problem solving

Digital media may be changing how you think

  • Reading from a screen may encourage users to focus on concrete details rather than more abstract thinking.

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.

http://www.eurekalert.org/pub_releases/2016-05/dc-dmm050516.php

Reference: 

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

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Finger tracing helps children doing geometry problems

  • Finger tracing key elements in worked problems seems to help some students better understand and apply mathematical concepts.

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.

http://www.eurekalert.org/pub_releases/2016-01/uos-ftc012816.php

Reference: 

[4046] Hu F-T, Ginns P, Bobis J. Getting the point: Tracing worked examples enhances learning. Learning and Instruction [Internet]. 2015 ;35:85 - 93. Available from: http://www.sciencedirect.com/science/article/pii/S0959475214000929

[4043] Ginns P, Hu F-T, Byrne E, Bobis J. Learning By Tracing Worked Examples. Applied Cognitive Psychology [Internet]. 2015 :n/a - n/a. Available from: http://onlinelibrary.wiley.com/doi/10.1002/acp.3171/abstract

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Some cognitive training helps less-educated older adults more

  • A large study in which older adults underwent various types of cognitive training has found that less-educated adults benefited more from training designed to speed processing.

Data from 2,800 participants (aged 65+) in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study has revealed that one type of cognitive training benefits less-educated people more than it does the more-educated.

While the effects of reasoning and memory training did not differ as a function of how much education the individual had, those older adults with less than a complete high school education experienced a 50% greater benefit from speed of information processing training than college graduates. This advantage was maintained for three years after the end of the training.

The training involved ten 60 to 75-minute sessions over six weeks that focused on visual search and processing information in shorter and shorter times.

Both reasoning and information processing speed training resulted in improved targeted cognitive abilities for 10 years among participants, but memory training did not. Memory training focused on mnemonic strategies for remembering lists and sequences of items, text material, and main ideas and details of stories and other text-based information. Reasoning training focused on improving the ability to solve problems containing a serial pattern.

The researchers speculate that speed of information processing training might help those with less than 12 years of education, who are at greater risk of dementia, close the gap between them and those with more education.

The training modules have been translated into online games delivered by Posit Science.

Less educated study participants were slightly older, less likely to be married, more likely to be African-American, and more likely to have hypertension or diabetes as well as heart disease than the more educated older adults.

http://www.eurekalert.org/pub_releases/2016-01/iu-irs012816.php

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Problem Solving

Older news items (pre-2010) brought over from the old website

Body movements can influence problem solving

There have been several studies in recent years finding that gestures can help us think, mainly by reducing working memory load. Now a study in which people were asked to tie the ends of two strings together has found that they could solve the problem more easily if they swung their arms while they thought. The strings were too far apart for a person holding one to reach the other, and there were several objects available to help solve the problem. The subjects were given eight, two-minute sessions to solve the problem, with 100 seconds devoted to finding a solution, interrupted by 20 seconds of exercise. During the exercise periods, some were told to swing their arms forward and backward, while others were told to alternately stretch their arms to the side. At the same time (to stop them consciously connecting these activities to the problem), they were told to count backwards by threes. The solution to the problem required attaching an object to one of the strings and swinging it so that it could be grasped while also holding the other string, and those in the arm-swinging group were 40% more likely to solve the problem — but, intriguingly, almost none of them were consciously aware of the connection between the exercise and the solution. The finding is another example of what is being called ‘embodied cognition’ — evidence that our bodies truly are part of our minds.

Thomas, L.E. & Lleras, A. 2009. Swinging into thought: Directed movement guides insight in problem solving. Psychonomic Bulletin & Review, in press.

http://www.eurekalert.org/pub_releases/2009-05/uoia-bmc051209.php

Brain's problem-solving function at work when we daydream

An imaging study has revealed that daydreaming is associated with an increase in activity in numerous brain regions, especially those regions associated with complex problem-solving. Until now it was thought that the brain's "default network" (which includes the medial prefrontal cortex, the posterior cingulate cortex and the temporoparietal junction) was the only part of the brain active when our minds wander. The new study has found that the "executive network" (including the lateral prefrontal cortex and the dorsal anterior cingulate cortex) is also active. Before this, it was thought that these networks weren’t active at the same time. It may be that mind wandering evokes a unique mental state that allows otherwise opposing networks to work in cooperation. It was also found that greater activation was associated with less awareness on the part of the subject that there mind was wandering.

