Do students know what’s good for them?

Of course they do, and of course they don’t.

Putting a student at the centre of their own learning seems like fundamental pedagogy. The Constructivist approach to education emphasises the need for knowledge to reassembled in the mind of the learner, and the related impossibility of its direct transmission from the mind of the teacher. Believe this, and student input into how they learn must follow.

At the same time, we know there is a deep neurobiological connection between the machinery of reward in our brain, and that of learning. Both functions seem to be entangled in the subcortical circuitry of a network known as the basal ganglia. It’s perhaps not surprising that curiosity, which we all know personally to be a powerful motivator of learning, activates the same subcortical circuitry involved in the pleasurable anticipation of reward. Further, curiosity enhances memory, even for things you learn while your curiosity is aroused about something else.

This neurobiological alignment of enjoyment and learning isn’t mere coincidence. When building learning algorithms for embedding in learning robots, the basic rules of learning from experience have to be augmented with a drive to explore – curiosity! – so that they don’t become stuck repeating suboptimal habits. Whether it is motivated by curiosity or other factors, exploration seems to support enhanced learning in a range of domains from simple skills to more complex ideas.

Obviously we learn best when motivated, and when learning is fun, and allowing us to explore our curiosity is a way to allow both. However, putting the trajectory of their experience into students’ hands can go awry.

False beliefs impede learning

One reason is false beliefs about how much we know, or how we learn best. Psychologists studying memory have long documented such metacognitive errors, which include overconfidence, and a mistaken reliance on our familiarity with a thing as a guide to how well we understand it, or how well we’ll be able to recall it when tested (recognition and recall are in fact different cognitive processes). Sure enough, when tested in experiments people will over-rely on ineffective study strategies (like rereading, or reviewing the answers to questions, rather than testing their ability to generate the answers from the questions). Cramming is another ineffective study strategy, with experiment after experiment showing the benefit of spreading out your study rather than massing it all together. Obviously this requires being more organised, but my belief is that a metacognitive error supports students’ over-reliance on cramming – cramming feels good, because, for a moment, you feel familiar with all the information. The problem is that this feel-good familiarity isn’t the kind of memory that will support recall in an exam, but immature learners often don’t realise the extent of that.

In agreement with these findings from psychologists, education scholars have reacted against pure student-led or discovery learning, with one review summarising the findings from multiple distinct research programmes taking place over three decades: “In each case, guided discovery was more effective than pure discovery in helping students learn and transfer”.

The solution: balancing guided and discovery learning

This leaves us at a classic “middle way”, where pure student-led or teacher-led learning is ruled out. Some kind of guided exploration, structured study, or student choice in learning is obviously a necessity, but we’re not sure how much.

There’s an exciting future for research which informs us what the right blend of guided and discovery learning is, and which students and topics suit which exact blend. One strand of this is to take the cognitive psychology experiments which demonstrate a benefit of active choice learning over passive instruction and to tweak them so that we can see when passive instruction can be used to jump-start or augment active choice learning. One experiment from Kyle MacDonald and Michael Frank of Stanford University used a highly abstract concept learning task in which participants use trial and error to figure out a categorisation of different shapes. Previous research had shown that people learned faster if they were allowed to choose their own examples to receive feedback on, but this latest iteration of the experiment from MacDonald and Frank showed that an initial session of passive learning, where the examples were chosen for the learner boosted performance even further. Presumably this effect is due to the scaffolding in the structure of the concept-space that the passive learning gives the learner. This, and myriad experiments, are possible to show when and how active learning and instructor-led learning can be blended.

Education is about more than students learning the material on the syllabus. There is a meta-goal of producing students who are better able to learn for themselves. The same cognitive machinery in all of us might push us towards less effective strategies. The simple fact of being located within our own selfish consciousness means that even the best performers in the world need a coach to help them learn. But as we mature we can learn to better avoid pitfalls in our learning and evolve into better self-determining students. Ultimately the best education needs to keep its focus on that need to help each of us take on more and more responsibility for how we learn, whether that means submitting to others’ choices or exploring things for ourselves – or, often, a bit of both.

