thesis

Exhausting #acwrimo

Today marks the end of the first week of #acwrimo (Academic Writing Month). How do I feel? To be honest, I feel exhausted. And that’s really surprised me.

I was expecting to feel energised. I know that when I’m productive I have a lot more energy. The more goals I set, the more I achieve, and the better I feel.

I’ve been looking forward to this year’s #acwrimo since…well, since #acwrimo 2012. And the timing is perfect – this #acwrimo I’m writing the literature review chapter of my PhD, which needs a good deal of updating since my first year review.

My daily goals are a bit complicated. I work as a technology trainer two days a week, so my first goal is 90 minutes early every weekday morning (including work days), and 4 to 6 pomodoros throughout the rest of the day on the three non-work weekdays.

So I’ve been getting up at 6:45am every morning, and beavering away from 7-8:30am. Then work or pomodoros.

On the non-work days, 4-6 pomodoros isn’t a huge amount. I’m really not working flat-out. I’ve read my book, played video games (usually Civilization V or Oblivion), gone for coffee with friends.

And I’ve been getting lots done. I’m really pleased with my progress so far. I’m still not sure whether finishing the literature review within the month is a realistic target, but that’s what I’m working towards.

But I’m still exhausted.

And I’m not sure what the answer is. Is this tiredness an inevitable part of the PhD process? Is it time to power through, knowing the end is in sight? Or is this a sign that I’m pushing myself too hard, and that I need a break? Perhaps it’s just my brain and my body reacting to the darkness (after all, winter *is* coming).

What do you think? Do you find the winter months more difficult? Is tiredness an inevitable part of the writing-up portion of the PhD? Or is it a signal to slow down? Let me know in the comments, or on Twitter (I’m @ellenspaeth)

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A no-failure perspective on #acwrimo

It’s November 1st, a day of many happenings. A day of Apple releasing a new iPad, of Starbucks starting their festive ‘red cup‘ drinks for the year, of shaved faces for Movember, and for Academic (and National Novel) Writing Month.

Twitter is atweeting with the hashtag #acwrimo. At this point, almost 550 academic writers have declared their goals on @mystudiouslife‘s accountability spreadsheet, and tweets are flying thick and fast about goals set and tasks completed.

The tweets are also coming through from people who haven’t achieved the tasks they set, who perceive this as failure.

But is it, really? What is #acwrimo if not a time to figure out what works best for you?

I propose an iterative approach to Academic Writing this November. In a previous series of posts, I talked about setting tasks, scheduling them, and reviewing your progress. In the posts, I suggest doing this weekly, but why not do this daily?

Here’s a quick recap:

1) In your initial task setting, make it very clear what your ‘measure for success’ is.

2) Make a backup, for the ‘least amount of work’ you’d need to get done to feel satisfied.

3) When you’re reviewing your tasks, make a record of what goals you achieved, and which you didn’t. And more importantly, try to think about WHY you achieved/didn’t achieve those goals. Is it because of interruptions? Did you underestimate how long something would take? Were you cold? Hungry?

4) Revise your tasks for the next day (or week, depending on how long a period til your next review) in light of those things.

Try it! And let me know how you get on in the comments section.

Experiment recruitment: Why people don’t turn up

If you have run experiments with people as part of your research, you’ll know that recruiting participants can be a tough job. Even trickier is maximising the likelihood that those participants will actually show up to their assigned slot. It’s no fun to wait all day for participants that never arrive.

In the past year, I have run two experiments where I’ve had to recruit student participants. In the first, a pilot study (which is like a smaller, practice, dress-rehearsal style study), lots of people signed up, but quite a few failed to turn up to the session. In the second, I put a number of plans in place to make sure that didn’t happen again. SPOILER: Those plans worked pretty well.

And so, I am presenting you with two posts, which will hopefully prevent any of you from sitting in an experimental room alone and participant-less. Today’s post will look at what stops people from turning up to experimental sessions. The next will give some advice on what you can do about that.

Why don’t people turn up?

When a participant doesn’t arrive for your study, a number of potential reasons swirl through your head. Are they late? Did you give them the wrong time? Has something awful happened? The first time I had two no-shows in a row, I wondered if some sort of portal to another world had opened up outside of the building. This was probably overly dramatic.

In reality, it seems like there are two main reasons for why people fail to come to experimental sessions:

1. They forget

It’s easy to forget something if it isn’t written down in the place where you need to see it. Even if it is written down, the piece of paper may be lost, or the online calendar may not synchronise properly. These things happen. The blame for forgetting doesn’t fall solely on the participant’s side – if you (as the experimenter) don’t contact them to confirm their slot, they may never consider it a firm arrangement.

