ArticlePDF Available

Neuroscience and Education: Issues and Opportunities

Authors:

Abstract

This commentary builds on the work of the recent TLRP-ESRC seminar series on Neuroscience and Education, which brought together national and international educational and scientific experts to discuss how these two areas might work together in the future, particularly in regard to collaborative research. By the time of its conclusion in June 2006, over 400 teachers, educational researchers, psychologists and neuroscientists had attended one or more of the events in this series. Each event involved formal discussions about the theoretical and methodological issues arising within this emergent and interdisciplinary field of enquiry, and the opportunities that may lie ahead.
Neuroscience and Education:
Issues and Opportunities
A Commentary by the Teaching and Learning Research Programme
Improving education is a national priority for the UK. In this
Commentary, we explore the scope for our emerging knowledge of
the working of the brain to contribute to better educational outcomes,
especially for children.
This publication unites two of the Economic and Social Research Council’s principal concerns. One is for
education. The Teaching and Learning Research Programme is the ESRC’s largest research initiative. It is
dedicated to performing excellent research that leads to better education for people at all stages of life.
From its inception, it has promoted discussion of the link between education and neuroscience.
In addition, the ESRC is one of the UK’s main supporters of psychology research. Our programmes reflect
an awareness that our knowledge of the brain is growing in power, and will be relevant to areas of social
science such as economic and political behaviour as well as to education.
In this publication, the latest in a series of TLRP Commentaries, researchers supported by the TLRP point to
a range of issues at the junction between neuroscience and education. As they say, the brain is the principal
organ involved in learning. It is natural that our increased knowledge of its working can inform educational
practice. But as they also make clear, attempts to introduce neuroscience approaches into the classroom
have to date been of mixed quality. Often they have relied too little upon research evidence and too much on
impressive-sounding but scientifically questionable formulae.
The authors leave us in no doubt that these are early days in this story. Because of the rapid progress now
being observed throughout neuroscience, some approaches that are now in use may soon be seen to be
invalid. Others that are now used will become better-corroborated. And unexpected approaches may
emerge from research now under way.
The ESRC is delighted to be involved in this exciting new field of science. We are keen that it should not be
regarded as a one-way process in which neuroscience sheds light on how people learn. Instead, we want a
two-way cooperation in which our knowledge of learning and of the brain feed one another. The result will be
new knowledge about neuroscience and about education, and improved learning outcomes.
We would welcome your response to this Commentary via our web site: www.esrcsocietytoday.ac.uk
Professor Ian Diamond FBA AcSS
Chief Executive
The Economic and Social Research Council
3
contents
The core team of the TLRP Seminar Series ‘Collaborative Frameworks in Neuroscience and Education’ were:
Sarah-Jayne Blakemore Institute of Cognitive Neuroscience, University College London
Guy Clax
Authored by Paul Howard-Jones (Graduate School of Education, University of Bristol)
on behalf of TLRP Seminar Series core team, with contributions from (in order of
appearance): Andrew Pollard, Sarah-Jayne Blakemore, Peter Rogers, Usha Goswami,
Brian Butterworth, Eric Taylor, Aaron Williamon, John Morton and Liane Kaufmann.
Introduction 4
Background 5
About the Brain 6
Brain Development 8
Early Years 8
Adolescence 8
Adulthood 9
Brain Care 10
Omega 3 10
Caffeine 10
Sleep 11
Water 11
Neuroscience and Developmental Disorders 12
Dyslexia 12
Dyscalculia 13
ADHD 14
Strategies for Teaching and Learning 15
Commercial ‘brain-based’ Programmes 15
Brain Scan to Lesson plan: the Role of Cognition 17
Issues on the Horizon 19
Smart Pills 19
Neurofeedback 20
Biology is not Destiny 21
The Future: Can Education, Neuroscience and Psychology Work Together? 22
The Need for Cautious Optimism 24
Introduction
In a recent survey of teachers, almost 90 per cent thought that a knowledge of the brain was
important, or very important, in the design of educational programmes1. Indeed, for at least two
decades, educational programmes claiming to be ‘brain-based’ have been flourishing in the UK.
Unfortunately, these programmes have usually been produced without the involvement of
neuroscientific expertise, are rarely evaluated in their effectiveness and are often unscientific in
their approach. Perhaps this is unsurprising since, although the central role of the brain in
learning may appear self-evident, formal dialogue between neuroscience and education is a
relatively new phenomenon.
This commentary builds on the work of the recent TLRP-ESRC seminar series on Neuroscience and Education,
which brought together national and international educational and scientific experts to discuss how these two
areas might work together in the future, particularly in regard to collaborative research. By the time of its
conclusion in June 2006, over 400 teachers, educational researchers, psychologists and neuroscientists had
attended one or more of the events in this series. Each event involved formal discussions about the theoretical
and methodological issues arising within this emergent and interdisciplinary field of enquiry, and the
opportunities that may lie ahead. These discussions helped inform the production of this document, and their
summaries can be found on the series web site (www.bris.ac.uk/education/research/sites/brain).
This TLRP commentary reports upon only a selection of areas where neuroscientific issues are impacting upon
education. But it provides an impression of the breadth of issues involved and ample evidence that this
influence is increasing. In the future, education may have much to gain from greater cognisance of
the workings of the brain and improved dialogue with those working in the neuroscience and
psychological communities. Such dialogue will help:
Produce a common language and understanding about learning. This will inform
attitudes, educational approaches and the quality of discussion around an increasing
range of educational issues such as those associated with ADHD and dyslexia
Prompt further, more educationally-focused, scientific inquiry
Develop multidisciplinary projects and forums that can identify tractable and useful
research questions, develop collaborative research to address them, scrutinise
neuro-myths and evaluate programmes of ‘brain-based’ learning
Provide greater preparedness for imminent social, cultural and scientific change.
In every phase of education, from early years to later life, there are educational
issues whose understanding requires concepts about brain function. The debate
about how this knowledge should be included in educational thinking has only
just begun.
5
Neuroscience and Education: Issues and Opportunities
Background
The current resurgence of educational interest in the brain reflects an increasing belief amongst
some scientists, as well as educators, that education can benefit from neuroscientific insights
into how we develop and learn. In the past decade, several attempts have been made to
assess the opportunities offered by this new perspective, and a fresh interdisciplinary dialogue
appears to be emerging2,3,4,5. Most notably, in 2000, Professor Uta Frith and her colleague
Dr Sarah-Jayne Blakemore completed a commission by the Teaching and Learning Research
Programme (TLRP) to review neuroscientific findings that might be of relevance to educators6.
This review attacked a number of ‘neuromyths’, including those concerning critical periods for
educational development, and highlighted new areas of potential interest to educators such as
the role of innate mathematical abilities, visual imagery, implicit processes, and sleep in learning.
Rather than point out areas where neuroscience could be immediately applied in the classroom,
the review sought to highlight neuroscientific research questions that might interest educators,
an important initial step towards defining an interdisciplinary area of collaborative research.
In 1999, as the Blakemore and Frith report was being commissioned in the UK, the supranational project on
‘Learning Sciences and Brain Research’ was being launched by the Centre for Educational Research and
Innovation (CERI) at the Organisation for Economic Cooperation and Development (OECD). The first phase of
the project (1999-2002) brought together international researchers to review the potential implications of recent
research findings in brain research for policy-makers, with a second phase (2002-2006) channelling its activities
into three significant areas, Literacy, Numeracy and Lifelong Learning. This OECD project revealed the high level
of international interest in developing a dialogue between neuroscience and education, as well as highlighting
the diversity of approaches across the world7. In April 2005, the TLRP began its second initiative in this area, by
commissioning the seminar series ‘Collaborative Frameworks in Neuroscience and Education’, upon which this
commentary is based.
Andrew Pollard
Director of the TLRP
This commentary draws upon those areas explored in the recent
TLRP seminar series that appear most significant in terms of their
existing or future impact upon education. It highlights the need
for improved collaboration between neuroscience, psychology
and education, and how this may help us engage with the issues
and opportunities that lie ahead.
About the Brain
Understanding the educational significance of neuroscientific findings does not require a high
level of specialist knowledge. However, acquiring a few anatomical terms and phrases can be
useful and some of those you will encounter in this document are explained here.
The adult brain contains about 100 billion brain cells – or neurons. Each neuron consists of a cell body, to
which are connected dendrites and an axon.
The terminals at the end of the axon make contact with the dendrites of other neurons and allow connections,
or synapses, to form between neurons, In this way, complex neural networks can be created.
Dendrites Cell Body
Axon Myelin
Presynaptic
Terminal
Neuroscience and Education: Issues and Opportunities
7
Within such networks, signals can flow down the axons of one neuron and cross the synapse to other neurons,
allowing neurons to communicate with each other. The signal passing down the axon is electric, and its
progress is hastened by insulation around the axon known as myelin. However, the process that allows the
signal to pass through from the synaptic terminals to the dendrites of the next neuron is chemical. This process
involves transmission across the synaptic gap of special substances known as neurotransmitters.
The brain is often described in terms of two hemispheres, left and right, joined together by a mass of fibres
known as the corpus callosum. These can further be divided into four lobes: the frontal, parietal, occipital and
temporal. Each lobe has been associated with a different set of cognitive functions. The frontal lobe may,
perhaps, be of particular interest to educators due to its involvement with many different aspects of reasoning
as well as movement. The temporal lobe is associated with some aspects of memory, as well as auditory skills.
The parietal lobes are heavily involved in integrating information from different sources and have also been
associated with some types of mathematical skill. The occipital lobes are critical regions for visual processing.
However, as we shall see, it is not advisable to consider
any one part of the brain as being solely involved with
any one task. Any everyday task recruits a large and
broadly distributed set of neural networks that
communicate with each other in a complex fashion.
The cortex of the brain refers to the wrinkled surface of
these lobes. This surface is more wrinkled in humans
than any other species, a characteristic thought to
reflect our greater reliance upon higher level thought
processes. The evolutionary pressure to maximise
cortical area has resulted in some of our cortex existing
well below the outer surface. One notable example of
this is the cingulate cortex. The anterior (or forward) part
of the cingulate cortex becomes active when we
engage with a wide variety of tasks, and appears to
have a significant role in the allocation of attention.
