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individual differences

Homework revisited

At the same time as a group of French parents and teachers have called for a two-week boycott of homework (despite the fact that homework is officially banned in French primary schools), and just after the British government scrapped homework guidelines, a large long-running British study came out in support of homework.

The study has followed some 3000 children from preschool through (so far) to age 14 (a subset of around 300 children didn’t attend preschool but were picked up when they started school). The latest report from the Effective Pre-school, Primary and Secondary Education Project (EPPSE), which has a much more complete database to call on than previous studies, has concluded that, for those aged 11-14, time spent on homework was a strong predictor of academic achievement (in three core subjects).

While any time spent on homework was helpful, the strongest effects were seen in those doing homework for 2-3 hours daily. This remained true even after prior self-regulation was taken into account.

Of course, even with such a database as this, it is difficult to disentangle other positive factors that are likely to correlate with homework time — factors such as school policies, teacher expectations, parental expectations. Still, this study gives us a lot of data we can mull over and speculate about.

For example, somewhat depressingly, only a quarter of students (28%) said they were sometimes given individualized work, and many weren’t impressed by the time it took some teachers to mark and return their homework (only 68% of girls, and 75% of boys, agreed that ‘Most teachers mark and return my homework promptly’), or with the standards of the work required (49% of those whose family had no educational qualifications, 34% of those whose family had school or vocational qualifications, and 30% of those whose family had higher qualifications, agreed with the statement that ‘teachers are easily satisfied’ — suggesting among other things that teachers of less privileged students markedly underestimate their students’ abilities). Also depressingly, over a third (36%) agreed with the statement that ‘pupils who work hard are given a hard time by others’ (again, this breaks down into quite different proportions depending on the student’s background, with 46% of those in the lowest ‘Home Learning Environment’ agreeing with the statement, decreasing steadily through the ranks to finally reach 27% (still too high!) among those in the highest HLE).

One supposed benefit of homework that has been much touted, especially by those who are in the ‘homework for the sake of homework’ camp, is that of teaching self-regulation (although it can, and has, be equally argued that, by setting useless homework, teachers weaken self-regulation). While the present study did find social-behavioral benefits associated with homework, which would seem to support the former view, these benefits were only seen in relation to behavior at age 14, not to any changes between 11 and 14. In other words, homework wasn’t affecting change over time. This would seem to argue against the idea that doing homework teaches children how to manage their own learning.

Another interesting (of the many) key findings of the report concerns children who ‘succeed against the odds’ — that is, they do better than expected considering their socioeconomic or personal circumstances. Parents of these children tend to engage in ‘active cultivation’ — reading and talking to them when young, providing them with many and wide-ranging learning experiences throughout their childhood, supporting and encouraging their learning. Such support tended to be lacking for those children who did not transcend their circumstances, whose parents often felt helpless about parenting and about education.

In view of my last blog post, I would also like to particularly note that ‘good’ students tended to have a strong internal locus of control, while ‘poor’ students tended to feel helplessness, and had the belief that the ability to learn was an inborn talent (that they didn’t possess).

But education providers shouldn’t simply blame the parents! Teachers, too, are important, and those students who succeeded against the odds also attributed part of their success to supportive and empowering teachers, while those disadvantaged students who didn’t succeed mentioned the high number of supply teachers and disorganized lessons.

There is also a role for peers, and for extracurricular activities — families with academically successful children tended to value extracurricular activities, while those with less successful students viewed them, dismissively, as ‘fun’, rather than of any educational value.

You can download the full report at https://www.education.gov.uk/publications/standard/publicationDetail/Page1/DFE-RR202  or see the summary at http://www.ioe.ac.uk/newsEvents/62517.html

There’s a lot of controversy about the value of homework, for understandable reasons. And the inconsistent findings of homework research point to the fact that we can’t say, simplistically, that all children of [whatever age] should do [so many] hours of homework. Because it rests on the quality and context of the homework, and the interaction with the individual. Homework may be an effective strategy, but it is one that is all too often carried out ineffectively.

Homework for the sake of homework is always a bad idea, and if the teacher can’t articulate what the purpose of the homework is (or that purpose isn’t a good one!), then they shouldn’t set it.

So what are good purposes for homework?

The most obvious is to perform tasks that can’t, for reasons of time or resources, be accomplished in the classroom. But this, of course, is less straightforward than it appears. Practice, for example, would seem to be a clear contender, but optimally distributed retrieval practice (i.e., testing — see also this news report and this) is usually best done in the classroom. Projects generally require time and resources beyond the classroom, but parts of the project may well require school resources or group activity or teacher feedback.

Maybe we should turn this question around: what are classrooms good for?

Contrary to popular practice, the simple regurgitation of information, from teacher to student, is not what classrooms are best used for. Such information is more efficiently absorbed from texts or videos or podcasts — which students can read/watch/listen to as often as they need to. No, there are five main activities for which classrooms are best suited:

  • Group activities (including class discussion)
  • Activities involving school resources (such as science experiments — I am using ‘classroom’ broadly)
  • Praxis (as seen in the apprenticeship model — a skill or activity is modeled by a skilled practitioner for students to imitate; the practitioner provides feedback)
  • Motivation (the teacher engages and enthuses the students; teacher and peer feedback provides on-going help to stay on-task)
  • Testing (not to put students under pressure to perform on tests that will decide their future, but because retrieval practice is the best strategy for learning there is — that is, testing needs to be done in a completely different way, and with students and teachers understanding that these tests are for the purposes of learning, not as a judgment on ability)

All of this is why the flipped classroom model is becoming so popular. I’m a great fan of this, although of course it needs to be done well. Here’s some links for those who want to learn more about this:

An article on flipped classrooms, what they are and some teachers’ and students’ experiences. http://www.azcentral.com/news/articles/2012/03/31/20120331arizona-school-online-flipping.html

A case study of ‘flipped classroom’ use at Byron High School, where math mastery has jumped from 30% in 2006 to 74% in 2011 according to the Minnesota Comprehensive Assessments. http://thejournal.com/articles/2012/04/11/the-flipped-classroom.aspx

A brief interview with high school chemistry teacher Jonathan Bergmann, who now helps other teachers ‘flip’ their classrooms, and is co-author of a forthcoming book on the subject. http://www.washingtonpost.com/local/education/the-flip-classwork-at-home-homework-in-class/2012/04/15/gIQA1AajJT_story.html

But there's one reason for all the argument on the homework issue that doesn't get a lot of airtime, and that is that there is no clear consensus on what school is for and what students should be getting out of it. And maybe part of the reason for that is that, for some people (some teachers, some education providers and officials), they don’t want to articulate what they believe school is all about, because they know many people would be outraged by their opinions. But if you think some people are going to be appalled, maybe you should rethink your thoughts!

Now of course different individuals are going to want different things from education, but until all parties can front up and lay out clearly exactly what they think school is for, then we’re not going to be able to construct a system and a curriculum that teaches effectively and reliably across the board.

Which is not to say I think we'd all agree. But if people openly and honestly put their agenda on the table, then we could openly state what particular schools are for, and different guidelines and assessment tools could be used appropriately.

But first and and most important: everyone (students, teachers, and parents) needs to realize that, notwithstanding the role of genes, intelligence and learning ‘talents’ are far from fixed. ((I’ve talked about this on a number of occasions, but if you want to read more about this, and the importance of self-regulation, from another source, check out this blog post at Scientific American.) If a child is not learning, it is a failure of a number of aspects of their situation, but it is not (absent severe brain damage), because the child is too stupid or lazy. (On which subject, you might like to read a great article in the Guardian about 'Poor economics'.)

What I think about homework is that we should get away completely from this homework/classwork divide. What we need to do is decide what work the student needs to do (to fulfil the articulate purpose), and then divide that into work that is most effectively (given the student's circumstances) done in the classroom and work that is best done in the student's own time and at their own pace.

So what do you think?

Decision-making, working memory, and age

In October I reported on a study that found older adults did better than younger adults on a decision-making task that reflected real-world situations more closely than most tasks used in such studies. It was concluded that, while (as previous research has shown) younger adults may do better on simple decision-making tasks, older adults have the edge when it comes to more complex scenarios. Unsurprisingly, this is where experience tells.

Last year I reported on another study, showing that poorer decisions by older adults reflected specific attributes, rather than age per se. Specifically, processing speed and memory are behind individual differences in decision-making performance. Both of these processes, of course, often get worse with age.

What these two studies suggest is that your ability to make good decisions depends a lot on whether

  • you have sufficient time to process the information you need,
  • your working memory is up to the job of processing all the necessary information, and
  • your long-term memory is able to provide any information you need from your own experience.

One particular problem for older adults, for example, that I have discussed on many occasions, is source memory — knowing the context in which you acquired the information. This can have serious consequences for decision-making, when something or someone is remembered positively when it should not, because the original negative context has been forgotten.

But the trick to dealing with memory problems is to find compensation strategies that play to your strengths. One thing that improves with age is emotion regulation. As we get older, most of us get better at controlling our emotions, and using them in ways that make us happier. Moreover, it appears that working memory for emotional information (in contrast to other types of information) is unaffected by age. Given new research suggesting that decision-making is not simply a product of analytic reasoning processes, but also involves an affective/experiential process that may operate in parallel and be of equal importance, the question arises: would older adults be better relying on emotion (their ‘gut’) for decisions?

