Becoming, being, and change: reflecting on early career (and what comes next)

I’ve been trying to write this post for a while, and I can’t quite get what is in my head onto this page in quite the right way. What I want to do is something a little indulgent, and reflect on my experiences, over the last 5 years, of becoming and being an ‘early career researcher’. I am a couple of weeks away from no longer officially being one, according to my country’s National Research Foundation, and some of the literature out there*, and I am pondering what is next, and whether I am quite ready.

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If you take 5 years as the ECR period – the guideline I am using – then my time is almost up. On the 10th of April, it will be five years since I graduated with my doctorate. This is giving me pause.

There is a certain amount of mental and emotional ‘space’ that comes with early career. People expect you to publish, but not to churn out top quality papers that make a huge impact in your field. You are joining, rather than steering, the conversations in your field. You’re learning how to publish, and conference, and engage as a peer in your field. People expect you to teach, and consciously grow as a scholar, but if you are not yet settled, it’s not really a big problem – yet. ‘Early career’ seems to offer a bit of space to hang back, and observe, and then choose your doing with help from mentors – perhaps a supervisor, or more senior academic peer – alongside you. And the doing can be halting, and uncertain at first and no one will get too het-up about it.

As I move towards the next phase – I assume ‘mid-career’ – I am starting to supervise my own students, and I am starting to apply for grants to run my own research projects. Thus far, I have been supervised and mentored, and joined projects others have won funding for. Moving from being mentored to being a mentor to others is one significant change from early to mid-career. I am now asked to be responsible for parts of others’ research journeys, and this is daunting. It means you have to know stuff – what to read, what networks to join, which are the good conferences to attend, what areas of study are novel – and be able to do stuff – offer feedback and advice on writing and thinking work, co-write grant applications, co-publish with students and peers more often. There are more things, I am sure, but these are the ones I can think of now (that are pressing on me, anyway). Less time to observe, and hang back, and see what happens.

Moving into a more ‘mid’ phase of my career now, I feel like the biggest shift is the one from becoming, to being (and a new trajectory of becoming). I have become a researcher, and now I have to really be one. I have become a doctor, and now I have to help others to achieve the same goal through being a supervisor. I have become a decent writer, and now I have to really be a published author. And this is what I signed up for, and actually I enjoy all of the work, but what is making an impression on me is that time is taking on a different dimension. My career is starting to really grow now, and things feel like they’re speeding up a bit. Citations are becoming a thing, and making my research more visible. There is pressure to publish a few papers a year, and I am writing a book. I feel I need to be thinking about other avenues for sharing my research with wider audiences, such as in newspapers or The Conversation. I need to really start thinking about wider forms of service to my scholarly community, such as serving on editorial boards, reviewing papers, examining dissertations and so on. I now have enough distance and time from my own doctorate to be able to offer these services, and do a relatively good job.

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I am struggling to sum this all up – probably because the becoming is ongoing really. I am still becoming a scholar, and mentor, and supervisor, and researcher, and critical peer, yet many of these roles are offered now because I am seen as being further along the path in terms of knowledge, experience and ability. I have climbed a few key staircases or ladders, and have the capacity to keep climbing, choosing which staircases to climb, and who to bring with me. I have different choices ahead of me: new research projects and related networks, different kinds of writing, teaching and travel opportunities, different ways of being an ‘academic scholar’ and playing this particular game.

Although there is less time for hanging back, there are new kinds of freedom: I have seen more of how the ‘game’ of academia works, and with that knowledge, I can make better choices about how I want to play it in this next career phase. I can see better some of the push and pull factors that I was blind to 5 or more years ago. Although I’d like a bit more time to be ‘early career’, especially to indulge in the mental allowances I have given myself to hang back at times, and be a participant guided by others but not a leader and guide, I can’t stay here forever.

I will, of course, always have mentors of different kinds as I go, and leaders are also participants, and time can be manipulated to suit your own life, and personality and pace. The becoming never becomes a static form of being – being is a just a landing on a much longer staircase of becoming. So, I suppose I am on a new landing, looking up at a new set of stairs, familiar and also strange. Now, I just have to find the strength, and courage, to start the climb.

