Category Archives: PhD

Habits, practices and dispositions of successful research students

This post brings together a number of things that I’ve come to see as important for research students. They are based on what I know from research I’ve done, literature I’ve read, experience as a supervisor, and conversations with many students and supervisors at universities around the world.

Constantly looking for your thesis thief

I’ve written a detailed blog post about this. Your thesis thief is the person who has ‘stolen’ your research by doing something really similar already! Regularly looking for this person is a good habit to cultivate as it avoids nasty shocks (believe me, I know how it can feel). It also requires and promotes good scholarly discipline in being able to define what ‘really similar’ would mean: in terms of topic, methodology, context, theory etc…


Ask for help… when you need it

Sounds obvious? Well experience tells us that many students ask for help when they don’t really need it. When I speak with other supervisors, we often chuckle about the number of times students approach us with questions where the answer would be on google (let me google that for you), somewhere in the university web pages, handbook, literature etc. That’s just a kind of minor annoyance / time wasting issue. What’s far more important is that any kind of research learning (master’s dissertation, doctoral thesis) requires the student to learn to help herself or himself. Of course, help-seeking is itself part of being an effective student (see below), but defaulting to dependence on others is the opposite of effective.

Student:           Can we have a meeting to talk about coding my data?

Supervisor:      What have you read about coding?

Student:           Er, not much. Just one paper but it was really confusing.

Supervisor:      Who have you talked to about coding? Have you asked any other students who have done it?

Student:           No. No-one.

Supervisor:      Have you tried some coding on your own data, a few times at least?

Student:           No, I wanted you to tell me how to do it right first.

Supervisor:      Sorry, no, I don’t think it is a good use of our time to meet. Come back when you’ve explored these other avenues.

I’m not saying this supervisor is doing the right thing, but it’s interesting to think about, isn’t it?


Cultivate, nurture and strategically access a constellation of supportive relationships

No matter how amazing and available your supervisor is (see below), you’re going to need other people to support you through the research journey. Some of these people it is their job to help you – librarians, IT support etc. I found personally that making a special effort with research / postgraduate administrators is a sound investment as they really are the oil and the fuel in the institutional machine. Others might be helping you as a favour, so you need to build a sense of mutuality in the relationship – peers who will help you with endnote, stats etc. Others have long been supportive of you, but now have to support you in this different endeavour, perhaps at a time when you’re less available to them – those providing emotional support, for example. There are others who might never meet you, or even know they’re helping you. I’m thinking here of Thesis Whisperer, Pat Thomson, and others in the amazing and helpful world of #phdchat and similar in the tweet- and blogospheres. Then there are academics in your field – people you meet at conferences and engage in corridor chat or discussions over coffee or dinner; people whose work you are reading whom you might email now and then; people who might be your examiners. So, your constellation will include your supervisor, family, friends, student peers, other academics; maybe dead people (authors of books can be a great source of support), people you never meet, people who don’t even know you exist!

It’s one thing to build this kind of supportive net around your research and your emotional and physical wellbeing. It is another thing altogether to use it effectively. The key is, when things get tricky, diagnosing what the problem really is, what kind of help you need right now, and who is best able to provide that help. Let me give an example from a study I did. A student doing economic history, Lucy, had waited months to get data from a national archive. It arrived by email and she opened up the file only to find huge holes in the data that meant she couldn’t do the study she had hoped to do. What did she do? She went out for a drink with a chemistry PhD student. Why? Because she knew this person well enough to feel ok crying (she needed to cry), but also because she knew chemists fail all the time (it’s true: they spend months trying to get experiments to work). She realised what she needed, right then, was not a solution to the data issue, but someone who could help her cope with the experience of her PhD falling out from under her feet.


Ensure time with your supervisor is as high value as possible

Your supervisor is important, but not all-important. She or he is very likely extremely busy, and in many countries, research supervision is a relatively (or completely) invisible form of work – ie not something that is awarded much time or money in the grand scheme of things. Yes, she or he is committed to supporting you, cares about you, and wants you to complete your study (as quickly as possible, if you don’t mind). But in the pecking order of things that are important and urgent today, reality is you probably don’t come top or even near the top of the list. So, your time with your supervisor is precious. Very precious. So precious that you’d be really, really stupid to waste it.

So what might ‘waste’ supervision time? I’m taking a rather extreme view here, but bear with me. I think anything more than a couple of minutes on something that your supervisor is not either uniquely or best able to help with, is wasteful. Exceptions might include time spent on things she or he needs to know, for example about circumstances outside your study that are affecting your work (though I’m not at all convinced the juicy details in this are warranted). If your time with your supervisor is limited and precious, why waste it talking about things that other people (or indeed just you) could sort out just as effectively?

Now, there are a lot of things that fall under the category of things your supervisor is uniquely or best able to help you with. She or he knows you (in a research capacity sense) and what you are doing better than anyone else (although of course pretty soon in the process you know more about your specific topic than your supervisor). But there are others who know just as much about administrative process, how to find literature, how to work software, how to correct grammar etc.

By implication, there is an onus on the research student to figure out what does indeed fall into this category that makes something an appropriate (ie high-value) use of supervision time. This will change over the course of your study. And there is responsibility on both sides to try to preserve supervision as a high-value-added activity.

Student:           Can you show me how to format endnote for APA 6th?

