intelligence

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?

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

Humans are the animals that manipulate their cognitive environment.

I reported recently on an intriguing study involving an African people, the Himba. The study found that the Himba, while displaying an admirable amount of focus (in a visual perception task) if they were living a traditional life, showed the same, more de-focused, distractible attention, once they moved to town. On the other hand, digit span (a measure of working memory capacity) was smaller in the traditional Himba than it was in the urbanized Himba.

This is fascinating, because working memory capacity has proved remarkably resistant to training. Yes, we can improve performance on specific tasks, but it has proven more difficult to improve the general, more fundamental, working memory capacity.

However, there have been two areas where more success has been found. One is the area of ADHD, where training has appeared to be more successful. The other is an area no one thinks of in this connection, because no one thinks of it in terms of training, but rather in terms of development — the increase in WMC with age. So, for example, average WMC increases from 4 chunks at age 4, to 5 at age 7, 6 at age 10, to 7 at age 16. It starts to decrease again in old age. (Readers familiar with my work will note that these numbers are higher than the numbers we now tend to quote for WMC — these numbers reflect the ‘magic number 7’, i.e. the number of chunks we can hold when we are given the opportunity to actively maintain them.)

Relatedly, there is the Flynn effect. The Flynn effect is ostensibly about IQ (specifically, the rise in average IQ over time), but IQ has a large WM component. Having said that, when you break IQ tests into their sub-components and look at their change over time, you find that the Digit Span subtest is one component that has made almost no gain since 1972.

But of course 1972 is still very modern! There is no doubt that there are severe constraints on how much WMC can increase, so it’s reasonable to assume we long since hit the ceiling (speaking of urbanized Western society as a group, not individuals).

It’s also reasonable to assume that WMC is affected by purely physiological factors involving connectivity, processing speed and white matter integrity — hence at least some of the age effect. But does it account for all of it?

What the Himba study suggests (and I do acknowledge that we need more and extended studies before taking these results as gospel), is that urbanization provides an environment that encourages us to use our working memory to its capacity. Urbanization provides a cognitively challenging environment. Our focus is diffused for that same reason — new information is the norm, rather than the exception; we cannot focus on one bit unless it is of such threat or interest that it justifies the risk.

ADHD shows us, perhaps, what can happen when this process is taken to the extreme. So we might take these three groups (traditional Himba, urbanized Himba, individuals with ADHD) as points on the same continuum. The continuum reflects degree of focus, and the groups reflect environmental effects. This is not to say that there are not physiological factors predisposing some individuals to react in such a way to the environment! But the putative effects of training on ADHD individuals points, surely, to the influence of the environment.

Age provides an intriguing paradox, because as we get older, two things tend to happen: we have a much wider knowledge base, meaning that less information is new, and we usually shrink our environment, meaning again that less information is new. All things being equal, you would think that would mean our focus could afford to draw in. However, as my attentive readers will know, declining cognitive capacity in old age is marked by increasing difficulties in ignoring distraction. In other words, it’s the urbanization effect writ larger.

How to account for this paradox?

Perhaps it simply reflects the fact that the modern environment is so cognitively demanding that these factors aren’t sufficient on their own to enable us to relax our alertness and tighten our focus, in the face of the slowdown in processing speed that typically occurs with age (there’s some evidence that it is this slowdown that makes it harder for older adults to suppress distracting information). Perhaps the problem is not simply, or even principally, the complexity of our environment, but the speed of it. You only have to compare a modern TV drama or sit-com with one from the 70s to see how much faster everything now moves!

I do wonder if, in a less cognitively demanding environment, say, a traditional Himba village, whether WMC shows the same early rise and late decline. In an environment where change is uncommon, it is natural for elders to be respected for their accumulated wisdom — experience is all — but perhaps this respect also reflects a constancy in WMC (and thus ‘intelligence’), so that elders are not disadvantaged in the way they may be in our society. Just a thought.

Here’s another thought: it’s always seemed to me (this is not in any way a research-based conclusion!) that musicians and composers, and writers and professors, often age very well. I’ve assumed this was because they are keeping mentally active, and certainly that must be part of it. But perhaps there’s another reason, possibly even a more important reason: these are areas of expertise where the proponent spends a good deal of time focused on one thing. Rather than allowing their attention to be diffused throughout the environment all the time, they deliberately shut off their awareness of the environment to concentrate on their music, their writing, their art.

Perhaps, indeed, this is the shared factor behind which activities help fight age-related cognitive decline, and which don’t.

I began by saying that humans are the animals that manipulate their cognitive environment. I think this is the key to fighting age-related cognitive decline, or ADHD if it comes to that. We need to be aware how much our brains try to operate in a way that is optimal for our environment — meaning that, by controlling our environment, we can change the way our brain operates.

If you are worried about your ‘scattiness’, or if you want to prevent or fight age-related cognitive decline, I suggest you find an activity that truly absorbs and challenges you, and engage in it regularly.