*Literature from Australia and the UK defines early career as five year post-the end of a PhD degree. In the US, early career is a little longer, perhaps 7 years and tends to incorporate the end of the PhD process. In Africa, early career often includes all or part of the PhD, and therefore can extend to a period of 7-10 years. So, there are different time-periods and also definitions of what needs to fill up this time to move a researcher from early into mid-career.

Creating a coherent text: ‘sign-posting’ your argument

Readers of this blog may know that a big part of my work-life is reading and commenting constructively on other people’s writing – PhD scholars, postdoctoral fellows, peers. I spend hours each year immersed in people’s words, ideas, arguments and theses. And, while this work is difficult, and can be really draining of my own writing energy, it has the benefit of giving me a deeper awareness of what makes a piece of writing work, and what does not. In this post I want to reflect specifically on ‘signposts’, as a tool to create a more coherent, reader-friendly text.

When we read, our brains work to make sense of what is in front of us. When the writer has worked hard to ensure that what we are reading is well thought-out, and carefully put together, this is easier. But, when the text is ‘patchy’, and the links between the pieces are unclear, this sense-making work becomes harder. As a reader it is frustrating, because it’s hard work. Readers who have to work too hard may give up and move on to reading something else. So, as a writer, putting this kind of text out there is risky. What we need to be putting out there for our readers is a text where the ‘moves’ we are making in putting the story together are clear, and signalled, so that the reader’s work is less trying to work that all out, and more trying to engage with and appreciate the story itself.

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So, you are writing a paper. You have a basic argument in mind – a claim, or series of claims that you know you need to make. You have done your reading, and have notes around the evidence that will go with these claims to support them. You start writing, and the argument develops and may take a somewhat different turn to what you originally thought. You start to worry that you have lost your argument thread – what are you actually saying anymore? How does this all fit together? Does it, even? This is all the first draft (and maybe second draft) process of working out what you are actually trying to say, and whether and how you can say it in this paper. Totally on track so far.

Where the more conscious connecting, and care, comes in is usually on draft three or more, where you have to start making the thread of the argument clear, and overt, for the reader. This is where you need to start thinking about structure, coherence, and the tools you can use to ensure this. There are a couple of tools that I use, as ‘sign-posts’, to guide readers through my argument. These are ‘foreshadowing’, descriptive sub-headings, and clear transitions.

Foreshadowing

This, in essence, is a tool that uses clever repetition to create links in the readers’ minds between paragraphs, and sections, of the paper. Repetition is often discouraged in academic writing, but there is a use for it, when it consolidates and advances the development of your argument.

From: https://doi.org/10.18546/LRE.15.1.04

See how these writers have used the term ‘bridge’ in the text, and then again in the sub-heading. And, how they have connected this idea of a bridge to disciplinary knowledge structures. This term, in a different way, is then repeated under the sub-heading, and the effect for the reader is to see, without being told in a sentence that starts with ‘The next section will …’, that they are going to read about what the writer thinks this bridge is, and how it is connected to knowledge in the disciplines. The value of trying to use repetition, carefully, to build connections between ideas, as well as complexity of ideas, over the course of a paper, is that you show the reader what your argument is (and why it is useful), rather than telling them what it is. This is a more reader-friendly approach, and more likely to engage the readers with the argument itself, than with the way the argument is structured.

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Descriptive sub-headings

Not everyone is allowed to do this. If you are writing for a journal in the natural or applied sciences, or that has a more ‘traditional’ approach to journal article structure, you may be given your subheading (Introduction, Materials and Methods, Results, and so on). But, if you are writing in a field, and for journals, that is less prescriptive about this, consider using your sub-headings, with your text, to create sign-posts for readers to move them from one sub-section to the next as your argument builds.

