Study & Education
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?
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)
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).
1. Sternberg, R.J. 1997. Successful intelligence: How practical and creative intelligence determine your success in life. Plume.
In the education world, fixed mind-set is usually contrasted with growth mind-set. In this context, fixed mind-set refers to students holding the idea that their cognitive abilities, including their intelligence, are set at birth, and they just have to accept their limitations. With a growth mind-set, however, the student recognizes that, although it might be difficult, they can grow their abilities.
A growth mind-set has been associated with a much better approach to learning and improved academic achievement, but new research suggests that this difference has been over-stated.
A recent meta-analysis of growth mind-set research found that
Overall, the study found the correlation between growth mind-set and academic achievement was very weak.
Perhaps unsurprisingly, one important factor was age — children and teenagers showed significant effects, while adults did not. Interestingly, neither academic risk status nor socioeconomic status was a significant factor, although various studies have suggested that growth mind-set is much more important for at-risk students.
A second, smaller meta-analysis was carried out to investigate whether growth-set interventions made a significant impact on academic achievement. Such interventions are designed to increase students' belief that intelligence (or some other attribute) can be improved with effort.
The study found that
Age was not a factor, nor was at-risk status. However, socioeconomic status was important, in that students from low-SES households were significantly impacted by a growth mind-set intervention, while those from higher-SES households were not.
The type of intervention was important: just reading about growth mind-set didn't help; doing something more interactive, such as writing a reflection, did. The number of sessions didn't have an effect. Oddly, the way the intervention was presented made a difference, with materials presented by computer or by a person not being effective, while print materials were. Interventions administered during regular classroom activities were not effective, but interventions that occurred outside regular activities did have a significant effect.
Taken overall, the depressing conclusion is that mind-set interventions are not the revolution some have touted them as. The researchers point out that previous research (Hattie et al 1996) found that the meta-analytic average effect size for a typical educational intervention on academic performance is 0.57, and all the meta-analytic effects of mind-set interventions in this study were smaller than 0.35 (and most were null).
All this is to say, not that mind-set theory is rubbish, but that it is not as straightforward and miraculous as it first appeared. Mind-set itself is more nuanced than has been presented. For example, do we really have a definite fixed mind-set or growth mind-set? Or is it that we have different mind-sets for different spheres? Perhaps we believe that our math ability is fixed, but our musical ability is something that can be developed. That we can develop our problem-solving ability, but our intelligence is set in stone. That our 'natural talents' can be grown, but our 'innate weaknesses' cannot.
Why would low-SES and high-risk students benefit from a growth mind-set intervention, while higher-SES students did not? An obvious answer lies in the beliefs held by such students. For example, it may be that many higher-SES students are challenged by the idea of a growth mind-set, because they're invested in the idea of their own natural abilities. It is their confidence in their own abilities that enables them to do well, just as other students are undermined by their lack of confidence. Given this different starting point, it would not be in any way surprising if such students responded differently to mind-set interventions.
Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To What Extent and Under Which Circumstances Are Growth Mind-Sets Important to Academic Achievement? Two Meta-Analyses. Psychological Science, 29(4), 549–571. http://doi.org/10.1177/0956797617739704
Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: A meta-analysis. Review of Educational Research, 66, 99–136.
Confirming what many of us have learned through practical experience, a study comparing different strategies of reading or listening has found that you are more likely to remember something if you read it out loud to yourself.
In the study, 75 undergraduate students first spent around 15 minutes being recorded as they read aloud 160 common words. They were not told any reason for this activity. Two weeks later, they attended another short session, in which they were told that they would be given the same words they had read earlier, and they would then be tested on their memory of them. Half of the 160 words were given to them in four learning conditions (20 words in each):
They were then given a self-paced recognition test involving all 160 words, and had to classify each one as “studied” or “new”.
The expected pattern of performance was consistent with that hypothesized: reading aloud was best, followed by hearing oneself, then hearing another, and finally reading silently. There was not a lot of difference between saying aloud and hearing oneself, however — words that were said aloud were only marginally better remembered than those in which one heard oneself say the word (hit rate of 77% vs 74%). Hearing someone else speak was significantly better than simply reading silently (69% vs 65%) (I know, it doesn’t seem much more different, but the first comparison didn’t reach statistical significance, and the second did, just). Much clearer was the comparison between those conditions with a self-referential component (reading aloud, hearing yourself) vs conditions with no such component — here the difference was very clearly significant. This was supported by the results of an unplanned comparison between the hear-self and hear-other conditions, which also produced a significant difference.
These results are consistent with previous research, though the differences are smaller than previous. It seems likely that this might be due to the necessity for participants to have previously experienced the words in the earlier session (obviously it would have been much better to have a substantially longer period between the sessions; I assume logistical issues were behind this choice).