Supervisor:      Let me google that for you.

[No further dialogue needed]


Internalise your supervisor(s)

This connects with the previous point, because it can make time with your supervisor high value. After a while, you should be able to anticipate what your supervisor might say about a chapter you’ve sent to her. In which case, write your draft, leave it for a few days, then look at it as if you were your supervisor: what would she say about my structure? Where would she be confused? What would she like? What would she say needs more work, and why? Then re-write the chapter. Then send it in. A sign you’re not doing this is that your supervisor is giving the same kind of feedback each time. For example, you sent in your first findings chapter and your supervisor said you had ‘quotitis’ (hiding behind raw data too much). So when you send in the discussion chapter, check beforehand that the same problem isn’t there too.


Know the early warning signs, monitor yourself (and others) for them, and act accordingly

Most people come off the rails, or are at risk of doing so, at some point during a research thesis or dissertation. Being on the rails means studying productively, effectively, efficiently, while also maintaining physical and emotional wellbeing, and also being the husband, wife, mother, father, son, daughter, sibling, friend etc that you need to be for others around you.

Kearns and colleagues have a checklist of self-sabotaging behaviours that are very common (I have experienced all of them personally, in my time), but often unnoticed or ignored. They are:

  • Overcommitting. Attempting a study that is bigger or more complex than it needs to be. Taking on too many other responsibilities, spreading yourself too thinly. Refusing to let go of things that are important in your study, but not crucial. Setting yourself impossible volumes to read etc.
  • Busyness. Doing lots of work but none of it actually being productive work (eg spending a morning printing things or downloading things to read, when you should really be reading).
  • Perfectionism. A proper academic disease. There is no place for perfectionism in research. Sure we want to avoid sloppiness, and yes we want our writing to reflect the best of what we can do. But that is not perfection. No-one ever wrote a perfect paper, dissertation or thesis. Trying to do so can only be harmful.
  • Procrastination. Either putting off thesis work, or putting off the unpleasant and difficult aspects.
  • Disorganisation. If you find you’re not getting time to read and write, you’re not as organised as you think you are.
  • Not putting in effort. It’s a long, gruelling journey. Our motivation flags. That is normal and natural. But should be spotted and dealt with.
  • Choosing performance-debilitating circumstances. Working in unsuitable locations (you think you are productive reading in the coffee shop, or at home with the kids around, but are you? Really?)


There are other early warning signs too. Things like: not wanting to go onto campus because you feel really stressed about your research. Having a knot in your stomach when you see an email from your supervisor. Deferring meetings, not turning up, or just asking for email feedback (ie avoiding direct contact with your supervisor). I’m veering into territory that I’m not at all qualified to write about (eg symptoms and signs of anxiety, depression etc), so I’ll go no further. But you get the point.

Make time to read and write

If you don’t read and write you will not complete your dissertation or thesis. If you spend hours each week doing other things but not reading or writing, sooner or later, you will plateau and stop making any progress. This is a deal-breaker. You simply have to make time to read and write.

Act as if you are fearless

Sending writing you know is not perfect off to your supervisor can be scary. I know. Submitting your thesis or dissertation for examination is even scarier. Being scared is fine. Letting that fear affect your actions is not fine. You have to send your writing off for feedback. You have to submit (abandon is probably a better word) your thesis or dissertation at some point, even though it is not perfect.

Walk the fundamental scholarly tightrope

To be an effective student you have to be confident, assertive and ready to defend your point of view (even if that means disagreeing with people more senior or experienced than you). But you also have to be humble about what you and others know, subject yourself relentlessly and ruthlessly to self critique (asking could it be otherwise, could it be better, could I be wrong?), and be open to change suggested by others. This is one of the tensions that is written into the DNA of academic work and it’s far from easy to know when which aspect is more appropriate. But it is clear, I think, that falling exclusively or even predominantly on one side or the other does not bode well for success.

Flipping PhD Supervision

First up this is not just about PhD supervision, but supervision of research degrees, whether Masters, PhD, Professional Doctorates etc. PhD in the title is just a convenient shorthand.

One of the interesting things that has been going on where I work is ‘Learning2014’. This is UTS’ approach to changing teaching and learning across all our campuses (including the online ones) and disciplines. One of the features of this concerns ‘New Approaches’ to pedagogy, and within this, a key idea is ‘flipped learning’.

Flipped learning is gaining currency as a way to describe certain ideas about what might happen before a key pedagogical interaction, such as a lecture or tutorial. While the term feels relatively new, it builds on key ideas that have informed teaching and learning for a long time.

Admittedly, I was initially a little cynical (as I tend to be about most things), but as I began planning classes in the coursework masters program, I found the idea of flipped learning was giving me a really important nudge in my thinking. Why was I asking students to read texts, or watch videos, before class? Could I explain this better to them? Could I scaffold them in doing so? How could I use this to improve what happens when we meet? I then started feeding the idea into workshops and masterclasses, and the feedback has been very encouraging. We’re able to get straight into meaningful discussion about key ideas, building on what students took from engaging with material, the questions that came up, and the issues that remain unclear. I’ve posted a short video that explains my approach to flipped active learning in classes and workshops.

Can flipped learning help with research supervision?

I began asking myself whether supervising doctoral and masters students might also benefit from some of the ideas of flipped learning. Here’s where I’ve got to so far.