Instead, for example, of ‘Literature review’, consider the main claims or points this section is contributing to the argument overall, and create a sub-heading that captures this. Instead of ‘Theoretical Framework’ or ‘Discussion’, try headings that capture what the theory or discussion contribute to the argument. This further enables the reader to see each step of the argument, and how they are being led in one direction, rather than wandering around in circles or zig-zags. See the examples below, and how the authors use a mix of foreshadowing and descriptive sub-headings (e.g., ‘driven by economic concerns’ and then ‘Drives to increase…’

From: http://www.tandfonline.com/doi/full/10.1080/14703297.2016.1155471

And here: they introduce the notion of the ‘politics of disciplinarity’ in the text, along with the ‘university system’ and then show with the sub-heading that they are moving forward to elaborate on these issues in the next section of the paper.

From: https://files.eric.ed.gov/fulltext/EJ523110.pdf

If you are working in a field that will not look kindly upon descriptive sub-headings, you will need to think more creatively about the transitions you create for your readers. I urge you to go beyond statements, like ‘the next section will discuss X’. Too many of these, and the reader starts to feel like they are being taken through a list of points, rather than a joined-up argument. Rather, think about what you have been writing about, and where you are going next, and what the ‘content’ connection is. What is the link between the present section, or paragraph, and the next one? How are they connected together in light of the overall point of this section, and the unfolding argument? Try to capture that in the transitional sentences.

From: http://dx.doi.org/10.1080/13562517.2011.611876
From: http://dx.doi.org/10.1080/13562517.2011.611876
From: http://dx.doi.org/10.1080/13562517.2011.611876

Hopefully, in these examples, you can see a small sense of what I am arguing for – a form of showing your reader your argument, through carefully thought-out links and transitions between paragraphs and between sub-sections that ‘sign-post’ the steps of the argument as it builds.

If you do not pay attention to sign-posting your argument, especially through carefully and clearly connecting ideas, and claims, to one another as part of a coherent whole, the effect on the reader is usually one of two things, in my experience. The first is the sense that they are reading a list of ideas – they may be in more or less the right ‘order’ to be making an argument, but the ways in which you are joining them together are left to the reader to figure out. The second, is the sense that this is a jumble of ideas, not all of which may belong in that paper, or chapter. Neither make for a reader-friendly experience, and if the reader is lost, or annoyed, or struggling to make sense, this is not good for the writer.

https://pixabay.com/users/geralt-9301/

Clear, careful, and visible signposts that are creatively woven into your text take time, and work, and iterations of drafting and feedback from readers. But, they are the ‘glue’ that binds your argument together.

Obtaining the data you really need: on conducting qualitative interviews

I have been planning a new qualitative research project, and reading draft proposals and draft methodology chapters for students I am coaching, so I have been thinking about qualitative data lately; particularly how to get the right kinds of data from participants when we are conducting interviews.

There are three main forms of interview that are discussed in methodology texts and guides: structured, semi-structured and unstructured. Generally, when embarking on a qualitative project, students tend to opt for semi-structured interviews. This enables them to have a set series of questions, hopefully well connected to their theory and literature, but also to create space for participants, or interviewees, to add views and insights that may not strictly follow the questions. It’s sort of a best-of-both-worlds scenario. Unstructured interviews are hard to manage, especially for postgraduate students, many of who are doing this form of fieldwork for the first time. And fully structured interviews can veer into not allowing any space for additional, unpredicted insights and information – they can, in other words, limit the conversation, and also the kind of data collected. *Caveat: you do need to choose the right tool for your project, regardless of whether it is hard to do or not.

But, semi-structured interviews, while they seem to be a dominant preference for many students doing qualitative research via interviews, are not easy to do well. A key issue I am thinking about in relation to my new project, and that I assist other researchers with, is this: how do I conduct the actual interview so that I get the data I really need? What tools or techniques so I need to be aware of? I have listed a few points here that have helped me, and that are also the product of my own mistakes and learning in conducting qualitative interviews.

interview 1

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  • The point of the first interview is to get a second interview. 

