Apps, Research, Technology

Apps in Research

On Monday I gave a presentation at the BASES Heads of Department Forum at Staffordshire University on using apps in research. You can download the presentation here. My take-home messages from the presentation were that (1) we need to do more studies on the validation of apps, particularly if they are going to be used for exercise prescription and in clinical use; (2) there are very exciting developments for using apps to recruit participants and collect data for research projects, such as Apple’s ResearchKit and IBM’s Watson Health Cloud, and (3) it’s not easy or cheap to develop apps for use in research projects. I firmly believe that there is considerable scope for both academic and community impact through the use of smartphone apps and other wearable computers. For example, it is estimated that by next year more than 2 billion people around the world will own a smartphone. Although I will continue to conduct research in sport, my growing research focus over the coming years will be the use of technology in physical activity and health. If you’re interested in this type of research then do get in touch.

Academia, Research

On this, I’m with Harry…

We seem to be obsessed. Obsessed with securing research grants. Oh, and that’s external research grants. Internal doesn’t cut it. Universities are even setting research grant targets. Don’t achieve the target, don’t get promoted…or worse. Conversely, achieve the target, you get promoted. But here’s the thing. I’m not against academics getting research grants. If you can get them, that’s great! What I am against is the disproportionate rewards that come your way when you get a grant, and the jaundiced criteria now being used for promotion. Why has it become like this? Two reasons.

First, we’re a bit like lemmings – always following the crowd1. Someone, probably in a red-brick university, decided that external research grants would now be the new ‘status symbol’ of being ‘the best’. What you published didn’t matter any more. Old hat. Research grants are harder to get2, so now that would be the new gold standard and measure of academic performance. I have a problem with this.

To me, research grants only have one purpose – to enable research to be conducted. In and of itself a grant is nothing, only potential. What ultimately matters is what we discover, and what we publish. Nobel prizes in the sciences are awarded based on published research, not research grants. Although we might think that those who secure research funding are the best researchers anyway and will end up changing the world, about a third of recent Nobel prizes were awarded based on research reporting no funding sources. Yes, world-class research can be conducted without external funding.

Given our obsession with external research grants, the end result is that we’re rewarding academics before they’ve actually done anything lasting. Nobody with heart disease cares that you were awarded a £2 million research grant from the Heart Foundation. They only care about how you’re going to cure their disease or improve the quality of their life. That can only be achieved through doing the research, publishing the findings, and integrating those findings into practice. Do that, and you should get rewarded, but not before. Yes, I appreciate that large-scale research projects cost a lot of money, but I’m not arguing against the grant itself. I’m arguing against the status placed on the winning of research grants and the rewards received based on that, before the researcher has discovered anything new. I’m also arguing against our performance as academics being judged solely on external grant income.

We’re also in an age of austerity. Money is hard to come by. Why then do we still value the ‘bigger is better’ approach? Why is expensive research so highly valued? I think we need a ‘less is more’ approach to research funding. Maybe a ‘research economy’ metric could be calculated simply as:

Research Impact ÷ Research Cost = Research Economy

Such a metric is certainly possible now that the current REF scores have been released. Each department was judged on their ‘impact’ and the cost of doing that research should be able to be calculated. We have to remember that most research funding comes from tax payers. If you can do great research with fewer pounds/dollars then that is a good use of public funds. Moreover, those who don’t need large sums of money to conduct their research are at a real disadvantage within the ‘bigger is better’ system3.

Second, research income is easy to measure. It’s a number and the bigger the better. For all our fancy degrees, titles, and complicated research, we seem to have settled on using a marker of ‘success’ just because it’s simple. Judging the quality of the research on the other hand, is more difficult. Yet, academics on the whole are fairly bright people. They have Ph.D.s and titles like Professor. Surely we can propose a better system for judging research quality? Don’t get me wrong, I’m all for simple, but simple only works if other more sophisticated methods are not better, and I’m convinced there are better, more holistic, ways to judge research performance. Others agree. Yes, there are those who argue that metrics are not very useful4. Like any number they can be misinterpreted or ‘gamed’, so I think both objective and subjective criteria (reading the paper!) should be used to provide a more holistic view of an academic’s research performance and their impact on the people who consume their research.

Placing external research income at the top of the tree also devalues many of the other roles that academics play – particularly teaching. Being judged solely on how much external grant income we secure sends out the message that research is the most important aspect of an academic’s life. Yes, research is what separates a university from a further education college and is an important part of what we do. It’s important that we do it. However, on this I’m with Harry Burns:

I’m not saying it doesn’t mean anything. I’m saying why does it have to mean everything?

For most universities we rely on the income from student fees. Without students we don’t have a job. Yet very few institutions (Maybe Oxford/Cambridge) could survive just on their research income. This means we have an obligation to use those fees to teach well and support students with the same standards of quality that we do for research. Yet, teaching has become a 2nd class citizen in most universities. Academics are driven by what will get them promotion5, and being a good teacher will not get you a promotion. Well, it might, but you have to be a world-class teacher and reach a standard far greater than a research-active academic would have to. Our obsession with research funding also seems to be having an effect on ‘academic citizenship’. You know, all those other things that keep an institution going, like committee work, external examining, peer review. Now that everyone is so busy writing grant applications, who will do those jobs? Someone has to.

So, I think it’s time we made a stand. Rather than being a lemming and following the crowd, let’s think for ourselves. Let’s reward academics on a wider range of measures (research, teaching, outreach, pastoral, admin, contribution to university committees, leadership etc). Let’s also reward academics when they’ve actually achieved something with their research, like publishing a groundbreaking paper, having their research cited in a policy document, when their research changes practice, or yes, even if they win a Nobel Prize. That’s right, judge us on output, not input.