Beyond identifying an area of the brain by its lobe,
scientists find it useful to name each valley or ridge on
the lobe’s wrinkled surface. A valley is referred to by the
latin name of sulcus (plural sulci) and a ridge is called a
gyrus (plural gyri).
The brain, however, is not composed entirely of cortex
and there are many other types of structure that are
critical for learning. These include structures deeper
within the brain such as the hippocampus – a part of
the brain critical to consolidating new memories, and
the amygdalae, which play an important role in our
emotional responses.
Frontal Lobe
Temporal Lobe
Parietal Lobe
Occipital Lobe
Cingulate Cortex
Brain Development
Early years: when should education begin?
Contrary to much popular belief, there is no convincing neuroscientific case for starting formal education as
early as possible. Three arguments for this approach have been used, but each involves the erroneous
interpretation, or over-interpretation, of the evidence. Firstly, it is true that synaptogenesis (the making of
synapses, or connections between neurons) occurs at a greater rate amongst children than in adults, as does
synaptic pruning (in which infrequently used connections are eliminated). It is fair to consider that such overt
changes in brain connectivity help make childhood a good time to learn. Much of what we know about
synaptogenesis and pruning is derived from research with other primates. In monkeys, these processes occur
early, suggesting that the first three years of their life may be especially significant in terms of learning8. However,
we now know that structural changes, including synaptogenesis and pruning, continue well into puberty and
throughout most of adolescence in some areas of the human brain that are very significant for education (see
below). A second argument, often linked to the first, has been constructed from the concept of the critical
period – a window in time when a child can learn a particular skill or ability. For example, it is known that adults
have more difficulty in discriminating sounds that they didn’t hear before the first six months of life9. However,
scientists now believe that critical periods should be referred to as sensitive periods. They are not fixed and
rigid. They exist more as subtle differences in the brain’s ability to be shaped by the environment. Furthermore,
they chiefly involve visual, movement and memory functions that are learned naturally in a normal environment.
Research on sensitive periods is fascinating but it cannot yet contribute to meaningful discussions regarding the
formal curriculum. The third argument points to research into the effects of enriched environments on learning
and the development of synapses10. However, this research involved rats living in environments that were no
more enriched than their natural habitat. These rats were compared with caged rats existing with no stimulus in
their cages at all. Thus, the results say more about the effects of deprived environments than enriched ones,
resonating with studies of neglected children showing delays and deficits in cognitive development. Overall,
there is some evidence to suggest that impoverished environments inhibit neural development, but no evidence
that enriched environments enhance it11.
Brain development in adolescence
Whatever the role of enriched environments, 0-3 years can be considered an
important period of brain development but so, it would appear, should later
childhood. Neuroscience has shown the surprising extent to which the brain
is still developing in adolescence, particularly in the frontal and parietal
cortices where synaptic pruning does not begin until after puberty12.
A second type of change occurring in these brain regions during
puberty involves myelination. This is the process by which the axons,
carrying messages from and to neurons, become insulated by a fatty
substance called myelin, thus improving the efficiency with which
information is communicated in the brain. In the frontal and parietal
lobes, myelination increases considerably throughout
adolescence and, to a less dramatic extent,
throughout adulthood, favouring an
increase in the speed with which
neural communication occurs in
these areas13.
Just as linguistically sensitive periods have been linked to synaptic pruning in very young children, continuing
synaptic pruning in adolescence suggests the possibility of sensitive periods here too. For example, research
has shown that teenagers activate different areas of the brain from adults when learning algebraic equations,
and this difference has been associated with a more robust process of long-term storage than that used
by adults18,19.
However, an important point here is that, while young children’s development in areas such as language is
advantaged by biological start-up mechanisms specific to these language skills, no such start-up mechanisms
for adolescents are likely to exist that are specific to the KS3 curriculum. Thus, formal education, as well as
social experience, may have a particularly important role in moulding the teenage brain.
Brain Development in Adulthood
Although the changes are less radical than during childhood, the brain continues to change and develop
through adulthood. With increasing age, of course, the brain does become less malleable, and we begin to lose
neurons at an increasing rate, although the educational effects of this loss are still not well understood.
However, there is also evidence that neurogenesis (the birth of new neurons) continues in at least one part of
the brain in adulthood. This is in the hippocampus, an area with an important role in learning and memory. The
brain’s continuing plasticity suggests that it is well designed for lifelong learning and adaptation to new situations
and experiences, and such adaptation can even bring about significant changes in its structure (see page 21 for
an example of this).
Neuroscience and Education: Issues and Opportunities
9
As in the earliest years of life, a second wave of reorganisation
of the brain is taking place during the teenage years. Research
on adolescent brain development suggests that secondary and
tertiary education are probably vital. The brain is still developing
during the period: it is thus presumably adaptable, and needs
to be moulded and shaped.
Dr Sarah-Jayne Blakemore
Institute of Cognitive Neuroscience
Taking these considerations together, one might expect the teenage brain to be less ready than an adult brain
to carry out a range of different processes. These include directing attention, planning future tasks, inhibiting
inappropriate behaviour, multitasking, and a variety of socially-orientated tasks. Indeed, psychological testing
has even shown a ‘pubertal dip’ in some areas of performance, such as matching pictures of facial expressions
to descriptors. In this task, 11-12 year olds performed worse than younger children14. A plateau has also been
shown for the prospective memory ability required to remember appointments15, as well as discontinuities in
abilities underlying social communication such as taking on the viewpoint of another person, or so-called
‘perspective-taking’16,17.
How does caffeine affect the learner?
The effects of caffeine (found in tea, coffee, cola, etc.) on our physiology and behaviour occur primarily
because caffeine blocks the action of adenosine at adenosine receptors. Adenosine is produced
naturally by the body. For example, adenosine levels increase during wakefulness and decrease during
sleep. Adenosine receptors are found on the surface of cells, including neurons, throughout the body
and brain. With regular consumption of caffeine, counter-regulatory changes occur in the adenosine
system, which result in adverse effects when caffeine is withdrawn. Even overnight abstinence from
caffeine can cause fatigue and slowed thinking and, although taking
some more caffeine rapidly reverses these effects, it does not appear to
increase functioning to above normal levels. It seems there is little net
benefit for mood and cognitive function from regular caffeine
consumption. Intermittent intake, as often occurs in children, increases
the risk of experiencing the fatigue and headache of caffeine withdrawal.
Dr Peter Rogers
Experimental Psychology
University of Bristol
Adenosine
Brain Care
Omega-3
The existing research suggests that good regular dietary habits are probably the most important nutritional issue
influencing educational performance and achievement20. By contrast with the proven importance of having
breakfast, evidence for the effectiveness of food supplements such as Omega-3 (in fish oils) is more
controversial. There have been several studies exploring the effects of fatty-acid supplements on children with
ADHD, but findings here have been contradictory and no clear consensus has emerged21. Further research may
help explain why such supplements appear to work in some contexts for some individuals with ADHD22 and not
in others23.There has been a flourishing of products on supermarket shelves that provide supplementary
Omega-3 despite the fact that, to date, there have been no published scientific studies that demonstrate
Omega-3 supplements enhance school performance or cognitive ability amongst the general population of
children. However, evidence for a link between ingesting Omega-3 and positive effects upon brain function does
appear to be growing, with intake being correlated with reduced risks of dementia in later life24 and consumption
of fish during pregnancy being correlated with infant IQ25.
Caffeine
Caffeine is the only psychoactive drug legally available to children and their consumption of it is very
widespread. A small 500 ml bottle of cola, such as those dispensed by a vending machine, has the same
amount of caffeine as a cup of coffee. It is hardly surprising, therefore, that children commonly experience
caffeine withdrawal26,27. Researchers recently studied children aged 9-10 who habitually consumed the
equivalent of no more than two cans a day of cola and showed these children demonstrated decreased
alertness relative to low users. Their alertness only rose to baseline levels when they had received some caffeine
and then, of course, only temporarily. Echoing the results of adult studies28, it would appear that the cola
‘caffeine fix’ provides only a momentary return to the state of alertness offered by a caffeine-free lifestyle.
Neuroscience and Education: Issues and Opportunities
11
Sleep
There is more bad news for the student ingesting caffeine to sustain late night revision: sleep is an important
part of learning. Neuroscience is beginning to reveal the processes by which sleep helps us ‘lay down’ and
consolidate our memories so that they remain more robust when we wish to access them later. The sleeping
brain has even been shown to reproduce the neural activities that characterise whatever we experienced in our
preceding hours of wakefulness29. The neurotransmitter ACh (acetylcholine) has been identified as a ‘switch’ that
changes our state of wakefulness and how we process information. High levels of ACh help maintain a wakeful
state that supports the encoding of information, while low levels of ACh during sleep minimise the encoding of
new memories but maximise consolidation of what has already been experienced30. As well as helping us
remember what we learn when awake, sleep also helps us prepare to learn more and use what we know to
generate insights31. Regular and sufficient sleep is essential for the brain to learn efficiently.
Water
In a popular book on educational kinaesthetics (Brain Gym), Cohen and Goldsmith33 ask teachers to encourage
their children to sing (with the tune of “Frere Jacques”):
“Let’s drink water, I love water.
It gives me En-er-gy”
The drinking of water has sometimes been promoted as a way to improve learning, usually on the basis that
even small amounts of dehydration can reduce cognitive ability. There are very few studies investigating the
effects of dehydration on children, but these few, together with adult studies34, confirm the deleterious effect of
even mild dehydration on our ability to think. However, a recent adult study has shown that drinking water when
not thirsty can also diminish cognitive ability35. In fact, we know that our brains possess a sophisticated system
by which we become thirsty when our bodies (including our brains) need water. So encouraging children to
drink water when they are thirsty may be a more sensible approach than constantly monitoring the amount of
water they consume. Exercise and unusually hot weather are the exception to this rule, when there is evidence
that children’s own monitoring systems are less reliable and they should be encouraged to drink in order to
avoid dehydration36,37.
