Is technology making PhD students lazy?

There was a time, not so very long ago, when searching for an article meant a trip to the library, finding a physical copy of the journal and taking it to the photocopier.

There was also a time, not so very long ago, when theses were typed on a typewriter. There were no word processors, there was no referencing software. Everything was done by hand.

Technology has made life much easier for academics; you can find, download and print an article in seconds, plus there are countless pieces of software and online resources now available. But is this same technology making some PhD students lazy?

Please note: I am not saying you should use a typewriter and search for literature by hand. These are examples of technology being a good thing! I’ve had some comments reacting as if I am arguing against the use of any technology. This would be ridiculous!

Lazy questions

By far, the most common question I get asked is,  “I’m studying X, please provide me with a thesis topic“. I must have been asked this 100 times in the last few months, and I’ve seen the same question in a number of online forums.

This is a lazy question, not because a student should think of it themselves, but because they haven’t taken the time to think about whether I’ll be able to answer. How on earth does anyone expect me to  instantly come up with a viable topic on demand? Yet the question keeps coming…

OK, so most students don’t ask this kind of question, but there is a sizable minority expecting instant answers. To those students, sorry, but it doesn’t work that way… The availability of online help does not absolve you of the responsibility of thinking.

Lazy use of software

Some analysis would be impossible without the use of software, but there is a risk that you end up not understanding your own analysis.

Take statistical software for example. It can save you a huge amount of time, but it is possible to use it without understanding what it is doing with your data nor the results it presents.

If it spits out a bunch of numbers, what do they mean? What is a p-value? What’s the difference between standard deviation and standard error? You have to take the time to understand these terms before you use them in a report.

Don’t pass responsibility onto the software!

Lazy searching

While search engines and other online resources give you instant access to information, sometimes what you need isn’t at the top of the results list. Sometimes it’s hidden away on page 27 of an article published in volume 4 of The International Journal of Obscure Research. Sometimes you need the patience and persistence to dig a little deeper and search a little longer.

Patience and persistence are crucial attributes for successful researchers. While search engines are great as an initial tool, what do you do when they don’t give you what you need? Do you have the patience to try searching in other ways?

Problem solving

Research is all about problem solving. It rarely, if ever, goes exactly according to plan, and you will have to adapt and solve problems as they arise.

Often, the first solution you try won’t work, so you’ll have to try something else… and something else…. and something else, but eventually you get it right.

It’s not that I’m so smart, it’s just that I stay with problems longer

– Albert Einstein

Success is often determined by the amount of time you are willing to spend with a problem, plus your willingness just to try things out and see whether they work, or in other words your willingness to make mistakes and keep going. Technology, whether search engines, discussion forums or software, is no substitute.


The blank page is your friend

There is a lot of advice for writers, and while some of it varies in approach there are also some ideas which seem to be universally accepted. One of these ideas is the fear of the blank page;  of that empty white space staring accusingly at you and demanding to know why you haven’t written anything.

Many will argue that you should still get words down quickly without thinking too much as a way of overcoming the fear. This might be a useful tactic in some circumstances, but to me it seems like a way of avoiding the issue.

Personally, I don’t find a blank page particularly frightening. Sometimes I might find it difficult to get started, but the blank page isn’t the problem. The problem is finding a starting point by deciding what to say first. If you solve that, the blank page problem disappears.

That doesn’t mean it’s easy — it takes a lot of patience and persistence — but by focusing on the more fundamental problem, your attention is directed towards creating something of value, rather than avoiding some abstract, poorly defined fear.

As a writer, you will face blank pages every day. So you can either build your writing strategy around an irrational fear of an essential medium for your work, or you can try to get comfortable with it. The latter, surely, is a more confident approach.

It’s time we writers got over this collective fear. The blank page is your friend. The blank page will hold your words for you when they are ready. It will be forever patient, and when one is full another will be waiting to serve you.


“Advice is a form of nostalgia”

Advice is a form of nostalgia. Dispensing it is a way of fishing the past from the disposal, wiping it off, painting over the ugly parts and recycling it for more than it’s worth.