Supervision is nearly always flipped in some way, anyway

Insofar as flipping means that students engage with some ideas or content in advance of a structured teaching moment, then many, if not the vast majority, of meetings between students and supervisors already have some flipped quality. Students might often write something, or be asked to explore particular areas of literature or methods, or do some fieldwork or experiments in a laboratory before meeting with a supervisor. This sense of flipping is widespread and really nothing new at all (it’s been going on in the Oxbridge tutorial system for centuries). Of course just because it’s not new doesn’t mean it’s bad or broken (that’s how I experienced all my supervision as a masters and PhD student and I did fine!). But as I’ve been working with the idea, I think there’s more to it…

In some ways supervision isn’t flipped

The more I thought about it, the more I could see some elements of the ‘student writes-supervisor reads-both discuss’ model potentially missed some of the benefits that I was seeing from other kinds of flipped learning in the classes and workshops. I realised that when a student arrives for a supervision, they often don’t know what I’m going to be saying about their draft, or what I’m going to be asking them. My comments and questions are being encountered for the first time, in the moment of supervision. At times this can be a very productive form of interaction, for many reasons, but it can also be experienced as quite challenging, even confronting. And I’m not convinced it always leads to the best discussion…

Flipping supervision

So I’ve been experimenting with two practices.

  1. Providing written feedback on students’ drafts (usually by hand), with a typed summary of key points and questions I will ask. I send this to students a few days before our scheduled meeting.
  2. Making a short (10 minutes or less) audio recording in which I talk through my responses to a piece of writing, and explain the questions I’d like to ask, and issues I think we should discuss when we meet. Again this is sent to students a few days before the meeting.

I think there’s potentially some value in these. What they do is give students a chance to think about the issues and questions before we meet. This changes it from an on-the-spot Q&A, to one where students have had time to digest the points, perhaps even read a bit, think of ways to defend their ideas, consider alternatives etc. The written version takes me a lot more time, but gives students a very concrete and detailed set of things to look at, and a nice shared reference point for us in meetings, as well as a clear audit trail. The spoken version is much quicker, and I like it because I can use my tone of voice to provide extra encouragement, and to soften the potential negative feeling when a draft needs yet more work!

So the potential benefits seem to be:

  1. It moves the discussion on a step when we actually meet, because I’m not introducing the points or questions for the first time, but rather can start with ‘so what did you think about my feedback?’. It becomes less about my response to the student, and more about her response to the issues and questions.
  2. It might make it less confronting for students, and make it feel less like a test in supervision. It might also help make supervisions feel more focused on positive aspects and next steps, rather than what is wrong with the latest draft.
  3. It could also foster independence in students, so they have time to explore resources and their own initiative in coming up with responses to issues and questions raised. I wonder how many times, in the past, a student has found it hard to ‘come up with an answer’ on the spot. What if she had had a few days to work on it?


But this is no panacea and some things I’m sensing a need to be careful about include:

  1. Making sure there isn’t increased risk of students feeling vulnerable or under-performing, because in the flipped mode, they read or hear the feedback when they are on their own, not in the meeting. So if it’s hitting them hard, I’m not going to be there to see that.
  2. Making sure students feel comfortable in saying ‘I’ve no idea!’, or ‘Yes that seems an important issue, but I really don’t know how to respond at the moment’. That is fine. What the flipped approach would allow us to explore is what a student tried out in the intervening few days, so we can think about why that wasn’t found to be so helpful, and explore alternatives.

In conclusion

It has been interesting to think through what flipped learning might mean in a research supervision context. I’ve tried these ideas out softly, and step by step at first, consulting with students as I go along, and trying to monitor what aspects appear to work well, why, and for whom. I can’t see that it would make sense for all supervisions with all students to use this approach, but it might offer some helpful variation in the rhythm and sequence of supervision pedagogy from time to time.

I’d love to hear from any other students or supervisors who are doing something similar. Maybe I’m way behind everyone else and have done nothing more then reinvent the wheel…

Why good supervisors might sometimes make easy things harder

I recently had an experience that made me reflect on an aspect of research supervision (supervision of a PhD, EdD, DCA, or Masters by Research).

Bear with me: I’m going to tell a short story relating to some training I do in freediving, and then I’m going to explain why I think it points to some helpful ideas about supervision and what postgrad students may be experiencing in terms of difficulties, particularly writing.

A lesson in freediving


When I’m not at work, one of the things I love to do most is freediving. Freediving involves holding your breath while being under water. It is an amazing activity that involves physical and mental challenge, discipline and practice. I am often at my most peaceful, focused and contented state when freediving. A large part of freediving involves depth: taking a big breath and swimming down towards the bottom of the sea. I’ve put a short video on youtube of a dive I did recently to give you a sense of what it involves.


Diving deep presents a number of challenges: you have to learn to relax while on the surface, and stay relaxed when you’re deep down – slowing your heart to conserve energy and oxygen; you have to swim with efficient, hydrodynamic technique and posture (not very well demonstrated on the video!); and you have to learn to resist the urge to breathe and learn which body signals you can ignore or suppress to give you longer under water.

Recently I’ve been going deeper more often – down to 28.4m on one dive. At this stage one thing tends to present a barrier to progress: equalisation. Equalisation is what you have to do in response to the increased pressure when under water at depth. You have to gently force air into your Eustachian tubes (basically your ears) so the pressure inside matches that in the water outside. It’s a more severe version of what you experience when you’re coming in to land in a plane.