Sleep is not just about resting but also about
consolidating what we have learnt during the day.
The sleeping brain (3 bottom images) appears to
reproduce the neural activities resembling those
recorded during preceding hours of wakefulness
(3 top images)32.
Neuroscience and Developmental Disorders
Dyslexia
Reading in adults is known to involve a network of language areas in the left hemisphere38, including the
posterior superior1temporal cortex. This area appears to be vitally involved in our ability to separate words into
sound-based components. Such phonological skills are a good indicator of later reading ability and a recent
study of young readers has shown that the amount of activity in this brain area correlates with these early
phonological skills39.
Children with developmental dyslexia display reduced activation in this and other typical left hemisphere sites for
reading, and also show atypical engagement of right hemisphere sites40,41,42. Some educational interventions that
improve language outcomes have also been shown to help remediate these differences in neural activity43,44,45.
This research demonstrates the potential effectiveness of brain imaging in investigating both learning difficulties
and the educational interventions intended to ameliorate them. It also demonstrates the plasticity of the brain
and the need to avoid considering differences in brain activity between different groups of children (and indeed
adults) as evidence for permanent, biologically determined differences in ability. Education can critically influence
how the brain operates.
As our understanding improves and techniques are further developed, it may be possible to identify children at
risk from dyslexia well before they begin school, allowing the earliest possible intervention. One promising
technique is electroencephalography (EEG), which involves placing a net of electrodes on the scalp to detect and
record the minute patterns of electrical activity produced by the brain. Because it is very non-invasive and child-
friendly, it has already proved immensely useful in identifying the earliest stirrings of linguistic awareness (see box).
What does Electroencephalography (EEG) tell us about dyslexia?
EEG has revealed infant processing of the stress patterns of natural language via a measure
called mis-match negativity – this is an electrical signal from the brain prompted by hearing a
difference in sound. Studies of this signal have suggested that children can begin to
distinguish different stress patterns as early as five months, and that the stress patterns of the
language around them quickly attain a special status in their memory46. Another EEG signal
that is usually detectable by 19 months is the N400, an indicator of semantic integration or
word meaning. The absence of this signal by 19 months can help predict whether expressive
language difficulties will be present47. Similar neural markers may be found for developmental
dyslexia. One promising candidate is duration detection and another is insensitivity to the auditory
parameters that yield the ‘stress beats’ or syllable rhythms of natural speech. In our research48, we found
significant differences in detection of the onset of the amplitude envelope (a cue to syllable stress)
between dyslexic and normally-reading children, and between young early readers and normal
developers. Dyslexic children were relatively insensitive, and young early readers were particularly
sensitive. If such measures prove robust at the individual level, then EEG would offer a number of
potential neural markers of risk for later language and reading impairments.
1Posterior meaning to the rear, superior meaning towards the top
Professor Usha Goswami
Centre for Neuroscience in Education
University of Cambridge
Neuroscience and Education: Issues and Opportunities
13
Dyscalculia
Insights into the causes of dyscalculia, which is thought to affect about 4-6 per cent of children in the UK49,
are beginning to emerge from the neuroscience of mathematical processing. In a neuroimaging study involving
normal participants, activity was observed in areas of the brain involved in word association and language
activity, the left frontal and angular gyri, when participants calculated answers exactly 50. If the type of exact
calculation we learn in school recruits areas of the brain associated with language, this suggests that the
acquisition of formal mathematics relies on our ability to learn rules and procedures. However, when the same
participants attempted to estimate answers, the role of a more ancient and innate ability to approximate was
seen to be linked to bilateral activity in the intraparietal sulci.
Even at six months, it seems, most of us can approximately differentiate between large numbers of items for
ratios of between1:2 and 2:352 and it seems that we share this approximate number sense with other animals53.
Such innate mathematical ability may have a critical role in ‘bootstrapping’ our capacity to formally grasp exact
differences and procedures54,55. Dyscalculia has been linked to a deficit in these ‘premathematical’ abilities.
A study56 of low birth-weight adolescents with numerical difficulties
revealed less gray matter in an area of the intraparietal sulcus.
Further research is needed to confirm the direction of cause and
effect in such studies, but insights from brain imaging research are
already inspiring interventions based on new notions of how we
develop our mathematical ability, and some of these are showing
promise (for example, see Liane Kaufmann’s research on page 22).
What is Dyscalculia?
The DfES currently characterises developmental dyscalculia as a number-specific cognitive deficit – a
difficulty in understanding simple number concepts, a lack an intuitive grasp of numbers and problems
learning number facts and procedures. Even when a correct answer arises or a correct method is used,
it may happen mechanically and without confidence. This difficulty is identifiable using tests that focus on
the building blocks of number understanding, such as measuring the time taken to count objects and to
order numbers by magnitude. These tests rely little on the child’s education, unlike standardised
arithmetic tests. Developmental dyscalculia is not a consequence of other cognitive disabilities, and can
appear in the most intelligent and well-educated of individuals – like dyslexia. It persists – probably in
most cases – into adulthood. It seems to be congenital and there is evidence that abnormalities in the
parietal lobe are involved.
Professor Brian Butterworth
Institute of Cognitive Neuroscience and
Department of Psychology
University College London
Side view of left hemisphere activities when
participants were asked to carry out exact
calculations (in blue) and approximations
(in yellow)51.
ADHD
Approximately 3-6 per cent57 of the school-age population is thought to suffer from Attention Deficit
Hyperactivity Disorder (ADHD). The behaviour of these children may be characterised as inattentive, overactive
and impulsive. They present a particular challenge to the teacher, and to themselves. The overt activity of
children with ADHD can often distract teachers from empathising with these pupils, who are often made
frustrated and distressed by their own behaviour.
The neuroscience of ADHD is still not clear but, from the many studies conducted, some agreement is emerging
that sufferers exhibit neural differences in areas such as the anterior cingulate and prefrontal cortex. Although
our understanding of ADHD at a brain level is still the subject of debate, its treatment has increasingly involved
the psychoactive drug methylphenidate, most commonly sold as Ritalin. In 1991, only 2000 prescriptions for
this drug were given out in the UK. By 2005, this figure had risen to 359,000, and it is currently growing by 18
per cent per year58. There are now concerns about the long-term effects of drugs such as methylphenidate on
the developing brain59 although the use of medication seems likely to endure as an important part of the solution
for many families.
However, the prevalence of drugs in the treatment of ADHD does not mean that this disorder is wholly a
medical problem beyond the influence of the school environment. On the contrary, there is growing evidence
that teachers following informed strategies can play an important role in improving the well-being and academic
performance of students suffering from ADHD60,61,62. Recent successful interventions include the application of
cognitive and instructional approaches to managing children’s behaviour, the inclusion of parents and teachers
in such interventions and the training of students themselves in self-management. Such research emphasises
the importance of teachers’ understanding of the disorder, its medication and management.
Why “ADHD”?
The idea of ADHD – Attention Deficit/Hyperactivity Disorder – identifies an important way in which
children differ. Some are much more impulsive, restless and disorganised than others; and the strongest
influences on this variation are genes that affect brain chemistry and neuropsychological functioning. It is
really helpful to use the idea in education because:
It emphasises that it is not a moral failing; the children cannot just choose not to have ADHD
There are some ways of teaching that suit such children better than the ordinary style of curriculum
and classroom management – and these deserve to be in a school's repertory
At the extreme of variation, some children will receive a medical diagnosis and perhaps medication.
Then it is important for there to be good communication between the prescriber and the school
Professor Eric Taylor
Institute of Psychiatry
King’s College London
Neuroscience and Education: Issues and Opportunities
15
Strategies for Teaching and Learning
Commercial ‘Brain-based’ Programmes
Since the 1990’s, an increasing number of educational programmes have claimed to have a ‘brain basis’. There
are few examples of such programmes having been evaluated, and they often appear to have developed
without neuroscientific scrutiny.
Some of the ideas promoted by these programmes have become part of the educational culture in many
schools. In the survey mentioned at the beginning of this commentary, about 30 per cent of teachers attending
an INSET day had already heard of the commercial programme known as ‘Brain Gym’63. This programme
promotes the idea that neural mechanisms can be influenced by specific physical exercises. The pseudo-
scientific terms that are used to explain how this works, let alone the concepts they express, are unrecognisable
within the domain of neuroscience. For example, there is a claim that, if children provide pressure on their
‘brain buttons’, they can help re-establish the brain organisation required for reading and writing64. ‘Brain
buttons’ are described as indentations between the 1st and 2nd ribs directly under the collar bone to the right and
left of the breastbone. Other exercises include the Cross-crawl, promoted on the basis of activating left/right,
top/bottom and back/front areas of the brain simultaneously, and varieties of ‘Hook-up’ for calming and stress-
relieving effects.
Approaches to learning that come under the broad heading of ‘Accelerated Learning’ are a more eclectic
mixture of ideas from popularly-reported neuroscience and psychology, synthesised with practice derived from
classroom experience. In books that promote accelerated learning, concepts from psychology and
neuroscience are often introduced as a means to promote
and explain learning processes. However, these too
often do not survive scientific scrutiny. For example, as
in Brain Gym, there is a still an emphasis on the
desirability of balance between the left and right part
of the brain. In Smith65, we are reminded
‘Remember that the synergy generated in creating
new pathways between left and right results in all-
round improvement’. In fact, except in the rare
case of brains which have been lesioned,
pathways exist permanently between the left
and right hemispheres, most notably via the
corpus callosum. At present, there is no
scientific evidence to suggest we can voluntarily
create new ones.
Accelerated learning also embraces other popular brain concepts such as Learning Style Preferences. Here,
psychological evidence supports the possibility that individual preferences exist regarding how we like to learn.