The increase in WMC in Himba who moved to town also suggests something else. Perhaps the reason that WM training programs have had such little success is because they are ‘programs’. What you do in a specific environment (the bounds of a computer and the program running on it) does not necessarily, or even usually, transfer to the wider environment. We are contextual creatures, used to behaving in different ways with different people and in different places. If we want to improve our WMC, we need to incorporate experiences that challenge and extend it into our daily life.

This, of course, emphasizes my previous advice: find something that absorbs you, something that becomes part of your life, not something you 'do' for an hour some days. Learn to look at the world in a different way, through music or art or another language or a passion (Civil War history; Caribbean stamps; whatever).

You can either let your cognitive environment shape you, or shape your cognitive environment.

Do you agree? What's your cognitive environment, and do you think it has affected your cognitive well-being?

The thing to remember about Ericsson’s famous expertise research, showing us the vital importance of deliberate practice in making an expert, is that it was challenging the long-dominant view that natural-born talent is all-important. But Gladwell’s popularizing of Ericsson’s “10,000 hours” overstates the case, and of course people are only too keen to believe that any height is achievable if you just work hard enough.

The much more believable story is that, yes, practice is vital — a great deal of the right sort of practice — but we can’t disavow “natural” abilities entirely.

Last year I reported on an experiment in which 57 pianists with a wide range of deliberate practice (from 260 to more than 31,000 hours) were compared on their ability to sight-read. Number of hours of practice did indeed predict much of the difference in performance (nearly half) — but not all. Working memory capacity also had a statistically significant impact on performance, although this impact was much smaller (accounting for only about 7% of the performance difference). Nevertheless, there’s a clear consequence: given two players who have put in the same amount of effective practice, the one with the higher WMC is likely to do better. Why should WMC affect sight-reading? Perhaps by affecting how many notes a player can look ahead as she plays — this is a factor known to affect sight-reading performance.

Interestingly, the effect of working memory capacity was quite independent of practice, and hours of practice apparently had no effect on WMC. Although it’s possible (the study was too small to tell) that a lot of practice at an early age might affect WMC. After all, music training has been shown to increase IQ in children.

So, while practice is certainly the most important factor in developing expertise, other factors, some of them less amenable to training, have a role to play too.

But do general abilities such as WMC or intelligence matter once you’ve put in the requisite hours of good practice? It may be that ability becomes less important once you achieve expertise in a domain.

The question of whether WMC interacts with domain knowledge in this way has been studied by Hambrick and his colleagues in a number of experiments. One study used a memory task in which participants listened to fictitious radio broadcasts of baseball games and tried to remember major events and information about the players. Baseball knowledge had a very strong effect on performance, and WMC had a much smaller effect, but there was no interaction between the two. Similarly, in two poker tasks, in which players had to assess the likelihood of drawing a winning card, and players had to remember hands during a game of poker, both poker knowledge and WMC affected performance, but again there was no interaction between domain knowledge and WMC.

Another study took a different tack. Participants were asked to remember the movements of spaceships flying from planet to planet in the solar system. What they didn’t know was that the spaceships flew in a pattern that matched the way baseball players run around a baseball diamond. They were then given the same task, this time with baseball players running around a diamond. Baseball knowledge only helped performance in the task in which the baseball scenario was explicit — activating baseball knowledge. But activation of domain knowledge had no effect on the influence of WMC.

Although these various studies fail to show an interaction between domain knowledge and WMC, this doesn’t mean that domain knowledge never interacts with basic abilities. The same researchers recently found such an interaction in a geological bedrock mapping task, in which geological structure of a mountainous area had to be inferred. Visuospatial ability predicted performance only at low levels of geological knowledge; geological experts were not affected by their visuospatial abilities. Unfortunately, that study is not yet published, so I don’t know the details. But I assume they mean visuospatial working memory capacity.

It’s possible that general intelligence or WMC are most important during the first stages of skill acquisition (when attention and working memory capacity are so critical), and become far less important once the skill has been mastered.

Similarly, Ericsson has argued that deliberate practice allows performers to circumvent limits on working memory capacity. This is, indeed, related to the point I often make about how to functionally increase your working memory capacity — if you have a great amount of well-organized and readily accessible knowledge on a particular topic, you can effectively expand how much your working memory can hold by keeping a much larger amount of information ‘on standby’ in what has been termed long-term working memory.

Proponents of deliberate practice don’t deny that ‘natural’ abilities have some role, but they restrict it to motivation and general activity levels (plus physical attributes such as height where that is relevant). But surely these would only affect number of hours. Clearly the ability to keep yourself on task, to motivate and discipline yourself, impinges on your ability to keep your practice up. And the general theory makes sense — that if you show some interest in something, such as music or chess, when you’re young, your parents or teachers usually encourage you in that direction; this encouragement and rewards lead you to spend more time and energy in that domain, and if you have enough persistence, enough dedication, then lo and behold, you’ll get better and better. And your parents will say, well, it was obvious from an early age that she was talented that way.

But is it really the case that attributes such as intelligence make no difference? Is it really as simple as “10,000 hours of deliberate practice = expert”? Is it really the case that each hour has the same effect on any one of us?