In Scientific American I ran across a study looking into this question. 60 younger (aged 18-30) and 60 older adults (65-85) were presented with health care choices that required them to hold in mind and consider multiple pieces of information. The choices were among pairs of health-care plans, physicians, treatments, and homecare aides. Working memory load increased across trials from one to four attributes per option. On each trial, one option had a higher proportion of positive to negative attributes. Each attribute had a positive and negative variant (e.g., “dental care is fully covered” vs “dental care is not covered”).

In the emotion-focus condition participants were asked to focus on their emotional reactions to the options and report their feelings about the options before making a choice. In the information-focus condition, participants were told to focus instead on the specific attributes and report the details about the options. There were no such instructions in the control condition.

As expected, working memory load had a significant effect on performance, but what’s interesting is the different effects in the various conditions. In the control condition, for both age groups, there was a dramatic decrease in performance when the cognitive load increased from 2 items to 4, but no difference between those in which the load was 4, 6, or 8 items. In the information-focus condition, the younger group showed a linear (but not steep) decrease in decision-making performance with each increase in load, except at the last — there was no difference between 6 and 8 items. The older group showed a dramatic drop when load was increased from 2 to 4, no difference between 4 and 6, and a slight drop when items increased to 8. In the emotion-focus condition, both groups showed the same pattern they had shown in the information-focus condition, except that, for the younger group, there was a dramatic drop when items increased to 8.

So that’s one point: that the effect of cognitive load is modified by instructional condition, and varies by age.

The other point, of course, concerns how level of performance varies. Interestingly, in the control condition, the two age groups performed at a similar level. In the information-focus condition, the slight superiority of the younger group when the load was lightest expanded significantly as soon as the number of items increased to four, and was greatest at the highest load. In the emotion-focus condition, however, the very slight superiority of the younger group at two items did not increase as the load increased, and indeed reversed when the load increased to eight.

Here’s what I think are the most interesting results of this study:

There was no significant difference in performance between the age groups when no instruction was given.

Younger adults were better off being given some instruction, but when the cognitive load was not too great (2, 4, 6 items), there was no difference for them in focusing on emotions or details. The difference — and it was a significant one — came when the load was highest. At this point, they were much better to concentrate on the details and apply their reasoning abilities.

Older adults, on the other hand, were better off, always but especially when the load was highest, in focusing on their feelings.

Performance on a digit-symbol coding task (a measure of processing speed) correlated significantly with performance in the information-focus condition for both age groups. When processing speed was taken into account, the difference between the age groups in that condition disappeared. In other words, younger adults' superior performance in the information-focus condition was entirely due to their higher processing speed. However, age differences in the emotion-focus condition were unaffected.

Younger adults performed significantly better in the information-focus condition compared to the control condition, indicating that specific instructions are helpful. However, there was no significant difference between the emotion-focus condition and the control for the older adults, suggesting perhaps that such processing is their ‘default’ approach.

The findings add weight to the idea that there is a separate working memory system for emotion-based information.

It should be noted that, somewhat unusually, the information was presented to participants sequentially rather than simultaneously. It may well be that these results do not apply to the situation in which you have all the necessary information presented to you in a document and can consider it at your leisure. On the other hand, in the real world we often amass information over time, or acquire it by listening rather than seeing it all nicely arrayed in front of us.

The findings suggest that the current emphasis on providing patients with all available information in order to make an “informed choice” may be misplaced. Many older patients may be better served by a greater emphasis on emotional information, rather than being encouraged to focus on myriad details.

But I'd like to see this experiment replicated using a simultaneous presentation. It may be that these findings should principally be taken as support for always seeking written documentation to back up spoken advice, or, if you're gathering information over time and from multiple sources, making sure you have written notes for each instance. Personally, I dislike making any decisions based solely on information given in conversation, and this is a reluctance I have found increasing steadily with age (and I'm not that old yet!).

References

Mikels, J.A., Löckenhoff, C.E., Maglio, S.J., Carstensen, L.L., Goldstein, M.K. & Garber, A. 2010. Following your heart or your head: Focusing on emotions versus information differentially influences the decisions of younger and older adults. Journal of Experimental Psychology: Applied, 16(1), 87-95.

Intelligence isn’t as important as you think

Our society gives a lot of weight to intelligence. Academics may have been arguing for a hundred years over what, exactly, intelligence is, but ‘everyone knows’ what it means to be smart, and who is smart and who is not — right?

Of course, it’s not that simple, and the ins and outs of academic research have much to teach us about the nature of intelligence and its importance, even if they still haven’t got it all totally sorted yet. Today I want to talk about one particular aspect: how important intelligence is in academic success.

First of all, to simplify the discussion, let’s start by pretending that intelligence equals “g” and is measured by IQ testing. (“g” stands for “general factor”, and reflects the shared element between multiple cognitive tests. It is a product of a statistical technique known as factor analysis, which measures the inter-correlation between scores on various cognitive tasks. It is no surprise to any of us that cognitive tasks should be correlated — that people who do well on one task are likely to do well on others, while people who do poorly on one are likely to perform poorly on others. No surprise, either, that some cognitive tasks will be more highly correlated than others. But here’s the thing: the g factor, while it explains a lot of the individual differences in performance on an IQ test, accounts for performance on some of the component sub-tests better than others. In other words, g is more important for some cognitive tasks than others. Again, not terribly unexpected. Some tasks are going to require more ‘intelligence’ than others. One way of describing these tasks is to say that they are cognitively more complex. In the context of the IQ test, the sub-tests each have a different “g-loading”.)  

Now there is no doubting that IQ is a good predictor of academic performance, but what does that mean exactly? How good is ‘good’? Well, according to Flynn, IQ tests that are heavily-loaded on g reliably predict about 25% of the variance in academic achievement (note that this is about variance, that is the differences between people; this is not the same as saying that IQ accounts for a quarter of academic performance). But this does vary significantly depending on age and population — for example, in a group of graduate students, the relative importance of other factors will be greater than it is in a cross-section of ten-year-olds. In the study I will discuss later, the figure cited is closer to 17%.

Regardless of whether it’s as much as 25% or as little as 17%, I would have thought that these figures are much smaller than most people would imagine, given the weight that we give to intelligence.

So what are the other factors behind doing well at school (and, later, at work)?

The most obvious one is effort. One way to measure how hard people work is through the personality dimension of Conscientiousness.

One study involving 247 British university students compared the predictive power of the “Big Five” personality traits (Neuroticism, Extraversion, Openness to Experience, Agreeableness, Conscientiousness) on later exam performance, and found that Conscientiousness had a significant effect, and was the only trait to have a significantly positive effect. Illuminatingly, of Conscientiousness’s components (Competence, Order, Dutifulness, Achievement striving, Self-discipline, Deliberation), only Dutifulness, Achievement striving, and (to a lesser extent), Self-discipline, had significant effects.

There were also, smaller and less reliable, negative effects of Neuroticism and Extraversion. The problems here came mainly from Anxiety and Impulsiveness, and Gregariousness and Activity.

Overall, Dutifulness, Achievement striving, and Activity, accounted for 28% of the variance in overall exam grades (over the three years of their undergraduate degrees).

But note that these students were highly selected — undergraduates were (at this point in time) accepted to the University College London at an application: acceptance ratio of 12:1 — so IQ is going to be less important as a source of individual difference.

In another study by some of the same researchers, 80 sixth-formers (equivalent to grade 10) were given both personality and intelligence tests. Conscientiousness and Openness to Experience were found to account for 13% of unique variance in academic performance, and intelligence for 10%. Interestingly, there were subject differences. Intelligence was more important than personality for science subjects (including math), while the reverse was true for English language (literature, language) subjects.

The so-called Big Five personality dimensions are well-established, but recently a new model has introduced a sixth dimension: Honesty-Humility. Unexpectedly (to me at least), a recent study showed this dimension also has some implications for academic performance.

The first experiment in this study involved 226 undergraduate students from a School of Higher Education in the Netherlands. Both Conscientiousness and Honesty-Humility were significantly and positively correlated to grade point average (with Conscientiousness having the greater effect). All the components of Conscientiousness (in this model, Organization, Diligence, Perfectionism, Prudence) were significantly related to GPA. Three of the four components of Honesty-Humility (Greed Avoidance, Modesty, Fairness) were significantly related to GPA (in that order of magnitude).

In the second experiment, a wider data-set was used. 1262 students from the same school were given the Multicultural Personality Test—Big Six, which measures Emotional Stability, Conscientiousness, Extraversion, Agreeableness, Openness, and Integrity (a similar construct to Honesty-Humility, involving the facets Honesty, Sincerity, Greed Avoidance). Again, Conscientiousness and Integrity showed significant and positive correlations to GPA. In this case, Conscientiousness was divided into Need for Rules and Certainty, Orderliness, Perseverance, and Achievement Motivation — all of which were separately significant predictors of GPA. For Integrity, Greed Avoidance produced the largest effect, with Honesty being a smaller effect but still highly significant, while Sincerity was of more marginal significance.

In summary, personality traits such as Diligence, Achievement Motivation, Need for Rules and Certainty, Greed Avoidance, and Modesty, were the traits most strongly associated with academic performance.

Of course, one flaw in personality tests is that they rely on self-reports. A much-discussed longitudinal study of eighth-graders found that self-discipline accounted for more than twice as much variance as IQ in final grades. Moreover, self-discipline also predicted which students would improve their grades over the course of the year, which IQ didn’t.