I can equalise my ears using something called Frenzel technique (using your tongue to squeeze air into the right places) pretty easily down to 20m or so. My problem is, when I go deeper than this, I start wasting mental and physical energy trying to equalise using air from my lungs. There are other options, though, making better use of the residual air left in your mouth, rather than topping up from your lungs. Using what’s already closer to your ears (ie in your mouth) is much more efficient and uses less energy.

So I had a freediving lesson recently in which I was learning this new technique. We never went deeper than 7m the whole time. I was trapping air in the roof of my mouth and concentrating really hard on only using that air to equalise. What was strange was that 7m dives, which I can do very easily and quite fast if I want, became really quite hard. Equalising became something I was battling with, and I had to focus hard on how to use the muscles around and in my mouth to get that last bit of air into my ears.

Now here’s my point: the fact that what was previously easy (a 7m dive) became hard was exactly the point. The battles I was having were a sign that I was doing precisely the right thing – only using the air in my mouth and not ‘cheating’ my topping up from my lungs. There were other benefits too: this is something I can practice much more safely because I don’t need to be diving down beyond 20m to keep doing it. Now, if I’m just freediving for fun less than 20m, I can use my old technique no problem. But when I want to go deeper, this new technique is going to be really important.

By making something easy harder, my instructor was helping me develop and learn.

So what does this mean about supervision?

Exactly the same point applies! Good supervisors may, at times, make something that used to be relatively easy or straightforward much harder to do. It could be presenting complex theoretical ideas or concepts which ‘make a mess’ of something that used to seem quite easy to make sense of. It could be taking your elegant research design to pieces and pointing to all its limitations and the other options. It could be pointing to qualities in academic writing (voice, flow, authority, meta-text, signposting etc), that make both the process and product of writing seem much more complicated and harder to achieve. So, when you go from being able to churn out 2,000 words in a day to struggling to produce 500 and even then thinking they aren’t that great… that could be a really good sign. When you keep going round in circles and end up with a sprawling mess of ideas relating to something that used to be nice and neat… that could be a really good sign. When you find it hard to fix on a design because the consequences of choices are hard to determine and the balancing act in navigating those choices is starting to seriously wobble… that could be a really good sign.

Obviously the end goal is not that our ideas are a mess or that writing feels like torture. But if we are going to get good at working with theory and concepts, design powerful, parsimonious studies, and write about complex ideas and techniques in a clear and persuasive way, then we may have to accept that things are going to get harder for a while.

So, if you’re a student, next time you’re working on stuff between supervisions, and are thinking “Grr! This hasn’t got better since we last met, it’s got worse!”, consider whether your supervisor may be doing something that is tough but productive in the long term.

As a supervisor I would try to share this explicitly with students if this is my purpose. “We’re working on developing a number of features in your writing right now, so it totally expected that it’s going to feel harder, slower, more frustrating for a while. These are all good signs”… or something to that effect.

Which reminds me of something I realise I keep saying to myself and to students I’m working with: “If you’re finding it easy, you’re probably not doing it very well”. While this is a bit crude, the point is that research degrees are supposed to be hard. The best writers draft and redraft, and start over, and agonise of word choice, sentence structure, paragraph order, what gets in and what doesn’t etc.

My point is not that good supervision makes everything as hard as possible and leaves no room for trying to make things easy. Far from it. But I think there are definitely times in the process when making things harder (with appropriate support, explicitness, and expectation management), a good thing.

At the time of writing this initially, my depth diving was limited by equalising, and I was taught a few techniques to practice in shallow water. These made equalising harder, as I explained above… however I can now report that it has all paid off! I recently managed a dive to -42m – over 12m deeper than my previous personal best (which was limited by equalising problems). So it really did work… and here is the video to prove it (the bit talking about ‘constant Frenzel’ is where I apply what I learned in shallow water)

There is no such thing as a doctoral student

This post is a playful thinking-through of what it means to be a doctoral student. Obviously it is based on being pedantic about words and phrases to explore and make a point, but where we end up is interesting…

(1) You can’t be a ‘student’ and be ‘doctoral’ at the same time

If ‘doctoral’ means ‘studying for a doctorate’ then obviously my claim (1) above is false. But, if ‘doctoral’ refers to ‘being of a doctoral level’ then it is arguably true.

(By the way, for simplicity I will use ‘PhD’ as a placeholder for most doctoral degrees, like PhD, EdD, DCA, DPhil; but probably not DSc or DLitt – the super-posh, rarely awarded degrees that don’t apply to the lowly likes of you and me.)

If you’re studying for a PhD the point is to learn what it means to do research of a particular scope, level and quality. This is usually referred to as ‘doctoral’ and implies a kind of ‘doctoralness’ in what you are doing. The doctoralness of what you have done is not established until your examiners proclaim it so. And it cannot be evidenced until the very last minute when it all hangs together in a thesis (or creative work and exegesis) of some kind. However brilliant, your literature review is not doctoral until it is part of a wider piece of work. Your analysis may be ground-breaking and reveal a remarkable discovery. It is not doctoral until it is placed in the context of your scene-setting, argument as to previous work and the gap it has left (so-called literature review), your discussion, and conclusions.

