what that contribution is or why they should care about it. Our papers have to answer the ‘So What?’ question clearly, and effectively. (Actually, all papers have to do this from first year onwards, but this has different implications for a first year student writing for a tutor, and a researcher writing for a wider audience of their professional peers in the field). If you don’t have an answer, you don’t have an argument. The Introduction to the paper is where we posit the argument, and where it fits into this field of ours, but the Conclusion is where we really get into what the argument of the paper is and what contribution it makes to the field – in other words, why it matters and should be engaged with  by readers.

Rather than summarising the restating the thesis and summarising the main ideas of the paper, the conclusion needs to be focused on discussing the point of the argument the paper has been made, and its implications for the area of the field you have located your research within. It needs to pull all the strands of your paper together, which are connected like links in chain, and close the paper off with clarity. If you are, for example, writing about a new form of evaluation of teaching practice, or a new way of creating energy from biomass, your conclusion should explore what meaning or relevance this form of evaluation or method of energy creation potentially has for the field – your audience – and could perhaps make recommendations, or posit areas for further research and development, building on your work.

Useful questions to guide this writing could include:

  • what is the argument my paper has made? Write it down in as couple of clear sentences.
  • on what basis have I made this argument? Briefly pull together the main forms of evidence – from the literature and data – that you have discussed and used to support this argument.
  • why have I made this argument? Briefly summarise the reasons behind your research – the gap in the field you located and are seeking to fill.
  • who would benefit from engaging with this argument, why should they engage with it, how? Talk to your readers here – tell them what the significance of your argument is to the research and/or practice you imagine they are engaged in, and why this research you have done matters to your shared endeavours.
  • do I have any recommendations for further research that builds on this research and what are they? Briefly, indicate how this argument could be furthered through new, or cumulative research.

The main point here is that you are avoiding the ‘restate and summarise’ version of the conclusion, and you are aiming for a clear, concise, pointed answer to the ‘So what?’ question. You need to show your readers why your argument matters, and remind them, without doing a point by point summary, of how and why you made your argument and are engaged in this research. They should be longer than one short, limp paragraph – a decent conclusion is at least 10 of the total word budget for your paper. Read the conclusions of papers in the field in which you work, preferably those by authors who are regarded as successful and knowledgeable. See if you can find the moves they make in their writing to convince you of the relevance of their argument, and replicate these in your own writing, Share your writing with peers and ask them if they can see the same moves in your drafts.

Conclusions are hard work, but strong, clear conclusion will stay with your reader and make your paper both useful and memorable.

It’s not less of a PhD if you didn’t survive it alone

In the world of postgraduate studies, there is a dominant narrative of struggle, and survival. PhDs and Masters’ degrees are difficult  – they demand that you struggle, often on your own, with ideas, theory, words, data, supervisors and so on. If you are not having a lonely and hard time, you are missing some vital part of Doing a PG degree Properly. I know far too many postgraduate students for whom this narrative is all too true. They struggle with supervisors who are too busy, or absent, and who give the most appalling feedback; they struggle to find peers to work alongside and share their research difficulties, and triumphs, with; they struggle to write, finding themselves blocked for days or weeks on end; they struggle to generate data, build theoretical frameworks, find and build their argument, and so on. Struggle, and loneliness, seem to be the central tropes of the postgraduate experience.

But, what if it doesn’t have to be that way? What if we can all work towards a culture of support in postgraduate studies that changes the narrative? What might this culture look like, and what would it take to create and maintain it in more than just a few, unusual, cases. There are indeed cases of supportive, collegial postgraduate environments: I was part of one at my university, and I am sure that it helped me to finish my degree more quickly, and less unhappily. I know of other programmes, within specific departments, where supervisors and students support one another, share research through presentation and feedback sessions, and meet at intervals for different kinds of ‘thesis support’ sessions and inputs. There is a growing body of research – both in published papers and in blogs – about the forms of postgraduate support that are needed in different contexts and the benefits to students, supervisors, universities and economies. But, these cases don’t yet seem to be the norm, and do not yet represent a systemic understanding of what successful postgraduate study demands of students, and requires of supervisors and universities in terms of formative, collegial support.

The first thing that we need to challenge is the single student to single (or two) supervisor ‘apprenticeship’ model of postgraduate work so common in the social sciences and humanities. In this model, students are often assigned supervisors) by their department or programme, although they do often have the opportunity to approach potential supervisors and choose to work with specific researchers. However, it’s not always easy to find out more about a prospective supervisor beyond their research publications and interests, and their departmental profile. For example, do they give constructive feedback? Are they present in the research process? Are they supportive? (Evonne Miller gives some useful advice on how to find this information here). Thus, many students in difficult supervision spaces, in imbalanced relationships with supervisors who hold all the power and do not necessarily use it for the student’s good. If we challenged this model to enable more instances of team or cohort supervision – students and their supervisors working on smaller projects within a larger overarching project, for example, or working on a range of projects but in a deliberately collective space – then neither students nor supervisors would need to navigate the process alone. Unequal and harmful power dynamics could be challenged, less experienced students and supervisors could be formatively mentored, and both could share with one another research, ideas, writing, advice, and general support.

The second thing that needs to be firmly challenged is the notion of struggle being part and parcel of any worthy postgraduate journey, especially at PhD level. If you are not struggling, you are not doing it right. I struggled with parts of my PhD – theory and data analysis especially. A PhD is not supposed to be easy: it is supposed to challenge you and change you, into a different kind of thinker, researcher, writer, person. But, I strongly object to the idea that this challenge has to be lonely, alienating, frustrating and interminable in order to be worthy. There are different kinds of struggle here: struggle that is productive, supported and results in steps forward in the research process; and struggle that bogs a student down in a mire of self-doubt and writing paralysis. I see too much of the latter in my work with students, often because the student struggling isn’t getting the help they need from peers or supervisor or department, and this is often because the nature of postgraduate study is misunderstood, or misconstrued. I think we need to start sharing more positive narratives around postgraduate study: of productive challenges that are worked through and overcome, of research wins where data generation works out and chapters are approved, of helpful supervision meetings and useful coffee chats with peers. And we need to stop making people who enjoy their PhDs feel like they’ve done something wrong, because it hasn’t been hard enough, or lonely enough.

I have had a few conversations with friends who really did enjoy their PhDs, as I did, and found the struggles hard but productive overall. These friends are all now productive researchers and constructive supervisors, having learned much more from their PhDs than just how to run a successful research project. They have learned how to ask for help, how to use the help they receive to move forward, how to write and read and think in critical ways, how to offer help to others, and how to reflect on and learn from mistakes, missteps and triumphs. This is not to imply that if you have a miserable PhD experience, you will be a miserable, unproductive researcher or supervisor, not at all. But you may feel you have lost parts of yourself along the way, rather than gained, and if you have been part of a poor supervision and research process, you may well find further research, writing, and supervision work more difficult than it could otherwise be. We could change the future of research and supervision work if we change the way we construct, support, and fund postgraduate education within our different contexts, especially in Africa where more young researchers and supervisors are needed.

We need to stop elevating the narrative of the lonely, alienated, struggling survivor above the narrative of the connected, challenged and productive thriver – and we need to create environments around postgraduate students and supervisors that make the latter narrative far more common across higher education.