This post originally appeared on the NPJ ‘Science of Learning’ Community

Does ‘brain training’ work?

You’ve probably heard of “brain training exercises” – puzzles, tasks and drills which claim to keep you mentally agile. Maybe, especially if you’re an older person, you’ve even bought the book, or the app, in the hope of staving off mental decline. The idea of brain training has widespread currency, but is that due to science, or empty marketing?

Now a major new review, published in Psychology in the Public Interest, sets out to systematically examine the evidence for brain training. The results should give you pause before spending any of your time and money on brain training, but they also highlight what happens when research and commerce become entangled.

The review team, led by Dan Simons of the University of Illinois, set out to inspect all the literature which brain training companies cited in their promotional material – in effect, taking them at their word, with the rationale that the best evidence in support of brain training exercises would be that cited by the companies promoting them.

The chairman says it works

A major finding of the review is the poverty of the supporting evidence for these supposedly scientific exercises. Simons’ team found that half of the brain training companies that promoted their products as being scientifically validated didn’t cite any peer-reviewed journal articles, relying instead on things like testimonials from scientists (including the company founders). Of the companies which did cite evidence for brain training, many cited general research on neuroplasticity, but nothing directly relevant to the effectiveness of what they promote.

The key issue for claims around brain training is that practising these exercises will help you in general, or on unrelated tasks. Nobody doubts that practising a crossword will help you get better at crosswords, but will it improve your memory, your IQ or your ability to skim read email? Such effects are called transfer effects, and so called “far transfer” (transfer to a very different task than that trained) is the ultimate goal of brain training studies. What we know about transfer effect is reviewed in Simons’ paper.

Doing puzzles make you, well, good at doing puzzles.
Jne Valokuvaus/

As well as trawling the company websites, the reviewers inspected a list provided by an industry group (Cognitive Training Data of some 132 scientific papers claiming to support the efficacy of brain training. Of these, 106 reported new data (rather than being reviews themselves). Of those 106, 71 used a proper control group, so that the effects of the brain training could be isolated. Of those 71, only 49 had so called “active control” group, in which the control participants actually did something rather than being ignored by the the researchers. (An active control is important if you want to distinguish the benefit of your treatment from the benefits of expectation or responding to researchers’ attentions.) Of these 49, about half of the results came from just six studies.

Overall, the reviewers conclude, no study which is cited in support of brain training products meets the gold standard for best research practises, and few even approached the standard of a good randomised control trial (although note their cut off for considering papers missed this paper from late last year).

A bit premature

The implications, they argue, are that claims for general benefits of brain training are premature. There’s excellent evidence for benefits of training specific to the task trained on, they conclude, less evidence for enhancement on closely related tasks and little evidence that brain training enhances performance on distantly related tasks or everyday cognitive performance.

The flaws in the studies supporting the benefits of brain training aren’t unique to the study of brain training. Good research is hard and all studies have flaws. Assembling convincing evidence for a treatment takes years, with evidence required from multiple studies and from different types of studies. Indeed, it may yet be that some kind of cognitive training can be shown to have the general benefits that are hoped for from existing brain training exercises. What this review shows is not that brain training can’t work, merely that promotion of brain training exercises is – at the very least – premature based on the current scientific evidence.

Yet in a 2014 survey of US adults, over 50% had heard of brain training exercises and showed some credence to their performance enhancing powers. Even the name “brain training”, the authors of the review admit, is a concession to marketing – this is how people know these exercises, despite their development having little to do with the brain directly.

The widespread currency of brain training isn’t because of overwhelming evidence of benefits from neuroscience and psychological science, as the review shows, but it does rely on the appearance of being scientifically supported. The billion-dollar market in brain training is parasitic on the credibility of neuroscience and psychology. It also taps into our lazy desire to address complex problems with simple, purchasable, solutions (something written about at length by Ben Goldacre in his book Bad Science).

