Category Archives: Psychology

Older adolescents and adults can learn certain thinking skills more effectively than younger people

A few weeks ago I told my students about an interesting question raised and answered by this study by Fuhrmann, Knoll and Blakemore: can adolescence also be regarded as a sensitive period? This new study by a.o. the same researcher adds to their findings: older adolescents and adults can learn certain thinking skills including non-verbal reasoning more effectively than younger people.

From the press release:

The study, published in Psychological Science, also highlights the fact that non-verbal reasoning skills can be readily trained and do not represent an innate, fixed ability.

“Although adults and older adolescents benefitted most from training in non-verbal reasoning, the average test score for adolescents aged 11-13 improved from 60% to 70% following three weeks of ten-minute online training sessions,” says senior author Professor Sarah-Jayne Blakemore (UCL Institute of Cognitive Neuroscience). “This calls into question the claim that entry tests for selective schools that include non-verbal reasoning ‘assess the true potential of every child’.”

The research involved 558 school pupils aged 11-18 and 105 adults, who were initially tested in various skills and then completed up to 20 days of online training in a particular skill before taking the tests again. They were then tested six months later to see whether the effect of training lasted.

The non-verbal reasoning test involved looking at a 3×3 grid of shapes with the final square left blank. Participants had to choose the correct shape to complete the pattern, and the shapes could vary by colour, size, shape and position. In another test, ‘numerosity discrimination’, participants were shown two groups of different coloured dots in quick succession and had to judge which group had the most dots.

“We find that these cognitive skills, which are related to mathematics performance, show greater training effects in late adolescence than earlier in adolescence,” explains co-lead author Dr Lisa Knoll. “These findings highlight the relevance of this late developmental stage for education and challenge the assumption that earlier is always better for learning. We find that fundamental cognitive skills related to mathematics can be significantly trained in late adolescence.”

At the testing stages, volunteers were tested on various tasks, not just the ones they had trained in, to see if the training effects transferred to other skills. No transfer effects were observed, suggesting that the effect of training was specific to each task.

“Some ‘brain training’ apps claim to improve your IQ by getting you to practise a specific task such as the non-verbal reasoning task we used in our experiment,” says co-lead author Ms Delia Fuhrmann (UCL Institute of Cognitive Neuroscience). “However, there is no evidence that this leads to an improvement in overall cognitive ability. All we can say for sure is that training to spot patterns in a 3×3 grid of abstract shapes improves your ability to spot patterns in a 3×3 grid of abstract shapes. While this ability is commonly tested in IQ tests, it might not be appropriate to make judgements about other forms of intelligence based on the outcomes of such tests.”

Abstract of the study:

In the current study, we investigated windows for enhanced learning of cognitive skills during adolescence. Six hundred thirty-three participants (11–33 years old) were divided into four age groups, and each participant was randomly allocated to one of three training groups. Each training group completed up to 20 days of online training in numerosity discrimination (i.e., discriminating small from large numbers of objects), relational reasoning (i.e., detecting abstract relationships between groups of items), or face perception (i.e., identifying differences in faces). Training yielded some improvement in performance on the numerosity-discrimination task, but only in older adolescents or adults. In contrast, training in relational reasoning improved performance on that task in all age groups, but training benefits were greater for people in late adolescence and adulthood than for people earlier in adolescence. Training did not increase performance on the face-perception task for any age group. Our findings suggest that for certain cognitive skills, training during late adolescence and adulthood yields greater improvement than training earlier in adolescence, which highlights the relevance of this late developmental stage for education.

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Is this another explanation for the ‘boy-problem’ in education?

This morning I saw a conversation on Twitter and it delivered me a great new insight in intelligence:

Wait? There is a greater male variance in IQ and it has been well replicated? I felt stupid because I didn’t knew. Let’s check the abstract (and the actual paper too of course):

The idea that general intelligence may be more variable in males than in females has a long history. In recent years it has been presented as a reason that there is little, if any, mean sex difference in general intelligence, yet males tend to be overrepresented at both the top and bottom ends of its overall, presumably normal, distribution. Clear analysis of the actual distribution of general intelligence based on large and appropriately population-representative samples is rare, however. Using two population-wide surveys of general intelligence in 11-year-olds in Scotland, we showed that there were substantial departures from normality in the distribution, with less variability in the higher range than in the lower. Despite mean IQ-scale scores of 100, modal scores were about 105. Even above modal level, males showed more variability than females. This is consistent with a model of the population distribution of general intelligence as a mixture of two essentially normal distributions, one reflecting normal variation in general intelligence and one reflecting normal variation in effects of genetic and environmental conditions involving mental retardation. Though present at the high end of the distribution, sex differences in variability did not appear to account for sex differences in high-level achievement.

This graph makes it more clear:

iq-male-and-female

Maybe this isn’t new to you, but if I have ever read it, I didn’t make a mental note of it. But I do see a parallel with what has been called the boy-problem in education. If you look at PISA-reports and reports alike, it’s clear to see that boys have a bigger chance to become a dropout. The past few years there are in many countries more females in higher education than males.