Christoff, K. et al. 2009. Experience sampling during fMRI reveals default network and executive system contributions to mind wandering. Proceedings of the National Academy of Sciences, 106 (21), 8719-8724. 

http://www.eurekalert.org/pub_releases/2009-05/uobc-bpf051109.php

Searching in space is like searching your mind

A study of search modes in both spatial and abstract settings has found evidence that how we look for things, such as our car keys or umbrella, could be related to how we search for more abstract needs, such as words in memory or solutions to problems. The studies compared two search modes: exploitation, where seekers stay with a place or task until they have gotten appreciable benefit from it, and exploration, where seekers move quickly from one place or one task to another, looking for a new set of resources to exploit. In the study, participants "foraged" in a computerized world, moving around until they stumbled upon a hidden supply of resources, then deciding if and when to move on, and in which direction. The scientists tracked their movements. Two different worlds ("clumpy", with fewer but richer resources, and "diffuse", with many more, but much smaller, supplies) encouraged one mode or other. The idea was to "prime" the optimal foraging strategy for each world. The volunteers then participated in a more abstract, intellectual search task -- a computerized game akin to Scrabble. It was found that although the human brain appears capable of using exploration or exploitation search modes depending on the demands of the task, it also has a tendency through "priming" to continue searching in the same way even if in a different domain, such as when switching from a spatial to an abstract task. Moreover, people who have a tendency to use one mode more in one task have a similar tendency to use that mode more in other tasks. The findings also support the view that goal-directed cognition is an evolutionary descendant of spatial-foraging behavior.

Hills, T.T., Todd, P.M.  & Goldstone, R.L. 2008. Search in External and Internal Spaces: Evidence for Generalized Cognitive Search Processes. Psychological Science, 19 (8), 802-808.

http://www.eurekalert.org/pub_releases/2008-09/iu-sis090908.php

Insight into insight

A study investigating brain rhythms and their dynamics while volunteers solved verbal problems has shed light on insightful problem-solving. The findings indicate that focusing or attending too much on a topic can have a detrimental effect, and that a strong Aha! sensation involves minimal metacognitive (monitoring of one's own thoughts) processes and unconscious or, better yet, automatic, recombination of information. Interestingly, when clues were provided, it was possible to predict success or failure based on the brain state prior to the clue presentation.

Sandkühler, S. & Bhattacharya, J. 2008. Deconstructing Insight: EEG Correlates of Insightful Problem Solving. PLoS ONE 3(1): e1459. Full text available at http://www.plosone.org/doi/pone.0001459

http://www.physorg.com/news120290586.html

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Group settings hurt expressions of intelligence, especially in women

March, 2012

Comparing performance on an IQ test when it is given under normal conditions and when it is given in a group situation reveals that IQ drops in a group setting, and for some (mostly women) it drops dramatically.

This is another demonstration of stereotype threat, which is also a nice demonstration of the contextual nature of intelligence. The study involved 70 volunteers (average age 25; range 18-49), who were put in groups of 5. Participants were given a baseline IQ test, on which they were given no feedback. The group then participated in a group IQ test, in which 92 multi-choice questions were presented on a monitor (both individual and group tests were taken from Cattell’s culture fair intelligence test). Each question appeared to each person at the same time, for a pre-determined time. After each question, they were provided with feedback in the form of their own relative rank within the group, and the rank of one other group member. Ranking was based on performance on the last 10 questions. Two of each group had their brain activity monitored.

Here’s the remarkable thing. If you gather together individuals on the basis of similar baseline IQ, then you can watch their IQ diverge over the course of the group IQ task, with some dropping dramatically (e.g., 17 points from a mean IQ of 126). Moreover, even those little affected still dropped some (8 points from a mean IQ of 126).