A survey of 104 chess masters found that, while all the players that became chess masters had practiced at least 3,000 hours, the amount of practice it took to achieve that mastery varied considerably. Although, consistent with the “10,000 hour rule”, average time to achieve mastery was around 11,000 hours, time ranged from 3,016 hours to 23,608 hours. The difference is even more extreme if you only consider individual practice (previous research has pointed to individual practice being of more importance than group practice): a range from 728 hours to 16,120 hours! And some people practiced more than 20,000 hours and still didn't achieve master level.

Moreover, a comparison of titled masters and untitled international players found that the two groups practiced the same amount of hours in the first three years of their serious dedication to chess, and yet there were significant differences in their ratings. Is this because of some subtle difference in the practice, making it less effective? Or is it that some people benefit more from practice?

A comparison of various degrees of expertise in terms of starting age is instructive. While the average age of starting to play seriously was around 18 for players without an international rating, it was around 14 for players with an international rating, and around 11 for masters. But the amount of variability within each group varies considerably. For players without an international rating, the age range within one standard deviation of the mean is over 11 years, but for those with an international rating, FIDE masters, and international masters, the range is only 2-3 years, and for grand masters, the range is less than a year. [These numbers are all approximate, from my eyeball estimates of a bar graph.]

It has been suggested that the younger starting age of chess masters and expert musicians is simply a reflection of the greater amount of practice achieved with a young start. But a contrary suggestion is that there might be other advantages to learning a skill at an early age, reflecting what might be termed a ‘sensitive period’. This study found that the association between skill and starting age was still significant after amount of practice had been taken account of.

Does this have to do with the greater plasticity of young brains? Expertise “grows” brains — in the brain regions involved in that specific domain. Given that younger brains are much more able to create new neurons and new connections, it would hardly be a surprise that it’s easier for them to start building up the dense structures that underlie expertise.

This is surely easier if the young brain is also a young brain that has particular characteristics that are useful for that domain. For music, that might relate to perceptual and motor abilities. In chess, it might have more to do with processing speed, visuospatial ability, and capacious memory.

Several studies have found higher cognitive ability in chess-playing children, but the evidence among adults has been less consistent. This may reflect the growing importance of deliberate practice. (Or perhaps it simply reflects the fact that chess is a difficult skill, for which children, lacking the advantages that longer education and training have given adults, need greater cognitive skills.)

Related to all this, there’s a popular idea that once you get past an IQ of around 120, ‘extra’ IQ really makes no difference. But in a study involving over 2,000 gifted young people, those who scored in the 99.9 percentile on the math SAT at age 13 were eighteen times more likely to go on to earn a doctorate in a STEM discipline (science, technology, engineering, math) compared to those who were only(!) in the 99.1 percentile.

Overall, it seems that while practice can take you a very long way, at the very top, ‘natural’ ability is going to sort the sheep from the goats. And ‘natural’ ability may be most important in the early stages of learning. But what do we mean by ‘natural ability’? Is it simply a matter of unalterable genetics?

Well, palpably not! Because if there’s one thing we now know, it’s that nature and nurture are inextricably entwined. It’s not about genes; it’s about the expression of genes. So let me remind you that aspects of the prenatal, the infant, and the child’s, environment affect that ‘natural’ ability. We know that these environments can affect IQ; the interesting question is what we can do, at each and any of these stages, to improve affect basic processes such as speed of processing, WMC, and inhibitory control. (Although I should say here that I am not a fan of the whole baby-Einstein movement! Nor is there evidence that many of those practices work.)

Bottom line:

• talent still matters
• effective practice is still the most important factor in developing expertise
• individuals vary in how much practice they need
• individual abilities do put limits on what’s achievable (but those limits are probably higher than most people realize).

A New Yorker cartoon has a man telling his glum wife, “Of course I care about how you imagined I thought you perceived I wanted you to feel.” There are a number of reasons you might find that funny, but the point here is that it is very difficult to follow all the layers. This is a sentence in which mental attributions are made to the 6^th level, and this is just about impossible for us to follow without writing it down and/or breaking it down into chunks.

According to one study, while we can comfortably follow a long sequence of events (A causes B, which leads to C, thus producing D, and so on), we can only comfortably follow four levels of intentionality (A believes that B thinks C wants D). At the 5^th level (A wants B to believe that C thinks that D wants E), error rates rose sharply to nearly 60% (compared to 5-10% for all levels below that).

Why do we have so much trouble following these nested events, as opposed to a causal chain?

Let’s talk about working memory.

Working memory (WM) has evolved over the years from a straightforward “short-term memory store” to the core of human thought. It’s become the answer to almost everything, invoked for everything related to reasoning, decision-making, and planning. And of course, it’s the first and last port of call for all things memory — to get stored in long-term memory an item first has to pass through WM, where it’s encoded; when we retrieve an item from memory, it again passes through WM, where the code is unpacked.

So, whether or not the idea of working memory has been over-worked, there is no doubt at all that it is utterly crucial for cognition.

Working memory has also been equated with attentional control, and working memory and attention are often used almost interchangeably. And working memory capacity (WMC) varies among individuals. Those with a higher WMC have an obvious advantage in reasoning, comprehension, remembering. No surprise then that WMC correlates highly with fluid intelligence.