But… if you look at the top students in education, there are males present too, sometimes even still more males than females. Actually, it looks a bit like the charts I just mentioned.

Yes, I know most of the discussions about IQ – btw, you should read the book by Stuart Ritchie – and I’m only suggesting a correlation and no, it doesn’t mean we need to accept that a lot of boys are lost in education. Still, if this is even only a bit true, it’s something interesting to bear in mind.

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Another day, another replication

It has been a very busy day as the academic year has started again with some intense teaching sessions for fresh soon to be teachers on my schedule. That’s why I haven’t shared this new example of replication study tackling a famous insight from psychology yet. And that’s a pity, because the study is mentioned in Nature (yeah!) and was conducted by a team from the KULeuven (a Belgian University and while being patriotic is the least Belgian one can act, still yeah!!).

From the article discussing the replication in Nature:

Physiologist Ivan Pavlov conditioned dogs to associate food with the sound of a buzzer, which left them salivating. Decades later, researchers discovered such training appears to block efforts to teach the animals to link other stimuli to the same reward. Dogs trained to expect food when a buzzer sounds can then be conditioned to salivate when they are exposed to the noise and a flash of light simultaneously. But light alone will not cue them to drool.

This ‘blocking effect’ is well-known in psychology, but new research suggests that the concept might not be so simple. Psychologists in Belgium failed to replicate the effect in 15 independent experiments, they report this month in the Journal of Experimental Psychology1.

“For a long time, you tend to think, ‘It’s me’ — I’m doing something wrong, or messing up the experiment,’” says lead author Tom Beckers, a psychologist at the Catholic University of Leuven (KU Leuven) in Belgium. But after his student, co-author Elisa Maes, also could not replicate the blocking effect, and the team failed again in experiments in other labs, Beckers realized that “it can’t just be us”.

The scientists do not claim that the blocking effect is not real, or that previous observations of it are wrong. Instead, Beckers thinks that psychologists do not yet know enough about the precise conditions under which it applies. (read more)

Abstract from the study:

With the discovery of the blocking effect, learning theory took a huge leap forward, because blocking provided a crucial clue that surprise is what drives learning. This in turn stimulated the development of novel association-formation theories of learning. Eventually, the ability to explain blocking became nothing short of a touchstone for the validity of any theory of learning, including propositional and other nonassociative theories. The abundance of publications reporting a blocking effect and the importance attributed to it suggest that it is a robust phenomenon. Yet, in the current article we report 15 failures to observe a blocking effect despite the use of procedures that are highly similar or identical to those used in published studies. Those failures raise doubts regarding the canonical nature of the blocking effect and call for a reevaluation of the central status of blocking in theories of learning. They may also illustrate how publication bias influences our perspective toward the robustness and reliability of seemingly established effects in the psychological literature.

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More than meets the eye: Chess skill is linked to intelligence

At first it looks like a ‘No shit, Sherlock’-kind of study: intelligence plays a significant role in determining chess skill. But there is more than meets the eye. Do know that for the e.g. the infamous 10000 rule chess research played an important role. But just relentless practice for 8 to 10 years won’t do the trick.  This new comprehensive meta-analysis provides some of the most conclusive evidence to date that cognitive ability is linked to skilled performance and refutes theories that expertise is based solely on intensive training.

From the press release:

“Chess is probably the single most studied domain in research on expertise, yet the evidence for the relationship between chess skill and cognitive ability is mixed,” said MSU’s Alexander Burgoyne, lead author on the study. “We analyzed a half-century worth of research on intelligence and chess skill and found that cognitive ability contributes meaningfully to individual differences in chess skill.”

The findings, reported online in the journal Intelligence, come out of Zach Hambrick’s Expertise Lab at MSU, which examines the origins of skill in domains such as chess, music and sports.

“When it comes to expertise, training and practice certainly are a piece of the puzzle,” said Hambrick, MSU professor of psychology. “But this study shows that, for chess at least, intelligence is another piece of the puzzle.”

For the in-depth study, known as a meta-analysis, the researchers considered nearly 2,300 scholarly articles on chess skill, looking specifically for studies that included a measure of cognitive ability (such as IQ score) and objective chess skill (such as the Elo rating, which ranks players based on game performance). The final sample included 19 studies with about 1,800 total participants.

The meta-analysis represents the first attempt by researchers to systematically investigate the best available scientific evidence for the link between intellect and chess skill, said Burgoyne, a graduate student in the Cognition and Cognitive Neuroscience program at MSU.

The study found that intelligence was linked to chess skill for the overall sample, but particularly among young chess players and those at lower levels of skill. This may be because the upper-level players represent a winnowed distribution of cognitive ability — in other words, they all tend to be fairly bright. (By way of comparison, Burgoyne said, consider the world’s best basketball players. Although there is essentially no correlation between height and points scored at that level, that doesn’t mean height isn’t important in basketball.)

Hambrick offered another potential explanation. “Imagine that a genius can become a skilled chess player relatively easily, whereas a person with average intelligence may take longer. So the idea is, as you practice more and develop more skills and knowledge about the game, you may be able to circumvent limitations in cognitive ability.” This might be true for chess, he added, but not for all activities. In an earlier study, Hambrick and a colleague found that working memory, a cognitive ability related to general intelligence, predicted success in sight-reading music even among highly practiced pianists.