2. Something else comes up

Reasons for participating in experiments vary: Sometimes it might be purely out of interest, or altruism, but more often than not (especially with a student population), it’s because of the compensation that’s received after the experiment (usually vouchers or cash). But sometimes things will come up that are more important than that money.

Say, you’re going to get £7 for an hour. But then you realise that you’re late with your coursework. You need that hour more than you need £7. So you don’t turn up.

The problem with this is that it doesn’t take into consideration how important that hour is for the experimenter.  The room may only be available for a limited amount of time, and all the participants have to be seen in that time. Fewer participants mean that working with the data might be more difficult, and it may not be possible to use the tests you’d originally planned.

Why don’t people tell you they’re not going to turn up?

As an experimenter, I have no problem if someone wants to cancel their session. If someone gets in touch in advance, and says they will no longer be able to attend, there are zero hard feelings. I don’t even need a reason. Obviously, the more notice is better. That way you can arrange for another participant to come instead. It’s not great receiving a cancellation email or text two minutes before the allotted time. But you know what, it’s so much better than never receiving any correspondence at all. At least, then, you can do something with that experimental slot, rather than sitting, nervously, wondering if someone is going to arrive twenty minutes late.

So why don’t people just tell you they can’t make it?

1. They forget

Look, if they’ve forgotten the experiment was even happening, they’re probably not going to remember to let you know. However, if they remember at the last minute…

2. They are pretending it isn’t happening (out of sight, out of mind)

It’d be pretty embarrassing to forget about an experiment until the last moment. There is the worry that if you contact the experimenter, you’ll receive a message in return, rebuking you for your behaviour. It may seem easier to just pretend that it isn’t happening. Similarly, even if you have plenty of notice to cancel, you may be wrestling with your decision to do something else instead. It may feel like you’re letting someone down, and maybe you should still go to the experiment. But things slide, and you can’t make it. And by then, it’s too embarrassing to get in touch. And thus, an empty experimental slot is born.

Next time…

We’ll look at some methods I used to keep my experimental schedule as full as possible, and to minimise no-shows…

Wrenching writing and difficult decisions

I had a realisation this morning, when I was sipping on coffee and redrafting the methods section of my paper. It’s something I’ve known for years, but it had never made its way into conscious thought until today.

I realised why I actively enjoy writing first drafts, and like each subsequent phase a little bit less.

It is because writing is essentially a continual process of making decisions.

In your first draft, if you can switch off your inner editor, you don’t need to make many decisions. This must be why I love free writing – it’s a way to get my ideas on the screen without any judgement of what comes out. There are no decisions that need to be made.

Each draft that follows embodies a series of decisions: Should this be included? Is this the most concise way to phrase my idea? Do I need a reference to back this up? Is this structure good? Do I need to explain this word? Am I repeating myself too much?

With the early drafts, you can reassure yourself by saying “oh, I’ll come back to this in my next draft. It doesn’t need to be perfect now.” And while I agree that fixating on one thing to the detriment of the rest of a piece of work is foolish, at some point you are going to have to answer these questions. You are going to have to make some final decisions.

Let’s be clear. I am not the voice of a woman who has everything figured out. I am a woman who finds the redrafting process anxiety-provoking. At the moment, I get through it by working hard, moving forward, and telling myself that I’ll come back and reconsider the decisions I’ve made at a later date. I am fully aware that at some point I am going to have to stop and call it “good enough”.

But our whole academic lives, we’ve been taught how to critically evaluate work by some of the leaders in our field. How can we consider our own work “good enough” by those standards? Perhaps there’s another post in that.

I do think that being aware that I am constantly making decisions is helpful. With parts of my thesis, I am getting to the point where I need to say “I have to make a proper decision on this now”. Or perhaps I should take the other approach: Trick my brain into thinking it’ll have the chance for an infinite number of “final” redrafts, and then, out of the blue, tell it that time is up.

What do you think? Do you have difficulty wrestling with writing decisions? Are you finding it easy to visualise your finished thesis, or do you feel like there are too many decisions to make between this point and submission? How do you know when to make the hard decisions, and call it finished? I’d love to hear from you in the comments section.