– Mary Schmich, “Wear Sunscreen”

This is so true, especially in the field of advice for students.

There is a huge amount of advice out there, and those of us giving it all believe our tips are useful.

But the truth is, none of us have discovered “the secret to end procrastination” and there is no perfect system for time management, no perfect system for working with literature, and no single approach to writing or research.

There is a danger, in our field, that we start to believe our own hype and that we make claims which aren’t really substantiated. The best we can hope for is that it works for some people, and doesn’t do any harm to others.

How can advice do harm? When we over-sell our advice, there is a possibility that those for whom it doesn’t work start to blame themselves. If that’s the case, and that person is low in confidence already, they aren’t likely to tell those of us giving advice that it didn’t work for them.

This introduces a kind of confirmation bias… we only hear from the people who like our work, and that can lead to a distorted view of how good our advice really is.

The common phrase (and I used to use it myself) is that “if I can do it, you can too”. But maybe the way I did it won’t work for you. Maybe I worked under different circumstances. Maybe I just think differently.

I can’t promise results. I don’t have all the answers, and I haven’t discovered a secret. I have just spent a really long time trying to figure out ways of working to make PhD life easier. The blog posts on this site and in my book are my best efforts so far, and I hope you find them useful.

UPDATE: This comic from XKCD kind of sums up what I’m talking about…

A beginner’s guide to statistics for PhD research

Statistics can be invaluable for adding a level of rigour to your analysis, but they can be extremely technical and difficult for non-specialists.

This is not by any means a comprehensive guide, but I will try to give some basic working principles to help reduce the pain and avoid the most common mistakes.

Plot your data

Before doing statistical analysis, wherever possible create a visual representation of your data.

This will give you a much better intuitive understanding of what is going on.

For example, if you have survey data using a Likert scale, where answers to questions are given as;

  1. Strongly disagree
  2. Disagree
  3. Neither agree nor disagree
  4. Agree
  5. Strongly agree

You may want to see how the answers to a specific question are distributed across all respondents. You can do this by plotting a histogram showing the number of responses at each point in the scale.

Here are 3 examples of possible distributions:

likert histogram 1 likert histogram 2 likert histogram 3

 Without doing any statistics, you can instantly see how the data is distributed, and you can use this as a basis for your analysis

What does the mean mean?

If you take the means of each of the three distributions above, you will get values of 3.7, 3 and 2.8.

But what do these values mean? In the top histogram, 3.7 clearly correlates to the peak at 4. In the second, the distibution is flat, so the mean just represents the middle of the range, and in the third, the mean is the least selected option.

It is up to you to then interpret what the mean means, but you can only do that when you can see the distribution of the data.

Standard deviation

The standard deviation is a measure of the spread of data around the mean. It is widely used, but you need to be careful.

If you use the standard deviation without plotting your data, then you can end up with a meaningless number.

Standard deviation is best used when you have something approximating a normal distribution of data (the classic “bell curve” below)


When you say the standard deviation = x, this indicates that about 68% of the data lies within ± x of the mean.

But what if you have a graph with 2 peaks? Then the standard deviation becomes meaningless, even though a statistical program will still give you an answer.


Don’t include numbers you don’t understand

When you use statistical analysis software, it will spit out countless different results, some will be useful, some not.

Do not include in any report or table of results numbers you don’t understand. Imagine an examiner asking, “what do these numbers mean?” and if you can’t answer, either find out or don’t include them.

How many decimal places?

Another potential hazard is that stats software will often give you numbers to many decimal places.

For example, let’s say you measure the height of every adult human being on earth and look for the mean. With several billion data points, your calculation of the mean might look something like 1.68234597864422 m (I just made this number up as an example). If you copy and paste this number, you are effectively claiming that you can measure the height of a human being to an accuracy of  0.00000000000002 m, which is much smaller than the radius of an atom.