So let’s talk about working memory capacity.

The idea that working memory can hold 7 (+/-2) items has passed into popular culture (the “magic number 7”). More recent research, however, has circled around the number 4 (+/-1). Not only that, but a number of studies suggest that in fact the true number of items we can attend to is only one. What’s the answer? (And where does it leave our high- and low-capacity individuals? There’s not a lot of room to vary there.)

Well, in one sense, 7 is still fine — that’s the practical sense. Seven items (5-9) is about what you can hold if you can rehearse them. So those who are better able to rehearse and chunk will have a higher working memory capacity (WMC). That will be affected by processing speed, among other factors.

But there is a very large body of evidence now pointing to working memory holding only four items, and a number of studies indicating that most likely we can only pay attention to one of these items at a time. So you can envision this either as a focus of attention, which can only hold one item, and a slightly larger “outer store” or area of “direct access” which can hold another three, or as a mental space holding four items of which only one can be the focus at any one time.

A further tier, which may be part of working memory or part of long-term memory, probably holds a number of items “passively”. That is, these are items you’ve put on the back burner; you don’t need them right at the moment, but you don’t want them to go too far either. (See my recent news item for more on all this.)

At present, we don’t have any idea how many items can be in this slightly higher state of activation. However, the “magic number 7” suggests that you can circulate 3 (+/-1) items from the backburner into your mental space. In this regard, it’s interesting to note that, in the case of verbal material, the amount you can hold in working memory with rehearsal has been found to more accurately equate to 2 seconds, rather than 7 items. That is, you can remember as much as you can verbalize in about 2s (so, yes, fast speakers have a distinct advantage over slower ones). You see why processing speed affects WMC.

Whether you think of WM as a focus of one and an outer store of 3, or as a direct access area with 4 boxes and a spotlight shining on one, it’s a mental space or blackboard where you can do your working out. Thinking of it this way makes it easier to conceptualize and talk about, but these items are probably not going into a special area as such. The thought now is that these items stay in long-term memory (in their relevant areas of association cortex), but they are (a) highly activated, and (b) connected to the boxes in the direct access area (which is possibly in the medial temporal lobe). This connection is vitally important, as we shall see.

Now four may not seem like much, but WM is not quite as limited as it seems, because we have different systems for verbal (includes numerical) and visuospatial information. Moreover, we can probably distinguish between the items and the processing of them, which equates to a distinction between declarative and procedural memory. So that gives us three working memory areas: verbal declarative; visuospatial declarative; procedural.

Now all of this may seem more than you needed to know, but breaking down the working memory system helps us discover two things of practical interest. First, which particular parts of the system are the parts that make a task more difficult. Second, where individual differences come from, and whether they are in aspects that are trainable.

For example, this picture of a mental space with a focus of one and a maximum of three eager-beavers waiting their turn, points to an important aspect of the working memory system: switching the focus. Experiments reveal that there is a large focus-switching cost, incurred whenever you have to switch the item in the spotlight. And the extent of this cost has been surprising — around 240ms in one study, which is about six times the length of time it takes to scan an item in a traditional memory-search paradigm.

But focus-switch costs aren’t a constant. They vary considerably depending on the difficulty of the task, and they also tend to increase with each item in the direct-access area. Indeed, just having one item in the space outside the focus causes a significant loss of efficiency in processing the focused item.

This may reflect increased difficulty in discriminating one highly activated item from other highly activated items. This brings us to competition, which, in its related aspects of interference and inhibition, is a factor probably more crucial to WMC than whether you have 3 or 4 or 5 boxes in your direct access area.

But before we discuss that, we need to look at another important aspect of working memory: updating. Updating is closely related to focus-switching, and it’s easy to get confused between them. But it’s been said that working memory updating (WMU) is the only executive function that correlates with fluid intelligence, and updating deficits have been suggested as the reason for poor comprehension (also correlated with low-WMC). So it’s worth spending a little time on.

To get the distinction clear in your mind, imagine the four boxes and the spotlight shining on one. Any time you shift the spotlight, you incur a focus-switching cost. If you don’t have to switch focus, if you simply need to update the contents of the box you’re already focusing on, then there will be an update cost, but no focus-switching cost.

Updating involves three components: retrieval; transformation; substitution. Retrieval simply involves retrieving the contents from the box. Substitution involves replacing the contents with something different. Transformation involves an operation on the contents of the box to get a new value (eg, when you have to add a certain number to an earlier number).

Clearly the difficulty in updating working memory will depend on which of these components is involved. So which of these processes is most important?

In terms of performance, the most important component is transformation. While all three components contribute to the accuracy of updating, retrieval apparently doesn’t contribute to speed of updating. For both accuracy and speed, substitution is less important than transformation.

This makes complete sense: obviously having to perform an operation on the content is going to be more difficult and time-consuming than simply replacing it. But it does help us see that the most important factor in determining the difficulty of an updating task will be the complexity of the transformation.