Again, however, it should be noted that this is a selected group — the students came from a magnet public school in which students were admitted on the basis of their grades and test scores.

This study measured self-discipline not only by self-report, but also by parent report, teacher report, monetary choice questionnaires (in an initial experiment involving 140 students), a behavioral delay-of-gratification task, a questionnaire on study habits, (in a replication involving 164 students).

One personality trait that many have thought should be a factor in academic achievement is Openness to Experience, and indeed, in some experiments it has been so. It may be that Openness to Experience, which includes Fantasy (vivid imagination), Aesthetic Sensitivity, Attentiveness to Inner Feelings, Actions (engagement in novel activities), Ideas, and Values (readiness to reexamine traditional values), is associated with higher intelligence but not necessarily academic success (depending perhaps on subject?).

It may also be that, as with Neuroticism, Extraversion, and Conscientiousness, only some (or even one) of the component traits is relevant to academic performance. The obvious candidate is Ideas, described as the tendency to be intellectually curious and open to new ideas. Supporting this notion, recent research provides evidence that Openness incorporates two related but distinct factors: Intellect (Ideas) and Openness (artistic and contemplative qualities, embodied in Fantasy, Aesthetics, Feelings, and Actions), with Values a distinct marker belonging to neither camp.

A recent meta-analysis, gathering data from studies that have employed the Typical Intellectual Engagement (TIE) scale (as a widely-used proxy for intellectual curiosity), has found that curiosity had as large an effect on academic performance as conscientiousness, and together, conscientiousness and curiosity had as big an effect on performance as intelligence.

Of course, while research has shown (not unexpectedly) that Conscientiousness and Intelligence are quite independent, the correlation between Intelligence and Curiosity is surely significant. In fact, this study found a significant correlation between both TIE and Intelligence, and TIE and Conscientiousness. Nevertheless, the best-fit model indicated that all three factors were direct predictors of academic performance.

More to the point, these three important attributes all together still accounted for only a quarter of the variance in academic performance.

Regardless of the precise numbers (this area of study depends on complex statistical techniques, and I wouldn’t want to rest any case on any specific figure!), it is clear from the wealth of research (which I have barely touched on), that although intelligence is an important attribute in determining success in the classroom and in employment, it is only one among a number of important attributes. And so is Diligence. Perhaps we should spend less time praising intelligence and hard work, and more time encouraging engagement and curiosity, and a disinterest in luxury goods or a high social status.

 

Read more about the curiosity study at https://medicalxpress.com/news/2011-10-curiosity-doesnt-student.html

References

Chamorro-Premuzic, T., & Furnham, A. (2003). Personality traits and academic examination performance. European Journal of Personality, 17(3), 237-250. doi:10.1002/per.473

Duckworth, A. L., & Seligman, M. E. P. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological science, 16(12), 939-44. doi:10.1111/j.1467-9280.2005.01641.x

Furnham, A., & Chamorro-premuzic, T. (2005). Personality and Intelligence : Gender , the Big Five , Self-Estimated and Psychometric Intelligence. International Journal of Selection and Assessment, 13(1), 11-24.

Furnham, A., Rinaldelli-Tabaton, E. & Chamorro-Premuzic, T. (2011). Personality and Intelligence Predict Arts and Science School Results in 16 Year Olds. Psychologia, 54 (1), 39-51.

von Stumm, S., Hell B., & Chamorro-Premuzic T. (2011). The Hungry Mind. Perspectives on Psychological Science. 6(6), 574 - 588.

Normal is a label too

We all like simple solutions. However much we may believe we are ‘above’ black-&-white dichotomies, that of course we understand that every situation is complex, nevertheless we have a brain that can only think of a very very few things at once. So it's unsurprising that we are drawn to solutions that can be summed up simply, that can fit comfortably within the limitations of working memory.

Here’s something I read about in Scientific American the other day: Huntington’s disease — which is a terrible disease that eats away at your brain, causing both physical and cognitive disabilities that continue to deteriorate until the sufferer dies an untimely death — is linked to an excess of a brain chemical (the neurotransmitter glutamate) that is in fact vital for learning and memory. Intriguingly, a recent study has found that those with the genetic mutation for this disease, but who were as yet asymptomatic, were significantly quicker to learn than those without the mutation. Indeed, those with the greatest number of copies of the mutation were the fastest to learn.

This may not simply be a matter of disease progression — an earlier study found that Huntington’s patients did better on one cognitive task than healthy controls (detecting whether a tone was long or short). It may be, the researchers suggested, that it is simplistic to talk of a decline in cognitive function in Huntington’s, rather some functions might be enhanced while others are impaired.

Huntington’s Disease is hardly alone in this. We often talk about ‘normal’ memory aging, and there’s no denying the concept of normal is a useful one — in certain contexts. But not, perhaps, in all those contexts in which it is used.

Psychology, as I’ve mentioned before, has historically been a search for what is ‘normal’ in human behavior. What is not normal is deemed ‘abnormal’ — a nice black & white dichotomy. Of course this is simplistic, but it gives us a place to stand. But now that psychology is a mature discipline, it can look around, explore the variability in human behavior. However it is only very very recently that we have begun to realize that the search for normal is merely a starting point to the question of what it is to be human, and it has become a straight-jacket.

As an example, let’s look briefly at something discussed in a provocative article about autism that appeared in the journal Nature. The writer of the article, Dr. Laurent Mottron, leads a research team that includes several autistic individuals. As a consequence, he has grown to appreciate the strengths that such individuals can bring to research.

The main thrust of his argument is that autism is not simply a “suite of negative characteristics”. There are advantages in some autistic characteristics. But because autism is defined as a ‘disorder’, researchers and clinicians systematically interpret behaviors in terms of impairment and abnormalities. More useful would be to examine each behavior on its own merits, and consider whether the behavior might be adaptive in certain contexts.

Mottron says that although intellectual disability is routinely estimated to be about 75% among autistics, only 10% of autistics have an accompanying neurological disease that affects intelligence, and if researchers used only those tests that require no verbal explanation, the level of intellectual disability would be seen to be much lower. An interesting comparison: “In measuring the intelligence of a person with a hearing impairment, we wouldn't hesitate to eliminate components of the test that can't be explained using sign language; why shouldn't we do the same for autistics?”

Mottron’s research term have coined a telling word: normocentrism, meaning the preconception you have that if you do or are something, it is normal, and if autistic do or have it, it is abnormal — I think this term could be usefully applied more widely. Similarly, the rise of the concept of ‘neurodiversity’ in the autistic community (whereby a ‘normal’ is ‘neurotypical’ and someone with an autism spectrum disorder is ‘neurodiverse’) could also be applied more widely. Rather than distinguishing between the two types, we should see human diversity as represented by a spectrum, where ‘neurotypical’ covers a wide middle range, and other ‘disorders’, such as autism, dyslexia, and ADHD, similarly occupy a range along the spectrum.

Because this is the point, this is what research has been revealing over the past few years: there is no such ‘thing’ (as in a single thing) as autism, as dyslexia, as ADHD, as Alzheimer’s. They all have multiple variants — variable characteristics; variable causes. Because they reflect subtly different differences in the brain.

Which means we shouldn’t assume that because something has a label (“Alzheimer’s”), there is only one path (and relatedly, one set of dangerous factors). For example, we ‘know’ that high blood pressure is bad, and certainly it’s an important risk factor for cardio- and cerebro-vascular disorders (including Alzheimer’s). And yet, according to a recent study, this is not the complete story. For the very elderly (say, 85+), high blood pressure may be a sign of better health. This isn’t just because risk factors are worked out on the basis of group studies while you are an individual (there is always individual variation). It’s also because almost everything has trade-offs. Like the Huntington’s disease gene variant that improves learning. Like the neurodiverse who have exceptional visual skills.

Similarly, just because someone has put a label on you (“dyslexic”), you shouldn’t assume that means that everything you know about dyslexia applies to you. Nor should you assume that there are no positives about your particular brain.

In the same way, you shouldn’t assume that being a ‘genius’, or having a ‘photographic memory’, is all positive. Everything is a trade-off (don’t mistake me, I’m not suggesting that there is something positive about Alzheimer’s! but it may be that humans are vulnerable to Alzheimer’s because of our superior brains, and because we live so long).

The message is, don’t simply fall prey to a label. Think about it. If you or someone you care for has been labeled, focus on the individual manifestations, not the label. The label is a guide — treat it as one. But never forget that each manifestation will have its own particular characteristics, some of which may be positive.

And 'normal' is a label, too. Here's an issue that's only recently become realized in the cognitive research community: our idea of what is 'normal' is largely based on one cultural group. Most cognitive research has been undertaken on American undergraduate students (according to a recent analysis, 96% of research subjects in a sample of hundreds of psychology studies came from Western industrialized countries, and 68% came specifically from the U.S. — of these, 67% were psychology students). In recent years, it has become evident that WEIRD people (those from Western, Educated, Industrialized, Rich, and Democratic societies) respond significantly differently on a whole lot of domains compared to non-Western groups — even on something as seemingly basic as a visual illusion. (see Scientific American for a nice discussion of this)

As I said at the beginning, our preference for simple solutions and simple labels is rooted in our limited working memory capacity. The only real way around this is to build up your knowledge piece by piece, so that the items in working memory are merely the tips of richly elaborated items held in long-term memory. That isn't quick or easy, so there'll be many areas in which you don't want to gather such elaborated knowledge. In the absence of being able to stretch the limits of working memory, it helps to at least be aware of what is limiting your thinking.