Much better to give the value as 1.68 or 1.682, since this reflects the accuracy with which you can make a single measurement.

Quoting errors

The same is true when giving an estimate of the error on a measurement. Giving an error of ± 2.336598774654654 is ridiculous! You can’t be that precise in an error estimate! Stick to one (or two at the most) significant figures.

Do analysis at a small scale early in your research

If you have 1 month left to submit your thesis, and you are doing analysis for the first time, it’s going to be difficult.

So do some analysis early, on a small scale, so you have some experience before you do the full analysis. You will be able to take your time, while the pressure is still low. Most mistakes happen when doing things in a rush at the last minute, especially if you have never done that type of analysis before.

If you know what methodology you are going to use, do a small trial run and analyse the data you get. Not only will this help you refine your methodology, but it will make the final analysis much, much easier.

Any questions?

I am not an expert in statistics, and cannot answer questions on specific analytical techniques or software, but am happy to answer questions on these basics.

If any statisticians want to contribute, you are more than welcome!


Here’s a quick writing tip used by the professionals…

When you are writing and there’s something you need to come back and insert later, like a reference, figure number, table etc, you probably leave a note for yourself as a reminder.

Do you have a consistent system for these “notes to self”? Or do you do it a different way every time?

When you have a tight deadline, it is easy to miss (insert figure here) or (find reference on X) when you scan through your document in a hurry.

So it’s better to have a system where you can’t possibly miss them!


TK is wisely used in journalism and printing as a placeholder for missing material, standing for “to come“.

The reason TK is used rather than TC is that it is an unusal letter combination (try to think of any words in English containing “tk”… there are a few, but not many), so if you do a CTRL-F search in your document for “tk” you will find every instance easily.

You could use XXX or any other letter combination that doesn’t appear in the rest of the text. If you are doing a thesis on pocketknives, for example, XXX is probably a better one to use.

Whatever you use, be consistent, and you will avoid submitting a thesis with an embarrasing (insert example here).

Is it OK to take time off while writing your thesis?

I just received this question in response to the short guide to writing a thesis fast;

It is common for students to think they have to work all the time to make progress in writing. Then, there is guilt if you do not work. But working all the time makes life miserable.

Did you schedule days off and time off during the day when you were writing your thesis?

Is this feeling common?

Yes. It is common to have a constant feeling that you aren’t doing enough and to feel guilty if you don’t work.

There are a few possible situations where this applies:

  1. When you intend to work, but can’t find the motivation and end up procrastinating
  2. Where you work, but the progress is very slow or it doesn’t feel like enough
  3. When you make a conscious decision to take time off and get away from the computer

If you feel miserable when you work, and guilty when you don’t then clearly writing will be a nightmare. So what is the solution?

Set the bar for success

Ask yourself; how much progress do you need to make in order to be happy?

In an ideal world, you want to finish each day and look back with satisfaction on what you have done. When I wrote my thesis, I set this at 500 words minimum per day, because I knew this was achievable even on a difficult day.

On a good day, I could smash the target and write maybe 2000 words. On other days I might have to fight and struggle my way to 500. Either way, I had a system which allowed me to feel good about my progress.

The target should not be your maximum

Your writing pace will naturally vary from one day to the next. Some days you might be able to write 2000 words, but this should not be your target  because most days you will fail.

It is better to set the bar low, then smash that target, rather than just about reaching it on your best days.

Time off during the day

While writing, I would take breaks just to give myself time to think. This thinking time is essential, but difficult to get if you feel constant pressure to WORK MORE WORK HARDER KEEP WORKING NEVER STOP NOT DOING ENOUGH…

You need some downtime, just to relax and think.

Being English, I am addicted to tea, so putting the kettle on got me away from the computer on a regular basis.

Go offline

Crucially, when I took breaks I was not checking email (I had no internet connection at all during the months I was writing), so this meant my brain could think over what I wanted to say before I went back to the desk.

Email and Facebook do not count as a break, and are by far the biggest productivity killers.