The finding that retrieval doesn’t affect speed of updating sounds odd, until you realize the nature of the task used to measure these components. The number of items was held constant (always three), and the focus switched from one box to another on every occasion, so focus-switching costs were constant too. What the finding says is that once you’ve shifted your focus, retrieval takes no time at all — the spotlight is shining and there the answer is. In other words, there really is no distinction between the box and its contents when the spotlight is on it — you don’t need to open the box.

However, retrieval does affect accuracy, and this implies that something is degrading or interfering in some way with the contents of the boxes. Which takes us back to the problems of competition / interference.

But before we get to that, let’s look at this issue of individual differences, because like WMC, working memory updating correlates with fluid intelligence. Is this just a reflection of WMC?

Differences in transformation accuracy correlated significantly with WMC, as did differences in retrieval accuracy. Substitution accuracy didn’t vary enough to have measurable differences. Neither transformation nor substitution speed differences correlated with WMC. This implies that the reason why people with high WMC also do better at WMU tasks is because of the transformation and retrieval components.

So what about the factors that aren’t correlated with WMC? The variance in transformation speed is argued to primarily reflect general processing speed. But what’s going on in substitution that isn’t going on in when WMC is measured?

Substitution involves two processes: removing the old contents of the box, and adding new content. In terms of the model we’ve been using, we can think of unbinding the old contents from the box, and binding new contents to it (remember that the item in the box is still in its usual place in the association cortex; it’s “in” working memory by virtue of the temporary link connecting it to the box). Or we can think of it as deleting and encoding.

Consistent with substitution not correlating with WMC, there is some evidence that high- and low-WMC individuals are equally good at encoding. Where high- and low-WMC individuals differ is in their ability to prevent irrelevant information being encoded with the item. Which brings me to my definition of intelligence (from 30 years ago — these ideas hadn’t even been invented yet. So I came at it from quite a different angle): the ability to (quickly) select what’s important.

So why do low-WMC people tend to be poorer at leaving out irrelevant information?

Well, that’s the $64,000 question, but related to that it’s been suggested that those with low working memory capacity are less able to resist capture by distracting stimuli than those with high WMC. A new study, however, provides evidence that low- and high-WMC individuals are equally easily captured by distracters. What distinguishes the two groups is the ability to disengage. High-capacity people are faster in putting aside irrelevant stimuli. They’re faster at deleting. And this, it seems, is unrelated to WMC.

This is supported by another recent finding, that when interrupted, older adults find it difficult to disengage their brain from the new task and restore the original task.

So what’s the problem with deleting / removing / putting aside items in focus? This is about inhibition, which takes us once again to competition / interference.

Now interference occurs at many different levels: during encoding, retrieval, and storage; with items, with tasks, with responses. Competition is ubiquitous in our brain.

In the case of substitution during working memory updating, it’s been argued that the contents of the box are not simply removed and replaced, but instead gradually over-written by the new contents. This fits in with a view of items as assemblies of lower-level “feature-units”. Clearly, items may share some of these units with other items (reflected in their similarity), and clearly the more they compete for these units, the greater interference there will be between the units.

You can see why it’s better to keep your codes (items) “lean and mean”, free of any irrelevant information.

Indeed, some theorists completely discard the idea of number of items as a measure of WMC, and talk instead in terms of “noise”, with processing capacity being limited by such factors as item complexity and similarity. While there seems little justification for discarding our “4+/-1”, which is much more easily quantified, this idea does help us get to grips with the concept of an “item”.

What is an item? Is it “red”? “red cow”? “red cow with blue ribbons round her neck”? “red cow with blue ribbons and the name Isabel painted on her side”? You see the problem.

An item is a fuzzy concept. We can’t say, “it’s a collection of 6 feature units” (or 4 or 14 or 42). So we have to go with a less defined description: it’s something so tightly bound that it is treated as a single unit.

Which means it’s not solely about the item. It’s also about you, and what you know, and how well you know it, and what you’re interested in.

To return to our cases of difficulty in disengaging, perhaps the problem lies in the codes being formed. If your codes aren’t tightly bound, then they’re going to start to degrade, losing some of their information, losing some of their distinctiveness. This is going to make them harder to re-instate, and it’s going to make them less distinguishable from other items.

Why should this affect disengagement?

Remember what I said about substitution being a gradual process of over-writing? What happens when your previous focus and new focus have become muddled?

This also takes us to the idea of “binding strength” — how well you can maintain the bindings between the contents and their boxes, and how well you can minimize the interference between them (which relates to how well the items are bound together). Maybe the problem with both disengagement and reinstatement has to do with poorly bound items. Indeed, it’s been suggested that the main limiting factor on WMC is in fact binding strength.

Moreover, if people vary in their ability to craft good codes, if people vary in their ability to discard the irrelevant and select the pertinent, to bind the various features together, then the “size” (the information content) of an item will vary too. And maybe this is what is behind the variation in “4 +/-1”, and experiments which suggest that sometimes the focus can be increased to 2 items. Maybe some people can hold more information in working memory because they get more information into their items.

So where does this leave us?