In other words, as with memory itself, you need to think about your own goals and interests, and choose those that you want to pursue. Becoming expert (or at least, a little bit expert!) in some areas shows you how different your thinking is in those areas; you will then be able to properly appreciate the limitations in your thinking in other areas. That’s not a bad thing! As with memory failures of other kinds, it’s a big step just to be aware of your fallibilities. Better that than to be fooled (as some experts are) into thinking that their expert thinking in one area means that they think equally clearly in other areas.

We are all fallible. We all forget. We all have false memories and believe in them. We all sometimes fall victim to labels. The trick is to realize our fallibility, and choose the occasions and domains in which to overcome it.

References

Mottron, L. (2011). Changing perceptions: The power of autism. Nature. 479(7371), 33 - 3

Is multitasking really a modern-day evil?

In A Prehistory of Ordinary People, anthropologist Monica Smith argues that rather than deploring multitasking, we should celebrate it as the human ability that separates us from other animals.

Her thesis that we owe our success to our ability to juggle multiple competing demands and to pick up and put down the same project until completion certainly makes a good point. Yes, memory and imagination (our ability to project into the future) enable us to remember the tasks we’re in the middle of, and allow us to switch between tasks. And this is undeniably a good thing.

I agree (and I don’t think have ever denied) that multitasking is not in itself ‘bad’. I don’t think it’s new, either. These are, I would suggest, straw men — but I’m not decrying her raising them. Reports in the media are prone to talking about multitasking as if it is evil and novel, and a symptom of all that is wrong in modern life. It is right to challenge those assumptions.

The problem with multitasking is not that it is inherently evil. The point is to know when to stop.

There are two main dangers with multitasking, which we might term the acute and the chronic. The acute danger is when we multitask while doing something that has the potential to risk our own and others’ safety. Driving a vehicle is the obvious example, and I have reported on many studies over the past few years that demonstrate the relative dangers of different tasks (such as talking on a cellphone) while driving a car. Similarly, interruptions in hospitals increase the probability of clinical errors, some of which can have dire consequences. And of course on a daily level, acute problems can arise when we fail to do one task adequately because we are trying to do other tasks at the same time.

A chronic danger of multitasking that has produced endless articles in recent years is the suggestion that all this technology-driven multitasking is making us incapable of deep thought or focused attention.

But Smith argues that we do not, in fact, engage in levels of multitasking that are that much different from those exhibited in prehistoric times. ‘That much’ is of course the get-out phrase. How much difference is too much? Is there a point at which multitasking is too much, and have we reached it?

These are the real questions, and I don’t think the answer is something we can draw a line with. Research with driver-multitasking has revealed significant differences between drivers, as a function of age, as a function of personal attributes, as a function of emotional or physical state. It has revealed differences between tasks —e.g. talking that involves emotions or decisions is more distracting than less engaging conversation; half-overheard conversations are surprisingly distracting (suggesting that having a passenger in the car talking on a phone may be more distracting than doing it yourself!). These are the sort of things we need to know — not that multitasking is bad, but when it is bad.

This approach applies to the chronic problem also, although it is much more difficult to study. But these are some of the questions we need to know the answers to:

  • Does chronic multitasking affect our long-term ability to concentrate, or only our ability to concentrate while in the multitasking environment?
  • If it does affect our long-term ability to concentrate, can we reverse the effect? If so, how?
  • Is the effect on children and adolescents different from that of adults?
  • Does chronic multitasking produce beneficial cognitive effects? If so, is this of greater benefit for some people rather than others? (For example, multitasking training may benefit older adults)
  • What are the variables in multitasking that affect our cognition in these ways? (For example, the number of tasks being performed simultaneously; the length of time spent on each one before switching; the number of times switching occurs within a defined period; the complexity of the tasks; the ways in which these and other factors might interact with temporary personal variables, such as mood, fatigue, alcohol, and more durable personal variables such as age and personality)

We need to be thinking in terms of multitasking contexts rather than multitasking as one uniform (and negative) behavior. I would be interested to hear your views on multitasking contexts you find beneficial, pleasant or useful, and contexts you find difficult, unpleasant or damaging.

Retraining the brain

A fascinating article recently appeared in the Guardian, about a woman who found a way to overcome a very particular type of learning disability and has apparently helped a great many children since.

As a child, Barbara Arrowsmith-Young had a brilliant, almost photographic, memory for information she read or heard, but she had no understanding. She managed to progress through school and university through a great deal of very hard work, but she always knew (although it wasn’t recognized) that there was something very wrong with her brain. It wasn’t until she read a book (The Man with a Shattered World: The History of a Brain Wound - Amazon affiliate link) by the famous psychologist Luria that she realized what the problem was. Luria’s case study concerned a soldier who developed mental disabilities after being shot in the head. His disabilities were the same as hers: “he couldn't tell the time from a clock, he couldn't understand bigger and smaller without drawing pictures, he couldn't tell the difference between the sentences ‘The boy chases the dog’ and ‘The dog chases the boy’.”

On the basis of enriched-environment research, she started an intensive program to retrain her brain — 8-10 hours a day. She found it incredibly exhausting, but after 3-4 months, she suddenly ‘got it’. Something had shifted in her brain, and now she could understand verbal information in a way she hadn’t before.

The ‘Arrowsmith Program’ is now available in 35 schools in Canada and the US, and the children who attend them have often, she claims, been misdiagnosed with ADD or ADHD, dyslexia or dysgraphia. She has just published a book about her experience (The Woman Who Changed Her Brain: And Other Inspiring Stories of Pioneering Brain Transformation - Amazon affiliate link).

I can’t, I’m afraid, speak to the effectiveness of her program, because I can’t find any independent research in peer-reviewed journals (this is not to say it doesn’t exist), although there are reports on her own website. But I have no doubt that intensive training in specific skills can produce improvement in specific skills in those with learning disabilities.

There are two specific things that I found interesting. The first is the particular disability that Barbara Arrowsmith-Young suffered from — essentially, it seems, a dysfunction in integrating information.

This disjunct between ‘photographic memory’ and understanding is one I have spoken of before, but it bears repeating, because so many people think that a photographic memory is a desirable ambition, that any failure to remember exactly is a memory failure. But it’s not a failure; the system is operating exactly as it is meant to. Remembering every detail is counter-productive.

I was reminded of this recently when I read about something quite different: an “inexact” computer chip that’s 15 times more efficient, “challenging the industry’s 50-year pursuit of accuracy”. The design improves efficiency by allowing for occasional errors. One way it achieved this was by pruning some of the rarely used portions of digital circuits. Pruning is of course exactly what our brain does as it develops (infancy and childhood is a time of making huge numbers of connections; then as the brain matures, it starts viciously pruning), and to a lesser extent what it does every night as we sleep (only some of the day’s events and new information are consolidated; many more are discarded).

The moral is: forgetting isn’t bad in itself. Memory failure comes rather when we forget what we want or need to remember. Our brain has a number of rules and guidelines to help it work out what to forget and what to remember. But here’s the thing: we can’t expect an automatic system to get it right all the time. We need to provide some direct (conscious) management.

The second thing I was taken with was this list of ‘learning dysfunctions’. I believe this is a much more useful approach than category labels. Of course we like labels, but it has become increasingly obvious that many disorders are umbrella concepts. Those with dyslexia, for example, don’t all have the same dysfunctions, and accordingly, the appropriate treatment shouldn’t be the same. The same is true for ADHD and Alzheimer’s disease, to take two very different examples.

Many of those with dyslexia and ADHD have shown improvement as a result of specific skills training, but at the moment we’re still muddling around, not sure of the training needed (a side-note for those who are interested — Scientific American has a nice article on how ADHD behavioral therapy may be more effective than drugs in long run). So, because there are several different problems all being lumped into a single disorder, research finds it hard to predict who will benefit from what training.

But the day will come, I have no doubt, when we will be able to specify precisely what isn’t working properly in a brain, and match it with an appropriate program that will retrain the brain to compensate for whatever is damaged.

Or — to return to my point about choosing what to forget or remember — the individual (or parent) may choose not to attempt retraining. Not all differences are dysfunctional; some differences have value. When we can specify exactly what is happening in the brain, perhaps we will get a better handle on that too.

In the meantime, there is one important message, and it is, when it comes down to it, my core message, underlying all my books and articles: if you (or a loved one, or someone in your care) has any sort of learning or memory problem, whatever the cause, think very hard about the precise difficulties experienced. Then reflect on how important each one is. Then try and discover the specific skills needed to deal with those difficulties that matter. That will require not only finding suggested exercises to practice, but also some experimentation to find what works for you (because we haven’t yet got to the point where we can work this out, except by trial and error). And then, of course, you need to practice them. A lot.

I’m not saying that this is the answer to everyone’s problems. Sometimes the damage is too extensive, or in just the wrong place (there are hubs in the brain, and obviously damage to a hub is going to be more difficult to work around than damage elsewhere). But even if you can’t fully compensate for damage, there are few instances where specific skills training won’t improve performance.

Sharing what works is one way to help us develop the database needed. So if you have any memory or learning problems, and if you have experienced any improvement for whatever reason, tell us about it!