Days off

Because I had a set target each day, which I exceeded, when I did take days off I didn’t feel guilty about it.

I felt like the thesis was under control, and so I wasn’t worried about taking a day or two to myself.

Finishing the day with something in reserve

I always tried to finish working at a point where I felt I could do more. This made it much easier to maintain my productivity from one day to the next, which in turn meant I was more likely to beat the target every day, which helped me feel in control, which made it easier to relax… (see “the self-sustaining cycle of thesis productivity”)


“I hate my PhD…”

When I was first offered a place on a PhD program, it felt great.

Just being accepted to study for a PhD felt like a success, like some kind of validation that I was good enough to do it. What I didn’t realise was that it is much, much easier to get onto a PhD program than to complete one.

It was tough, and there were times when I felt like the whole thing was pointless… that I would fail and there was nothing I could do about it. There were times when I hated my PhD, and there were times when I just wanted to quit.

I hate my PhD

This is a common feeling, but what makes it worse is that it is easy to end up trapped by your PhD.

If you have a job you hate, then you look for another one. There is no stigma attached to quitting a job, and it is the obvious thing to do if you are truly unhappy.

But with a PhD, even if you hate every day and wake up dreading going to the lab or library, it is very hard to leave.

Why it is so difficult to leave a PhD

Unlike a job, a PhD has a defined aim which you either achieve or you don’t; to graduate. So leaving can feel like failure, because you haven’t achieved what you set out to do.

How, then, do you explain to a potential employer that 5 year gap on your CV? How do you explain to your family and friends? How will you feel years from now when you look back on that incomplete goal?

As long as you stay, there is still maybe some hope… perhaps if you work harder or longer hours then things will change…. But they never do, because if you are unhappy and lacking confidence, it is impossible to fully apply yourself and work to the best of your ability.

So people stay, month after month, year after year; unable to make progress, too scared to leave.

What can you do?

You have 3 options

  1. Just carry on and hope for the best
  2. Quit
  3. Make fundamnetal changes to the way you work

Of these, the first option is by far the worst. If you are unhappy, stressed or depressed, then it is a signal that something needs to change. It is easier to stay in the relative safety of the familiar (no matter how unpleasant) than to walk away and into the unknown, but this is just a way of avoiding responsibility for your own happiness and wellbeing.

If you quit, you are at least making your own decision and taking back control of your own life. Although scary, it can open up an entire world of possibilities… By letting go of the PhD, you can create the space in your life to do whatever you want to. You could;

  • Fly to Iceland and look at volcanoes
  • Learn to dance
  • Write a novel
  • Run an ultramarathon
  • Start a business and change the world

Life is what you make of it. The only limitations are the ones you place on yourself, and a PhD is not the only challenge out there.

Making changes to the way you work

It is possible to turn things around, but you need to not only change the way you work, but also the way you think about the work.

Being more organised and working harder are not solutions in themselves. Any burst of willpower or new time-management technique will work for a few days, but lasting change can only come from a fundamental change in your mindset.

For me, the change happened when I relaxed, and stopped worrying about the end result, and just focused on doing things carefully. I told myself, “I don’t care if this works or not, but I’m going to do it to the best of my ability anyway”.

I couldn’t control the end result, because I was doing experiments which only worked maybe 5% of the time. But I could control the care and attention I gave to whatever task I took on.

Pass or fail, trust in your ability to cope

There was a real possibility I would fail my PhD, but I told myself that if I did fail, I would be OK. It would not be the worst thing that would happen in my life, and although it wouldn’t be nice, I would cope.

I would find a job somehow. I didn’t know how, and I had no plan, but I trusted in my own ability to cope with whatever happened.

True confidence is not having certainty over exactly how things will work out, because that is impossible. True confidence, whether you quit your PhD or continue, comes from not knowing how things will work out, but doing it anyway.


“The best of the best”

On the very first day of my PhD, I sat with all the other new students through a whole day of induction meetings.