The Simons review ends with recommendations for researchers into brain training, and for journalists reporting on the topic. My favourite was their emphasis that any treatment needs to be considered for its costs, as well as its benefits. By this standard there is no commercial brain training product which has been shown to have greater benefits than something you can do for free. Also important is the opportunity cost: what could you be doing in the time you invest in brain training? The reviewers deliberately decided to focus on brain training, so they didn’t cover the proven and widespread benefits of exercise for mental function, but I’m happy to tell you now that a brisk walk round the park with a friend is not only free, and not only more fun, but has better scientific support for its cognitive-enhancing powers than all the brain training products which are commercially available.

The Conversation

Tom Stafford, Lecturer in Psychology and Cognitive Science, University of Sheffield

This article was originally published on The Conversation. Read the original article.

a literary case of the exploding head

eOne of the most commented-upon posts on this blog is this from 2009, ‘Exploding head syndrome‘. The name stems from the 1920s, and describes an under-documented and mysterious condition in which the suffer experiences a viscerally loud explosion, as if occurring inside their own head.

I’m reading V.S.Naipaul’s “The Enigma of Arrival”, and the autobiographical main character experiences the same thing. Here we are on p93 of my edition of that novel:

In this dream there occurred always, at a critical moment in the dream narrative, what I can only describe as an explosion in my head. It was how every dream ended, with this explosion that threw me flat on my back, in the presence of people, in a street, a crowded room, or wherever, threw me into this degraded posture in the midst of standing people, threw me into the posture of sleep in which I found myself when I awakened. The explosion was so loud, so reverberating and slow in my head that I felt, with the part of my brain that miraculously could still think and draw conclusions, that I couldn’t possibly survive, that I was in fact dying, that the explosion this time, in this dream, regardless of the other dreams that had revealed themselves at the end as dreams, would kill, that I was consciously living through, or witnessing, my own death. And when I awoke my head felt queer, shaken up, exhausted; as though some discharge in my brain had in fact occurred.

The Enigma of Arrival on Goodreads
Vaughan’s 2009 post on Exploding Head Syndrome
Wikipedia: Exploding head syndrome

How curiosity can save you from political tribalism

Neither intelligence nor education can stop you from forming prejudiced opinions – but an inquisitive attitude may help you make wiser judgements.

Ask a left-wing Brit what they believe about the safety of nuclear power, and you can guess their answer. Ask a right-wing American about the risks posed by climate change, and you can also make a better guess than if you didn’t know their political affiliation. Issues like these feel like they should be informed by science, not our political tribes, but sadly, that’s not what happens.

Psychology has long shown that education and intelligence won’t stop your politics from shaping your broader worldview, even if those beliefs do not match the hard evidence. Instead, your ability to weigh up the facts may depend on a less well-recognised trait – curiosity.

The political lens

There is now a mountain of evidence to show that politics doesn’t just help predict people’s views on some scientific issues; it also affects how they interpret new information. This is why it is a mistake to think that you can somehow ‘correct’ people’s views on an issue by giving them more facts, since study after study has shown that people have a tendency to selectively reject facts that don’t fit with their existing views.

This leads to the odd situation that people who are most extreme in their anti-science views – for example skeptics of the risks of climate change – are more scientifically informed than those who hold anti-science views but less strongly.

But smarter people shouldn’t be susceptible to prejudice swaying their opinions, right? Wrong. Other research shows that people with the most education, highest mathematical abilities, and the strongest tendencies to be reflective about their beliefs are the most likely to resist information which should contradict their prejudices. This undermines the simplistic assumption that prejudices are the result of too much gut instinct and not enough deep thought. Rather, people who have the facility for deeper thought about an issue can use those cognitive powers to justify what they already believe and find reasons to dismiss apparently contrary evidence.

It’s a messy picture, and at first looks like a depressing one for those who care about science and reason. A glimmer of hope can be found in new research from a collaborative team of philosophers, film-makers and psychologists led by Dan Kahan of Yale University.