Let’s go back to our New Yorker cartoon. The difference between a chain of events and the nested attributions is that chaining doesn’t need to be arranged in your mental space because you don’t need to keep all the predecessors in mind to understand it. On the other hand, the nested attributions can’t be understood separately or even in partitioned groups — they must all be arranged in a mental space so we can see the structure.

We can see now that “A believes that B thinks C wants D” is easy to understand because we have four boxes in which to put these items and arrange them. But our longer nesting, “A wants B to believe that C thinks that D wants E”, is difficult because it contains one more item than we have boxes. No surprise there was a dramatic drop-off in understanding.

So given that you have to fill your mental space, what is it that makes some tasks more difficult than others?

• The complexity and similarity of the items (making it harder to select the relevant information and bind it all together).
• The complexity of the operations you need to perform on each item (the longer the processing, the more tweaking you have to do to your item, and the more time and opportunity for interference to degrade the signal).
• Changing the focus (remember our high focus-switching costs).

But in our 5^th level nested statement, the error rate was 60%, not 100%, meaning a number of people managed to grasp it. So what’s their secret? What is it that makes some people better than others at these tasks?

They could have 5 boxes (making them high-WMC). They could have sufficient processing speed and binding strength to unitize two items into one chunk. Or they could have the strategic knowledge to enable them to use the other WM system (transforming verbal data into visuospatial). All these are possible answers.

This has been a very long post, but I hope some of you have struggled through it. Working memory is the heart of intelligence, the essence of attention, and the doorway to memory. It is utterly critical, and cognitive science is still trying to come to grips with it. But we’ve come a very long way, and I think we now have sufficient theoretical understanding to develop a model that’s useful for anyone wanting to understand how we think and remember, and how they can improve their skills.

There is, of course, far more that could be said about working memory (I’ve glossed over any number of points in an effort to say something useful in less than 50,000 words!), and I’m planning to write a short book on working memory, its place in so many educational and day-to-day tasks, and what we can do to improve our skills. But I hope some of you have found this enlightening.

I recently read an interesting article in the Smithsonian about procrastination and why it’s good for you. Frank Partnoy, author of a new book on the subject, pointed out that procrastination only began to be regarded as a bad thing by the Puritans — earlier (among the Greeks and Romans, for example), it was regarded more as a sign of wisdom.

The examples given about the perils of deciding too quickly made me think about the assumed connection between intelligence and processing speed. We equate intelligence with quick thinking, and time to get the correct answer is part of many tests. So, regardless of the excellence of a person’s cognitive product, the time it takes for them to produce it is vital (in test).

Similarly, one of the main aspects of cognition impacted by age is processing speed, and one of the principal reasons for people to feel that they are ‘losing it’ is because their thinking is becoming noticeably slower.

But here’s the question: does it matter?

Certainly in a life-or-death, climb-the-tree-fast-or-be-eaten scenario, speed is critical. But in today’s world, the major reason for emphasizing speed is the pace of life. Too much to do and not enough time to do it in. So, naturally, we want to do everything fast.

There is certainly a place for thinking fast. I recently looked through a short book entitled “Speed Thinking” by Ken Huds. The author’s strategy for speed thinking was basically to give yourself a very brief window — 2 minutes — in which to come up with 9 thoughts (the nature of those thoughts depends on the task before you — I’m just generalizing the strategy here). The essential elements are the tight time limit and the lack of a content limit — to accomplish this feat of 9 relevant thoughts in 2 minutes, you need to lose your inner censor and accept any idea that occurs to you.

If you’ve been reading my last couple of posts on flow, it won’t surprise you that this strategy is one likely to produce that state of consciousness (at least, once you’re in the way of it).

So, I certainly think there’s a place for fast thinking. Short bouts like this can re-energize you and direct your focus. But life is a marathon, not a sprint, and of course we can’t maintain such a pace or level of concentration. Nor should we want to, because sometimes it’s better to let things simmer. But how do we decide when it’s best to think fast or best to think slow? (shades of Daniel Kahneman’s wonderful book Thinking, Fast and Slow here!)

In the same way that achieving flow depends on the match between your skill and the task demands, the best speed for processing depends on your level of expertise, the demands of the task, and the demands of the situation.

For example, Sian Beilock (whose work on math anxiety I have reported on) led a study that demonstrated that, while novice golfers putted better when they could concentrate step-by-step on the accuracy of their performance, experts did better when their attention was split between two tasks and when they were focused on speed rather than accuracy.

Another example comes from a monkey study that has just been in the news. In this study, rhesus macaques were trained to reach out to a target. To do so, their brains needed to know three things: where their hand is, where the target is, and the path for the hand to travel to reach the target. If there’s a direct path from the hand to the target, the calculation is simple. But in the experiment, an obstacle would often block the direct path to the target. In such cases, the calculation becomes a little bit more complicated.

And now we come to the interesting bit: two monkeys participated. As it turns out, one was hyperactive, the other more controlled. The hyperactive monkey would quickly reach out as soon as the target appeared, without waiting to see if an obstacle blocked the direct path. If an obstacle did indeed appear in the path (which it did on 2/3 trials), he had to correct his movement in mid-reach. The more self-controlled monkey, however, waited a little longer, to see where the obstacle appeared, then moved smoothly to the target. The hyperactive monkey had a speed advantage when the way was clear, but the other monkey had the advantage when the target was blocked.