In any case, the findings do support the idea that reading aloud helps memory through all three of its ‘extra’ components:
Notably, this study suggests that it is the third of these (self-referential) that is the most important aspect, with the motor aspect being least important.
 Forrin, N. D., & MacLeod C. M.
(2018). This time it’s personal: the memory benefit of hearing oneself.
Memory. 26(4), 574 - 579.
A largish study
There has been quite a lot of research into the relationship between students’ expectations and academic performance. It’s fairly well-established that students tend to have inflated expectations of their performance, but the effect of this has been disputed. Does over-confidence discourage students from preparing for exams, or do high expectations motivate students to study harder? A largish study has investigated this question.
The study involved 592 second-year students taking a statistics course at the HSE International College of Economics and Finance in Moscow. The students take three written exams during the course of the year, with each exam being divided into two parts of 80 minutes by a small break. Researchers surveyed the students during these breaks to see what final scores they were expecting. Students were encouraged to take their best guess by the promise that reasonably close predictions would be rewarded with an extra point on their score. Exams were marked out of 100 (rather than with a broad letter grade).
Students’ ability was assessed using previous grades in mathematics and statistics, first-year GPA, second-year homework, and performance on the previous exam.
The study found that, given similar ability, students who expected higher scores did actually attain them, supporting the idea that high expectations motivate students to work harder.
Consistent with previous research, students (of both genders) were overwhelmingly inclined to overestimate their abilities. However, with each passing exam, their predictions become more accurate. Overall, female students tended to be more realistic in their expectations, and faster to learn from each exam.
The researchers suggest the finding supports giving tests at the beginning of a course so that students are able to adapt their expectations more quickly. Note, however, that these exams covered cumulative knowledge. Courses where exams cover different, unrelated, material each time, will probably not see the same benefit.
Full text available at https://www.frontiersin.org/articles/10.3389/fpsyg.2017.02346/full
 Magnus, J. R., & Peresetsky A. A.
(2018). Grade Expectations: Rationality and Overconfidence.
Frontiers in Psychology. 8,
In a series of experiments involving college students, drawing pictures was found to be the best strategy for remembering lists of words.
The basic experiment involved students being given a list of simple, easily drawn words, for each of which they had 40 seconds to either draw the word, or write it out repeatedly. Following a filler task (classifying musical tones), they were given 60 seconds to then recall as many words as possible. Variations of the experiment had students draw the words repeatedly, list physical characteristics, create mental images, view pictures of the objects, or add visual details to the written letters (such as shading or other doodles).
In all variations, there was a positive drawing effect, with participants often recalling more than twice as many drawn than written words.
Importantly, the quality of the drawings didn’t seem to matter, nor did the time given, with even a very brief 4 seconds being enough. This challenges the usual explanation for drawing benefits: that it simply reflects the greater time spent with the material.
Participants were rated on their ability to form vivid mental images (measured using the VVIQ), and questioned about their drawing history. Neither of these factors had any reliable effect.
The experimental comparisons challenge various theories about why drawing is beneficial:
The researchers suggest that it is a combination of factors that work together to produce a greater effect than the sum of each. These factors include mental imagery, elaboration, the motor action, and the creation of a picture. Drawing brings all these factors together to create a stronger and more integrated memory code.
 Wammes, J. D., Meade M. E., & Fernandes M. A.
(2016). The drawing effect: Evidence for reliable and robust memory benefits in free recall.
The Quarterly Journal of Experimental Psychology. 69(9), 1752 - 1776.
A study involving 60 undergraduate students confirms the value of even a single instance of retrieval practice in an everyday setting, and also confirms the value of cues for peripheral details, which are forgotten more readily.
In three experiments involving 20 undergraduate students, students were shown foreign or otherwise obscure movie clips that contained scenes of normal everyday events. The 24-second clips from 40 films were shown over a period of about half an hour. After a delay of either several minutes, three days, or seven days, the students were questioned on their memory of the general plot, as well as details such as sounds, colors, gestures, and background details that allow a person to re-experience an event in rich and vivid detail.
In the second experiment, students were given a brief visual cue, such as a simple glimpse of the title and a sliver of a screenshot, on testing. In the third experiment, students recalled the information soon after viewing, in addition to the later test.
The finding confirms the value of even a single instance of retrieval practice, even without any delay. Note that memory was tested after a week. For longer recall, additional retrieval practice is likely to be needed — but it's probably fair to say that it's that first instance of retrieval that has the biggest effect. I discuss all this in much greater detail in my book on practice.
It's also worth thinking about this in conjunction with the earlier report that there's a special benefit in recounting the information to another person.
 Sekeres, M. J., Bonasia K., St-Laurent M., Pishdadian S., Winocur G., Grady C., et al.