Kahan and his team were interested in politically biased information processing, but also in studying the audience for scientific documentaries and using this research to help film-makers. They developed two scales. The first measured a person’s scientific background, a fairly standard set of questions asking about knowledge of basic scientific facts and methods, as well as quantitative judgement and reasoning. The second scale was more innovative. The idea of this scale was to measure something related but independent – a person’s curiosity about scientific issues, not how much they already knew. This second scale was also innovative in how they measured scientific curiosity. As well as asking some questions, they also gave people choices about what material to read as part of a survey about reactions to news. If an individual chooses to read about science stories rather than sports or politics, their corresponding science curiosity score was marked up.

Armed with their scales, the team then set out to see how they predicted people’s opinions on public issues which should be informed by science. With the scientific knowledge scale the results were depressingly predictable. The left-wing participants – liberal Democrats – tended to judge issues such as global warming or fracking as significant risks to human health, safety or prosperity. The right-wing participants – conservative Republicans – were less likely to judge the issues as significant risks. What’s more, the liberals with more scientific background were most concerned about the risks, while the conservatives with more scientific background were least concerned. That’s right – higher levels of scientific education results in a greater polarisation between the groups, not less.

So much for scientific background, but scientific curiosity showed a different pattern. Differences between liberals and conservatives still remained – on average there was still a noticeable gap in their estimates of the risks – but their opinions were at least heading in the same direction. For fracking for example, more scientific curiosity was associated with more concern, for both liberals and conservatives.

The team confirmed this using an experiment which gave participants a choice of science stories, either in line with their existing beliefs, or surprising to them. Those participants who were high in scientific curiosity defied the predictions and selected stories which contradicted their existing beliefs – this held true whether they were liberal or conservative.

And, in case you are wondering, the results hold for issues in which political liberalism is associated with the anti-science beliefs, such as attitudes to GMO or vaccinations.

So, curiosity might just save us from using science to confirm our identity as members of a political tribe. It also shows that to promote a greater understanding of public issues, it is as important for educators to try and convey their excitement about science and the pleasures of finding out stuff, as it is to teach people some basic curriculum of facts.

This is my BBC Future column from last week. The original is here. My ebook ‘For argument’s sake: evidence that reason can change minds’ is out now

The mechanics of subtle discrimination: measuring ‘microaggresson’

Many people don’t even realise that they are discriminating based on race or gender. And they won’t believe that their unconscious actions have consequences until they see scientific evidence. Here it is.

The country in which I live has laws forbidding discrimination on the grounds of ethnicity, religion, sexuality or sex. We’ve come a long way since the days when the reverse was true – when homosexuality was illegal, for instance, or when women were barred from voting. But this doesn’t mean that prejudice is over, of course. Nowadays we need to be as concerned about subtler strains of prejudice as the kind of loud-mouthed racism and sexism that makes us ashamed of the past.

Subtle prejudice is the domain of unjustified assumptions, dog-whistles, and plain failure to make the effort to include people who are different from ourselves, or who don’t fit our expectations. One word for the expressions of subtle prejudice is ‘microaggressions’. These are things such as repeating a thoughtless stereotype, or too readily dismissing someone’s viewpoint – actions that may seem unworthy of comment, but can nevertheless marginalise an individual.

The people perpetrating these microaggressions may be completely unaware that they hold a prejudiced view. Psychologists distinguish between our explicit attitudes – which are the beliefs and feelings we’ll admit to – and our implicit attitudes – which are our beliefs and feelings which are revealed by our actions. So, for example, you might say that you are not a sexist, you might even say that you are anti-sexist, but if you interrupt women more than men in meetings you would be displaying a sexist implicit attitude – one which is very different from that non-sexist explicit attitude you profess.

‘Culture of victimhood’

The thing about subtle prejudice is that it is by definition subtle – lots of small differences in how people are treated, small asides, little jibes, ambiguous differences in how we treat one person compared to another. This makes it hard to measure, and hard to address, and – for some people – hard to take seriously.

This is the skeptical line of thought: when people complain about being treated differently in small ways they are being overly sensitive, trying to lay claim to a culture of victimhood. Small differences are just that – small. They don’t have large influences on life outcomes and aren’t where we should focus our attention.

