school-age child

Early development

Children’s understanding, and their use of memory and learning strategies, is a considerably more complex situation than most of us realize. To get some feeling for this complexity, let’s start by looking at a specific area of knowledge: mathematics.

Children's math understanding

Here’s a math problem:

Pete has 3 apples. Ann also has some apples. Pete and Ann have 9 apples altogether. How many apples does Ann have?

This seems pretty straightforward, right? How about this one:

Pete and Ann have 9 apples altogether. Three of these belong to Pete and the rest belong to Ann. How many apples does Ann have?

The same problem, phrased slightly differently. Would it surprise you to know that this version is more likely to be correctly answered by children than the first version?

Whether or not a child solves a math problem correctly is not simply a matter of whether he or she knows the math — the way the problem is worded plays a crucial part in determining whether the child understands the problem correctly. Slight (and to adult eyes, insignificant) differences in the wording of a problem have a striking effect on whether children can solve it.

Mathematics also provides a clear demonstration of the seemingly somewhat haphazard development in cognitive abilities. It’s not haphazard, of course, but it sometimes appears that way from the adult perspective. In math, understanding different properties of the same concept can take several years. For example, children’s understanding of addition and subtraction is not an all-or-none business; adding as combining is grasped by young children quite early, but it takes some 2 to 3 years at school to grasp the essential invariants of additive relations. Multiplicative relations are even harder, with children up to age 10 or so often having great difficulty with proportion, probability, area and division.

Neurological differences between children and adults

Part of the problems children have with math stems from developmental constraints — their brains simply aren’t ready for some concepts. A recent imaging study of young people (aged 8-19 years) engaged in mental arithmetic, found that on simple two-operand addition or subtraction problems (for which accuracy was comparable across age), older subjects showed greater activation in the left parietal cortex, along the supramarginal gyrus and adjoining anterior intra-parietal sulcus as well as the left lateral occipital temporal cortex. Younger subjects showed greater activation in the prefrontal cortex (including the dorsolateral and ventrolateral prefrontal cortex and the anterior cingulate cortex), suggesting that they require comparatively more working memory and attentional resources to achieve similar levels of performance, and greater activation of the hippocampus and dorsal basal ganglia, reflecting the greater demands placed on both declarative and procedural memory systems.

In other words, the evidence suggests that the left inferior parietal cortex becomes increasingly specialized for mental arithmetic with practice, and this process is accompanied by a reduced need for memory and attentional resources.

Not just a matter of brain maturation

But this isn't the whole story. As the earlier example indicated, difficulties in understanding some concepts are often caused by the way the concepts are explained. This is why it’s so important to keep re-phrasing problems and ideas until you find one that “clicks”. Other difficulties are caused by the preconceptions the child brings with them — cultural practices, for example, can sometimes help and sometimes hinder learning.

Other domains: neurological differences between children and adults

What's true of mathematics is also true of other learning areas. When we teach children, we do need to consider developmental constraints, but recent studies suggest we may have over-estimated the importance of development.

In an intriguing imaging study, brain activity in children aged 7-10 and adults (average age 25 years) while doing various language tasks was compared. Six sub-regions in the left frontal and the left extrastriate cortex were identified as being significant. Both these areas are known to play a key role in language processing and are believed to undergo substantial development between childhood and adulthood.

Now comes the interesting part. The researchers attempted to determine whether these differences between children and adults were due to brain maturation or simply the result of slower and less accurate performance by children. By using information regarding each individual's performance on various tasks, they ended up with only two of the six sub-regions (one in the frontal cortex, one in the extrastriate cortex) showing differences that were age-related rather than performance-related (with the extrastriate region being more active in children than adults, while the frontal region was active in adults and not in children).

The researchers concluded that, yes, children do appear to use their brains differently than adults when successfully performing identical language tasks; however, although multiple regions appeared to be differentially active when comparing adults and children, many of those differences were due to performance discrepancies, not age-related maturation.

Childhood amnesia

Let's talk about childhood amnesia for a moment. "Childhood amnesia" is a term for what we all know -- we have very few memories of our early years. This is so familiar, you may never have considered why this should be so. But the reason is not in fact obvious. Freud speculated that we repressed those early memories (but Freud was hung up on repression); modern cognitive psychologists have considered immature memory processing skills may be to blame. This is surely true for the first months -- very young babies have extremely limited abilities at remembering anything for long periods of time (months), and research suggests that the dramatic brain maturation that typically occurs between 8 and 12 months is vital for long-term memory.

But an intriguing study (carried out by researchers at my old stomping ground: the University of Otago in New Zealand) has provided evidence that an important stumbling block in our remembrance of our early years is the child's grasp of language. If you don't have the words to describe what has happened, it seems that it is very difficult to encode it as a memory -- or at least, that it is very difficult to retrieve (before you leap on me with examples, let me add that noone is saying that every memory is encoded in words -- this is palpably not true).