(2016). Recovering and preventing loss of detailed memory: differential rates of forgetting for detail types in episodic memory.
Learning & Memory. 23(2), 72 - 82.
A Canadian study involving French-speaking university students has found that repeating aloud, especially to another person, improves memory for words.
In the first experiment, 20 students read a series of words while wearing headphones that emitted white noise, in order to mask their own voices and eliminate auditory feedback. Four actions were compared:
They were tested on their memory of the words after a distraction task. The memory test only required them to recognize whether or not the words had occurred previously.
There was a significant effect on memory. The order of the conditions matches the differences in memory, with memory worst in the first condition, and best in the last.
In the second experiment, 19 students went through the same process, except that the stimuli were pseudo-words. In this case, there was no memory difference between the conditions.
The effect is thought to be due to the benefits of motor sensory feedback, but the memory benefit of directing your words at a person rather than a screen suggests that such feedback goes beyond the obvious. Visual attention appears to be an important memory enhancer (no great surprise when we put it that way!).
Most of us have long ago learned that explaining something to someone really helps our own understanding (or demonstrates that we don’t in fact understand it!). This finding supports another, related, experience that most of us have had: the simple act of telling someone something helps our memory.
 Lafleur, A., & Boucher V. J.
(2015). The ecology of self-monitoring effects on memory of verbal productions: Does speaking to someone make a difference?.
Consciousness and Cognition. 36, 139 - 146.
We know that the neurotransmitter dopamine is involved in making strong memories. Now a mouse study helps us get more specific — and suggests how we can help ourselves learn.
The study, involving 120 mice, found that mice tasked with remembering where food had been hidden did better if they had been given a novel experience (exploring an unfamiliar floor surface) 30 minutes after being trained to remember the food location.
This memory improvement also occurred when the novel experience was replaced by the selective activation of dopamine-carrying neurons in the locus coeruleus that go to the hippocampus. The locus coeruleus is located in the brain stem and involved in several functions that affect emotion, anxiety levels, sleep patterns, and memory. The dopamine-carrying neurons in the locus coeruleus appear to be especially sensitive to environmental novelty.
In other words, if we’re given attention-grabbing experiences that trigger these LC neurons carrying dopamine to the hippocampus at around the time of learning, our memories will be stronger.
Now we already know that emotion helps memory, but what this new study tells us is that, as witness to the mice simply being given a new environment to explore, these dopamine-triggering experiences don’t have to be dramatic. It’s suggested that it could be as simple as playing a new video game during a quick break while studying for an exam, or playing tennis right after trying to memorize a big speech.
Remember that we’re designed to respond to novelty, to pay it more attention — and, it seems, that attention is extended to more mundane events that occur closely in time.
In a similar vein, a human study has found that the benefits of reward extend forward in time.
In the study, volunteers were shown images from two categories (objects and animals), and were financially rewarded for one of these categories. As expected, they remembered images associated with a reward better. In a second session, however, they were shown new images of animals and objects without any reward. Participants still remembered the previously positively-associated category better.
Now, this doesn’t seem in any way surprising, but the interesting thing is that this benefit wasn’t seen immediately, but only after 24 hours — that is, after participants had slept and consolidated the learning.
Previous research has shown similar results when semantically related information has been paired with negative, that is, aversive stimuli.
 Takeuchi, T., Duszkiewicz A. J., Sonneborn A., Spooner P. A., Yamasaki M., Watanabe M., et al.
(2016). Locus coeruleus and dopaminergic consolidation of everyday memory.
Nature. advance online publication,
 Oyarzún, J. P., Packard P. A., de Diego-Balaguer R., & Fuentemilla L.
(2016). Motivated encoding selectively promotes memory for future inconsequential semantically-related events.
Neurobiology of Learning and Memory. 133, 1 - 6.
Four studies involving a total of more than 300 younger adults (20-24) have looked at information processing on different forms of media. They found that digital platforms such as tablets and laptops for reading may make you more inclined to focus on concrete details rather than interpreting information more abstractly.
As much as possible, the material was presented on the different media in identical format.
In the first study, 76 students were randomly assigned to complete the Behavior Identification Form on either an iPad or a print-out. The Form assesses an individual's current preference for concrete or abstract thinking. Respondents have to choose one of two descriptions for a particular behavior — e.g., for “making a list”, the choice of description is between “getting organized” or “writing things down”. The form presents 25 items.
There was a marked difference between those filling out the form on the iPad vs on a physical print-out, with non-digital users showing a significantly higher preference for abstract descriptions than digital users (mean of 18.56 vs 13.75).
In the other three studies, the digital format was always a PDF on a laptop. In the first of these, 81 students read a short story by David Sedaris, then answered 24 multichoice questions on it, of which half were abstract and half concrete. Digital readers scored significantly lower on abstract questions (48% vs 66%), and higher on concrete questions (73% vs 58%).