Until you have the whole thing in place, doctoralness is an elusive quality. It may be that particular pieces of work that you do along the way are of a standard that will serve you well when it comes to putting it all together and making your case for the title ‘Dr’. But technically none of these things are yet, nor can they be, doctoral. A doctoral thesis is more than the sum of its parts. That’s what makes it doctoral. Any one part or task along the way can certainly fail to meet the standard, but this standard is not ‘doctoralness’, but something different.

Does this mean I’m saying journal papers can never be doctoral? Well, yes! (perhaps for the sake of argument). This doesn’t mean that journal papers are all ‘sub-doctoral’ in the sense that they are at a masters or lower level in terms of the robustness of the contribution or their intellectual sophistication. Journal articles are not miniature PhDs. Doctoralness is an aesthetically and substantively unique concept, and the only way to demonstrate doctoralness is in a doctoral thesis of one kind or another. That’s why a thesis by publication requires a linking text (exegisis, kapa etc) that frames the papers as part of a wider body of work, and (crucially) your development as a scholar.

What I’ve written above implies a lot about what doctoralness is – I’m not going to spell it all out (at least not here). But I am going to say it is worth some serious thought. If journal articles, even the most highly cited, groundbreaking ones, are not doctoral, what is? If the building blocks you create along the way (data, chapters) are not doctoral, what does this mean for your thesis?


(2) There is no such thing as a doctoral student in the same way there is no such thing as a baby

In the mid twentieth century, Donald Winnicott coined what has become a famous aphorism: “There is no such thing as a baby*”. What?! I’m guessing most, if not all, readers of this post would think, quite reasonably, that they were a baby at some point in their lives. Perhaps you were only a baby very briefly, before you morphed into that intellectually dazzling toddler… Or maybe you can’t be sure you were ever a baby, but you’re pretty sure babies exist: that last long haul flight was plagued by one of them screaming her lungs out, stopping you getting any sleep; those things in the really annoying pushchairs that get in the way pretty much everywhere aren’t just worryingly realistic (and noisy, smelly) dolls, they’re little human beings, right?

Yes, you’re right. And I’m no baby-hater. But Winnicott had a point. He went on to say: “A baby cannot exist alone, but is essentially part of a relationship”. Elsewhere he wrote “if you set out to describe a baby, you will find you are describing a baby and someone” (1947).

I think the same could be said of doctoral students.

A doctoral student cannot exist alone. Though an interaction on ResearchGate showed me that some like to think so. A prospective student posed the question, ‘Can I study for a PhD without a supervisor?’. To me this wreaked of arrogance (although everyone else on the planet and in history has needed a bit of help, I’m so brilliant I can do it by myself), and revealed a painful reluctance to do any homework on what a PhD is and what it means to study for one. The only rationale I could see here was someone thinking more about the certificate than the learning that leads to it.

My distaste at this proposition reveals how Winnicott’s idea applies. It was inconceivable to me that a PhD could be obtained without some kind of supervision or assistance from others. Yes, supervisors disappear sometimes, relationships break down, students don’t get the feedback they need. But zero support means no degree. It really is as simple as that. [I expect among readers there might be people who feel they are doing or did their PhD alone, abandoned by supervisors, or perhaps professionals who put together a thesis based on publications without much or even any supervision; in the first case my bet is you were not as alone as you think you were; in the second case this is not the kind of thesis I’m talking about, and my response to the first case also applies].

When you describe a doctoral student, you will quickly find yourself describing the other people around them. This is not to bloat the role of supervisors, or to negate the independence, creativity and shaping that come from doctoral students. But your thesis would be a different thesis if you had a different supervisor or different supervisors. It would be different if you had chosen to study somewhere else. Your thesis is a product of you, your work, and the intellectual environment you are part of.

Doctoral students can’t be imagined outside of other relationships, too, although we might often feel that our institutions forget this. Every doctoral student is always one or more of the following: someone’s sister or brother, mother or father, daughter or son, friend, colleague, housemate, facebook friend, twitter follower etc etc. Doctoral students are always other kinds of human beings. I might even be so bold as to say they are other kinds of human beings first.

So, when someone asks you “Are you a doctoral student?”, have fun and do your best to discombobulate the person asking the question. You might try these responses:

“No. There’s no such thing!”

“No, I’m a person [sister, mother, daughter] who happens to be studying for a PhD.”

“No. I’m learning to do research, and might by the end of it be able to show that what I’ve done is doctoral, but until then, I’m more student than doctoral.”

“No, I’m a doctoral student working with an amazing [or terrible, or something in between] supervisor.”



* Tracing the precise origins and wording of this phrase are a bit hard to pin down. It seems he spoke the words “There is no such thing as an infant” in 1940 in a discussion at the Scientific Metting of the British Psycho-Analytic Society. Since then different print versions and attributions have proliferated. A good place to look is Winnicott D (1964) The child, the family and the outside world. Hammondsworth: Penguin Books.

A metaphor and a simple framework for thinking about research design


I’ve published a video, freely available on youtube, outlining a framework I’ve been using for thinking about research design, particularly in social sciences.

It is based on 4 central ideas, that gradually adopt a more fine-grained focus, and a necessary gesture towards analysis: hence the idea of a 4+ part framework.