Individual differences

Humans have a long tradition of holding genes responsible for individual differences in behavior (of course, we called it "blood", then, or "family"). In the 20th century, a counter-belief arose: that it was all down to environment, to upbringing. In more recent decades, we have become increasingly aware of how tightly and complexly genes and environment are entwined.

It's not enough to say merely that environment tempers genes, or that genes affect how the environment works on an individual — genes and environment work on each other in an ongoing interaction, that continues throughout our lifetimes. This ongoing change even affects attributes most people deeply believe are, if not hard-wired in the womb, at least set in childhood: attributes such as intelligence, 'natural' talent, and gender differences.

Gender Differences

  • In general, males are better at spatial tasks involving mental rotation.
  • In general, females have superior verbal skills.
  • Males are far more likely to pursue math or science careers, but gender differences in math are not consistent across nations or ages.
  • A number of imaging studies have demonstrated that the brains of males and females show different patterns of activity on various tasks.
  • Nicotine has been shown to differentially alter men's and women's brain activity patterns so that the differences disappear.
  • Both estrogen and testosterone have been shown to affect cognitive function.
  • Training has been shown to bring parity to differences in cognitive performance between the sexes.
  • Age also alters the differences between men and women.

Widely cited gender differences in cognition

It is clear that there are differences between the genders in terms of cognitive function; it is much less clear that there are differences in terms of cognitive abilities. Let me explain what I mean by that.

It's commonly understood that males have superior spatial ability, while females have superior verbal ability. Males are better at math; females at reading. There is some truth in these generalizations, but it's certainly not as simple as it is portrayed.

First of all, as regards spatial cognition, while males typically outperform females on tasks dealing with mental rotation and spatial navigation, females tend to outperform males on tasks dealing with object location, relational object location memory, and spatial working memory.

While the two sexes score the same on broad measures of mathematical ability, girls tend to do better at arithmetic, while boys do better at spatial tests that involve mental rotation.

Having said that, it does depend where you're looking. The Programme for International Student Assessment (PISA) is an internationally standardised assessment that is given to 15-year-olds in schools. In 2003, 41 countries participated. Given the constancy of the gender difference in math performance observed in the U.S., it is interesting to note what happens in other countries. There was no significant difference between the sexes in Australia, Austria, Belgium, Japan, the Netherlands, Norway, Poland, Hong Kong, Indonesia, Latvia, Serbia, and Thailand. There was a clear male superiority for all 4 content areas in Canada, Denmark, Greece, Ireland, Korea, Luxembourg, New Zealand, Portugal, the Slovak Republic, Liechtenstein, Macao and Tunisia. In Austria, Belgium, the United States and Latvia, males outperformed females only on the space and shape scale; in Japan, the Netherlands and Norway only on the uncertainty scale. And in Iceland, females always consistently do better than males!

Noone knows why, but it is surely obvious that these differences must lie in cultural and educational factors.

Interestingly, the IEA Third International Mathematics and Science Study (TIMSS) shows this developing -- while significant gender differences in mathematics were found only in 3 of the 16 participating OECD countries for fourth-grade students, gender differences were found in 6 countries at the grade-eight level, and in 14 countries at the last year of upper secondary schooling.

This inconsistency is not, however, mirrored in verbal skills -- girls outperform boys in reading in all countries.

Gender differences in language have been consistently found, and hardly need reiteration. However, here's an interesting study: it found gender differences in the emerging connectivity of neural networks associated with skills needed for beginning reading in preschoolers. It seems that boys favor vocabulary sub-skills needed for comprehension while girls favor fluency and phonic sub-skills needed for the mechanics of reading.The study points to the different advantages each gender brings to learning to read.

There's a lesson there.

There are other less well-known differences between the sexes. Women tend to do better at recognizing faces. But a study has found that this superiority applies only to female faces. There was no difference between men and women in the recognition of male faces.

Moreover, pre-pubertal boys and girls have been found to be equally good at recognizing faces and identifying expressions. However, they do seem to do it in different ways. Boys showed significantly greater activity in the right hemisphere, while the girls' brains were more active in the left hemisphere. It is speculated that boys tend to process faces at a global level (right hemisphere), while girls process faces at a more local level (left hemisphere).

It's also long been recognized that women are better at remembering emotional memories. Interestingly, an imaging study has revealed that the sexes tend to encode emotional experiences in different parts of the brain. In women, it seems that evaluation of emotional experience and encoding of the memory is much more tightly integrated.

But of course, noone denies that there are differences between men and women. The big question (one of the big questions) is how much, if any, is innate.

Studies of differences, even at the neural level, don't demonstrate that. It's increasingly clear that environmental factors affect all manner of thing at the neural level. However, one study of 1-day-old infants did find that boys tended to gaze at three-dimensional mobiles longer than girls did, while girls looked at human faces longer than boys did.

Of course, even a 1-day-old infant isn't entirely free of environmental influence. In this case, the most important environmental influence is probably hormones.

Hormones and chemistry

A lot of studies in recent years have demonstrated that estrogen is an important player in women's cognition. Spatial ability in particular seems vulnerable to hormonal effects. Women do vary in their spatial abilities according to where they are in the menstrual cycle, and there is some evidence that spatial abilities (in both males and females) may be affected by how much testosterone is received in the womb.

Another study has found children exposed to higher levels of testosterone in the womb also develop language later and have smaller vocabularies at 2 years of age.

Hormones aren't the only chemical affecting male and female brains differently. Significant differences have been found in the brain activity of men and women when engaged in a broad range of activities and behaviors. These differences are more acute during impulsive or hostile acts. But — here's the truly fascinating thing — nicotine causes these brain activity differences to disappear. A study has found that among both smokers and non-smokers on nicotine, during aggressive moments, there are virtually no differences in brain activity between the sexes. A finding that supports other studies that indicate men's and women's brains respond differently to the same stimuli — for example, alcohol.

What does all this mean? Well, let's look at the question that's behind the whole issue: are men smarter than women? (or alternately, are women smarter than men?)

Is one sex smarter than the other?

Here's a few interesting studies that demonstrate some more differences between male and female brains.

A study of some 600 Dutch men and women aged 85 years found that the women tended to have better cognitive speed and a better memory than the men, despite the fact that significantly more of the women had limited formal education compared to the men. This may be due to better health. On the other hand, there do appear to be differences in the way male and female brains develop, and the way they decline.

For example, women have up to 15% more brain cell density in the frontal lobe, which controls so-called higher mental processes, such as judgement, personality, planning and working memory. However, as they get older, women appear to shed cells more rapidly from this area than men. By old age, the density is similar for both sexes.

A study of male and female students (aged 18-25) has found that men's brain cells can transmit nerve impulses 4% faster than women's, probably due to the faster increase of white matter in the male brain during adolescence.

An imaging study of 48 men and women between 18 and 84 years old found that, compared with women, men had more than six times the amount of intelligence-related gray matter. On the other hand, women had about nine times more white matter involved in intelligence than men did. Women also had a large proportion of their IQ-related brain matter (86% of white and 84% of gray) concentrated in the frontal lobes, while men had 90% of their IQ-related gray matter distributed equally between the frontal lobes and the parietal lobes, and 82% of their IQ-related white matter in the temporal lobes. Despite these differences, men and women performed equally on the IQ tests.

It has, of course, long been suggested that women are intellectually inferior because their brains are smaller. A study involving the intelligence testing of 100 neurologically normal, terminally ill volunteers found that a bigger brain size is indeed correlated with higher intelligence — but only in certain areas, and with odd differences between women and men. Verbal intelligence was clearly correlated with brain size for women and — get this — right-handed men! But not for left-handed men. Spatial intelligence was also correlated with brain size in women, but much less strongly, while it was not related at all to brain size in men.

Also, brain size decreased with age in men over the age span of 25 to 80 years, suggesting that the well-documented decline in visuospatial intelligence with age is related, at least in right-handed men, to the decrease in cerebral volume with age. However age hardly affected brain size in women.

What is all this telling us?

Male and female brains are different: they develop differently; they do things differently; they respond to different stimuli in different ways.

None of this speaks to how well information is processed.

None of these differences mean that individual brains, of either sex, can't be trained to perform well in specific areas.

Here’s an experiment and a case study which bear on this.

It's all about training

The experiment concerns rhesus monkeys. The superiority of males in spatial memory that we're familiar with among humans also occurs in this population. But here's the interesting thing — the gender gap only occurred between young adult males and young untrained females. In other words, there was no difference between older adults (because performance deteriorated with age more sharply for males), and did not occur between male and female younger adults if they were given simple training. Apparently the training had little effect on the males, but the females improved dramatically.

The “case study” concerns Susan Polgar, a chess master. The Polgar sisters are a well-known example of “hot-housing”. I cited them in my article on the question of whether there is in fact such a thing as innate talent. Susan Polgar and her sisters are examples of how you can train “talent”; indeed, whether there is in fact such a thing as “talent” is a debatable question. Certainly you can argue for a predisposition towards certain activities, but after that … Well, even geniuses have to work at it, and while you may not be able to make a genius, you can certainly create experts.

This article was provoked, by the way, by comments by the President of Harvard University, Lawrence Summers, who recently stirred the pot by giving a speech arguing that boys outperform girls on high school science and math scores because of genetic differences between the genders, and that discrimination is no longer a career barrier for female academics. Apparently, during Dr Summers' presidency, the number of tenured jobs offered to women has fallen from 36% to 13%. Last year, only four of 32 tenured job openings were offered to women.