I didn’t know this during my own PhD, which was also my first major research project. I did one set of interviews, and I do recall, on reading the transcripts, wishing that I could go back and ask some of the questions differently or find out more about specific issues. But I didn’t really know I could (and I didn’t plan for this so I ran out of time). But, now it makes complete sense. Unless you are interviewing someone you already know well, chances are you and the interviewee will be strangers to one another. Establishing a rapport, and trust, can take time – certainly more time than one interview allows for. So, you need to make the goal of the first interview establishing a connection that will enable you to go back, and talk to that person again. You may get the basic data you need in the first interview, but chances are that you will need more that interview #1 can yield. You will want richer, or deeper responses to some of the questions, or will see that certain questions could be asked differently, to yield slightly better, or more relevant, responses considering your research questions and aims.

Plan enough time for at least two interviews, and ensure that you check with the interviewee that you could approach them again if needed. Listen to the recording of the interview as soon as you can, then, make notes, and think about what the data is saying in relation to those research questions. Then work out whether you have enough of the rights kinds of data to include in your analysis, where any gaps are, and plan interview #2 accordingly.

  • Record your interviews and take notes.

You always want to audio-record the interviews, so that your transcription, analysis and reporting will be accurate, and rich. But, you also want to take notes – not so many that you are unable to maintain eye contact and engagement in the interview, but have a notebook and pen to record things that the audio may not capture. Perhaps body language is a factor to consider in terms of the kind of data you are generating – if participants appear nervous, or distracted, this may be something you want to consider in the analysis alongside their words. Perhaps what their words say, and what their body language says are two different things, and this could be important as a possible finding. Perhaps they mention names of other people you could consider interviewing as well, or names of websites, documents and other sources of information you need to follow up on. All of this can be captured in a few short notes, and can add to the richness of your overall findings and analysis later on.

  • Plan for a pilot interview.

This has been a big point of learning for me. I tend to get over-eager in interviews, and I just plain talk too much. I find myself listening to the audio and cringing, and wishing I could just be quiet, and let the interviewee talk! There are two benefits, here, to a pilot interview: the first is that you can practise being an interviewer. You can work out how to record and take notes, how to talk less and listen more, how to direct and redirect the conversation as needed, and how to manage your own facial expressions and body language, to remain as neutral as possible so as not to bias or shift the interview in unhelpful directions (like looking shocked or disapproving at something an interviewee says to you). The second is that you can figure out whether the style you are using and questions you have as a guide are yielding the answers you need. Are there too many questions? Are some of the questions too long and ‘wordy’? Do any of the questions yield answers that seem a bit off topic, or that are repetitive? Make notes and adjust the interview plan before the real interviews begin. You need to do a pilot with someone who represents the interviewee demographic, and preferably with enough time to make changes and adjustments before you start meeting with the study’s group of participants.

interview 2

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  • Plan for a conversation, rather than a Q&A session.

This has been a really big point of learning for me. In a qualitative study, regardless of the topic, you need rich, detailed data. Qualitative research is about depth, rather than breadth, in simple terms. Thus, you need depth in the data, to achieve depth in your analysis, findings and conclusions. Thus, what you want to do with conducting the interview is create a conversational space, rather than a stiff, Q&A session where you ask a long list of questions, and the interviewee responds. The best way, I find, is to start off by asking the interviewees to tell me a story, related to the research I am doing and my interview questions. For example, if I am doing a project on postgraduate supervision, and my interviewees are students and supervisors, I don’t want to start off with something like: “Do you enjoy supervising students, and why or why not?” (Typical kind of question you find in interview schedules). This will not help me to get a richer sense of what the supervisor does as a supervisor, and what aspects they do and do not enjoy. So, what I could rather do is ask the question like this: “Can you start off by telling me a bit about your current supervision situation?” And then just listen. In that response, then, I listen for what aspects they seem to like, or not like, and in the follow up, I could ask: “You seem to find supervision a struggle, rather than a joy, right now. Would you say that is accurate? Could you say a bit more about that?” And then listen. And so on. So my questions become a guide, but not a determinant to the structure of the interview.

The main thing in doing qualitative interviews, I am learning, is for an interviewer to have empathy. Trying to be in the moment, and create a sense for the interviewee that their stories are valuable, and worth sharing and hearing, enables the creation of a rapport that can lead to follow-on interviews, and that can encourage interviewees to see me as an ally, and someone who will share their stories responsibly, ethically and with care. This is crucial when you are working with people who trust you enough to give you truthful stories, experiences and accounts. Ultimately, you need to listen closely, and record accurately, so that what you share in your study is able to meaningfully shape knowledge, research and practice in your field.