The parts are:

1. Strategy – the big picture, how you name the kind of research you are doing. This does a lot of work in setting the tone and character of your research, signals to others what they might expect, and from this, many implications for other parts of design flow.

2. Sampling – not necessarily implying positivistic / quantitative notions, but pointing to the need to think seriously about who is involved in research (or what, if you’re looking at documents for example), who isn’t, what your relationships with these people or objects are, what inclusions and exclusions there are, whether and how these matter etc.

3. Methods – the broad tools you use in your research to gather information (or generate data, if you’re coming from a more constructivist paradigm where things aren’t out there waiting to be discovered…). I raise the question of alignment between these and your research questions, but distinguish methodological issues from…

4. Techniques – this is how you use the tools in (3). What kind of interview are you doing? How are you observing? What is your survey like? Here I point explicitly to aesthetic aspects of the accomplishment or performance of research methods, the art that goes with the (social) science.

4+ – Analysis. Learning from my own mistakes in the (now dim and distant) past: going and getting data, or designing research without thinking through how the analysis will proceed is a no-go. It doesn’t mean you can predict and anticipate exactly what you’ll do analytically, but it’s better to think ahead than to get what looks like great data and then realise there’s no sensible way to analyse it that links to your research question (I say this from experience!).


The tree metaphor

The video makes use of a tree metaphor, talking about research as planting seeds and growing a tree.

Where do you plant the seeds here and not there (ie. why this topic / question and not another? what other trees are growing here? what else has been done?)

How tall does your tree have to be? (ie. what do you have to do to stand out and make a new contribution in this field?)

How thick is your trunk? (ie. how do your make your research sturdy, able to withstand the odd thing going wrong, and the gusty winds of academic critique?)

How wide are your branches? (ie. how far can your analysis take you beyond what you studied to saying something of wider relevance? This doesn’t mean empirical generalisability necessarily!)

How tasty is your fruit? (ie. how palatable are your conclusions? or at least, how inviting is what you have to say in terms of capturing people’s attention. You don’t necessarily want to say what people want to hear, but you’ve got to get them enticed somehow!).


The prezi itself can be viewed at but this will be without the audio commentary on the video.


I hope you find this helpful!


I should acknowledge that this post and the video float in a void in terms of references to methods literature. I’m not claiming anything revolutionary here and am sure that may people talk about similar issues in research design. The tree metaphor is probably new (at least as far as I’m aware), and I think some clarity around saying design involves thinking about strategy, sampling, methods, techniques (oh, and analysis!) may be helpful. These terms are used in many different ways in the literature. This is simply how I find it useful to think about them.

Video about journal publishing basics

I’ve been preparing for some workshops on journal publishing for postgraduate research students and early career researchers. Following the idea of Flipped Learning, and the ‘Learning 2014’ strategy at UTS, my home university, I’ve been trying to minimise the time participants spend in the workshops sitting listening to me talk, and to create more time for group discussion and activities instead.

So I created a 30 minute video covering some basic points – many of which I’ve written about in other posts. Although readers of this blog won’t by default be able to come to the workshops I’m running, I thought I’d share the video anyway in the hope it might still be useful. One day I might even put my face in front of the camera!

If you’re interested, the workshops will then go on to look at: why papers get rejected, what reviews look like and how to respond to nasty ones (which are a sad inevitability in academic life), how to frame a response letter when you’re asked to revise and resubmit, and the ethics of peer review.

The main video can be viewed here

There are two supplementary videos

1. How to find out the ‘zombie’ rank of a journal.

2. A bit more about researching the relative rather than absolute impact factor (or other status measure) of a journal.

The second one gets a bit more into technical side of using excel once you’ve imported relevant journal metrics data from an external source such as Scopus or SciMago SJR.

Please do add feedback and comments below! Are the videos useful? Do you disagree? Do you choose journals in a different way? Do you assess journal status differently? Am I out of date about copyright issues?

On this last point, a big BUYER BEWARE warning: copyright things are changing very fast. Only this week Taylor and Francis announced AAM (author accepted manuscripts) can be put on personal or departmental websites, free of embargo (this doesn’t mean you can make the final paper pdf freely available, but the pre-proofed word version)… so some of my comments will get out of date quite quickly if things keep changing!


A guide to choosing journals for academic publication

The key is the match between your paper and the journal

Choosing a journal for your paper is a complex and nuanced process. Don’t expect to be able to ask anyone else off the cuff and get a sensible answer. Only people who know what you want to say and what you want to achieve in saying it can provide guidance, and even then it’s up to you to judge. In writing this I hope to make this process more transparent, and to help you be as informed as possible about your decisions. If you disagree, or can add more things to consider, or more measures of status please leave a response at the bottom!

Chicken and egg

Which comes first the paper or the choice of journal? Neither. Both. In my view you can’t write a good paper without a sense of the journal you are writing for. How you frame the argument / contribution, how long it is, which literature you locate it within, how much methodological detail, how much theoretical hand-holding is needed for readers, what kind of conclusions you want to present, what limitations you should acknowledge: ALL of these are shaped by the journal. But how do you know the answers to these questions? Usually by writing a draft! See the chicken-egg problem? My process is as follows:

  1. Come up with a rough idea for a paper – what data am I going to analyse, with what theoretical focus, presenting what new idea?
  2. Come up with a short list of potential journals (see below)
  3. Plan the paper down to paragraph level helps me think through the ideas and make good judgements about the fit between it and journals in the short list.
  4. Choose a journal. If in doubt write the abstract and send it to the editor for initial comment: what’s the worst that could happen? She or he could ignore it!