I’ll leave the final word to a Nobel laureate:

I firmly believe that the only reason I was able to do the work in question is because I was being paid by the University of Sussex not explicitly to do research but to teach, so that I had no need of a grant and its accompanying pressures. It is my great regret that neither the US system (ever) nor, alas, the British system (now) operates on this principle.


  1. By ‘crowd’ we usually mean those from Oxford or Cambridge! 
  2. For those of us whose research is on sport performance, it’s almost impossible. 
  3. Most sport science research would fall into this category, needing relatively small sums of money, certainly when compared with other fields of study. 
  4. I respect David Colquhoun and his views on many things, but on alt-metrics I’m a little more optimistic about their usefulness. 
  5. Although institutions do include criteria other than research, at best they pay lip service to those non-research criteria. 
Programming, Technology


At Apple’s 2014 World Wide Developers Conference (WWDC) a new programming language called Swift was introduced. Big deal you say? Well, for most Apple developers (both full-time and part-time – (like me)) it was a shock. There had been no rumours, which for an Apple release was unusual. We thought Objective-C would live forever! But the king was dead – long live the king. For me, Objective-C had played a large part in helping me to learn to programme. It’s quite ‘English-like’ in it’s syntax, which means you can generally tell what a piece of code is doing. For example:

NSString *myText = @"Hello World";

It’s fairly clear what this line of code is doing – you are assigning the words ‘Hello World’ to a variable called ‘myText’ (forget about the NSString[1] thing for now). Easy hey? Now here’s how to do it in Swift:

var myText = "Hello World"

Even easier! There’s no need to reference the class of object (NSString) because Swift knows that ‘Hello World’ is a string of characters (hence the class name). This is called type inference, and it’s a big thing. You can do this with other data types as well like numbers. Assigning a number to a variable in Objective-C and then Swift involves:

int myNumber = 5;   //Objective-C
var myNumber = 5   //Swift

Again, Swift knows that 5 is a whole number and it’s therefore an integer (int), so there’s no need for you as the programmer to inform the computer about this. To assign a floating point number involves:

float myNumber = 5.2;   //Objective-C
var myNumber = 5.2   //Swift

Swift also makes it really easy to combine strings together, like:

var string1 = "Jim"   
var string2 = " You're great!"   
var combinedString = string1 + string2

It’s a little more complicated in Objective-C:

NSString *string1 = @"Jim";
NSString *string2 = @" You're great!";
NSString *combinedString = [string1 stringByAppendingString:string2];

Incorporating data into text is easy in Swift too:

let num1 = 6
let num2 = 4

if num1 > num2 {
    println("\(num1) is greater than \(num2)")
} else {
    println("\(num1) is not greater than \(num2)")

The equivalent in Objective-C:

int num1 = 6;
int num2 = 4;
if (num1 > num2) {
     NSLog(@"%i is greater than %i", num1, num2);
} else {
     NSLog(@"%i is not greater than %i", num1, num2);

Not a lot of difference there, but I think the Swift version is a little easier to read.

Now, arrays. An array is a collection of objects. For example, a collection of numbers. In Objective-C it’s this:

NSMutableArray *myArray = [[NSMutableArray alloc] init];
[myArray addObject:[NSNumber numberWithInt: 2]];
[myArray addObject:[NSNumber numberWithInt: 4]];
[myArray addObject:[NSNumber numberWithInt: 6]];
[myArray addObject:[NSNumber numberWithInt: 8]];

In Swift it’s just this:

var myArray = [2, 4, 6, 8]

Yep, that’s all there is to it! One of the problems with learning to programme is that people think it’s too hard. They say “I’m not smart enough to do this”. Well, if I can learn it then anyone can! That being said, there are quite a few ‘gotchas’ with Objective-C, and aspects of the language that are difficult to grasp. I think Swift is easier to comprehend than Objective-C and therefore easier to learn, so I’m confident that Swift will enable more people[2] to pick up programming for iOS and the Mac, and that’s a good thing.


  1. This is what’s called a ‘class’. A class is essentially a template for making things. In this case it’s a template for making ‘string’ objects, which in everyday language are words. I’m guessing the word string comes from a ‘string of characters’, which is what a word is. When you want to make a new string, you ask the class to give you one. You can then do things with that string, like assign it to a label that appears on screen. The ‘NS’ is a reference to NeXTSTEP, which was an operating system created by NeXT Computer, a company that Steve Jobs started after he was kicked out of Apple in the mid 1980’s. NeXT Computer, and the NeXTSTEP operating system were bought by Apple in 1997 when Jobs returned to Apple and were eventually turned into OSX and iOS.  ↩
  2. On that note, I’d encourage any university student to have a crack at learning a language. A number of my PhD students have started doing so and it has allowed them to analyse data in new ways that they couldn’t do with off-the-shelf apps.  ↩
Academia, Technology

Hello world

Welcome to my new blog. Here I’ll be writing about academia, sport science, technology, programming, and anything else really that I’m interested in. I’ve just taken delivery of a new Macbook Pro, so thought it would be an ideal opportunity to start writing. I bought a nice little app from the Mac AppStore called Byword, which uses a plain-text based language called Markdown. Markdown makes it easy to focus on the content rather than formatting. The blog is being hosted on WordPress, and together with the Byword app on Mac and iPhone, it means I can write wherever, whenever I like. There are clear advantages to writing within a minimal environment rather than bloated apps like Word, and already I’m enjoying the experience. Check it out for yourself. I’m also keen to explore how Markdown and Byword could be used to write an academic paper, and based on others experience, citations and footnotes might need some experimentation.

Along with my other social media endeavors, I’m very keen to write more long-form pieces about my experiences within academia. There’s a lot to get off my chest. Hearing about my journey might also be useful to those who follow.