In education, learners may be allocated to one of three types of learning style (Visual, Auditory or Kinesthetic -
VAK). Some believe that presenting material in a way that suits an individual’s preferred learning style can
improve their learning. (Note that it could also be argued that the reverse might also be helpful, as a remedial
intervention to improve processing associated with the other learning styles.) However, there is a considerable
scarcity of quality research to support the value of identifying learning styles66. A recent psychological
investigation of the VAK principle tested recall of information presented in the three different styles67. This study
showed no benefit from having material presented in one’s preferred learning style, concluding that attempts to
focus on learning styles were ‘wasted effort’. Of course, this does not detract from the general value for all
learners when teachers present learning materials using a full range of forms and different media. Such an
approach can engage the learner and support their learning processes in many different ways, but the existing
research does not support labelling children in terms of a particular learning style.
Variations on the basic concept of learning preferences and styles can include sorting pupils into other types of
category. For example, some texts encourage teachers to determine whether a child is left or right brained68.
It is true that some tasks can be associated with extra activity that is predominantly in one hemisphere or the
other. For example, language is considered to be left lateralised. However, no part of the brain is ever normally
inactive in the sense that no blood flow is occurring. Furthermore, performance in most everyday tasks,
including learning tasks, requires both hemispheres to work together in
a sophisticated parallel fashion. The division of people into left-
brained and right-brained takes the misunderstanding one stage
further. There is no reliable evidence that such categorisation is
helpful for teaching and learning.
Many ideas about the brain in education may be at odds with
present scientific understanding, but perhaps not all of them
should be dismissed entirely. For example, short sessions
of Brain Gym exercise have been shown to improve
response times69, and such strategies, if they are effective,
may work because exercise can improve alertness. If they
do help learning, the basis for this effect should be
researched further, to support improved understanding and
practice. Teachers are not always satisfied with knowing that an
approach appears to be working. They would also like to
know why and how. Educators also care about the validity
of scientific claims used to promote an idea70 while a
greater understanding of underlying processes also
contributes to more effective evaluation. One thing is
clear. Education has already invested an immense
amount of time and money in ‘brain-based’ ideas that
were never based on any recognisable scientific understanding
of the brain. Many of these ideas remain untested and others are
being revealed as ineffective. In the future, an improved dialogue
between neuroscience and education will be critical in supporting the
development, application and evaluation of educational programmes
based on a sound scientific understanding of the brain.
Neuroscience and Education: Issues and Opportunities
17
Brain scan to lesson plan – the role of cognition
Many different experimental techniques are used in brain research. But the outcomes of high resolution imaging
such as functional Magnetic Resonance Imaging (fMRI) have probably attracted the greatest popular interest.
However, such techniques only provide us with an image of the biological changes occurring in the brain, such
as blood flow. They do not allow us to ‘see’ thinking or learning directly. To understand what such an image has
to do with learning, we need a psychological model to help us relate it to our mental processes – i.e. a cognitive
model. When cognitive models and our knowledge of biological processes inform each other, we can feel more
confident about both. Cognitive neuroscience is very much concerned with exploring this relationship between
the biology of the brain and the cognition of the mind. In this way, cognitive neuroscience is also drawing new
attention to a variety of existing psychological concepts relevant to education, and in a very visual manner.
Working memory is one example of how neuroscience is helping to ‘concretise’ psychological concepts. Working
memory refers to our capacity to temporarily hold a limited set of information in our attention when we are
processing it. This limitation is the reason why we prefer to write down a telephone number a few digits at a time
rather than be told the whole number and then start writing. The average upper limit of this type of memory is
about seven chunks of information, but there are individual differences in this limit that are linked to differences in
educational achievement72. However, understanding pupils’ dependency upon working memory becomes more
‘real’ when brain activities associated with mathematical training are visible. In one recent study, adults learning
long multiplication demonstrated a shift, with practice, in the areas of the brain they were using to complete their
calculations73. At first, considerable demand upon working memory was demonstrated by activity in the left
inferior frontal gyrus, as students explicitly and formally followed the processes they were learning. After practice,
this activity reduced and was replaced by greater activity in the left angular gyrus, as processes became more
automatic. The images generated by this study provide a helpful and very visual illustration of how the types of
mental resource required to solve a problem change with practice. They resonate well with classroom
observations of the difficulties faced by many learners when engaging with new problems. In such situations,
it can be particularly helpful for pupils to show their working since, apart from many other advantages, external
representations can help offload some of these heavy initial demands upon working memory.
A model of Brain->Mind->behaviour from cognitive neuroscience. Scientifically observable facts reside at the brain
and behaviour levels, but cognitive theories are required to link these together71.
Examples of
Environmental factors
Examples of
Intra-individual factors Factor affected
Oxygen
Nutrition
Toxins
Synaptogenesis
Synaptic pruning
Neuronal connections
BRAIN
Teaching
Cultural institutions
Social factors
Learning
Memory
Emotion
MIND
Temporary restrictions
e.g. teaching tools
Performance
Errors
Improvement
BEHAVIOUR
Many other psychological insights being explored by neuroimaging have broad implications for teaching and
learning strategies. For example, it has been known for some time that visualisation is a useful strategy for
learning. As well as being able to produce strong physiological responses, we now know that visualising an
object recruits most of the brain areas activated by actually seeing it75. This ability of mental imagery to engage
so much of the brain circuitry involved with a real perceptual experience emphasises its potential power and
usefulness as a learning tool.
The construction of meaning has also been identified as a key to understanding and remembering information.
When we learn new information, the links that form between this new information and our existing knowledge
serve to make it meaningful. An area of the left hemisphere, the left inferior prefrontal cortex, has been identified
as a vital structure in this construction of meaning. When learning something new, additional activity in this area
occurs when we try to decide upon its meaning in relation to what we know already. The new information
becomes more memorable once we have completed this process of ‘meaning making.’ How much more
memorable the information becomes is linked to the amount of increased neural activity in the left inferior
prefrontal cortex76.
A better understanding of the earliest processes involved in learning a new subject may also help orientate new
approaches to mainstream teaching. Again, psychological data suggests that we have an automatic and early
preference to represent the magnitude of a number as if on a line travelling from left to right77. Neuroimaging
studies have linked this ability to activity in the intraparietal sulcus78 and Goswami79 suggests that such evidence
supports spatially-based approaches to teaching about ordinality (i.e. the order and sequence of numbers) and
place value. These approaches include using empty number lines to improve efficiency, for example when
adding and subtracting numbers of more than one digit80.
Hot spots show where brain activity decreased after
participants undertook mathematical training –
reflecting a decreased demand on working memory
A different analysis of the same participants, this time
with hot spots showing areas where brain activity
increased after mathematical training – reflecting an
increase in automatic processing74
Neuroscience and Education: Issues and Opportunities
Issues on the Horizon
Smart Pills
Although the use of methylphenidate (e.g. Ritalin) has accelerated in recent years, it is still generally confined to
a particular group of students and requires a prescription. There is now a new wave of drugs being developed
that may find a broader market amongst learners. A recent report commissioned by the Office of Science and
Innovation foresees that cognitive enhancers (or ‘cogs’, ‘smart pills’) will start appearing in the UK labour force
around 2011 and, by 2017, may become “an acceptable part of the knowledge professional's tool kit”81. The
first generation of these drugs was developed to help relieve memory loss amongst sufferers of Alzheimer’s
disease, and their prescribed use is currently very restricted. One drug, donepezil, operates by inhibiting the
chemical cholinesterase in the brain. This chemical is part of the brain's housekeeping system, and mops up
some of the neurotransmitter acetylcholine which, as discussed on page 13, is produced by circuits responsible
for working memory and attention, which in turn influence the encoding of long-term memory. By inhibiting the
clean-up operation, these circuits are allowed to produce more acetylcholine,
allowing the brain to work at higher levels of efficiency. Donepezil has been
found to significantly improve the memory of healthy adults, including
young adults82. Some well-respected scientists are now suggesting that
all of us might benefit from such drugs in the future. The neuroscientist
Michael Gazzaniga wrote recently “The government should keep out of
it, letting our own ethical and moral sense guide us through the new
enhancement landscape”83.
Despite reports in the popular press, smart pills are not about to be
stacked next to vitamins on supermarket shelves, but they can
already be purchased over the internet. Attitudes to them are
likely to be different from those associated with the casual
use of drugs for leisure. Pressures to use them will be
economic and professional. Undergraduates’ well-known
tendency to experiment, combined with strong professional
motivations, may produce particularly high rates of use in
some areas of higher education, where their use may be
inspired more by office culture than club culture.
Discussion during the recent TLRP seminar series included
a focus on the ethical implications of cognitive enhancers for
education. Various questions emerged about their use. Is the
value of a qualification reduced by having used drugs to achieve
it and, if so, will measures be required to monitor and regulate
drug use? Will these drugs worsen the division between the rich
and poor in terms of access to education?
19
Does neurofeedback work?
The results of our research with RCM students showed that one particular neurofeedback protocol had
quite a beneficial effect on the quality of students’ performances, in some cases improving performance
marks by as much as one degree class. Furthermore, the students who showed the greatest
improvement were those who had learned the neurofeedback protocol most successfully. The challenge
for the Royal College of Music – and indeed other Higher Education music institutions – is to determine
the best means for integrating such successful learning interventions into our curricula.
Neurofeedback
Neurofeedback refers to the monitoring of one’s own brain activity with a view to influencing it. Recent work
investigating electroencephalographic (EEG) neurofeedback has found it helpful in improving the performance
ability of music students. Conservatoire students received training using neurofeedback and improvements in
their musical performance were highly correlated with their ability to progressively influence neural signals
associated with attention and relaxation84. Similar results have been found for dancers85. This is an interesting
and unusual example of a technique being borrowed from neuroscience to provide direct improvements for
learners. Despite its apparent success, these interventions are not built around any particular cognitive model
and the processes involved are not completely understood. However, the helpfulness of EEG feedback in raising
levels of attention indicates its potential benefit in a broad variety of educational areas86.