Abstract of the study:

Why are some people more skilled in complex domains than other people? Here, we conducted a meta-analysis to evaluate the relationship between cognitive ability and skill in chess. Chess skill correlated positively and significantly with fluid reasoning (Gf) (View the MathML source = 0.24), comprehension-knowledge (Gc) (View the MathML source = 0.22), short-term memory (Gsm) (View the MathML source = 0.25), and processing speed (Gs) (View the MathML source = 0.24); the meta-analytic average of the correlations was (View the MathML source = 0.24). Moreover, the correlation between Gf and chess skill was moderated by age (View the MathML source = 0.32 for youth samples vs. View the MathML source = 0.11 for adult samples), and skill level (View the MathML source = 0.32 for unranked samples vs. View the MathML source = 0.14 for ranked samples). Interestingly, chess skill correlated more strongly with numerical ability (View the MathML source = 0.35) than with verbal ability (View the MathML source = 0.19) or visuospatial ability (View the MathML source = 0.13). The results suggest that cognitive ability contributes meaningfully to individual differences in chess skill, particularly in young chess players and/or at lower levels of skill.

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Interesting read: Evidence Rebuts Chomsky’s Theory of Language Learning

This article in Scientific American comes just in time for some courses I’ll be teaching in a few weeks:

The idea that we have brains hardwired with a mental template for learning grammar—famously espoused by Noam Chomsky of the Massachusetts Institute of Technology—has dominated linguistics for almost half a century. Recently, though, cognitive scientists and linguists have abandoned Chomsky’s “universal grammar” theory in droves because of new research examining many different languages—and the way young children learn to understand and speak the tongues of their communities. That work fails to support Chomsky’s assertions.

The research suggests a radically different view, in which learning of a child’s first language does not rely on an innate grammar module. Instead the new research shows that young children use various types of thinking that may not be specific to language at all—such as the ability to classify the world into categories (people or objects, for instance) and to understand the relations among things. These capabilities, coupled with a unique hu­­­man ability to grasp what others intend to communicate, allow language to happen. The new findings indicate that if researchers truly want to understand how children, and others, learn languages, they need to look outside of Chomsky’s theory for guidance.

This conclusion is important because the study of language plays a central role in diverse disciplines—from poetry to artificial intelligence to linguistics itself; misguided methods lead to questionable results. Further, language is used by humans in ways no animal can match; if you understand what language is, you comprehend a little bit more about human nature.

Read the full text here!

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Famous psychology study ‘killed by replication’: does a pencil in your mouth make you feel happy?

Replication is very important in science, but sometimes the results can hurt. Hurt a lot. Yesterday I found this new replication meta-study on a very famous insight in psychology via this tweet by Stuart Ritchie:

The study he discusses is the 1988 study by Strack, Martin & Strepper:

We investigated the hypothesis that people’s facial activity influences their affective responses. Two studies were designed to both eliminate methodological problems of earlier experiments and clarify theoretical ambiguities. This was achieved by having subjects hold a pen in their mouth in ways that either inhibited or facilitated the muscles typically associated with smiling without requiring subjects to pose in a smiling face. Study 1’s results demonstrated the effectiveness of the procedure. Subjects reported more intense humor responses when cartoons were presented under facilitating conditions than under inhibiting conditions that precluded labeling of the facial expression in emotion categories. Study 2 served to further validate the methodology and to answer additional theoretical questions. The results replicated Study 1’s findings and also showed that facial feedback operates on the affective but not on the cognitive component of the humor response. Finally, the results suggested that both inhibitory and facilitatory mechanisms may have contributed to the observed affective responses.

It’s a famous study and I think there is indeed a big chance you’ve heard about the results.

But this new replication meta-study examining 17 studies replicating the original research is quite damning:

According to the facial feedback hypothesis, people’s affective responses can be influenced by their own facial expression (e.g., smiling, pouting), even when their expression did not result from their emotional experiences. For example, Strack, Martin, and Stepper (1988) instructed participants to rate the funniness of cartoons using a pen that they held in their mouth. In line with the facial feedback hypothesis, when participants held the pen with their teeth (inducing a “smile”), they rated the cartoons as funnier than when they held the pen with their lips (inducing a “pout”). This seminal study of the facial feedback hypothesis has not been replicated directly. This registered replication report describes the results of 17 independent direct replications of Study 1 from Strack et al. (1988), all of which followed the same vetted protocol. A meta- analysis of these studies examined the difference in funniness ratings between the “smile” and “pout” conditions. The original Strack et al. (1988) study reported a rating difference of 0.82 units on a 10 point Likert scale. Our meta-analysis revealed a rating difference of 0.03 units with a 95% confidence interval ranging from -0.11 to 0.16.

Or shown as an image:

https://pbs.twimg.com/media/CqJkhbBVUAEDZgN.jpg

Via the tweet conversations following the tweet by Stuart Ritchie I also found this reply by Strack and this reply on this reply by the researchers.

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