Data from the 27 brain scans (one had to be omitted for technical reasons) suggest that everyone was initially hindered by the group setting, but ‘high performers’ (those who ended up scoring above the median) managed to largely recover, while ‘low performers’ (those who ended up scoring below the median) never did.

Personality tests carried out after the group task found no significant personality differences between high and low performers, but gender was a significant variable: 10/13 high performers were male, while 11/14 low performers were female (remember, there was no difference in baseline IQ — this is not a case of men being smarter!).

There were significant differences between the high and low performers in activity in the amygdala and the right lateral prefrontal cortex. Specifically, all participants had an initial increase in amygdala activation and diminished activity in the prefrontal cortex, but by the end of the task, the high-performing group showed decreased amygdala activation and increased prefrontal cortex activation, while the low performers didn’t change. This may reflect the high performers’ greater ability to reduce their anxiety. Activity in the nucleus accumbens was similar in both groups, and consistent with the idea that the students had expectations about the relative ranking they were about to receive.

It should be pointed out that the specific feedback given — the relative ranking — was not a factor. What’s important is that it was being given at all, and the high performers were those who became less anxious as time went on, regardless of their specific ranking.

There are three big lessons here. One is that social pressure significantly depresses talent (meetings make you stupid?), and this seems to be worse when individuals perceive themselves to have a lower social rank. The second is that our ability to regulate our emotions is important, and something we should put more energy into. And the third is that we’ve got to shake ourselves loose from the idea that IQ is something we can measure in isolation. Social context matters.

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Teaching those with ASD to 'talk things through' may help them plan

February, 2012

A study showing that those with ASD are less likely to use inner speech when planning their actions, a failure linked to their communication ability, has implications for us all.

I’ve reported before on evidence that young children do better on motor tasks when they talk to themselves out loud, and learn better when they explain things to themselves or (even better) their mother. A new study extends those findings to children with autism.

In the study, 15 high-functioning adults with Autism Spectrum Disorder and 16 controls (age and IQ matched) completed the Tower of London task, used to measure planning ability. This task requires you to move five colored disks on three pegs from one arrangement to another in as few moves as possible. Participants did the task under normal conditions as well as under an 'articulatory suppression' condition whereby they had to repeat out loud a certain word ('Tuesday' or 'Thursday') throughout the task, preventing them from using inner speech.

Those with ASD did significantly worse than the controls in the normal condition (although the difference wasn’t large), but they did significantly better in the suppression condition — not because their performance changed, but because the controls were significantly badly affected by having their inner speech disrupted.

On an individual basis, nearly 90% of the control participants did significantly worse on the Tower of London task when inner speech was prevented, compared to only a third of those with ASD. Moreover, the size of the effect among those with ASD was correlated with measures of communication ability (but not with verbal IQ).

A previous experiment had confirmed that these neurotypical and autistic adults both showed similar patterns of serial recall for labeled pictures. Half the pictures had phonologically similar labels (bat, cat, hat, mat, map, rat, tap, cap), and the other nine had phonologically dissimilar labels (drum, shoe, fork, bell, leaf, bird, lock, fox). Both groups were significantly affected by phonological similarity, and both groups were significantly affected when inner speech was prevented.

In other words, this group of ASD adults were perfectly capable of inner speech, but they were much less inclined to use it when planning their actions.

It seems likely that, rather than using inner speech, they were relying on their visuospatial abilities, which tend to be higher in individuals with ASD. Supporting this, visuospatial ability (measured by the block design subtest of the WAIS) was highly correlated with performance on the Tower of London test. Which may not seem surprising, but the association was minimal in control participants.

Complex planning is said to be a problem for many with ASD. It’s also suggested that the relative lack of inner speech use might contribute to some of the repetitive behaviors common in people with autism.