In the next study, 60 students studied a table of information about four, fictitious Japanese car models for two minutes, before being required to select the superior model. While one model was objectively superior in regard to the attributes and attribute rating, the amount of detail means (as previous research has shown) that those employing a top-down “gist” processing do better than those using a bottom-up, detail-oriented approach. On this problem, 66% of the non-digital readers correctly chose the superior model, compared to 43% of the digital readers.
In the final study, 119 students performed the same task as in the preceding study, but all viewed the table on a laptop. Before viewing the table, however, some were assigned to one of two priming activities: a high-level task aimed at activating more abstract thinking (thinking about why they might pursue a health goal), or a low-level task aimed at activating more concrete thinking (thinking about how to pursue the same goal).
Being primed to think more abstractly did seem to help these digital users, with 48% of this group correctly answering the car judgment problem, compared to only 25% of those given the concrete priming activity, and 30% of the control group.
I note that the performance of the control group is substantially below the performance of the digital users in the previous study, although there was no apparent change in the methodology. However, this was not noted or explained in the paper, so I don't know why this was. It does lead me not to put too much weight on this idea that priming can help.
However, the findings do support the view that reading on digital devices does encourage a more concrete style of thinking, reinforcing the idea that we are inclined to process information more shallowly when we read it from a screen.
Of course, this is, as the researchers point out, not an indictment. Sometimes, this is the best way to approach certain tasks. But what it does suggest is that we need to consider what sort of processing is desirable, and modify our strategy accordingly. For example, you may find it helpful to print out material that requires a high level of abstract thinking, particularly if your degree of expertise in the subject means that it carries a high cognitive load.
Kaufman, G., & Flanagan, M. (2016). High-Low Split : Divergent Cognitive Construal Levels Triggered by Digital and Non-digital Platforms. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1–5. doi:10.1145/2858036.2858550 http://dl.acm.org/citation.cfm?doid=2858036.2858550
I've reported before on studies showing how gesturing can help children with mathematics and problem-solving. A new Australian study involving children aged 9-13 has found that finger-tracing has a similar effect.
Students who used their finger to trace over practice examples while simultaneously reading geometry or arithmetic material were able to complete the problems more quickly and correctly than those who didn't use the same technique.
In the first experiment, involving 52 students aged 11-13, some students were instructed to use their index fingers to trace elements of worked examples in triangle geometry, involving two angle relationships (Vertical angles are equal; Any exterior angle equals the sum of the two interior opposite angles.). Students were given two minutes to study a short instructional text on the relationships and how they can be used to solve particular problems. They were then given two minutes to study two worked examples. The tracing group were given additional instruction in how to use their index finger to trace out highlighted elements. The non-tracing group were told to keep their hands in their lap. Testing consisted of six questions, two of which were the same as the acquisition problems but with different numbers, and four of which were transfer questions, requiring more thoughtful responses.
A ceiling effect meant there was no difference between the two groups on the first two test questions. The tracing group answered significantly more transfer questions, although the difference wasn't great. There was no difference in how difficult the groups rated the test items.
In the second experiment, involving 54 Year 4 students, the instruction and problems concerned the fundamental order of operations. The tracing group were told to trace the operation symbols. The tracing group did significantly better, although again, the difference wasn't great, and again, there was no difference in assessment of problem difficulty.
In another experiment, involving 42 Year 5 students (10-11 years), students were given 5 minutes to study three angle relationships involving parallel lines (vertical angles are equal; corresponding angles are equal; the sum of co- interior angles is 180°). While answers to the 'basic' test questions failed to show significant differences, on the advanced transfer problems, the tracing group solved significantly more test questions than the non-tracing group, solved them more quickly, made fewer errors, and reported lower levels of test difficulty.
In the final experiment, involving 72 Year 5 students, on the advanced test problems, students who traced on the paper outperformed those who traced above the paper, who in turn outperformed those who simply read the material.
The researchers claim the findings support the view that tracing out elements of worked examples helps students construct good mental schemas, making it easier for them to solve new problems, and reducing cognitive demand.
As with gesturing, the benefits of tracing are not dramatic, but I believe the pattern of these results support the view that, when cognitive load is high (something that depends on the individual student as well as the task and its context), tracing key elements of worked examples might be a useful strategy.
Further research looking at individual differences would be helpful. I think greater benefits would be shown for students with low working memory capacity.
 Hu, F-T., Ginns P., & Bobis J.
(2015). Getting the point: Tracing worked examples enhances learning.
Learning and Instruction. 35, 85 - 93.
 Ginns, P., Hu F-T., Byrne E., & Bobis J.
(2015). Learning By Tracing Worked Examples.
Applied Cognitive Psychology. n/a - n/a.
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