Various people came to speak to us over the course of several hours; the safety officer, someone from the finance department, somebody else to talk about the monthly reports we were supposed to fill in…

But there was one that stuck in my mind. It was the “motivational speech” where we were told that we had been accepted onto a PhD program because, by definition, we were,

… the best of the best…

I’m sure it was meant to motivate us and give us confidence, but for me it had the exact opposite effect.

I was definitely not the best of the best. I hadn’t done particularly well as an undergraduate, and I felt like I had bluffed my way onto a PhD program. Maybe these other people were the best of the best, but I was the impostor and I spent the next couple of years with a small but ever-present worry that I would be found out.

Worrying about what you don’t know

I was always worried about what I didn’t know. My maths wasn’t that great by physicists standards, and there was a lot of fairly basic stuff that I had either forgotten or simply never learned in the first place.

I would occasionally try to fill those gaps… I would get a book and leave it on my desk in the hope that the knowledge would enter my head by virtue of proximity, but of course it never did.

Background stress…

The fear of being found out added a level of background stress. It wasn’t particularly bad… my life was perfectly comfortable and I woudn’t say that I was suffering, but there was certainly a slow erosion of confidence.

But this background stress stopped me working to the best of my ability. When I did an experiment, I never really believed that it would work, and so subconsciously I undermined my own effort by not doing thiogs quite as carefully as I could.

Of course, this menat that things were less likely to work, which reinforced my negative beliefs, and the whole thing became a self-sustaining cycle of futility.

The realisation…

It was only in my third year of the PhD, after nearly quitting, that I realised something crucial…

Everybody has different skills and expertise. It did not matter that I had weaknesses and gaps in my knowledge, because there were other things that I was really quite good at. Other people weren’t better or worse, they just knew different things.

I had forgotten a lot of basic physics and maths becasue I didn’t need it for my project and wasn’t using it. But I had learned a huge amount about the experimental technique I was using, and knew the equipment as well as anybody.

I had become a specialist. An expert in one or two things, and so I decided to focus on that and not worry about how much I didn’t know.

I didn’t have time anyway to fill in all the gaps, so there was no point worrying about it.

The thesis

When I came to write my thesis, I decided to focus only on material I knew and understood well. By focusing on my strongest areas, I could write faster and with more confidence.

There was always a risk that an examiner would ask me a question I didn’t know the answer to, but I just took the view that this is my work, I am proud of it and I am happy to defend it, and if the examiner doesn’t like it, I don’t care.

With this attitude, I was able to relax and actually enjoy the writing process.

Get really good at something

The best of the best is meaningless. Everyone has different skills and strengths and weaknesses, and nobody knows or is good at everything.

So don’t worry about comparing yourself to others, and don’t worry about the gaps in your knowledge, because you can never fill all of them.

But what you can do is get really good at a small number of things, know where your strengths lie, and focus on them instead.

PhD research proposals: a good idea is not enough

In many PhD projects, you have to write your own research proposal. This is in some ways similar to the process that professional academics go through when applying for funding to do research.

It is not enough to have a good idea and research plan. You need to be be able to convince other academics that the project is interesting or valuable or useful.

A PhD research proposal is a pitch for investment of resources… whether that investment is money, equipment or time. Before anyone will invest in your project, you need to do two things…

1. get their interest

Of course, different people find different things interesting, valuable or useful. Your research may be very far removed from any obvious practical application, but it can still be of academic interest to others working in the field.

So you need to know who you are selling it to, and why they should be interested. It is this understanding, as much as your technical knowledge, that will help you sell your research idea.

This means becoming familiar with the literature and knowing how your work fits into the broader context, but it also means getting to know people in the field, what motivates them and what they find interesting.

2. reassure them

Any investment carries some risk. If someone invests money in your project, or agrees to invest time supervising it then they carry some of the risk if your project is a disaster.

So you need to reassure them that the research idea is viable, that you have done adequate background research, and that you have thought through clearly how you will carry out the project.

If you can convince other academics that your project is interesting, then reassure them that you can deliver, then you will have a high chance of success.