You can read a little more about what Dr Summers said at http://education.guardian.co.uk/gendergap/story/0,7348,1393079,00.html, and there's a rather good response by Simon Baron-Cohen (professor in the departments of psychology and psychiatry, Cambridge University, and author of The Essential Difference) at: http://education.guardian.co.uk/higher/research/story/0,9865,1399109,00.html

References
  • Canli, T., Desmond, J.E., Zhao, Z. & Gabrieli, J.D.E. 2002. Sex differences in the neural basis of emotional memories. Proceedings of the National Academy of Sciences, 99, 10789-10794.
  • Everhart, D.E., Shucard, J.L., Quatrin, T. & Shucard, D.W. 2001. Sex-related differences in event-related potentials, face recognition, and facial affect processing in prepubertal children. Neuropsychology, 15(3), 329-341.
  • Fallon, J.H., Keator, D.B., Mbogori, J., Taylor, D. & Potkin, S.G. 2005. Gender: a major determinant of brain response to nicotine. The International Journal of Neuropsychopharmacology, 8(1), 17-26. (see https://www.eurekalert.org/news-releases/524916)
  • Geary, D.C. 1998. Male, Female: The Evolution of Human Sex Differences. Washington, D.C.: American Psychological Association.
  • Haier, R.J., Jung, R.E., Yeo, R.A., Head, K. & Alkire, M.T. 2005. The neuroanatomy of general intelligence: sex matters. NeuroImage, 25(1), 320-327.
  • Hanlon, H. 2001. Gender Differences Observed in Preschoolers’ Emerging Neural Networks. Paper presented at Genomes and Hormones: An Integrative Approach to Gender Differences in Physiology, an American Physiological Society (APS) conference held October 17-20 in Pittsburgh.
  • Kempel, P.. Gohlke, B., Klempau, J., Zinsberger, P., Reuter, M. & Hennig, J. 2005. Second-to-fourth digit length, testosterone and spatial ability. Intelligence, 33(3), 215-230.
  • Lacreuse, A., Kim, C.B., Rosene, D.L., Killiany, R.J., Moss, M.B., Moore, T.L., Chennareddi, L. & Herndon, J.G. 2005. Sex, age, and training modulate spatial memory in the Rhesus monkey (Macaca mulatta). Behavioral Neuroscience, 119 (1).
  • Levin, S.L., Mohamed, F.B. & Platek, S.M. 2005. Common ground for spatial cognition? A behavioral and fMRI study of sex differences in mental rotation and spatial working memory. Evolutionary Psychology, 3, 227-254.
  • Lewin, C. & Herlitz, A. 2002. Sex differences in face recognition-Women's faces make the difference, Brain and Cognition, 50 (1), 121-128.
  • OECD. Learning for Tomorrow's World –First Results from PISA 2003 https://www.oecd.org/newsroom/top-performerfinlandimprovesfurtherinpisa…
  • Reed, T.E., Vernon, P.A. & Johnson, A.M. 2005. Confirmation of correlation between brain nerve conduction velocity and intelligence level in normal adults. Intelligence, 32(6), 563-572.
  • van Exel, E., Gussekloo, J., de Craen, A.J.M, Bootsma-van der Wiel, A., Houx, P., Knook, D.L. & Westendorp, R.G.J. 2001. Cognitive function in the oldest old: women perform better than men. Journal of Neurology, Neurosurgery & Psychiatry, 71, 29-32.
  • Witelson, S.F., Beresh, H. & Kigar, D.L. 2006. Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. Brain, 129, 386-398.
  • Witelson, S.F., Kigar, D.L. & Stoner-Beresh, H.J. 2001. Sex difference in the numerical density of neurons in the pyramidal layers of human prefrontal cortex: a stereologic study. Paper presented to the annual Society for Neuroscience meeting in San Diego, US.

For more on this, see the research reports

The question of innate talent

Some personal experience

I have two sons. One of them was a colicky baby. Night after night my partner would carry him around the room while I tried to get a little sleep. One night, for his own amusement, my partner chose a particular CD to play. Magic! As the haunting notes of the hymns of the 12th century abbess Hildegard of Bingen rang through the room, the baby stopped crying. And stayed stopped. As long as the music played. Experimentation revealed that our son particularly liked very early music (plainchant from the 15th century Josquin des Pres was another favorite).

We felt sorry for all those parents with crying babies who hadn't discovered this magic cure-all.

And then we had another son.

This one didn't like music. No magic this time. And we realized, it wasn't that 12th century music had magical properties to calm a crying baby. No, it was this particular baby that responded to this sort of music.

The years went on. Nothing we saw contradicted that first impression - one son was "musical", and one was not. It seemed pretty clear to us. One son took after me, and one took after my partner.

My partner plays the piano, and the pipe organ, and the harpsichord. He is "into" Bach. He has played in churches and concerts. He has a shelf full of books on music and cupboards full of music scores, CDs by the score.

Me? I like to sing, to myself. I learned the violin for a while in my youth. I like to listen to CDs of jazz, and popular show tunes. I like music, but I'm not sophisticated about it. It's background to me. My partner actually listens to it.

So which child took after which parent?

Well, we believe the "musical" one took after me, and the "non-musical" one took after my partner. Because - he got there by training. By practicing and learning and persevering and taking an interest. He has no sense of rhythm, no particularly keen sense of pitch. But he's the one who can produce music. Me, I have an ear for music. Remembering a rhythm is effortless for me; I respond, instinctively, to music. But I could never bother to practice, and my response to music has stayed at the same level. Instinctive.

Our "musical" son has been involved in learning music the Suzuki way since he was four. We never particularly encouraged our other son to do likewise, simply told him he could if he wanted to. His brother persuaded him he did want to. So, fine, we said.

You can guess, I'm sure, how things have been. It's been obvious, watching and listening to our older son, that he has a talent for music, that it comes easily to him. Equally obvious that it hasn't come that easily to our younger son. But it's the younger son who has made much faster progress in the past year, because he practices more, because he's keen to learn. And it's been amazing to watch his ear for music develop.

Do you need an inborn talent to do well?

Suzuki flew in the face of "common-sense" when he decided very young children with no demonstrable genius could be taught to play the violin. I can only imagine the stunned amazement with which the first Suzuki concerts were greeted. They still amaze today.

Suzuki himself, while he supported the training of all children, believed that, of course, some would be "naturally" gifted, and that outstanding performance would require a gift, as well as training. However, as his experience with children and his method increased, he grew to believe that “every child can be highly educated if he is given the proper training” and blamed early training failures on incorrect methods.

Howard Gardner (inventor of the Multiple Intelligences theory) reviewed the exceptional music performance attained by children trained in the Suzuki method, and noted many of these children, who displayed no previous signs of musical talent, attained levels comparable to music prodigies of earlier times. Therefore, he concluded, the important aspect of talent must be the potential for achievement and the capacity to rapidly learn material relevant to one of the intelligences. That is, since we didn't see the talent before we started training, and since the fact that they do perform so well demonstrates that they must have talent, then the talent must have existed in potential.

This is, of course, a wholly circular argument.

And one that is widely believed. According to an informal British survey, more than ¾ of music educators believe children can’t do well unless they have special innate gifts10. It is believed that saying that someone has a “gift” for something explains why they have excelled at something - although it is an entirely circular argument: Why do they do well? Because they have a gift. How do you know they have a gift? Because they do well.

It is also widely believed that such innate talents can be detected in early childhood.

The problem with this view is that many children are denied the opportunities and support to achieve excellence, because it has been decreed that they don’t “have” an appropriate talent.

The circular argument becomes truly a vicious circle. You don't do this easily first time, therefore you don't have any talent, therefore it's not worth pushing you to do well, therefore you won't do well - which proves what we told you in the first place, you have no talent!

So how much justification is there for believing excellence requires a "natural" talent?

Is there such a thing as inborn talent?

A questionnaire study found that early interest and delight in musical sounds fails to predict later musical competence25.

We have all heard stories of child prodigies who supposedly could do amazing things from a very young age. In no case however, is this very early explosion of skills (in the first three years) observed directly by an impartial observer – the accounts all being (naturally enough you might think), retrospective and anecdotal. Noone denies that very young children, from 3 years old, have been observed to have remarkable skills for their age, but although the parents typically say the child learned these skills entirely unaided, this is not supported by the evidence. For example, in a typical case, the parents claimed (and no doubt sincerely believed) that their child learned to read entirely unaided and that they only discovered this on seeing her reading Heidi. However they had kept detailed records of her accomplishments. As Fowler19 pointed out, it is difficult to believe that parents who keep such accounts have not been actively involved in the child’s early learning.

Music is an area where infant prodigies abound – many famous composers are reported to have displayed unusual musical ability at a very young age. Again, however, such accounts are reported many years later (after the composer has become famous). Early biographies of prominent composers reveal they all received intensive and regular supervised practice sessions29. “The emergence of unusual skills typically followed rather than preceded a period during which unusual opportunities were provided, often combined with a strong expectation that the child would do well."

Art is another area where infant "geniuses" are occasionally cited. However, although some 2 and 3 year olds have produced drawings considerably more realistic than is the norm45, among major artists, few are known to have produced drawings that display exceptional promise before age 8 or so44.

There is no doubt that some individuals acquire some skills more easily than others, but this doesn’t necessarily have anything to do with 'talent'. Motivational and personality factors, as well as previous learning experiences, can all affect such facility.