This finding is supported by a recent study that found that language, in the form of specific kinds of sentences spoken aloud, helped 4-year-old children remember mirror image visual patterns.

The role of social interaction in memory development

Another study from my favorite university looked at the role mothers played in developing memory in their young children. The study distinguished between reminiscing (discussing shared experiences) and recounting (discussing unshared experiences). Children 40 months old and 58 months old were studied as they talked about past events with their mothers. It was found that mothers who provided more memory information during reminiscing and requested more memory information during recounting had children who reported more unique information about the events.

In general, parents seldom try to teach memory strategies directly to children, but children do learn strategies by observing and imitating what their parents do and this may in fact be a more effective means of teaching a child rather than by direct instruction.

But parents not only provide models of behavior; they also guide their children's behavior. The way they do this is likely to be influenced by their own beliefs about their children’s mnemonic abilities. If you don't believe your child can possibly remember something, you are unlikely to ask them to make the effort. But when parents ask 2 – 4 year olds to remind them to do something in the future, even 2 year olds remember to remind their parents of promised treats 80% of the time.

By 3 yrs old, children whose mothers typically asked questions about past events performed better on memory tasks than those children whose mothers only questioned them about present events. Observation of mothers as they taught their 4 year olds to sort toys, copy etch-a-sketch designs, and respond to questions regarding hypothetical situations found 3 interaction styles found that related to the child’s performance:

  • imperative-normative, in which mother gave little justification for requests or demands;
  • subjective, in which mother encouraged child to see his own behaviour from another’s point of view;
  • cognitive-rational, in which mother offered logical justifications for requests and demands.

Children whose mothers used the last two styles were more verbal and performed better on cognitive tasks.

A study of kindergarten and elementary school teachers found that children from classes where teachers frequently made strategy suggestions were better able to verbalize aspects of memory training and task performance. Although this made no difference for high achieving children, average and low achievers were more likely to continue using the trained strategy if they had teachers who frequently made strategy suggestions.

Conclusion

What lessons can we learn from all this?

First, we must note that there are indeed developmental constraints on children's capabilities that are rooted in physical changes in the brain. Some of these are simply a matter of time, but others are changes that require appropriate stimulation and training.

Secondly, the importance of language in enabling the child cannot be overestimated.

And thirdly, for children as with older adults, expectations about memory performance can reduce their capabilities. Supportive, directed assistance in developing memory and reasoning strategies can be very effective in helping even very young children.

References: 

  • Best, D.L. 1992. The role of social interaction in memory improvement. In D. Herrmann, H. Weingartner, A. Searleman & C. McEvoy (eds.) Memory Improvement: Implications for Memory Theory. New York: Springer-Verlag. pp 122-49.
  • Liston, C. & Kagan, J. 2002. Brain development: Memory enhancement in early childhood. Nature, 419, 896-896.
  • Reese, E. & Brown, N. 2000. Reminiscing and recounting in the preschool years. Applied Cognitive Psychology, 14 (1), 1-17.
  • Rivera, S.M., Reiss, A.L., Eckert, M.A. & Menon, V. 2005. Developmental Changes in Mental Arithmetic: Evidence for Increased Functional Specialization in the Left Inferior Parietal Cortex. Cerebral Cortex, 15 (11), 1779-1790.
  • Schlaggar, B.L., Brown, T.T., Lugar, H.M., Visscher, K.M., Miezin, F.M. & Petersen, S.E. 2002. Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science, 296, 1476-9.
  • Vergnaud, G. 1997. The Nature of Mathematical Concepts. In T. Nunes & P. Bryant (Eds.), Learning and Teaching Mathematics: An International Perspectives (pp. 5-28). Eastern Sussex: Psychology Press Ltd.

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Air pollution exposure walking to school linked to slower growth of working memory

  • A large study has found higher levels of traffic-related air pollution, still within the EU safe limits, are associated with slower growth in working memory capacity in primary/elementary school children.

A Spanish study investigating the effects of traffic-related air pollution on children walking to school has found higher levels of particulate matter and black carbon were associated with decreased growth in working memory capacity. Working memory capacity grows during childhood (and tends to fall in old age).

The study involved 1,234 children aged 7-10, from 39 schools across the city of Barcelona. The children were tested four times over a year to establish their developmental trajectories in working memory and inattentiveness. Average particulate matter, black carbon, and nitrogen dioxide, were estimated for the children’s walking routes using standard measures.

None of the pollutants were associated with inattentiveness. The effect of NO2 on working memory was inconclusive. However, increased concentrations of particulate matter and black carbon were associated with a reduction in the annual growth of working memory of 4.6% and 3.9%, respectively. Boys were more affected than girls.

The study followed an earlier study showing that exposure to traffic-related pollutants in schools was associated with slower cognitive development. Research has previously shown that 20% of a child's daily dose of black carbon (which is directly related to traffic) is inhaled during urban commutes.