Ladder 1 Rung 3: Reviewing tasks

In this “ladder” (or series) of blog posts, I’m talking about how I’m trying to make my PhD more like a video game. I have always responded well to structured, achievable tasks, and the lack of these has been really difficult for me during my PhD so far.

This ladder is looking at the short bursts of achievement that video games can give you. As such, the focus is identifying, scheduling, and reviewing tasks. There are 3 “rungs” (or steps) to the ladder, with one blog post for each rung.

In the first rung, I talked about how to identify tasks using to do lists and free writing.

The second rung covered how to schedule those tasks, whether using a pad of paper, a diary or calendar, or a task management app like Producteev.

In this, the third rung, I’ll be discussing how to review your progress with the tasks you set.

Please note…

After the first and second rungs (where you’ll have identified and scheduled your tasks), you need to actually attempt the tasks you’ve set. I would usually set tasks for one week, and set a time at the end of the week to review the past week and identify and schedule tasks for the next week.

So to make full use of this post, it’s a good idea if you’ve already identified, scheduled, and attempted your first set of tasks (say, a week’s worth).

Ready?

  1. Do you have your list of tasks, and the times you scheduled them for? I tend to have these in a file in Scrivener from when I was identifying and scheduling the tasks.
  2. Has it been a week (or however long you scheduled your tasks for) since you scheduled those tasks?
  3. Do you have a way of writing things down? I use Scrivener for this too, because it means that it’s easy for me to have my “identify” and “review” files open next to each other using “split view”, and refer to both

Let’s go!

Use whatever method you’ve chosen (pad of paper, Word, Open Office, Scrivener…) to write words to make three headings

  1. Tasks you completed
  2. Tasks you started but didn’t finish
  3. Tasks you didn’t start

For each of the tasks you’d identified and scheduled for the week, choose which heading fits best. Then, write the task under that heading with a gap between each task (you’ll be writing more in those gaps).

Have you done that for all of your tasks?

Next, under each task write:

  1. A sentence or two about the task (when you did it, whether you encountered any problems, what you found or achieved)
  2. Why you think you managed to/didn’t manage to complete it.

For me, point 2 is the most important part of this rung, and one of the most important parts of the whole ladder.

Look at your reasons for completion or lack thereof. Are there any themes within the headings? Write them down!

To give you an idea, I’m going to share some of the patterns from my first review session.

1) Tasks you completed

Things tended to get done if they were:

  • Manageable
  • Specific
  • Scheduled
  • Urgent

In my first week (and in following weeks), most of my completed tasks were done during a writing session with a friend. That’s one session in the week. If this working pattern sounds familiar to you, I highly recommend this blog post from the Thesis Whisperer.

It’s easy to view the rest of the week as a failure, or write-off, but instead I’m trying to try and focus on the achievement of that one very productive session, and to figure out how to replicate it

2) Tasks you started, but didn’t finish

This mainly happened with tasks where the criteria for completion were unclear.  I started using the “measure for success” heading when identifying tasks as a way of combatting this problem.

3) Tasks you didn’t start

With me, these were mostly because I was ill or tired, or other things came up. “Tasks I didn’t start” seemed to be due to unforeseen circumstances. It’s also possible to have a high amount of tasks in this list if you overestimated the amount of time you’d have, or underestimated the time it would take you to do the tasks.

Once you’ve done that, think about ways you might replicate the conditions that helped you to complete these tasks. If you’re interested in the idea of improving a situation by embracing the positive rather than banishing the negative, appreciative inquiry is a research approach that draws on this. As my research focuses on improving healthcare, I’m also including this abstract for a paper which uses appreciative inquiry in a healthcare context.

In my first review session, mine were

  1. Set immovable work sessions (this was because my writing-with-friend session was so successful)
  2. Acknowledge when it’s a busy week, and set fewer tasks accordingly
  3. Set specific tasks, and incorporate a “measure for success”
  4. Have contingency plans in place (this and the previous bulletpoint were addressed by adding the “measure for success” and “backup plan” headings in the identification phase)

If you review your tasks each week, and schedule the next batch of tasks at the same time, you’ll start to get a good idea of:

  1. What time of day is best for you
  2. What working environment is best for you
  3. How much time you can devote to these tasks
  4. How long it takes you to get things done
  5. What stops you from getting things done

And that’s the end of this ladder. Well done, you reached the top!

I’d really like to write more posts on improving productivity by taking hints from video games. If you have any requests or ideas, please let me know in the comments section. You can also use the comments section to say nice things, let me know if you’ve found these posts helpful, or if you have any suggestions.