Biological factors that might underlie "talent"

There are various underlying factors that are at least partly genetic and no doubt influence ability – for example response speed2 and working memory capacity8,9 - but there is no clear neural correlate for any specific exceptional skill.

The closest such correlate is that of "perfect" pitch. There does appear to be a structural difference in the brain of those who have absolute pitch, and certainly some young children have been shown to have perfect pitch. However, even if this difference in the brain is innate and not, as it could well be, the result of differences in learning or experience, having perfect pitch is no guarantee that you will excel at music. Moreover, it appears that it can be learned. It’s relatively common in musicians given extensive musical training before five or six12, and even appears to be learnable by adults, although with considerably more difficulty3,42.

It is always difficult to demonstrate that an observed neurological or physical difference is innate rather than the product of training or experience. For example, many people have pointed to particular physical features as being the reason for particular sports people to excel at their particular sport. However, while individual differences in the composition of certain muscles are reliable predictors of differences in athletic performance, the differences in the proportion of the slow-twitch muscle fibers that are essential for success in long-distance running, for example, are largely the result of extended practice, rather than the cause of differential ability11. Differences between athletes and others in the proportions of particular kinds of muscle fibers are specific to those muscles that are most fully exercised in the athletes’ training22.

There is little evidence, too, for the idea that exceptional athletes are born with superior motor and perceptual abilities. Tests for basic motor and perceptual abilities fail to predict performance15. Exceptional sportspeople do not reliably score higher than lesser mortals on such basic tests.

Savants

So-called idiot-savants are widely cited in support of the idea of innate talent. However, studies of cases have found the opportunities, support and encouragement for learning the skill have preceded performance by years or even decades12,23,43. Moreover, their skills are learnable by others.

The only ability that can’t be reproduced after brief training is the reputed ability to reproduce a piece of music after a single hearing. However, in a study of one such savant5 it was shown that such reproduction depended on the familiarity of the sequences of notes. Tonally unconventional pieces were remembered poorly. Thus, musical savants, like normal experts, need access to stored patterns and retrieval structures to enable them to retain long, unfamiliar musical patterns.

Predicting adult performance

Several interview and biographical studies of exceptional people have been carried out (e.g., pianists40,41; musicians31; tennis players35; artists37; swimmers26; mathematicians20). In no case could you have predicted their eventual success from their early childhood behavior; few showed signs of exceptional promise prior to receiving parental encouragement.

Composers21, chess players36, mathematicians20, sportspeople26,32 have all been shown to require many years of sustained practice and training to reach high levels of expertise.

Twin studies

Twin studies support the view that family experience is more important than genes for the development of specific abilities (e.g., The Minnesota Study of Twins Reared Apart found self-ratings of musical talent correlated .44 among identical twins reared apart, compared to .69 for identical twins reared together30; correlations on a number of measures of musical ability were not much lower for fraternal twins (.34 to .83) than for identical twins (.44 to .9)7.

Moreover, the importance of inherited factors reduces as training and practice increases1,28,15.

Practice and performance level

The performance level of student violinists in their 20s is strongly correlated with the number of hours that they practiced13,14. Similarly with pianists27. No significant differences have been found between highly successful young musicians and other children in the amount of practice time they required to make a given amount of progress between successive grades in the British musical board exams; achieving the highest level (grade 8) required an average of some 3300 hours of practice regardless of the ability group to which the student had been assigned39. Another study found that by age 20, the top-level violinists had practiced an average of more than 10000 hrs, some 2500 hrs more than the next most accomplished group15.

Practice accounts for far more than most of us might realize. Several studies have demonstrated the high levels of performance (often higher than experts had regarded as possible) that can be attained by perfectly ordinary adults, given enough practice4,6,12.

It has been argued that talent encourages children to practice more, but this is contradicted by the finding that, even among highly successful young musicians, most admit they would never have regularly practiced at the required level without strong parental encouragement38,24.

The top of the cream?

It may well be, of course, that there is a quality to the exceptionally talented person’s performance that is missing from others, however hard they have practiced.

It is also possible that, although practice, training, and other influences may account for performance differences in most people, there is a small number of people to whom this doesn’t apply.

However, there is at this time no evidence that this is true.

What is clear is that “no case has been encountered of anyone reaching the highest levels of achievement in chess-playing, mathematics, music, or sports without devoting thousands of hours to serious training” (Howe et al 1999).

The pattern of learning seems to be the same for everyone, arguing against some qualitative difference between "geniuses" and ordinary folk. Studies of prodigies in chess and music show that the skills are acquired in the same manner by everyone, but that prodigies reach higher levels faster and younger16,17. Moreover, rather than acquiring their skills in a vacuum, it appears that “the more powerful and specific the gift, the more need for active, sustained and specialized intervention” (Feldman, 1986, p123).

The producing of an outstanding talent indeed, seems to require a great deal of parental support and early intervention.

It is particularly instructive to observe the case of the Polgar daughters. With no precocious love for the chess board observable in their three daughters, Laslo & Klara Polgar, simply as an educational experiment, decided to raise their daughters to be chess experts. All did extraordinarily well, and one became the youngest international chess grand master ever18.

It has been noted that the performance of experts of yesteryear is now attainable by many. When Tchaikovsky asked two of the greatest violinists of the day to play his violin concerto, it is said, they refused, deeming it unplayable33 - now it is standard repertoire for top violinists. Paganini, it is claimed, would cut a sorry figure on a concert stage today34. Such is the standard we have come to expect from our top performers.

And we are all familiar with the way sports records keep being broken – the winning time for the 1st Olympic marathon is now the qualifying time for the Boston marathon.

Are we suddenly breeding more talent?

No. But training has improved immeasurably.

Practicing effectively

It is not, then, simply practice that is important. It is the right practice. Ericsson & Charness distinguish between deliberate practice – which involves specifically tailored instruction and training, with feedback, and supervision - and the sort of playful repetition more characteristic of people who enjoy an activity and do it a lot. Most people reach an acceptable level of performance, and then are satisfied. The "talented" ... keep on.

References
  1. Ericsson, K.A. & Charness, N. Expert performance: Its structure and acquisition. In S.J. Ceci & Wendy M. Williams (eds) The nature-nurture debate: The essential readings. Essential Readings in Developmental Psychology. Oxford: Blackwell. Pp200-255.
  2. Howe, M.J.A., Davidson, J.W. & Sloboda, J.A. 1999. Innate talents: Reality of myth? In S.J. Ceci & Wendy M. Williams (eds) The nature-nurture debate: The essential readings. Essential Readings in Developmental Psychology. Oxford: Blackwell. Pp168-175.