Dr Aaron Williamon
Royal College of Music
Neuroscience and Education: Issues and Opportunities
21
Biology provides no simple limit to our learning, not least because our learning can influence our biology. For
example, although the number of neurons we possess does not change greatly throughout the lifecourse, it has
been known for some time that experience can change the number of connections between them, our synaptic
density. More recently, there have been several pieces of research demonstrating how even the structure of the
brain, including the adult brain, can be changed by educational experience. In a recent study of juggling, the
brain areas activated at the beginning of a three-month training period increased in size by the end of it. After
three months of rest, these areas had shrunk back and were closer to their original size89. This graphic example
of ‘if you don’t use it, you lose it’ demonstrates the potential importance of education in mediating brain
development throughout our lives. Further evidence of the effects of education on brain structure comes from
research into Alzheimer’s disease, which is associated with the death of brain cells due to the development of
deposits called plaques within the brain and the formation of tangles of fibrils within individual brain cells.
Despite the biological basis of the disease, it is becoming increasingly clear that the risks of developing
Alzheimer’s in later life are reduced not only by previous educational attainment90, but also by the level of
challenge encountered in one’s working life91. Even after the onset of Alzheimer’s, there is evidence that the
progress of some symptoms can be diminished by training92.
Biology is not Destiny
The existence of differences in brain structure or function between different groups of learners may inspire
insights and contribute to more effective learning programmes and interventions. However, it can also lead to
unhelpful notions of permanent deficits and of ceilings to performance that are biologically determined.
This was illustrated recently in the public debate inspired by ‘The Dyslexia Myth’ on Channel 4 (2005), which
demonstrated how easily biological knowledge becomes incorrectly and unhelpfully associated with
deterministic ideas. Commentators noted how the original TV documentary promoted “all-or-none theorising
amongst the public” and how these misconceptions highlighted the need to “combine formal and pedagogic
approaches, preferably incorporating modern views on brain function”87. The call to include modern
neuroscience arises because current developmental cognitive neuroscience avoids predictive mechanisms of
biological cause and effect88. Current resonances between neuroscience and education encourage models of
learning that emphasise the complexity of interaction between biological and educational environments, and the
enduring possibility of mitigation (see box).
Cause is not an easy word. Its popular use would
be laughable if it was not so dangerous, informing,
as it does, government policy on matters that affect
us all. There is no single cause of anything and
nothing is determined.
Professor John Morton
Institute of Cognitive Neuroscience
University College London
The Future: Can Education, Neuroscience and
Psychology Work Together?
Our burgeoning knowledge of the brain is producing expectations of new educational insights,
and many such insights are already beginning to surface. At the same time, neuroscientists are
becoming increasingly interested in how the brain functions in complex environments more
closely resembling those found in classrooms. Education thus appears set to become an
interesting area of challenge for cognitive neuroscience, as it attempts to explore new contexts.
Some neuroscientists have even suggested that education might be considered as “a process
of optimal adaptation such that learning is guided to ensure proper brain development and
functionality”93. This sense of increasing mutual interest underlies calls for a two-way dialogue
between neuroscience and education that could helpfully inform both areas94. On a broader
canvass, the synergy of psychology and education has a very long history – though one which
has not been so much in evidence in recent decades.
Of course, brain scans cannot give rise directly to lesson plans. There is a need for bridging studies that
interpret scientific results in terms of possible interventions, and evaluation of these interventions in suitable
learning contexts. One example of such research comes from Innsbruck, where brain imaging and educational
interventions have both been used to understand the basis of dyscalculia and methods to remediate it95,96.
Experimental imaging results suggested the need for basic numerical and conceptual knowledge at an early
stage of mathematics education. A classroom intervention also demonstrated that children with dyscalculia can
show considerable improvements in a broad range of calculation abilities when these areas of learning, often
neglected in school mathematics, are specifically focused upon. Another challenge for professionals dealing with
dyscalculia concerns the fact that calculation abilities often appear to be related to non-numerical skills such as
visual-spatial cognition, language, working memory etc. Thus, only a very small proportion of children with
calculation difficulties exhibit a ‘pure’ dyscalculia, with most having difficulties in non-numerical domains as well.
In order to track down the neurocognitive overlaps of the symptoms of dyscalculia and spatial deficiencies, an
ongoing fMRI project involving Liane Kaufmann is using fMRI to delineate these two areas in children with and
without dyscalculia (see box). A deeper understanding of the interplay between numerical and spatial cognition
appears likely to influence teaching methods and mathematics curricula in the future.
Neuroscientists are putting increasing efforts into developing imaging
paradigms with process-orientated tasks that are also ecologically valid and
educationally relevant…but there’s still a long way to go. Nevertheless, I’m
convinced a better understanding of the neural underpinnings of behaviour
and learning will not only enhance our knowledge of how the brain-behaviour
relationship develops, but will also help tailor pedagogical curricula towards
pupils’ individual neurocognitive resources.
Dr Liane Kaufmann
Innsbruck University Children’s Hospital
Neuroscience and Education: Issues and Opportunities
23
There is also a growing need for collaborations between neuroscience, psychology and education that embrace
insights and understanding from each perspective, and that involve educators and scientists working together at
each stage. Such collaborations are not straightforward, since the philosophies of education and natural science
are very different – with various forms of psychology, in a sense, bridging the two. Educational research, with its
roots in social science, places strong emphasis upon the importance of social context and the interpretation of
meaning. Natural science, on the other hand, is more concerned with controlled experimental testing of
hypotheses and the development of generalisable cause-effect mechanisms. This suggests that collaborative
research projects may need to extend the cognitive neuroscience model of brain->mind->behaviour illustrated on
page 17, to incorporate processes of social construction pertinent to learning. Although challenging, such
interdisciplinary projects may be the most effective way to co-construct and communicate concepts involving
neuroscience, psychology and education that are both scientifically sound and educationally relevant.
A recent example of this type of collaboration arose in the teaching of drama. Here, an educational question
about the fostering of creativity resulted in an fMRI study in which trainee teachers participated97. The study
revealed that brain activities associated with creative effort increased when the initial stimuli for a creative story
decreased in their relatedness to each other. For example, producing a story that includes the words ‘dolphin,
jewel, print’ produced more activity in areas associated with creative effort than ‘artist, brushes, paint’. The
stories produced using unrelated words were also judged as more creative by an independent panel, but the
fMRI results suggest this is linked to increased ‘creative’ brain activity rather than arising simply from the story
including three unrelated words. These results, combining insights at an educational and brain level, support the
value of such strategies in fostering creativity in the classroom and have prompted further insights into their
application. Teacher trainers are now using the results of this study, together with other insights from
neuroscience and psychology, in a project to help enhance trainees’ understanding about fostering creativity in
their pupils98. The project aims to co-construct, with the trainee teachers, an understanding that is scientifically
valid and suitable for non-specialist communication. Such interdisciplinary research may be an efficient way to
approach the challenging interface between neuroscience, psychology and education, both in terms of revealing
new insights and through the development of a common language by which to express them.
To interrelate the most valuable insights from
cognitive neuroscience and the social science
perspectives of education and psychology
(represented by arrows), the brain->mind-
>behaviour model may need to be extended.
Even the example of two individuals interacting,
as represented here, is suggestive of the
complexity that can arise when behaviour becomes
socially mediated. Such complexity remains chiefly
the realm of social scientists, who often interpret
the meaning of such communication in order to
understand the underlying behaviour. Cognitive
neuroscience has established its importance in
understanding behaviour at an individual level but is
only just beginning to contemplate the types of
complex social domains studied by researchers in
social psychology and education.
The Need for Cautious Optimism
We are still at an early stage in our understanding of the brain. Most of what we know arises from scientific
experimentation, in environments that differ greatly from everyday learning contexts. Another limitation in
applying such studies is their focus upon individual cognitive factors rather than the complex abilities required in
everyday or academic settings. And, even in respect of these basic cognitive factors, many recent findings have
served to emphasise how much more there is to know.
The techniques being used to explore the brain are developing rapidly, but many important limitations still exist
here too. EEG can provide accurate timing information but provides little impression of where in the brain a
particular activity is occurring. In contrast, fMRI provides some accurate idea of the location of brain activity, but
is less effective when it comes to identifying when it occurs, especially on a cognitive time scale of milliseconds.
Also, techniques such as fMRI are often not considered suitable for routine studies using children, so most fMRI
investigations only involve adult participants. The neuroimaging literature tells us more about the adult brain than
about that of a developing child.
Given these and other limitations, considerable caution needs to be applied when attempting to transfer
concepts between neuroscience and education. Such attempts need to be well-informed by expertise from
within both fields. On the other hand, to ignore the relevance of present neuroscientific understanding to
education flies in the face of a common-sense connection. There is a belief,
shared by an increasing number of researchers in both fields, that
neuroscience has a fundamental and increasing relevance to
education that, together with related psychological perspectives,
needs to be cautiously explored. More pressingly, popular ideas
about the brain have flourished without check and are impacting
upon teaching and learning already. Such ideas deserve improved
scientific and educational evaluation. New developments on the
horizon, including the enhancement of brain function, further
emphasise the need for educational perspectives that include a
greater understanding of developments within neuroscience. In the
future, neuroscience promises to positively influence the
policy, practice and experience of education in a number of
important areas, but the full and successful realisation
of that promise will require careful educational and
scientific scrutiny at all stages.