Now you will have your own intuitions about that view, but my interest is in how you could test the idea that a thousand small cuts do add up. A classic experiment on the way race affects our interactions shows not only the myriad ways in which race can affect how we treat people, but shows in a clever way that even the most privileged of us would suffer if we were all subjected to subtle discrimination.

In the early 1970s, a team led by Carl Word at Princeton University recruited white students for an experiment they were told was about assessing the quality of job candidates. Unbeknown to them, the experiment was really about how they treated the supposed job candidates, and whether this was different based on whether they were white or black.

Despite believing their task was to find the best candidate, the white recruits treated candidates differently based on their race – sitting further away from them, and displaying fewer signs of engagement such as making eye-contact or leaning in during conversation. Follow-up work more recently has shown that this is still true, and that these nonverbal signs of friendliness weren’t related to their explicit attitudes, so operate independently from the participants’ avowed beliefs about race and racism.

So far the the Princeton experiment probably doesn’t tell anyone who has been treated differently because of their race anything they didn’t know from painful experience. The black candidates in this experiment were treated less well than the white candidates, not just in the nonverbal signals the interviewers gave off, but they were given 25% less time during the interviews on average as well. This alone would be an injustice, but how big a disadvantage is it to be treated like this?

Word’s second experiment gives us a handle on this. After collecting these measurements of nonverbal behaviour the research team recruited some new volunteers and trained them to react in the manner of the original experimental subjects. That is, they were trained to treat interview candidates as the original participants had treated white candidates: making eye contact, smiling, sitting closer, allowing them to speak for longer. And they were also trained to produce the treatment the black candidates received: less eye contact, fewer smiles and so on. All candidates were to be treated politely and fairly, with only the nonverbal cues varying.

Next, the researchers recruited more white Princeton undergraduates to play the role of job candidates, and they were randomly assigned to be nonverbally treated like the white candidates in the first experiment, or like the black candidates.

The results allow us to see the self-fulfilling prophesy of discrimination. The candidates who received the “black” nonverbal signals delivered a worse interview performance, as rated by independent judges. They made far more speech errors, in the form of hesitations, stutters, mistakes and incomplete sentences, and they chose to sit further away from the interviewer following a mid-interview interruption which caused them to retake their chairs.

It isn’t hard to see that in a winner-takes-all situation like a job interview, such differences could be enough to lose you a job opportunity. What’s remarkable is that the participants’ performance had been harmed by nonverbal differences of the kind that many of us might produce without intending or realising. Furthermore, the effect was seen in students from Princeton University, one of the world’s elite universities. If even a white, privileged elite suffer under this treatment we might expect even larger effects for people who don’t walk into high-pressure situations with those advantages.

Experiments like these don’t offer the whole truth about discrimination. Problems like racism are patterned by so much more than individual attitudes, and often supported by explicit prejudice as well as subtle prejudice. Racism will affect candidates before, during and after job interviews in many more ways than I’ve described. What this work does show is one way in which, even with good intentions, people’s reactions to minority groups can have powerful effects. Small differences can add up.

This is my BBC Future column from last week. The original is here.

Serendipity in psychological research

micDorothy Bishop has an excellent post ‘Ten serendipitous findings in psychology’, in which she lists ten celebrated discoveries which occurred by happy accident.

Each discovery is interesting in itself, but Prof Bishop puts the discoveries in the context of the recent discussion about preregistration (declaring in advance what you are looking for and how you’ll look). Does preregistration hinder serendipity? Absolutely not says Bishop, not least because the context of ‘discovery’ is never a one-off experiment.

Note that, in all cases, having made the initial unexpected observation – either from unstructured exploratory research, or in the course of investigating something else – the researchers went on to shore up the findings with further, hypothesis-driven experiments. What they did not do is to report just the initial observation, embellished with statistics, and then move on, as if the presence of a low p-value guaranteed the truth of the result.

(It’s hard not to read into these comments a criticism of some academic journals which seem happy to publish single experiments reporting surprising findings.)