It may be that strategies targeted at encouraging inner speech may help those with ASD develop such skills. Such strategies include encouraging children to describe their actions out loud, and providing “parallel talk”, whereby an observer plays alongside the child while verbalizing their actions.

It is also suggested that children with ASD could benefit from verbal learning of their daily schedule at school rather than using visual timetables as is currently a common approach. This could occur in stages, moving from pictures to symbols, symbols with words, before finally being restricted to words only.

ASD is estimated to occur in 1% of the population, but perhaps this problem could be considered more widely. Rather than seeing this as an issue limited to those with ASD, we should see this as a pointer to the usefulness of inner speech, and its correlation with communication skills. As one of the researchers said: "These results show that inner speech has its roots in interpersonal communication with others early in life, and it demonstrates that people who are poor at communicating with others will generally be poor at communicating with themselves.”

One final comment: a distinction has been made between “dialogic” and “monologic” inner speech, where dialogic speech refers to a kind of conversation between different perspectives on reality, and monologic speech is simply a commentary to oneself about the state of affairs. It may be that it is specifically dialogic inner speech that is so helpful for problem-solving. It has been suggested that ASD is marked by a reduction in this kind of inner speech only, and the present researchers suggest further that it is this form of speech that may have inherently social origins and require training or experience in communicating with others.

The corollary to this is that it is only in those situations where dialogic inner speech is useful in achieving a task, that such differences between individuals will matter.

Clearly there is a need for much more research in this area, but it certainly provides food for thought.

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How your hands affect your thinking

October, 2011

Two recent studies in embodied cognition show that hand movements and hand position are associated with less abstract thinking.

I always like studies about embodied cognition — that is, about how what we do physically affects how we think. Here are a couple of new ones.

The first study involved two experiments. In the first, 86 American college students were asked questions about gears in relation to each other. For example, “If five gears are arranged in a line, and you move the first gear clockwise, what will the final gear do?” The participants were videotaped as they talked their way through the problem. But here’s the interesting thing: half the students wore Velcro gloves attached to a board, preventing them from moving their hands. The control half were similarly prevented from moving their feet — giving them the same experience of restriction without the limitation on hand movement.

Those who gestured commonly used perceptual-motor strategies (simulation of gear movements) in solving the puzzles. Those who were prevented from gesturing, as well as those who chose not to gesture, used abstract, mathematical strategies much more often.

The second experiment confirmed the results with 111 British adults.

The findings are consistent with the hypothesis that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving.

That can be helpful, but not always. Even when we are solving problems that have to do with motion and space, more abstract strategies may sometimes be more efficient, and thus an inability to use the body may force us to come up with better strategies.

The other study is quite different. In this study, college students searched for a single letter embedded within images of fractals and other complex geometrical patterns. Some did this while holding their hands close to the images; others kept their hands in their laps, far from the images. This may sound a little wacky, but previous research has shown that perception and attention are affected by how close our hands are to an object. Items near our hands tend to take priority.

In the first experiment, eight randomly chosen images were periodically repeated 16 times, while the other 128 images were only shown once. The target letter was a gray “T” or “L”; the images were colorful.

As expected, finding the target letter was faster the more times the image had been presented. Hand position didn’t affect learning.

In the second experiment, a new set of students were shown the same shown-once images, while 16 versions of the eight repeated images were created. These versions varied in their color components. In this circumstance, learning was slower when hands were held near the images. That is, people found it harder to recognize the commonalities among identical but differently colored patterns, suggesting they were too focused on the details to see the similarities.

These findings suggest that processing near the hands is biased toward item-specific detail. This is in keeping with earlier suggestions that the improvements in perception and attention near the hands are item-specific. It may indeed be that this increased perceptual focus is at the cost of higher-order function such as memory and learning. This would be consistent with the idea that there are two largely independent visual streams, one of which is mainly concerned with visuospatial operations, and the other of which is primarily for more cognitive operations (such as object identification).

All this may seem somewhat abstruse, but it is worryingly relevant in these days of hand-held technological devices.