Developing well-constructed data gathering tools, or methods, for your study

I spent the better part of last week working with emerging researchers who are at the stage of their PhD work where they are either working out what data they will need and how to get it, or sitting with all their data and working out how to make sense of it. So, we are talking theory, literature, methodology, analysis, meaning making, and also planning. In this post I want to focus on planning your data gathering phase, specifically developing ‘instruments’, such as questionnaires, interview schedules and so on.

tools

Whether your proposed study is quantitative, qualitative or mixed methods,  you will need some kind of data to base your thesis argument on. Examples may include data gathered from documents in the media, in archives, or from official sources; interviews and/or focus groups; statistical datasets; or surveys. Whatever data your research question tells you to generate, so as to find an answer, you need to think very carefully about how your theory and literature can be drawn into developing the instruments you will use to generate or gather this data.

In a lot of the postgraduate writing I have read and given feedback on, there are two main trends I have noticed in the development of research methods. The first is what I considered ‘too much theory’, and the other ‘not quite enough’. In the first instance, this is seen in researchers putting technical or conceptual terms into their interview questions, and actually asking the research questions in the survey form or interview schedule. For example: ‘Do you think that X political party believes in principle of non-racialism?’ Firstly, this was the overall research question, more or less. Secondly, this researcher wanted to interview students on campus, and needed to seriously think about whether this question would yield any useful data  – would her participants know what she meant by ‘the principle of non-racialism’ as she understood it theoretically, or even have the relevant contextual knowledge? Let’s unpack this a bit, before moving on to trend #2.

The first issue here is that you are not a reporter, you are a researcher. This means you are theorising and abstracting from your data to find an answer that has significance beyond your case study or examples. Your research questions are thus developed out of a deep engagement with relevant research and theory in your field that enables you to see both the ‘bigger picture’ as well as your specific piece of it. If you ask people to answer your research question, without a shared understanding of the technical/conceptual/theoretical terms and their meanings, you may well end up conflating their versions of these with your own, reporting on what they say as being a kind of ‘truth’, rather than trying to elicit, through theorising, valid, robust and substantiated answers to your research questions, using their input.

This connects to the second issue: it is your job to answer your research question, and it is your participants’ job to tell you what they know about relevant or related issues that reference your research question. For example, if you want to know what kinds of knowledge need to be part of an inclusive curriculum, you don’t ask this exact question in interviews with lecturers. Rather, you need to try and find out the answer by asking them to share their curriculum design process with you, talk you through how they decide what to include and exclude, ask them about their views on student learning, and university culture, and the role of the curriculum, and knowledge, in education. This rich data will give you far more with which to find an answer to that question than asking it right out could. You ask around your research questions, using theory and literature to help you devise sensible, accessible and research-relevant questions. This also goes for criteria for selecting and collating documents to research, should you be doing a study that does not involve people directly.

analysis of data

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The second trend is ‘not enough theory’. This tends to take the form of having theory that indicates a certain approach to generating data, yet not using or evidencing this theory in your research instruments.  For example structuralist theories would require you finding out what kinds of structures lie beneath the surface of everyday life and events, and also perhaps how they shape people, events and so on. An example of disconnected interview questions could be asking people whether they enjoy working in their university, and whether there are any issues they feel could be addressed and why, and what their ideal job conditions would be, etc., rather than using the theoretical insights to focus, for example, on how they experience doing research and teaching, and what kinds of support they get from their department, and what kinds of support they feel they need and where that does and should come from, etc. You need to come back to using the theory to make sense of your data, through analysis, so you need to ensure that you use the theory to help you create clear, unambiguous, focused questions that will get your participants, or documents, talking to you about what matters to your study. Disconnecting the research instruments from your theory, and from the point of the research, may lead to a frustrating analysis process where the data will be too ‘thin’ or off point to really enable a rich analysis.