Neuroscience and Education: Issues and Opportunities
25
References
1. Pickering, S. J. and Howard-Jones, P.A. (2007) Educators’ views of the role of Neuroscience in Education: A study of UK and
International perspectives, Mind, Brain and Education, 1(3)
2. Byrnes, J.P. and Fox, N.A. (1998) The educational relevance of research in cognitive neuroscience, Educational Psychology Review,
10(3), 297-342
3. Geake, JG and Cooper, PW (2003) Implications of cognitive neuroscience for education. Westminster Studies in Education,
26(10), 7-20
4. Goswami, U., Thomson, J., Richardson, U., Stainthorp, R., Hughes, D., Rosen, S. and Scott, S.K. (2002). Amplitude envelope onsets
and developmental dyslexia: A new hypothesis, Proceedings of the National Academy of Sciences, 99 (16), 10911-10916
5. Goswami, U. (2006) Neuroscience and Education: From Research to Practice? Nature Reviews Neuroscience 7(5), 406-413
6. Blakemore, S.J. and Frith, U. (2000) Report on the implications of recent developments in neuroscience for research on teaching and
learning, a consultation paper commissioned by the Teaching and Learning Research Programme, ESRC
7. OECD (2002) Understanding the brain: Towards a new learning science, Paris: OECD Publications
8. Rakic, P. (1995). Corticogenesis in human and non-human primates. In M.S. Gazzaniga (Ed.) The Cognitive Neurosciences (pp 127-
145). Cambridge, MA: MIT Press
9. Kuhl, P.K., Williams, K.A., Lacerda, F., Stevens, K.N. and Lindblom, B. (1992) Linguistic experience alters phonetic perception in
infants by 6 months of age, Science, 255 (5044), 606-608
10. Diamond, M.C., Greer, E.G., York, A., Lewis, D., Barton, T. and Lin, J. (1987) Rat cortical morphology following crowded-enriched
living conditions, Experimental Neurology, 96 (2), 241-247
11. Blakemore, S.J., and Frith, U. (2005) The Learning Brain: lessons for education. Oxford: Blackwell Publishing
12. Huttenlocher, P.R. (1979) Synaptic density in human frontal cortex – developmental changes and effects of aging, Brain Research,
163, 195-205
13. Sowell, E.R., Peterson, B.S., Thompson, P.M., Welcome, S.E., Henkenius, A.L. and Toga, A.W. (2003) Mapping cortical change
across the human life span, Nature Neuroscience, 6 (3), 309-315
14. McGivern, R.F., Andersen, J., Byrd, D., Mutter, K.L. and Reilly, J. (2002). Cognitive efficiency on a match to sample task decreases at
the onset of puberty in children. Brain and Cognition, 50, 73-89
15. Mackinlay, R., Charman, T. and Karmiloff-Smith, A. (2003). Remembering to remember: A developmental study of prospective
memory in a multitasking paradigm, Poster presented at the Society for Research in Child Development, Biennial Meeting, Tampa,
Florida, 24-27 April.
16. Blakemore S.J. and Choudhury, S. (2006) Development of the adolescent brain: implications for executive function and social
cognition, J Child Psychol Psychiatry, 47(3-4), 296-312
17. Choudhury, S., Blakemore, S. J. and Charman, T. (2006) Social cognitive development during adolescence, Social Cognitive and
Affective Neuroscience, 1, 165-174
18. Luna, B. (2004) Algebra and the adolescent brain, Trends in Cognitive Sciences, 8, 437-439
19. Qin, Y., Carter, C.S., Silk, E.M., Stenger, V.A., Fissell, K., Goode, A. and Andersen, J.R. (2004) The change of the brain activation
patterns as children learn algebra equation solving, Proceedings of the National Academy of Sciences, 101, 5686-5691
20. Bellisle, F. (2004) Effects of diet on behaviour and cognition in children, British Journal of Nutrition, 92: S227-S232 Suppl. 2
21. Richardson, A. J. (2006) Omega-3 fatty acids in ADHD and related neurodevelopmental disorders, International Review of Psychiatry,
18(2), 155-172
22. Richardson A.J. and Puri B.K. (2002) A randomized double-blind, placebo-controlled study of the effects of supplementation with
highly unsaturated fatty acids on ADHD-related symptoms in children with specific learning difficulties, Prog Neuropsychopharm Biol
Psychiat, 26(2) 233-239
23. Voigt, R. G., Llorente, A.M., Jensen, C.L., Fraley, J.K., Berretta, M.C. and Heird, W.C. (2001) A randomized, double-blind, placebo-
controlled trial of docosahexaenoic acid supplementation in children with attention-deficit/hyperactivity disorder, The Journal of
Pediatrics, 139, 189-96
24. Morris, M.C., Evans, D.A., Bienias, J.L., Tangney, C.C., Bennett, D.A., Wilson, R.S., Aggarwal, N. and Schneider J (2003)
Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease, Archives of Neurology, 60 (7), 940-946
25. Oken, E., Wright, R.O., Kleinman, K.P., Bellinger, D., Amarasiriwardena, C.J., Hu, H., Rich-Edwards, and J.W. Gillman, M.W. (2005)
Maternal fish consumption, hair mercury, and infant cognition in a US cohort, Environmental Health Perspectives, 113 (10), 1376-
1380
26. James, J.E. (1997) Understanding Caffeine: A biobehavioural analysis, Thousand Oaks, CA: Sage
27. Heatherley, S.V., Hancock, K.M.F. and Rogers, P.J. (2006) Psychostimulant and other effects of caffeine in 9- to 11-year-old children,
Journal of Child Psychology and Psychiatry, 47:2 (2006), 135-142
28. Rogers, P.J. and Dernoncourt, C. (1998) Regular caffeine consumption: A balance of adverse and beneficial effects for mood and
psychomotor performance, Pharmacology Biochemistry and Behaviour, 59, 1039-1045
29. Maquet, P., Laureys, S., Peigneux, P., Fuchs, S., Petiau, C., Phillips, C., Aerts, J., Del Firoe, G., Degueldre, C., Meulmans, T., Luxen,
A., Franck, G., Van Der Linden, Smith, C. and Cleermans, A. (2000) Experience dependent changes in cerebral activation during
human REM sleep, Nature Neuroscience, 3(8), 831-6
30. Rasch, B.H., Born, J. and Gais, S. (2006) Combined blockade of cholinergic receptors shifts the brain from stimulus encoding to
memory consolidation, Journal of Cognitive Neuroscience, 18(5), 793-802
31. Wagner, U., Gais, S., Haider, H., Verleger, R. and Born, J. (2004) Sleep inspires insight, Nature, 427 (6792): 352-5
32. Maquet, P., Laureys, S., Peigneux, P., Fuchs, S., Petiau, C., Phillips, C., Aerts, J., Del Firoe, G., Degueldre, C., Meulmans, T., Luxen, A.,
Franck, G., Van Der Linden, Smith, C. and Cleermans, A. (2000) Experience dependent changes in cerebral activation during human
REM sleep, Nature Neuroscience, 3(8), 831-6. Adapted by permission from Macmillan Publishers Ltd: Nature Neuroscience, 3(8) (2000)
References (continued)
33. Cohen, I. and Goldsmith, M. (2000) Hands On: how to use Brain Gym ® in the Classroom, Sea Point, South Africa: Hands On Books
34. Cian, C., Koulmann, N., Barraud, P.A., Raphel, C., Jimenez, C., and Melin, B. (2000) Influence of variations in body hydration on
cognitive function: effect of hyperhydration, heat stress, and exercise-induced dehydration, Journal of Psychophysiology, 14, 29-36
35. Rogers, P.J., Kainth, A. and Smit, H.J. (2001) A drink of water can improve or impair mental performance depending on small
differences in thirst, Appetite, 36, 57-58
36. Bar-David, Y., Urkin, J. and Kozminsky, E. (2005) The effect of voluntary dehydration on cognitive functions of elementary school
children, Acta Paediatrica, 94, 1667-1673
37. Bar-Or, O., Dotan, R., Inbar, O., Rotshstein, A. and Zonder, H. (1980) Voluntary hypohydration in 10 to 12 year old boys, Journal of
Applied Physiology, 48, 104-8
38. Fiez, J.A. and Petersen, S.E. (1998) Neuroimaging studies of word reading. Proceedings of the National Academy of Sciences, 95,
914-921
39. Turkeltaub, P.E., Gareau, L., Flowers, D.L., Zeffiro, T.A., Eden, G.F. (2003) Development of neural mechanisms for reading, Nature
Neuroscience, 6(6), 767-773
40. Temple, E. Poldrack, R.A., Salidis, J., Deutsch, G.K., Tallal, P., Merzenich, M.M. and Gabrieli, J.D.E. (2001) Disrupted neural
responses to phonological and orthographic processing in dyslexic children: an fMRI study, Neuroreport, 12, 299-308
41. Shaywitz, B.A., Shaywitz, S.E., Pugh, K.R., Mencl, W.E., Fullbright, R.K., Skudlarski, P., Constable, R.T., Marchione, K.E., Fletcher,
J.M., Lyon, G.R. and Gore, J.C. (2002) Disruption of posterior brain systems for reading in children with developmental dyslexia,
Biological Psychiatry, 52 (2), 101-110
42. Shaywitz, S.E., Shaywitz, B.A., Fulbright, R.K., Skudlarski, P., Mencl, W.E., Constable, R.T., Pugh, K.R., Holahan, J.M., Marchione,
K.E., Fletcher, J.M., Lyon, G.R. and Gore, J.C. (2003) Neural systems for compensation and persistence: young adult outcome of
childhood reading disability, Biological Psychiatry, 54 (1) 25-33
43. Shaywitz, B.A., Shaywitz, S.E., Blachman, B.A., Pugh, K.R., Fullbright, R.K., Skudlarski, P., Mencl, W.E., Constable, R.T., Holahan,
J.M., Marchione, K.E., Fletcher, J.M., Lyon, G.R. and Gore, J.C. (2004) Development of left occipitotemporal systems for skilled
reading in children after a phonologically- based intervention, Biological Psychiatry, 55( 9), 926-933
44. Temple, E. et al. (2003) Neural deficits in children with dyslexia ameliorated by behavioral remediation: Evidence from functional fMRI,
Proceedings of the National Academy of Sciences, 100, 2860-2865
45. Simos. P.G., Fletcher, J.M., Bergman, E., Breier, J.I., Foorman, B.R., Castillo, E.M., Davis, R.N., Fitzgerald, M. and Papanicolaou,
A.C.(2002) Dyslexia-specific brain activation profile becomes normal following successful remedial training, Neurology, 58(8),
1203-1213
46. Weber, A., Hahne, A., Friedrich, M. and Friederici, A.D. (2004). Discrimination of word stress in early infant perception:
Electrophysiological evidence, Cognitive Brain Research, 18, 149-161
47. Friedrich, M. and Friederici, A.D. (2006). Early N400 development and later acquisition, Psychophysiology, 43, 1-12
48. Goswami, U., Thomson, J., Richardson, U., Stainthorp, R., Hughes, D., Rosen, S. and Scott, S.K. (2002). Amplitude envelope
onsets and developmental dyslexia: A new hypothesis, Proceedings of the National Academy of Sciences, 99 (16), 10911-10916
49. Lewis, C., Hitch, G. and Walker, P. (1994). The prevalence of specific arithmetic difficulties and specific reading difficulties in 9- and
10-year-old boys and girls, Journal of Child Psychology and Psychiatry, 35, 283-292
50. Dehaene, S., Spelke, E., Pinel, P., Stanescu, R. and Tsivkin, S. (1999) Sources of mathematical thinking: behavioral and brain-
imaging evidence, Science, 284, 970-974
51. Dehaene, S., Spelke, E., Pinel, P., Stanescu, R. and Tsivkin, S. (1999) Sources of mathematical thinking: behavioral and brain-
imaging evidence, Science, 284, 970-974
52. Starkey, P. And Cooper, R.G. (1980) Perception of numbers by human infants, Science, 210, 1033-1035
53. Boysen, S.T. and Capaldi, E.J. (1993) The development of numerical competence: Animal and Human Models, Erlbaum
54. Johnson, M.H. (2004). Developmental Cognitive Neuroscience: An Introduction, 2nd Edition, Oxford: Blackwell
55. Carey, S. (2004) Bootstrapping and the origins of concepts, Daedalus, 59-68
56. Isaacs, E.B., Edmonds C.J., Lucas A. and D.G. Gadian (2001) Calculation difficulties in children of very low birthweight – A neural
correlate, Brain, 124, 1701-1707
57. Robison, L.M., Sclar, D.A., Skaer, T.L. and Galin, R.S. (1999) National trends in the prevalence of attention-deficit/hyperactivity
disorder and the prescribing of methylphenidate among school-age children: 1990-1995, Clinical Paediatrics, 38, 209-217
58. Information Centre for Health and Social Care (2005) Prescribing monitoring report for Quarter 2: 2004-2005, UK: IC Prescription
subscribing unit
59. Anderson, S.L. (2005) Stimulants and the developing brain, Trends in Pharmacological Sciences, 26 (5), 237-243
60. Gureasko-Moore, S., DuPaul, G.J. and White, G. (2006) The effects of self-management in general education classrooms on the
organizational skills of adolescents with ADHD, Behavior Modification, 30:2, 159-183
61. Corkum, PV, McKinnon, MM, Mullane, JC (2005) The effect of involving classroom teachers in a parent training program for families
of children with ADHD, Child and Family Behavior Therapy, 27:4, 29-49
62. Miranda, A, Presentacion, MJ and Soriano, M (2002)Effectiveness of a school-based multicomponent program for the treatment of
children with ADHD, Journal of Learning Disabilities, 35(6), 546-562
63. Pickering, S. J. and Howard-Jones, P.A. (2007) Educators’ views of the role of Neuroscience, in Education: A study of UK and
International perspectives, Mind, Brain and Education, 1(3)
64. Cohen, I. and Goldsmith, M. (2000) Hands On: how to use Brain Gym ® in the Classroom, Sea Point, South Africa: Hands On Books
Neuroscience and Education: Issues and Opportunities
27
References (continued)
65. Smith, A. (1996) Accelerated Learning in the Classroom, Bodmin: Network Educational Press Ltd
66. Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004) Learning styles and pedagogy in post-16 learning: A systematic and critical
review, (Report No. 041543). London: Learning and Skills Research Centre
67. Kratzig, G.P. and Arbuthnott, K.D. (2006) Perceptual learning style and learning proficiency: A test of the hypothesis, Journal of
Educational Psychology, 98(1), p238-246
68. Hoffman, E. (2002) Introducing Children to their Amazing Brains, Middlewich: LTL Books Ltd
69. Sifft, J.M. and Khalsa, G.C.K. (1991) Effect of educational kinesiology upon simple response-times and choice response-times,
Perceptual and Motor Skills, 73 (3), 1011-1015
70. Pickering, S. J. and Howard-Jones, P.A. (2007) Educators’ views of the role of Neuroscience, in Education: A study of UK and
International perspectives, Mind, Brain and Education, 1(3)
71. Morton, J. and Frith, U. (1995). Causal Modelling: A Structural Approach to Developmental Psychopathology, in Cicchetti, D. and
Choen, D.J. (eds.) Manual of Developmental Psychopathology: Volume 1, New York: W iley
72. Pickering, S.J. (2006) (Ed.) Working Memory and Education. Academic Press
73. Delazer, M., Domahs, F., Bartha, L., Brenneis, C., Lochy, A., Trieb, T. and Benke, T. (2003) Learning complex arithmetic – an fMRI
study, Cognitive Brain Research, 18, 76-88
74. Reprinted from Cognitive Brain Research, 18, Delazer, M., Domahs, F., Bartha, L., Brenneis, C., Lochy, A., Trieb, T. and Benke, T.
Learning complex arithmetic – an fMRI study, 76-88, (2003), with permission from Elsevier
75. Kosslyn, S.M. (2005) Mental images and the brain, Cognitive Neuropsychology, 22 (3-4), 333-347
76. Fletcher, P.C., Stephenson, C.M.E., Carpenter, T,A., Donovan, T. and Bullmore E.T. (2003) Regional brain activations predicting
subsequent memory success: An event-related FMRI study of the influence of encoding tasks, Cortex, 39 (4-5), 1009-1026
77. Berch, D.B., Foley, E.J., Hill, R.J. and Ryan, P.M. (1999) Extracting parity and magnitude from Arabic numerals: Developmental
changes in number processing and mental representation, Journal of Experimental Child Psychology, 74 (4), 286-308
78. Dehaene, S., Piazza, M, Pinel, P. and Cohen, L. (2003) Three parietal circuits for number processing, Cognitive Neuropsychology, 20
(3-6), 487-506
79. Goswami, U. (2006) Neuroscience and Education: From Research to Practice? Nature Reviews Neuroscience 7(5), 406-413
80. Bramald, R. (2000) Introducing the empty number line: the Dutch approach to teaching number skills. Education 3-13, 28, 5-12
81. Jones, R., Morris, K. and Nutt, D. (2005) Drugs Futures 2025? Foresight: Brain Science, Addiction and Drugs State of Science
Review, at www.foresight.gov.uk and in Nutt, D., Robbins, T., Stimson, D., Ince, M. and Jackson, A. (2006) Drugs and the Future,
Academic Press
82. Gron, G., Kirstein, M., Thielscher, A., Riepe, M.W. and Spitzer, M. (2005) Cholinergic enhancement of episodic memory in healthy
young adults, Psychopharmacology, 182 (1), 170-179
83. Gazzaniga, M.S. (2005) Smarter on Drugs, Scientific American: Mind, 16(3), 32-37
84. Gruzelier, J. H. and Egner, T. (2004). Physiological self-regulation: Biofeedback and neurofeedback. In A. Williamon (Ed.), Musical
Excellence (pp. 197-219). Oxford: Oxford University Press
85. Raymond, J., Sajid, I., Parkinson, L. and Gruzelier, J.H. (2005) The beneficial effects of alpha/theta and heart rate variability training
on dance performance, Applied psychophysiology and biofeedback, 30, 65-73
86. Egner, T. and Gruzelier, J.H. (2001) Learned self-regulation of EEG frequency components affects attention and event-related brain
potentials in humans, Neuroreport, 12 (18), 411-415
87. Nicolson, R. (2005) Dyslexia: Beyond the myth, The Psychologist, 18(11), 658-659
88. Morton, J. (2004) Understanding Developmental Disorders: A Causal Modelling Approach, Oxford: Blackwell
89. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U. and May, A. (2004) Nature, 427, 311-31
90. Elkins, J.S., Longstreth, W.T., Manolio, T.A., Newman, A.B., Bhadelia, R.A. and Johnston, S.C. (2006) Education and the cognitive
decline associated with MRI-defined brain infarct, Neurology 67, 435-440
91. Wilson, R.S. (2005) Mental challenge in the workplace and risk of dementia in old age: is there a connection? Occupational and
Environmental Medicine, 62, 72-73
92. Loewenstein D.A., Acevedo, A., Czaja. S.J and Duara, R. (2004) Cognitive rehabilitation of mildly impaired Alzheimer disease Patients
on cholinesterase inhibitors, American Journal of Geriatric Psychiatry, 12 (4), 395-402
93. Koizumi, H. (2004) The concept of “developing the brain”: a new natural science for learning and education, Brain and Development
26, 434-441
94. Geake, J.G. (2004). Cognitive neuroscience and education: two-way traffic or one-way street? Westminster Studies in Education,
27(1), 87- 98
95. Kaufmann, L., Handl, P. and Thony, B. (2003) Evaluation of a numeracy intervention program focusing on basic numerical knowledge
and conceptual knowledge: a pilot study, Journal of Learning Disabilities, 36 (6), 564-573
96. Delazer, M., Ischebeck, A., Domahs, F., Zamarian, L., Koppelstaetter, F., Siedentopf, C.M., Kaufmann, L, Benke, T. and Felber, S .
(2005) Learning by strategies and learning by drill – evidence from an fMRI study, Neuroimage 25 (3), 838-849
97. Howard-Jones, P.A., Blakemore, S.J., Samuel, E., Summers, I.R. and Claxton, G. (2005) Semantic divergence and creative story
generation: an fMRI investigation, Cognitive Brain Research, 25, 240-250
98. Howard-Jones, P.A., Winfield, M. and Crimmins, G. (2007) Co-constructing an understanding of creativity in drama education that
draws on neuropsychological concepts, Proceedings of the British Educational Research Association Annual Conference 2007,
Institute of Education, London
Neuroscience and Education:
Issues and Opportunities
www.tlrp.org
About this publication
This is the fourth in a series of TLRP Commentaries designed to make research-informed
contributions to contemporary discussion of issues, initiatives or events in UK education.