The point of both these studies is not that one strategy (whether of hand movements or hand position) is wrong. What you need to take away is the realization that hand movements and hand position can affect the way you approach problems, and the things you perceive. Sometimes you want to take a more physical approach to a problem, or pick out the fine details of a scene or object — in these cases, moving your hands, or holding something in or near your hands, is a good idea. Other times you might want to take a more abstract/generalized approach — in these cases, you might want to step back and keep your body out of it.

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Helping students & children get enough sleep

October, 2011

Simple interventions can help college students improve their sleep. Regular sleep habits are important for young children. Sleep deprivation especially affects performance on open-ended problems.

One survey of nearly 200 undergraduate college students who were not living with a parent or legal guardian found that 55% reported getting less than seven hours sleep. This is consistent with other surveys. The latest study confirms such a result, but also finds that students tend to think their sleep quality is better than it is (70% of students surveyed described their sleep as "fairly good" or better). It’s suggested that this disconnect arises from students making comparisons in an environment where poor sleep is common — even though they realized, on being questioned, that poor sleep undermined their memory, concentration, class attendance, mood, and enthusiasm.

None of this is surprising, of course. But this study did something else — it tried to help.

The researchers launched a campuswide media campaign consisting of posters, student newspaper advertisements and a "Go to Bed SnoozeLetter", all delivering information about the health effects of sleep and tips to sleep better, such as keeping regular bedtime and waking hours, exercising regularly, avoiding caffeine and nicotine in the evening, and so on. The campaign cost less than $2,500, and nearly 10% (90/971) said it helped them sleep better.

Based on interviews conducted as part of the research, the researchers compiled lists of the top five items that helped and hindered student sleep:

Helpers

  • Taking time to de-stress and unwind
  • Creating a room atmosphere conducive to sleep
  • Being prepared for the next day
  • Eating something
  • Exercising

Hindrances

  • Dorm noise
  • Roommate (both for positive/social reasons and negative reasons)
  • Schoolwork
  • Having a room atmosphere not conducive to sleep
  • Personal health issues

In another study, this one involving 142 Spanish schoolchildren aged 6-7, children who slept less than 9 hours and went to bed late or at irregular times showed poorer academic performance. Regular sleep habits affected some specific skills independent of sleep duration.

69% of the children returned home after 9pm at least three evenings a week or went to bed after 11pm at least four nights a week.

And a recent study into the effects of sleep deprivation points to open-ended problem solving being particularly affected. In the study, 35 West Point cadets were given two types of categorization task. The first involved cate­gorizing drawings of fictional animals as either “A” or “not A”; the second required the students to sort two types of fic­tional animals, “A” and “B.” The two tests were separated by 24 hours, during which half the students had their usual night’s sleep, and half did not.

Although the second test required the students to learn criteria for two animals instead of one, sleep deprivation impaired performance on the first test, not the second.

These findings suggest the fault lies in attention lapses. Open-ended tasks, as in the first test, require more focused attention than those that offer two clear choices, as the second test did.

News reports on sleep deprivation are collated here.

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[2521] Orzech KM, Salafsky DB, Hamilton LA. The State of Sleep Among College Students at a Large Public University. Journal of American College Health [Internet]. 2011 ;59:612 - 619. Available from: http://www.tandfonline.com/doi/abs/10.1080/07448481.2010.520051

[2515] Cladellas R, Chamarro A, del Badia MM, Oberst U, Carbonell X. Efectos de las horas y los habitos de sueno en el rendimiento academico de ninos de 6 y 7 anos: un estudio preliminarEffects of sleeping hours and sleeping habits on the academic performance of six- and seven-year-old children: A preliminary study. Cultura y Educación. 2011 ;23(1):119 - 128.

Maddox WT; Glass BD; Zeithamova D; Savarie ZR; Bowen C; Matthews MD; Schnyer DM. The effects of sleep deprivation on dissociable prototype learning systems. SLEEP 2011;34(3):253-260.

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The right sort of video game can increase your intelligence

June, 2011

Games that use the n-back task, designed to challenge working memory, may improve fluid intelligence, but only if the games are at the right level of difficulty for the individual.