The finding emphasizes that even “short exposures to very high concentrations of pollutants can have a disproportionately high impact on health”, and this may be especially true for children, with their smaller lung capacity and higher breathing rate.

The researchers emphasize that the solution for parents is not to stop children walking to school, since those who commute by car or public transport are also exposed to the pollution. Rather, the aim should be to try and find (or make) less polluted, low-traffic paths to school.

https://www.eurekalert.org/pub_releases/2017-10/bifg-ape100517.php

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Air pollution during pregnancy linked to cognitive impairment in children

  • A largish study involving school-age children not at any particular risk has found that higher levels of air pollution experienced by the mother during pregnancy are linked to less gray matter in some brain regions.

Research using data from a population-based birth cohort from Rotterdam, in The Netherlands, has found that children exposed to higher levels of air pollution when they were in womb had significantly thinner cortex in several brain regions. Some of this appeared to be related to impaired inhibitory control.

The study involved 783 children aged 6 to 10, who were given brain imaging and cognitive tests. Levels of air pollution in the mother’s environment during pregnancy were estimated using a standardized procedure. Mean fine particle levels were 20.2 μg/m3, and nitrogen dioxide levels were 39.3μg/m3. Note that the EU limit for mean fine particles is actually above that (25μg/m3), while the NO2 level is at the EU limit (40μg/m3), with 45% of the Dutch population experiencing higher levels. The World Health Organization sets a much lower level for fine particles: 10 μg/m3.

Children whose mothers were smokers were excluded from the study, as were children from areas where pollution measures weren’t available. Children included tended to be from a higher socio-economic position compared to those not included. Moreover, children with ADHD, or developmental or behavioral problems, were also excluded.

Global brain volume was not affected by fetal exposure. However, several brain regions showed significantly thinner cortex — in particular, the precuneus and rostral middle frontal regions, which partially accounted for the observed association between fetal exposure to fine particles and impaired inhibitory control (the ability to control your own behavior, especially impulsive behavior). This sort of cognitive impairment at early ages could have significant long-term consequences in academic achievement, later career success, and even in risk of mental disorders.

The findings are consistent with other studies linking acceptable air pollution levels with problems including cognitive impairment and child development.

https://www.eurekalert.org/pub_releases/2018-03/e-apl030818.php

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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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Air pollution linked to children's low GPAs

  • A large study links high levels of motor vehicle emissions around the home to poorer academic performance in children.
  • The findings support other studies that found similar results looking at vehicle pollution around schools.

Data from 1,895 fourth and fifth grade children living in El Paso, Texas has found that those who were exposed to high levels of motor vehicle emissions had significantly lower GPAs, even when accounting for other factors known to influence school performance.

The link between air pollution and academic performance may be direct (pollutants damage the brain) or indirect — through illness and absenteeism.

The finding adds to other evidence linking air pollution around schools to children's academic performance.

The level of toxic air pollutants around the children's homes was estimated using the Environmental Protection Agency's National Air Toxics Assessment. GPAs, as well as demographic factors, were assessed from parental questionnaires.

El Paso was ranked 8th out of 277 U.S. metropolitan areas for annual particulate pollution in 2014.

http://www.eurekalert.org/pub_releases/2015-08/uota-sla082715.php

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One Alzheimer's risk gene may begin to affect brains from childhood

A gene linked to Alzheimer's has been linked to brain changes in childhood. This gene, SORL1, has two connections to Alzheimer’s: it carries the code for the sortilin-like receptor, which is involved in recycling some molecules before they develop into amyloid-beta; it is also involved in lipid metabolism, putting it at the heart of the vascular risk pathway.

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Higher levels of omega-3 in diet associated with better sleep

A study involving 362 children with reading problems has found that 16 weeks of daily 600 mg supplements of omega-3 DHA from algal sources improved their sleep. According to a sleep questionnaire filled out by parents, 40% of these children had significant sleep problems. Monitoring of 43 of the poor sleepers found that children taking daily supplements of omega-3 had nearly one hour (58 minutes) more sleep and seven fewer waking episodes per night compared with children taking a placebo.

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More evidence of the value of gesture in teaching math

A new study claims to provide ‘some of the strongest evidence yet’ for the benefits of gesturing to help students learn.

The study involved 184 children aged 7-10, of whom half were shown videos of an instructor teaching math problems using only speech, while the rest were shown videos of the instructor teaching the same problems using both speech and gestures. The problem involved mathematical equivalence (i.e., 4+5+7=__+7), which is known to be critical to later algebraic learning.

04/2013

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Interactive robot trains kids with autism

A humanoid robot has been designed, and shows promise, for teaching joint attention to children with ASD. Robots are particularly appealing to children, and even more so to those with ASD.

http://www.futurity.org/health-medicine/interactive-robot-trains-kids-with-autism/

04/2013

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