What miming a steering wheel tells us about what we learn

Pro-tip - keep your eyes open while doing this

One of my favourite podcasts is '99% Invisible' by Roman Mars. It's about design, and about the consequences for good and ill design has on our day to day life. You should listen to it, because it is awesome. 

An older episode fell into my ball park a little bit, and I thought it was a nice idea worth repeating. It's about the steering wheel, and what we learn when we learn to use them. The moral of the story is this: when we learn, we don't acquire internal models of the features of a task which we can then access later on. Instead, we learn how to interact with a given task dynamic and how to use the information made available by that task dynamic.

Help with a lay summary of my throwing research

I am applying for a research fellowship and part of the application is a 2500 character lay summary; see below. I would love all and any feedback from you about how well it scans for you.

I have also put a public copy of this and the scientific abstract on Google Drive that can take comments, if you are so inclined:
Lay summary
Scientific abstract

The remit of the section is
Provide a lay summary of your proposed project. This should be understandable by an A-level science student. Explain why you have chosen to work in this subject area and what it is about your proposed research that you find particularly exciting, interesting or important. Also explain the potential impact or wider benefits to society of your research. 

EDIT AFTER FEEDBACK:
Imagine you are standing on the rocky shore of a lake with a friend, who challenges you to a competition: who will be first to hit that floating branch with a rock? You and your friend hunt for suitable rocks to throw, hefting them in your hand until you find some that feel just right. You then take turns throwing those rocks to try and hit the branch, getting closer on each throw until finally one of you scores a direct hit.

The simplicity of this commonplace game is deceptive. Throwing is actually so difficult that humans are the only species who have specialised in it. We have hands that can grasp objects; bodies that help make the precisely timed throwing action possible; and the ability to perceive which objects are most suitable for throwing. Evolutionary biologists believe that throwing provided our relatively small and weak ancestors with the ability to hunt large animals such as mammoths. But throwing still plays a large role in modern life, even if it is more likely to show up these days in the sports arena than on the plains of North America.

Thanks to sports science, we know a lot about what throwing looks like when it happens. What we don’t know is how a skilled thrower produces that throw in the first place. What makes an object ideal for throwing, and how do we perceive this when we heft that object? How do we perceive where our target is? And, most importantly, how do we use this information to select a throw that will move this object in just the right way so as to hit that target? This project is all about answering those questions. We will measure expert and novice throwers aiming to hit distant targets and track their movements with high speed cameras. We will then analyse this data using cutting edge techniques to identify how people produce the throws they do.

I find throwing fascinating because there are so many unanswered questions from many different disciplines. Psychologists want to know how we perceive the environment and produce the throw; neuroscientists want to know how our brain works to support this behaviour; evolutionary biologists want to know how all these skills came together in our species and how this might have supported the evolution of language. My colleagues and I have the tools we need to actually answer these questions, and we believe that the answers will be of interest to many people, including scientists but also coaches and athletes interested in improving their techniques and accelerating their learning.

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ORIGINAL
Imagine you are standing on the rocky shore of a lake with a friend, who challenges you to a competition: who will be first to hit that floating branch with a rock? You and your friend hunt for suitable rocks to throw, hefting them in your hand until you find some that feel just right. Then you take turns throwing those rocks to try and hit the branch, getting closer on each throw until finally one of you scores a direct hit.

This game might seem an odd thing to want to study scientifically – it all seems so straight forward. But this simplicity is deceptive. Throwing to hit a target like this is actually a surprisingly difficult action that requires you to produce a precisely timed movement that suits the task at hand (how far is the target? How big?). Throwing is in fact so difficult that humans are the only species who have specialised in it. We have hands that can grasp objects, bodies that help make the precisely timed throw possible, and the ability to perceive which objects are most suitable for throwing. Evolutionary biologists believe that throwing provided our relatively small and weak ancestors with the ability to hunt large animals such as mammoths. But even today, throwing still plays a large role in modern life, even if it’s more likely to show up in the sports arena than on the plains of North America.

Thanks to research in sports, we know a lot about what throwing looks like when it happens. What we don’t know is how a skilled thrower produces that throw in the first place. What makes an object ideal for throwing, and how do we perceive this when we heft that object? How do we perceive where our target is? And, most importantly, how do we use this information to select a throw that will move this object in just the right way so as to hit that target? This project is all about answering those questions, using modern motion-capture and data analysis techniques.

I find throwing fascinating because there are so many unanswered questions from so many different disciplines (e.g. psychology, neuroscience, evolutionary biology). But even better, my colleagues and I have the tools we need to actually answer these questions! We believe that the answers will be of interest to many people, including scientists but also coaches and athletes interested in improving their techniques and accelerating their learning. It’s rare to find a research question with such wide appeal, and this makes it a very exciting topic for me to work on as a scientist.
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What are the units that perception measures the world in? Firestone vs Proffitt

Perception is an act of measurement, and, like all acts of measurement, it needs a scale in order to be useful. Think about placing something on your kitchen scales; all that actually happens is that the object presses on the scale and the scale registers that something has changed by some amount in response (the location of a tray, for example). In order to know what that change means, the change is presented to us on a calibrated scale (by moving a needle around to point at some number, for example). The needle always moves the same amount for a given weight but the resulting number can vary (you might have an imperial rather than metric kitchen scale, for example). Without the scale, you can say that one thing is heavier than another by noting that it moves the scale more (this is an ordinal evaluation) but you need the scale in order to say what the weight difference is (the metric evaluation).