So perhaps we should start thinking of processing speed as a personality, rather than cognitive, variable!

[An aside: it’s worth noting that the discovery that the two monkeys had different strategies, undergirded by different neural activity, only came about because the researcher was baffled by the inconsistencies in the data he was analyzing. As I’ve said before, our focus on group data often conceals many fascinating individual differences.]

The Beilock study indicates that the ‘correct’ speed — for thinking, for decision-making, for solving problems, for creating — will vary as a function of expertise and attentional demands (are you trying to do two things at once? Is something in your environment or your own thoughts distracting you?). In which regard, I want to mention another article I recently read — a blog post on EdWeek, on procedural fluency in math learning. That post referenced an article on timed tests and math anxiety (which I’m afraid is only available if you’re registered on the EdWeek site). This article makes the excellent point that timed tests are a major factor in developing math anxiety in young children. Which is a point I think we can generalize.

Thinking fast, for short periods of time, can produce effective results, and the rewarding mental state of flow. Being forced to try and think fast, when you lack the necessary skills, is stressful and non-productive. If you want to practice thinking fast, stick with skills or topics that you know well. If you want to think fast in areas in which you lack sufficient expertise, work on slowly and steadily building up that expertise first.

You may have heard of “g”. It’s the closest we’ve come to that elusive attribute known as “intelligence”, but it is in fact a psychometric construct, that is, we surmise its presence from the way in which scores on various cognitive tests positively correlate.

In other words, we don’t really know what it is (hence the fact it is called “g”, rather than something more intelligible), and in fact, it is wrong to think of it as a thing. What it is, is a manifestation of some property or properties of the brain — and we don’t know what these are.

Various properties have been suggested, of course. Speed of processing; synaptic plasticity; fluid cognition. These are all plausible, but experimental studies have failed to provide clear evidence for any of them. The closest has been fluid cognition, or fluid intelligence, which is paired with crystallized intelligence. These two terms point to a useful distinction.

Fluid intelligence refers to cognitive functions associated with general reasoning and problem-solving, and is often described as executive function, or working memory capacity.

Crystallized intelligence, on the other hand, refers to cognitive functions associated with previously acquired knowledge in long-term store.

There is of course some interplay between these functions, but for the most part they are experimentally separable.

There are a couple of points worth noting.

For a start, different IQ tests measure fluid intelligence and crystallized intelligence to varying extents – the Raven’s Progressive Matrices Test, for example, predominantly measures fluid intelligence, while the WAIS disproportionately measures crystallized intelligence. An analysis of the most widely used intelligence test batteries for children found that about 1/3 of the subtests measure crystallized intelligence, an additional ¼ measure knowledge and reading/writing skills, while only 7% directly measure fluid intelligence, with perhaps another 10% measuring skills that have a fluid intelligence component – and nearly all the fluid subtests were found in one particular test battery, the W-J-R.

The so-called Flynn effect – the rapid rise in IQ over the past century – is for the most part an increase in fluid intelligence, not crystallized intelligence. While it has been hypothesized that fluid intelligence paves the way for the development of crystallized intelligence, it should be noted that the distinction between fluid and crystallized intelligence is present from a very early age, and the two functions have quite different growth patterns over the life of an individual.

So, what we’re saying is that most IQ tests provide little measure of fluid intelligence, although fluid intelligence appears to reflect “g” more closely than any other attribute, and that although crystallized intelligence is assumed to reflect environment (e.g., education) far more than fluid intelligence, it is fluid intelligence that has been rising, not crystallized intelligence.

In fact, for this and other reasons, it seems that fluid intelligence is far more affected by environment than has been considered.

I’ll leave you to ponder on the implications of this. Let me make just one more point.

The brain areas known to be important for fluid cognition are part of an interconnected system associated with emotion and stress response, and it is hypothesized that functions heretofore considered distinct from emotional arousal, such as reasoning and planning, are in fact very much part of a system in which emotional response is involved.

We’re not saying here that emotions can disrupt your reasoning processes, we all know that. What is being suggested is more radical – that emotions are part and parcel of the reasoning process. Okay, I always knew this, but it’s nice to see science coming along and providing some evidence.

The point about the close interaction between emotional reactivity and fluid intelligence is that stress may have a significant effect on fluid intelligence.

And I’ll leave you to ponder the implications of that.

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 capacity_8,9 - 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 difficulty_3,42.

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 decades_12,23,43. 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., pianists_40,41; 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, sportspeople_26,32 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 increases_1,28,15.

Practice and performance level

The performance level of student violinists in their 20s is strongly correlated with the number of hours that they practiced_13,14. 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 practice_4,6,12.

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 encouragement_38,24.

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 younger_16,17. 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 1^st 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.