An ongoing conversation

Most journal editors want to publish papers that join and extend a dialogue between authors that is already happening in their journal. This gives the journal a certain shape and develops its kudos in particular fields or lines of inquiry. If no-one has even come close to mentioning your topic in a particular journal in the last 5 years, I’d think twice about targeting that outlet. Unless you really are planning a major disruption and claiming woeful neglect of your topic (which says something about the editors…)

Check out the editors, and stated aims and scope

Editors have the ultimate say over whether or not to accept your paper. Check out who they are, and do some research. What are their interests? How long have they been on the editorial board? If it’s a new editorial board, are they signalling a broadening, narrowing, or change in scope perhaps? What special issues have come out?

Don’t be stupid

Don’t get the journal equivalent of ‘bright lights syndrome’ and choose somewhere just because it is uber-high status (like Nature). Don’t be a ‘sheep’ either and choose a journal just because someone you know has got their paper accepted in it. Don’t send a qualitative paper to a major stats / quantitative journal. Don’t send a piece of policy analysis from (insert your random country of choice here) to a major US journal (for example) when your paper has nothing to say to a US audience.

The devil is in the detail: yes – more homework

Check out things like word limits, and whether they include references. If the journal allows 3,000 words including references, and your argument takes 5,000 to develop, either change your argument or change the journal. Simples. Also check out the review process. Look under abstracts in published papers for indications as to the timeline for review, and check if there are online preview or iFirst versions published (which massively reduces the time to publication). Don’t be caught out with a whopping fee for publication if your paper is accepted. And don’t be shocked when you read the copyright form and find it costs $3,000 for open access. Some journals publish their rejection rates: you’d be foolish to plough on not knowing 90% of papers are rejected even before review (if this was the case).

Publish where people you want be visible to are reading

Think who you want to read your paper. Forget dreams of people from actual real life reading academic journals. The only people who read them (except some health professionals) are, on the whole, other academics. This isn’t about getting to the masses: there are other, better venues for that. This is about becoming visible among your disciplinary colleagues. Where are the people you like and want to be known to in your field publishing? What journals do they cite in their papers?

Understand the status of the journal you are submitting to and its implications for your career

This is the biggie. So big I’ve written a whole section on how to do this below. But for now a few key points.

  1. It pays to know what will be counted by universities in terms of outputs, and what will have kudos on your CV. In Australia, for example, journals not on the ERA list are pretty much no-go. In some fields (particularly hard science and health), journals not indexed in Web of Science aren’t recognised as worth the paper (or pixels) they are printed on.
  2. Remember that status measures only measure what can be measured. A really prestigious journal in your field – with lots of top people publishing lots of great papers in it – might be lower (or not even register at all) in all the various indices and metrics.
  3. There is no single flawless measure of status. Take a multi-pronged approach to suss out where a particular journal lies between ‘utter crap that publishes anything’ to ‘number 1 journal in the world for Nobel Laureates only’.
  4. There are many good reasons for publishing deliberately in lower status journals. It may be they have the ‘soft’ status I mentioned above. Maybe that is where you can actually say what you want to say without having to kow-tow to ridiculous reviewers who don’t understand or accept your innovative approach (which they view as floppy, oddball etc.).

How journal status is measured and how to find this information out

A whole book could be written on this, so please forgive my omissions.

Impact Factor

This is the one everyone talks about. It is also the bane of many people’s lives outside natural and health sciences. Impact Factor is a measure of the mean number of citations to recent articles published in a particular journal, excluding citations in other papers in the same journal. So an Impact Factor of 2.01 in Journal X means that each paper in X has been cited a mean of 2.01 times in all the other indexed journals, except X, over the past two years (five year figures are also used). The higher the impact factor, the higher the status, because it shows that the papers are not only read but they are cited lots too. Excluding the ‘home’ journal stops editors bumping up their own Impact Factor by forcing authors to cite papers in their journal. Why is this problematic? Where do I start?!

  1. Not all citations are for the same reason but they all get counted the same. If you cite paper P as one of several that have investigated a topic, and paper Q as a hopeless study with flawed methods, and paper R as hugely influential and formative, shaping your whole approach, they all get counted the same. In theory, publishing a terrible paper that gets cited lots for being terrible can boost an Impact Factor.
  2. The key is in the reference to other indexed journals. The issue is: what gets to be indexed? There are strict rules governing this, and while it works okay in some fields, lots of important, robust journals in social sciences and humanities aren’t indexed in the list used to calculate Impact Factor; at least that is my experience. This can deflacte Impact Factor measures in these fields because lots of citations simply don’t get counted. The formal ‘Impact Factor’ (as in the one quoted on Taylor and Francis journal websites, for example) is based on Journal Citation Reports (Thomson Reuters), drawing on over 10,000 journals. Seems a lot? In my field, many journals are missed off this index.
  3. The time taken to be cited is often longer than two years (google ‘citation half-life’ for more). Lets say I read a paper today in the most recent online iFirst. I think it’s brilliant, and being a super-efficient writer, I weave it into my paper and submit it in a month’s time. It takes 9 months to get reviewed, and then another 3 months to get published online. Then someone reads it. Process starts again. If the world was full of people who read papers the day they came out, and submitted papers citing them almost immediately, still the lag-time to publication in many fields prevents citations within the magic 2 year window. There are versions of Impact Factor that take five years into account to try to deal with this problem. This is better, but doesn’t benefit the journals that publish the really seminal texts that are still being cited 10, 15, 20 years later.
  4. Impact Factors are not comparable across disciplines. An Impact Factor of 1.367 could be very low in some sciences, but actually quite high in a field like Education. So don’t let people from other fields lead your decision making astray.
  5. Impact Factor may work very well to differentiate highly read and cited for less highly read and cited journals in some fields (where the value range is great, say from 0 to over 20), but in fields when the range for most journals is between 0 and 1.5 its utility for doing so is less good.
  6. Editors can manipulate Impact Factors to a degree (eg by publishing lots of review articles, that tend to get cited lots). See Wikipedia’s page on impact factor for more.