Visual perception measures the world in terms of angles; objects subtend a certain number of visual angles that depends on their size, distance, etc. Your thumbnail held at arm's length is about 1° of visual angle. You can get ordinal information directly from angles (the fact that one thing is closer/bigger/etc) but you need a scale to get the metric information required to use vision to control action. For example, you need to perceive how big something actually is in useful units in order to scale your hand size appropriately when grasping it; relative size doesn't help. One of the fundamental questions in (visual) perception research is, therefore, what are the metric units that the perceptual systems use to scale their measurements?

Dennis Proffitt has been studying this question for a long time and is in favour of task-specific, body-scaled units. His evidence comes from studies in which people perceive their environments differently as a function of their ability to act on that environment. Probably the most well-known example is the study that showed people judge hills to be steeper when they are wearing a heavy backpack (Bhalla & Proffitt, 1999). The idea is that the backpack will make traversing that hill more difficult, and when the visual system measures the slope, it scales its measurement in line with this perceived effort. The hypothesis is that this is functional; it's a feature of the visual system that helps us plan appropriate actions. 

Perspectives on Psychological Science recently hosted a point-counterpoint debate on this topic. Firestone (2013) reviewed the literature on this type of action-scaling in perception and concluded that not only do the data not really support Proffitt's account, but that this account couldn't work even in principle. Proffitt (2013) rebutted Firestone's arguments and defended his view. I'm interested in this because Proffitt is at least a little ecological, and the basic idea he defends is one I would defend as well (although not in the form that he proposes). So who won?

Replication will not save psychology

"Replication is our only hope." "No. There is another"

Psychology is big into replication these days. A lot of people think that a major problem with the field is that many important results have not been replicated, and that this is in part because journals don't like to publish replications (not original or sexy enough). 

I'm all for replication; it's part of good science. But I've never been that into the whole 'replication movement' that's kicking around, and the reason crystallised for me during a 4am baby feed: 

Being able to replicate a study is an effect, not a cause of good scientific practice. So the emphasis on replication as a goal has the whole thing backwards. We should actually be focusing on improving the experiments we run in the first place. If we run better experiments, the replicability will take care of itself. 

Embodiment and design; the affordances of pedestrian crossings

I'm a sucker for good design. I'm interested in things that work well because they are designed with the right task in mind. Take the greatest potato masher of all time, the Spudnik. It works well because it mashes as the result of a very natural action with the arm, easier and less effortful than the more traditional device. Good design works with the user and the task (rather than trying to impose a behavior) because behaviours that are supported by the task and the environment will be stable, reliable and easy to maintain. 

Design is interesting for embodied cognition because it's an attempt to artificially manipulate the environment to create affordances for some but not other behaviours. Sometimes it's just a matter of getting the physical layout right (see the Spudnik). Some of these required behaviours, however, are quite complex and not the sort of thing that would typically create information if left to their own devices. A great example is the design of streets to promote safe driving and pedestrian behaviour; a lot of the rules being designed for are human conventions, not physical necessities, and so without someone intervening and building something there couldn't be perceptual information anywhere about that rule. In addition, the designed element often creates information about something other than itself (see the Aboutness dimension in Sabrina's information taxonomy). This in turn creates the possibility for there to be more than one way to create an environment that produces relevant information and can therefore shape behaviour, and in turn, this allows the possibility that some designs will be better than others.

With this in mind, let me introduce you to two examples of design that I would like to change; the staggered pedestrian crossing, and puffin crossings. Both of these artificially restrict access to useful information in ways that mean well but that I think fight too much against human behaviour. I actually started preparing a grant to empirically investigate these designs from a more embodied perspective, and the EPSRC thought it was in their ballpark. More pressing concerns intervened, but I would love to actually do these studies and would like to hear from anyone who might be interested in collaborating ("Dear Pamela lab..."). I think our embodied cognition approach (Wilson & Golonka, 2013), with it's focus on task analyses and information, could really have an impact on an interesting part of our day to day life.

Social priming: Of course it only kind of works

Social priming is the field of research about how thinking about or interacting with something (like warm coffee, or old age) can affect later, vaguely related behaviour. (Rolf Zwaan has a useful summary of the theoretical background here and here, and a recipe for how to whip one of these up for yourself here.) It has been a top target for replication efforts in psychology. Although social priming effects in general have been widely demonstrated, many specific results (e.g. priming people to think about old age makes you walk slower; Bargh, Chen & Burrows, 1996) have failed to reliably replicate (even thought the effect sizes for individual studies are often surprisingly large). Most of the attention has been on the work of John Bargh because he basically invented the field (all discussed in this profile from January 2013).  Last year Bargh exploded all over the internet with a bit of a tantrum about these failures on his Psychology Today blog (now deleted, but archived for posterity here and here and discussed in detail by Ed Yong here). This made him something of a punching bag on Twitter, etc and so people are a bit excited that another Bargh social priming result has failed to replicate (oh and hey, here's another, non-Bargh one). Cue panic, gnashing of teeth and reflexive defensive moves by social psychologists (plus coverage of the topic in the NYT).

I'm a bit bemused by it all, really. I am not at all surprised that while social priming works in general, there is wide variation in how well specific social priming tasks work out. Of course priming works - it couldn't not work. But the lack of control over the information contained in social priming experiments guarantees unreliable outcomes for specific examples. Let me see if I can explain what I mean.

Perceiving causes; why knowledge doesn't trump perception

You're an organism, wandering round the world. Some stuff happens; then, other stuff happens. How do we know whether the first stuff caused the second stuff to happen, or whether it's all just one damn thing after another? A new study in Psychological Science (Bechlivanidis & Lagnado, 2013) investigates whether what we know can affect what we perceive, and claims to show that perception can get overridden. This caught my eye because it sounds like the kind of result that will be a problem for our embodied cognition (Wilson & Golonka, 2013), but thinking through the experiment using the tools of dynamics and event perception shows that this result is not going to cause us much concern - it just isn't studying what it says it's studying.