Footnoted references

  1. Ackerman, P.L. 1988. Determinants of individual differences during skill acquisition: cognitive abilities and information processing. Journal of Experimental Psychology: General, 117, 299-318.
  2. Bouchard, T.J., Lykken, D.T., McGue, M., Segal, N.L. & Tellegen, A. 1990. Sources of human psychological differences: the Minnesota Study of Twins Reared Apart. Science, 250, 223-8.
  3. Brady, P.T. 1970. The genesis of absolute pitch. Journal of the Acoustical Society of America, 48, 883-7.
  4. Ceci, S.J., Baker, J.G. & Bronfenbrenner, U. 1988. Prospective remembering, temporal calibration, and context. In M. Gruneberg, P. Morris, & R. Sykes (eds). Practical aspects of memory: Current research and issues. Wiley.
  5. Charness N Clifton J & MacDonald L. 1988. Case study of a musical mono-savant. IN LK Obler & DA Fein (eds) The exceptional brain: Neuropsychology of talent and special abilities (pp277-93). NY: Guilford Press.
  6. Chase, W.G. & Ericsson, K.A. 1981. Skilled memory. In J.R. Anderson (ed). Cognitive skills and their acquisition. Erlbaum.
  7. Coon, H. & Carey, G. 1989. Genetic and environmental determinants of musical ability in twins. Behavior Genetics, 19, 183-93.
  8. Dark, V.J. & Benbow, C.P. 1990. Enhanced problem translation and short-term memory: components of mathematical talent. Journal of Educational Psychology, 82, 420-9.
  9. Dark, V.J. & Benbow, C.P. 1991. The differential enhancement of working memory with mathematical versus verbal precocity. Journal of Educational Psychology, 83, 48-60.
  10. Davis, M. 1994. Folk music psychology. Psychologist, 7, 537.
  11. Ericsson, K.A. 1990. Peak performance and age: an examination of peak performance in sports. In P.B. Baltes & & M.M. Baltes (eds). Successful aging: Perspectives from the Behavioral Sciences. Cambridge University Press.
  12. Ericsson, K.A. & Faivre, I.A. 1988. What's exceptional about exceptional abilities? In K. Obler & D. Fein (eds). The exceptional brain. Guilford Press.
  13. Ericsson, K.A., Tesch-Romer, C. & Krampe, R. Th. 1990. The role of practice and motivation in the acquisition of expert-level performance in real life. In M.J.A. Howe (ed). Encouraging the development of exceptional abilities and talents. British Psychological Society.
  14. Ericsson, K.A., Krampe, R.Th. & Heizmann, S. 1993. Can we create gifted people? In G.R. Bock & K. Ackrill (eds). The origins and development of high ability. CIBA Foundation Symposium, 178. Wiley.
  15. Ericsson, K.A., Krampe, R.Th. & Tesch-Romer, C. 1993. The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406.
  16. Feldman, D.H. 1980. Beyond universals in cognitive development. Norwood, NJ: Ablex.
  17. Feldman, D.H. 1986. Nature's gambit: Child prodigies and the development of human potential. NY: Basic Books.
  18. Forbes, C. 1992. The Polgar sisters: Training or genius? NY: Henry Holt.
  19. Fowler, W. 1981. Case studies of cognitive precocity: the role of exogenous and endogenous stimulation in early mental development. Journal of Applied Developmental Psychology, 2, 319-67.
  20. Gustin, W.C. 1985. The development of exceptional research mathematicians. In B.S. Bloom (ed). Developing talent in young people. Ballantine.
  21. Hayes, J.R. 1981. The complete problem solver. Franklin Institute Press.
  22. Howald, H. 1982. Training-induced morphological and functional changes in skeletal muscle. International Journal of Sports Medicine, 3, 1-12.
  23. Howe, M.J.A. 1990. The origins of exceptional abilities. Oxford, UK: Blackwell.
  24. Howe, M.J.A. & Sloboda, J.A. 1991. Young musicians' accounts of significant influences in their early lives: 2. Teachers, practising and performing. British Journal of Music Education, 8, 53-63.
  25. Howe, M.J.A., Davidson, J.W., Moore, D.G. & Sloboda, J.A. 1995. Are there early childhood signs of musical ability? Psychology of Music, 23, 162-76.
  26. Kalinowski, A.G. 1985. The development of Olympic swimmers. In B.S. Bloom (ed). Developing talent in young people. Ballantine.
  27. Krampe, R.Th. 1994. Maintaining excellence: cognitive-motor performance in pianists differing in age and skill level. Max-Planck-Institut fur Bildungsforschung.
  28. Krampe, R.Th. & Ericsson, K.A. 1996. Maintaining excellence: cognitive-motor performance in pianists differing in age and skill level. Journal of Experimental Psychology: General, 125, 331-68.
  29. Lehmann, A.C. 1997. The acquisition of expertise in music: efficiency of deliberate practice as a moderating variable in accounting for sub-expert performance. In J.A. Sloboda & I. Deliege (eds). Perception and cognition of music. Erlbaum.
  30. Lykken, D. 1998. The genetics of genius. In A. Steptoe (ed). Genius and the mind. Oxford University Press.
  31. Manturzewska, M. 1986. Musical talent in the light of biographical research. In Musikalische Begabung Finden und Forden, Bosse.
  32. Monsaas, J. 1985. Learning to be a world-class tennis player. In B.S. Bloom (ed). Developing talent in young people. Ballantine.
  33. Platt, R. 1966. General introduction. In J.E. Meade & A.S. Parkes (eds). Genetic and environmental factors in human ability. Edinburgh: Oliver & Boyd.
  34. Roth H 1982 . Master violinists in performance. Neptune City, NJ: Paganinia
  35. Schneider, W. 1993. Acquiring expertise: determinants of exceptional performance. In K.A. Heller, F.J. Monks & A.H. Passow (eds). International Handbook of Research and Development of Giftedness and Talent. Pergamon.
  36. Simon, H.A. & Chase, W.D. 1973. Skill in chess. American Scientist, 61, 394-403.
  37. Sloan, K.D. & Sosniak, L.A. 1985. The development of accomplished sculptors. In B.S. Bloom (ed). Developing talent in young people. Ballantine.
  38. Sloboda, J.A. & Howe, M.J.A. 1991. Biographical precursors of musical excellence: an interview study. Psychology of Music, 19, 3-21.
  39. Sloboda, J.A., Davidson, J.W., Howe, M.J.A. & Moore, D.G. 1996. The role of practice in the development of performing musicians. British Journal of Psychology, 87, 287-309.
  40. Sosniak, L.A. 1985. Learning to be a concert pianist. In B.S. Bloom (ed). Developing talent in young people. Ballantine.
  41. Sosniak, L.A. 1990. The tortoise, the hare, and the development of talent. In M.J.A. Howe (ed). Encouraging the development of exceptional abilities and talents. British Psychological Society.
  42. Takeuchi, A.H. & Hulse, S.H. 1993. Absolute pitch. Psychological Bulletin, 113, 345-61.
  43. Treffert DA 1989 Extraordinary people: Understanding “Idiot Savants”. NY: Harper & Row.
  44. Winner, E. & Martino, G. 1993. Giftedness in the visual arts and music. In K.A. Heller, F.J. Monks & A.H. Passow (eds). International Handbook of Research and Development of Giftedness and Talent. Pergamon.
  45. Winner, E. 1996. The rage to master: the decisive role of talent in the visual arts. In K.A. Ericsson (ed). The road to excellence: The acquisition of expert performance in the arts and sciences. Erlbaum.

Right-Brain/Left-Brain

Are you right-brained or left-brained?

One of the dumber questions around.

I think it’s safe to say that if you only had one hemisphere of your brain, you wouldn’t be functioning.

Of course, that’s not the point. But the real point is little more sensible. The whole idea of right brain vs left brain did come out of scientific research, but as is so often the case, the myth that developed is light years away from the considerably duller scientific truths that spawned it.

It is true that, for most of us, language is processed predominantly in the left hemisphere. But what is becoming increasingly more evident is that even the most specialized tasks activate areas across the brain.

In any case, I don’t think the real meaning behind this simplistic dichotomy of right-brain / left-brain has much to do with the physical nature of the brain. People hope by rooting the concept in something that is physically real, that they will thereby make the concept real. Well, I’m sorry, but the supposed scientific foundation for the concept doesn’t exist. However, what we can ask is, is the concept valid? Are some people logical, analytical, sequential thinkers? Are others holistic, intuitive, creative thinkers?

Yes, of course. This is news?

But I don’t like dichotomies. It should never be forgotten that people aren’t either/or. Attributes invariably belong on a continuum, and we are all capable of responding in ways that differ as a function of the task we are confronted with, and the context in which it appears (especially, for example, the way something is phrased). Rather than saying a person is an analytical thinker, we should say, does a person tend to approach most problems in an analytical manner? This is not simply a matter of semantics; there’s an important distinction here.

But there are other personal attributes of importance in learning and problem-solving. For example, working memory capacity, imagery ability, anxiety level, extraversion / introversion, self-esteem (in this case, meaning assessment of one’s own abilities), field-dependence / field-independence (field dependence represents the tendency to perceive and adhere to an existing, externally imposed framework while field independence represents the tendency to restructure perceived information into a different framework). Which attributes are most important? Is this in fact a meaningful question?

The fact is, different personal attributes interact with different task and situational variables in different ways. While it’s probably always good to have a high working memory capacity (the capacity to hold more items in conscious memory at one time), it’s more important in some situations than others. To be a “high-imagery” person may sound a good thing, but if you realize it’s measured on a verbal-imagery continuum, you can see that it’s a trade-off. Personally, I’ve never found being high-verbal, low-imagery a drawback!

The point is, of course, that different styles lend themselves to different tasks (by which I mean, different ways of doing different tasks). It’s not so much what you are, as that you recognize what your strengths and weaknesses are, and realize, too, the pluses and minuses of those abilities / conditions.

For example, a study of 13-year olds investigated the question of interaction between working memory capacity and cognitive style, measured on two dimensions, Wholist-Analytic, and Verbaliser - Imager. They found working memory capacity made a marked difference for Analytics but had little effect for Wholists, and similarly, Verbalisers were affected but not Imagers [1].

Thus, if your working memory capacity is low, in demanding tasks you might find yourself better to approach it holistically – looking at the big picture, rather than focusing on the details.

Once you recognize your strengths and weaknesses, you can consciously apply strategies that work for you, and approach tasks in ways that are better for you. You can also work on your weaknesses. An interesting recent study that I believe has wider applicability than the elderly population who participated in it, found elderly people who draw on both sides of the brain seem to do better at some mental tasks than those who use just one side [2].

Web resources

Cognitive style

There’s an article about cognitive style from a business perspective:
http://www.elsinnet.org.uk/abstracts/aom/sad-aom.htm

If you’re really interested in cognitive style, the Wholist-Analytic, Verbal-Imager inventory was constructed by R.J. Riding, and he’s written a, fairly scholarly, book, entitled “Cognitive Styles and Learning Strategies: Understanding Style Differences in Learning and Behaviour”
http://tinyurl.com/6gpu8

Left-brain / Right-brain

You can also read an essay by William H. Calvin, an affiliate professor at the University of Washington School of Medicine in Seattle, Washington: Left Brain, Right Brain: Science or the New Phrenology?
http://williamcalvin.com/bk2/bk2ch10.htm

And an article first published in the New Scientist on 'Right Brain' or 'Left Brain' - Myth Or Reality? by John McCrone.
http://www.rense.com/general2/rb.htm

This article originally appeared in the January 2005 newsletter.

References
  1. Riding. R.J., Grimley, M., Dahraei, H. & Banner, G. 2003. Cognitive style, working memory and learning behaviour and attainment in school subjects. British Journal of Educational Psychology, 73 (2), 149–169.
  2. Cabeza, R., Anderson, N.D., Locantore, J.K. & McIntosh, A.R. 2002. Aging Gracefully: Compensatory Brain Activity in High-Performing Older Adults. NeuroImage, 17(3), 1394-1402.