It has been difficult to train individuals in such a way that they improve in general skills rather than the specific ones used in training. However, recently some success has been achieved using what is called an “n-back” task, a task that involves presenting a series of visual and/or auditory cues to a subject and asking the subject to respond if that cue has occurred, to start with, one time back. If the subject scores well, the number of times back is increased each round.

In the latest study, 62 elementary and middle school children completed a month of training on a computer program, five times a week, for 15 minutes at a time. While the active control group trained on a knowledge and vocabulary-based task, the experimental group was given a demanding spatial task in which they were presented with a sequence of images at one of six locations, one at a time, at a rate of 3s. The child had to press one key whenever the current image was at the same location as the one n items back in the series, and another key if it wasn’t. Both tasks employed themed graphics to make the task more appealing and game-like.

How far back the child needed to remember depended on their performance — if they were struggling, n would be decreased; if they were meeting the challenge, n would be increased.

Although the experimental and active control groups showed little difference on abstract reasoning tasks (reflecting fluid intelligence) at the end of the training, when the experimental group was divided into two subgroups on the basis of training gain, the story was different. Those who showed substantial improvement on the training task over the month were significantly better than the others, on the abstract reasoning task. Moreover, this improvement was maintained at follow-up testing three months later.

The key to success seems to be whether or not the games hit the “sweet spot” for the individual — fun and challenging, but not so challenging as to be frustrating. Those who showed the least improvement rated the game as more difficult, while those who improved the most found it challenging but not overwhelming.

You can try this task yourself at http://brainworkshop.sourceforge.net/.

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Jaeggi, Susanne M, Martin Buschkuehl, John Jonides, and Priti Shah. “Short- and long-term benefits of cognitive training.” Proceedings of the National Academy of Sciences of the United States of America 2011 (June 13, 2011): 2-7. http://www.ncbi.nlm.nih.gov/pubmed/21670271.

[1183] Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. From the Cover: Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences [Internet]. 2008 ;105(19):6829 - 6833. Available from: http://www.pnas.org/content/early/2008/04/25/0801268105.abstract

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Effect of motivation on IQ score

May, 2011

A new review pointing to the impact of motivation on IQ score reminds us that this factor is significant, particularly for predicting accomplishments other than academic achievement.

Whether IQ tests really measure intelligence has long been debated. A new study provides evidence that motivation is also a factor.

Meta-analysis of 46 studies where monetary incentives were used in IQ testing has revealed a large effect of reward on IQ score. The average effect was equivalent to nearly 10 IQ points, with the size of the effect depending on the size of the reward. Rewards greater than $10 produced increases roughly equivalent to 20 IQ points. The effects of incentives were greater for individuals with lower baseline IQ scores.

Follow-up on a previous study of 500 boys (average age 12.5) who were videotaped while undertaking IQ tests in the late 80s also supports the view that motivation plays a part in IQ. The tapes had been evaluated by those trained to detect signs of boredom and each boy had been given a motivational score in this basis. Some 12 years later, half the participants agreed to interviews about their educational and occupational achievements.

As found in other research, IQ score was found to predict various life outcomes, including academic performance in adolescence and criminal convictions, employment, and years of education in early adulthood. However, after taking into account motivational score, the predictiveness of IQ score was significantly reduced.

Differences in motivational score accounted for up to 84% of the difference in years of education (no big surprise there if you think about it), but only 25% of the differences relating to how well they had done in school during their teenage years.

In other words, test motivation can be a confounding factor that has inflated estimates of the predictive validity of IQ, but the fact that academic achievement was less affected by motivation demonstrates that high intelligence (leaving aside the whole thorny issue of what intelligence is) is still required to get a high IQ score.

This is not unexpected — from the beginning of intelligence testing, psychologists have been aware that test-takers vary in how seriously they take the test, and that this will impact on their scores. Nevertheless, the findings are a reminder of this often overlooked fact, and underline the importance of motivation and self-discipline, and the need for educators to take more account of these factors.

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