How do you find out the Impact Factor for a journal? If you don’t know this you haven’t been using your initiative or looking at journal webpages closely enough. Nearly all of them clearly state their Impact Factor somewhere on the home page. What can be more useful though is knowing the Impact Factors for journals in your field. In this case you need to use your go to Web of Science. I recommend downloading the data and importing it into excel so you can really do some digging. In some cases it may not be so obvious to find, in which case try entering ‘Journal title Research Gate’ into google eg ‘Studies in Higher Education Research Gate’. The top result should give the journal title and research gate, and a url like this: . Immediately on clickling the link you will find data on Impact Factor, 5 year Impact Factor and more (based on Thomson Reuters). Note this is not an official database and may be out of date at times.

Alternatives to Impact Factor: SJR

An alternative that may work better in some fields is the Scopus Scimago Journal Rankings (SJR). This includes a range of metrics or measures, and I have found it includes more of the journals I’ve been reading and publishing in (in Education). The SJR indicator is calculated in a different way from Impact Factor (which I admit I don’t fully understand, see this Wikipedia explanation). It has a normalising function as part of the calculation which reduces some of the distortions of Impact Factor and can make it more sensitive within fields where there are close clusters. SJR also has its version of impact called the ‘average citations per document in a 2-year period’. When I compare the SJR and Thomson Reuters measures for journals in my field, some are very similar and some are quite different. So it pays to do your homework. SJR data are also easily exportable to excel and you can then easily find where journals lie in a list from top to bottom by either of these measures (or others that SJR provide). The easiest way to find out the SJR data for a particular journal is simple: type the journal name and SJR into google eg ‘Studies in Higher Education SJR’. Almost always the top result will be from SCImago Journal & Country Rank, something like . If you go there you’ll fild a little graph on the left hand side showing the SJR and cites per doc tracking over 5 years, given to 2 decimal places. There is also a big graph, with a line for each of these two metrics. If you hover over the right hand end, you get the current figure to 3 decimal places. See the screen shot below.

Scimago info

A screen shot from SJR showing the Indicator and cites per paper data

Alternatives to Impact Factor: Zombie Journal Rankings

In Australia, lots of journals were, at one time, ranked A*, A, B or C. This was done using a pool of metrics and also peer-based data with groups of academics providing information based on their expertise. For various reasons (don’t get me started) these have been abolished. However they are a common reference point still in many fields in Australia and New Zealand, and so I call them ‘zombie rankings’. Even if you’re not in Australasia, it might be useful to look up what the rank was, to see if it confirms what you’re finding from other measures. The quickest way to is go to the Deakin University hosted webpage and to check under Historical Data, then Journal Ranking Lists, then 2010 (the rankings were alive in 2010, and abolished shortly afterwards). The direct URL is here: . Type in the journal name, or a keyword and ta-dah! If you just type in keywords you will get multiple results and may be able to see a range of options. I’ve put an image of what it looks like below. Pretty easy stuff.

Zombie Ranks

A screen shot from the Deakin website showing former ERA journal rankings

Alternatives to Impact Factor: ERA list

Now there are no rankings, ‘quality’ is indicated in a binary way as either included in the ERA list or not. We’ve just had a process in Australia of nominating new journals to be included in the list for 2015. But the current 2012 list is also available through Deakin. .

Alternatives to Impact Factor: rejection rates

The more a journal rejects, the better it must be, right? Well that is the (dubious, in my view) logic underpinning the celebration of high rejection rates in some journals. I’m more interested in what gets in and what difference that makes to scholarly discourse, that what is thrown out. But hey, if you can find this information out (and it’s not always easy to do), then it may be worth taking into consideration. More for your chances of survival than as a status indicator perhaps.

Alternatives to Impact Factor: ask people who know!

While only you can judge the match between your paper and a journal, lots of people in your field can give you a sense of where is good to publish. This ‘sense’, in my view is not to be dismissed because it cannot be expressed in a number or independently verified. It is to be valued because it draws (or should do) on knowledge of all the metrics, but years of experience and reading.


Choosing journals is tricky. If you’re finding it quick and easy it’s probably because you’re not doing enough homework, and a bit more time making a really well informed decision will serve you well in the long run. As I said earlier this post is not exhaustive either in terms of things to consider in your choice, or status indicators. But I hope this is useful as a starting place.