Intelligence in a cultural context

One theory of intelligence sees intelligence in terms of adaptiveness. Thus: "What constitutes intelligence depends upon what the situation demands" (Tuddenham 1963). Intelligence in these terms cannot be understood outside of its cultural context. Naturally to us it may seem self-evident that intelligence has to do with analytical and reasoning abilities, but we are perceiving with the sight our culture taught us.

If we lived, for example, in a vast desert, where success relied on your ability to find plants, water, prey and to remember these locations, an "intelligent" person would be one who was skilled at finding their way around and remembering what they'd seen and where they'd seen it. In a society where people are stuck within a limited social group, where people are forced to get on with each other because they can't escape each other, and where survival requires you to depend on these people, social skills will be highly valued. An "intelligent" person might well be a person who is skilled in social relations.

If I lived in such a society, would I have become skilled in these areas?

If I had spent my childhood playing with construction toys such as Lego, would I be better at spatial relations?

In other words, is intelligence something that you simply have in some measure, which manifests itself in the skills that you practice when young / that are valued in your society or within your family? Or are you born instead with particular talents that, if you are lucky, are valued by your society and thus seen as signs of intelligence?

Here's one of my favorite stories.

An anthropologist, Joe Glick, was studying a tribe in Africa₁. The Kpelle tribe. Glick asked adults to sort items into categories. Rather than producing taxonomic categories (e.g. "fruit" for apple), they sorted into functional groups (e.g. "eat" for apple). Such functional grouping is something only very young children in our culture would do usually. Glick tried, and failed, to teach them to categorize items. Eventually he decided they simply didn't have the mental ability to categorize in this way. Then, as a last resort, he asked them how a stupid person would do this task. At this point, without any hesitation, they sorted the items into taxonomic categories!

They could do it, but in their culture, it was of no practical value. It was stupid.

Our IQ tests use categorization, and assumptions of how items relate to each other, to test "intelligence". (And how many of us, when filling in IQ tests, thought of different ways to answer questions, but answered the way we knew would be considered "right"?) These tests measure our ability to understand the mind of the test setter / marker. Do they measure anything else?

Multiple intelligences

One theory of intelligence that has had a certain influence on educational policy in the last 10-15 years is that of Howard Gardner’s idea of multiple intelligences (Gardner 1983). Gardner suggested that there are at least seven separate, relatively independent intelligences: linguistic, logical-mathematical, spatial, bodily kinaesthetic, intrapersonal, interpersonal, and musical.

Each intelligence has core components, such as sensitivity to the sounds, rhythms and meaning of words (linguistic), and has a developmental pattern relatively independent of the others. Gardner suggested the relative strengths of these seven intelligences are biologically determined, but the development of each intelligence depends on environmental influences, most particularly on the interaction of the child with adults.

This model of intelligence has positively influenced education most particularly by perceiving intelligence as much broader than the mathematical-language focus of modern education, and thus encouraging schools to spend more time on other areas of development.

It also, by seeing the development of particular intelligences as dependent on the child’s interaction with adults, encourages practices such as mentoring and apprenticeships, and supports parental and community involvement in educational environments. Because intelligence is seen as developing in a social context, grounding education in social institutions and in “real” environments takes on particular value.

All these are very positive aspects of the influence of this theory. On the downside, the idea of intelligence as being biologically determined is a potentially dangerous one. Gardner claims that a preschool child could be given simple tests that would demonstrate whether or not they had specific talents in any of those seven intelligences. The child could then be given training tailored to that talent.

Should we then deny that training to those who don't have that talent?

Do you know how many outstanding people - musicians, artists, mathematicians, writers, scientists, dancers, etc - showed signs of remarkable talent as very young children? Do you know how many so-called child prodigies went on to become outstanding in their field when adult? In both cases, not many.

The idea of "talent" is grounded in our society, but in truth, we have come no further in demonstrating its existence than the circular argument: he's good at that, therefore he has a talent for it; how do we know he has a talent? because he's good at it. Early ability does not demonstrate an innate talent unless the child has had no special opportunity to learn and practice the ability (and notwithstanding parental claims and retrospective reports, independent observation of this is lacking). (More on the question of innate talent)

Schooling and intelligence

The more we believe in innate talent, or innate intelligence, the less effort we will put into educating those who don't exhibit ability - although there are many environmental reasons for such failures.

The whole province of intelligence testing is, I believe, a dangerous one. Indeed, I was appalled to hear of its prevalence in American education. While intelligence was seen as some inborn talent unaffected by training or experience by the early makers and supporters of psychometric tests, recent research strongly suggests that schooling affects IQ score.

If you take two children who at age 13 have identical IQs and grades and then retest them five years later, after one child has finished high school while the other has dropped out of school in ninth grade, you find that the child who dropped out of school has lost around 1.8 IQ points for every year of missed school (Ceci, 1999).

Starting school late or leaving early results in a decrease in IQ relative to a matched peer who received more schooling. In families where children attend school intermittently, there is a high negative correlation between age and IQ, implying that as the children got older, their IQ dropped commensurately.

The most obvious, and simplest, explanation is that much of what is tested in IQ tests is either directly or indirectly taught in school. This is not to say schooling has any effect on intelligence itself (whatever that is).