Data gathering tools, or methods for getting the data you need to answer your research questions, is a crucial part of a postgraduate research study. Our data gives us a slice of the bigger research body we are connecting our study to, and enables us to say something about a larger phenomenon or set of meanings that can push collective knowledge forward, or challenge existing knowledge. This is where we make a significant part of our overall contribution to knowledge, so it is really important to see these instruments, or methods, not as technical or arbitrary requirements for some ethics committee. Rather, we need to conceptualise them as tools for putting our methodology into action, informed and guided by both the literature our study is situated within as well as what counts as our theoretical or principled knowledge. Taking the time to do this step well will ensure that your golden thread is more clearly pulled through the earlier sections of your argument, through your data and into your analysis and findings.

 

 

PhD workout: warming up your writing muscles

So, I am writing a book. I have been sort-of-kind-of writing a book for a long time now. We have an on and off relationship, my book and I. But, a proposal is being reviewed, and the hope is that the feedback will be a green light, so I have to get writing. And soon. But, I am a bit out of practice. I wrote a fair bit last year – 3 book chapters (a few drafts each) as well as part of a paper with colleagues. But this is a different beast altogether – as long and as complex as a PhD thesis. I am finding I am out of shape here.

This is not an unfamiliar feeling. I wrote here and here about moving from one year of PhD or post-doc into the next, after having a break and getting a bit flabby around the writing middle, so to speak. I know, therefore, that I have felt unfit before, and have made myself fitter and gotten the writing work done. But, this is – like actual fitness – hard work and requires a level of emotional and psychic energy that can be hard to find sometimes. I have decided, therefore, that I am going to start with gentle warm-ups, rather than jumping straight into the whole thing (Thank you, Roger Federer :-)).

rfed warm up

The first thing I am doing is starting with something manageable, that I could want to do every day – or at least 4-5 times a week. If I want to do it, and it feels manageable, it is very likely I will actually do it (and enjoy the experience). Instead of doing what I too often do, and writing ‘Chapter 1 draft’ on one day of my calendar, I am writing ‘one pomodoro’ every other day. I can do this. It’s 30 minutes of writing. I can then tick this off, and actually add days as a I go, or keep it every other day and work up to 2 pomodoros at least. If I can do it, I won’t fail, and if I don’t fail, I can keep enjoying this writing time and make it productive. Too often I set myself overly lofty goals, in life and writing, and set myself up to fail rather than succeed. Last week I wrote my first blog post in over 4 months, scheduled this post, and also managed about 1000 words on my book. HUGE success I say. All in these little manageable chunks.

The second thing I am going to do is keep it steady. Rather than having a good week, and thinking I can now escalate to high levels of writing productivity, I am going to keep going at this pace for now. Probably, realistically, this will be the pace for the year, with bursts of higher productivity around deadlines and when I have excess time and energy. As one of my writing students said to me last year: ‘Eat the elephant one bite at a time’. Apologies to elephant lovers – I am one too – but this is a good metaphor for taking it steady with life and writing. One task, one pomodoro, one idea at a time. This way, things actually do get done as opposed to being menacing, un-ticked-off tasks on your to-do list.

Finally, for now anyway, I am going to get me some writing buddies. Face-to-face if I can, but virtually if not. I am always thinking I should join a Twitter shut-up-and-write group, or create my own writing group. And then work, and kids, and life, and my writing gets pushed down (with me attached) to the bottom of my list. My writing time is also time for me – it’s personal as well as professional. So, I have to actually value it, and myself. As a working mother I am too often too far down my list. And so is my writing. I am hopeful, that with positive peer encouragement, we can collectively make our writing more present each week in the to-do lists, and make appreciable progress on our projects.

group yoga

Warming up these tired writing muscles to fuller strength will take some time – what do people say?If it’s too easy you’re not doing it right? Maybe so. I don’t think writing should always be hard, but good writing should take effort and time. Maybe you are in this spot too, coming back to work and PhD and research writing, and working out how to begin your “elephant meal”. Hopefully some of these steps to warming up your writing muscles will help you, too.

If you have other ideas, please share in the comments. All the best for 2019!