Bishop’s list contains 3 findings from electrophysiology (recording brain cell activity directly with electrodes), which I think is notable. In these cases neural recording acts in the place of a microscope, allowing fairly direct observation of the system the scientist is investigating at a level of detail hitherto unavailable. It isn’t surprising to me that given a new tool of observation, the prepared mind of the scientists will make serendipitous discoveries. The catch is whether, for the rest of psychology, such observational tools exist. Many psychologists use their intuition to decide where to look, and experiments to test whether their intuition is correct. The important serendipitous discoveries from electrophysiology suggest that measures which are new ways of observing, rather than merely tests of ideas, must also be important for psychological discoveries. Do such observational measures exist?

Good tests make children fail – here’s why

Many parents and teachers are critical of the Standardised Assessment Tests (SATs) that have recently been taken by primary school children. One common complaint is that they are too hard. Teachers at my son’s school sent children home with example questions to quiz their parents on, hoping to show that getting full marks is next to impossible.

Invariably, when parents try out these tests, they focus on the most difficult or confusing items. Some parents and teachers can be heard complaining on social media that if they get questions wrong, surely the tests are too hard for ten-year-olds.

But how hard should tests for children be?

As a psychologist, I know we have some well-developed principles that can help us address the question. If we look at the SATs as measures of some kind of underlying ability, then we can turn to one of the oldest branches of psychology – “psychometrics” – for some guidance.

Getting it just right

A good test shouldn’t be too hard. If most people get most questions wrong, then you have what is called a “floor effect”. The result is that you can’t tell any difference in ability between the people taking the test.

If we started the school sports day high jump with the bar at two metres high (close to the world record), then we’d finish sports day with everybody getting the same – zero successful jumps – and no information about how good anyone is at the high jump.

But at the same time, a good test shouldn’t be too easy. If most people get everything right, then the effect is, as you might expected, called a “ceiling effect”. If everybody gets everything right then again we don’t get any information from the test.

The key idea is that tests must discriminate. In psychometric terms, the value of a test is about the match between the thing it is supposed to measure and the difficulty of the items on the test. If I wanted to gauge maths ability in six-year-olds and I gave them all an A-Level paper, we can presume that nearly everyone would score zero. Although the A-Level paper might be a good test, it is completely uninformative if it is badly matched to the ability of the people taking the test.

Here’s the rub: for a test to be sensitive to differences in ability, it must contain items which people get wrong. Actually, there’s a precise answer to the proportion that you should get wrong – in the most sensitive test it should be half of the items. Questions which you are 50% likely to get right are the ones which are most informative.

How we feel about measuring and labelling children according to their skill at taking these tests is a big issue, but it is important that we recognise that this is what tests do. A well designed test will make all children get some items wrong – it is inherent in their design. It is up to us how we conceptualise that: whether tests are an unnecessary distraction from true education, or a necessary challenge we all need to be exposed to.

Better tests?

If you adopt this psychometric perspective, it becomes clear that the tests we use are an inefficient way of measuring any individual child’s particular ability to do the test. Most children will be asked a bunch of questions which are too easy for them, before they get to the informative ones which are at the edge of their ability. Then they will go on to attempt a bunch of questions which are far too hard. And pity the people for who the test is poorly matched to their ability and consists mostly of questions they’ll get wrong – which is both uninformative in psychometric terms, and dispiriting emotionally.

A hundred years ago, when we began our modern fixation with testing and measuring, it was hard to avoid the waste where many uninformative and potentially depressing questions were asked. This was simply because all children had to take the same exam paper.

Nowadays, however, examiners can administer tests via computer, and algorithmically identify the most informative questions for each child’s ability – making the tests shorter, more accurate, and less focused on the experience of failure. You could throw in enough easy questions that no child would ever have the experience of getting most of the questions wrong. But still there’s no getting around the fact that an informative test has to contain questions most people sitting it will get wrong.

Even a good test can measure an educationally irrelevant ability (such as merely the ability to do the test, or memorise abstract grammar rules), or be used in ways that harm children. But having difficult items isn’t a problem with the SATs, it’s a problem with all tests.

The Conversation

This article was originally published on The Conversation. Read the original article.