They are under the research programme's editorial control, but their production and distribution
may be supported by sponsors. The first commentary, on Personalised Learning, is available
from the TLRP office or at our web site.
About the Teaching and Learning Research Programme
The Teaching and Learning Research Programme (TLRP) is the UK’s largest investment in
education research. It aims to enhance outcomes for learners in all educational sectors across
the UK. Managed by the Economic and Social Research Council (ESRC), it runs from 2000 to
2011. Some 500 researchers are involved in 65 specific projects, and further work is being
undertaken on the identification and analysis of common, empirically grounded themes.
About the Economic and Social Research Council
The Economic and Social Research Council is the UK’s leading research and training agency
addressing economic and social concerns. We aim to provide high-quality research on issues of
importance to business, the public sector and government. The issues considered include
economic competitiveness, the effectiveness of public services and policy, and our quality of life.
The ESRC is an independent organisation, established by Royal Charter in 1965, and funded
mainly by the Government.
TLRP
Institute of Education
University of London
20 Bedford Way
London
WC1H 0AL
Tel: 020 7911 5577
Email: tlrp@ioe.ac.uk
Web: www.tlrp.org
... In language learning studies, in particular, Li et al. (2014) assert that recent bilingual language acquisition studies, along with other attention, memory and perception studies, emphasize the continuation of brain plasticity in adults in an unprecedented conceived way. Not only does plasticity continue in adulthood, but also neurogenesis -the birth of new neurons-occur in adulthood, particularly in language-related areas (Howard-Jones, 2007). In particular, neurogenesis occurs in the hippocampus which has a focal role in the learning process; accordingly, changes continue to occur in the brain structure through puberty and adolescence particularly in language-related areas (Howard-Jones, 2007). ...
... Not only does plasticity continue in adulthood, but also neurogenesis -the birth of new neurons-occur in adulthood, particularly in language-related areas (Howard-Jones, 2007). In particular, neurogenesis occurs in the hippocampus which has a focal role in the learning process; accordingly, changes continue to occur in the brain structure through puberty and adolescence particularly in language-related areas (Howard-Jones, 2007). ...
... In this regard, a governing rule was postulated by Hebb (1949) stating that the brain neurons that fire together, wire together; contrastively, when a skill is idle, it gets lost (Howard-Jones, 2007). This is because the neuron connections weaken through time if not recurrently used. ...
Preprint
Full-text available
It is widely documented that L2 learners, particularly late learners, find difficulties in acquiring and appropriately using L2 in a comparable proficiency to L1 (S. Segalowitz et al., 1998). It has further been documented that even advanced learners may face difficulties in producing target-like word combinations and phrases (Yusuf, 2017). To account for these difficulties and to facilitate L2 acquisition, this research proposes a neuroeducational model (LIRRA) for improving L2 proficiency in late learners. The neuroeducational model rests primarily on five key brain-adaptive features as evidenced in the literature viz. exposure to L2 lexical phrases, implicit learning of L2, reiterative exposure to L2 phrases, a rewarding/motivating learning environment, and an attentional-stimulating learning setting. From this perspective, this paper first introduces neuroeducation; then sheds light on some of the misconceptions pertaining to L2 learning particularly for late learners. Following this, the paper provides in-depth illustration of the brain-adaptive features and provides the rationale behind proposing a neuroeducational model on the premise thereof. Furthermore, this paper argues in support of the integration of this neuroeducational model in neuroeducation programs for L2 acquisition in late learners and provides recommendations therein.
... Above all else, neurogenesis -the birth of new neurons-is evidenced to occur in language-related areas during adulthood, particularly in the hippocampus (Howard-Jones, 2007). ...
Preprint
Full-text available
Almost without exception, adult second language (L2) learners fail to acquire an L2 to a comparable level of proficiency as their first language (L1). In part, traditional teaching approaches fail to address this issue or adapt to the equipotential brain. In light of this, this research attempted to explore language acquisition from a neuroeducation perspective. Accordingly, a neuroeducation program was developed which draws on concepts from neuroscience. The neuroeducation program was developed based on the LIRRA neuroeducational model which was proposed to automatize L2 and improve language acquisition for late learners. The program hinged on reiterative implicit exposure of lexical phrases in an attention-and reward-stimulating setting. This was to allow for procedural memory processing (like in L1) where L2 becomes automatized. In this regard, in a pre-post design, 30 English intermediate-level undergraduates were enrolled to the study. The program was a computerized online one encompassing 23 sessions and was implemented using a variety of engaging techniques such as games, riddles, and interactive readings. The outcomes were measured using a pre/post-test comprising three sections: a lexical-phrases production test, a reading proficiency test, and a writing test. The results revealed that the students showed a significant speed-up performance and considerable automaticity gains. Additionally, students showed a significant improvement in their acquisition of L2 lexical phrases and their reading proficiency. This research holds a promising future for the implementation of neuroeducation programs in language learning and for self-directed learning.
... In the present study, given the neuroeducational perspective which establishes that neuroimaging can also offer information to optimise and guide educative intervention, but seems most likely to assure theoretically sound (Howard-Jones, 2007;Howard-Jones et al., 2015), we investigated the effect of an exergaming didactic intervention in PE, compared to a traditional didactic intervention, on brain functioning associated with motor coordination. As Daniel (2012) warns brain science findings do not necessarily translate to the context of the classroom, Howard-Jones et al. (2015) state that greater dialogue between the two disciplines is necessary to bridge the gap between scientific research and classroom application, and also some «brain based» education programmes have In the present study, given the In the present study, given the neuroeducational perspective neuroeducational perspective which establishes that which establishes that neuroimaging can also offer neuroimaging can also offer information to optimise and information to optimise and guide educative intervention, guide educative intervention, we investigated the effect of an we investigated the effect of an exergaming didactic intervention exergaming didactic intervention in PE on brain functioning in PE on brain functioning never been evaluated or are «unscientific» (Goswami, 2006) we try to give neuroscientific evidence that support the efficacy of our intervention. ...
Article
Full-text available
Este estudio busca analizar el efecto de una intervención educativa, basada en el uso de un exergame, sobre la actividad cerebral relacionada con procesos de coordinación motora. Cinco alumnos formaron parte del grupo control (fueron los que recibieron la intervención didáctica tradicional) y cuatro alumnos formaron parte del grupo experimental (recibieron la intervención educativa basada en el uso del exergame). Las medidas de espectroscopía funcional de infrarrojo cercano (fNIRS) se recogieron en dos momentos diferenciados (antes –medida PRE– y después –medida POST– de la intervención) con un sistema NIRScout de 64 canales, cubriendo el área motora suplementaria (SMA) durante la realización de una tarea de coordinación bimanual de flexión-extensión digital. Los resultados mostraron que parece existir un patrón de actividad más eficiente en el grupo que realizó la intervención de exergaming gamificada en comparación con el grupo que realizó la intervención didáctica tradicional. En conclusión, nuestro estudio muestra evidencia neurofuncional sobre los efectos de los exergames en la coordinación motora.
... In the present study, given the neuroeducational perspective which establishes that neuroimaging can also offer information to optimise and guide educative intervention, but seems most likely to assure theoretically sound (Howard-Jones, 2007;Howard-Jones et al., 2015), we investigated the effect of an exergaming didactic intervention in PE, compared to a traditional didactic intervention, on brain functioning associated with motor coordination. As Daniel (2012) warns brain science findings do not necessarily translate to the context of the classroom, Howard-Jones et al. (2015) state that greater dialogue between the two disciplines is necessary to bridge the gap between scientific research and classroom application, and also some «brain based» education programmes have In the present study, given the In the present study, given the neuroeducational perspective neuroeducational perspective which establishes that which establishes that neuroimaging can also offer neuroimaging can also offer information to optimise and information to optimise and guide educative intervention, guide educative intervention, we investigated the effect of an we investigated the effect of an exergaming didactic intervention exergaming didactic intervention in PE on brain functioning in PE on brain functioning J. C. Bustamante, A. Quintas, M. Segura, C. Peñarrubia y J. L. Antoñanzas never been evaluated or are «unscientific» (Goswami, 2006) we try to give neuroscientific evidence that support the efficacy of our intervention. ...
Article
Full-text available
Our study investigated the effect of an exergaming didactic intervention in Physical Education (PE) on brain functioning associated with motor coordination. Five students formed the control group (received traditional didactic intervention) and four made up the experimental group (received exergaming didactic intervention). Functional near-infrared spectroscopy (fNIRS) measures were acquired at two time points (before and after intervention) by a 64-channel NIRScout system covering the supplementary motor area (SMA) while performing a bimanual digital flexion-extension coordination task. The results showed a more efficient activity pattern for the group that performed the gamified exergaming intervention than for the control group (traditional didactic intervention). In conclusion, our study reports neurofunctional evidence for effects of exergames on motor coordination.
... Education is also influenced by numerous factors not traditionally considered by neuroscience, such as the curriculum, the teacher, school resources and the wider social context such as family background. In addition, the discipline has been plagued by the existence of 'neuromyths' (such as left-and rightbrained thinking, teaching pupils via one 'preferred' learning-style exclusively, the existence of critical periods of development, and that we only use 10% of our brains), the uptake of which has been prolific in schools (Geake, 2009;Howard-Jones, 2007;Oliver, 2011). However, while education and neuroscience traditionally operate on different scales (educators may not consider learning at the cellular level, and neuroscientists may not study learning from the progress of a class, school, region or nation (Willingham, 2008)), the two disciplines share an interest at the cognitive system level, such as working memory or impulse inhibition. ...
Article
Full-text available
This article is the second of a two-part series that explores science teachers’ and their pupils’ experiences of using different pedagogical approaches based on understandings of how brains learn. Part 1 (Torrance Jenkins, 2017) focused on the two approaches rooted in cognitive psychology: Cognitive Load Theory (CLT) and Cognitive Acceleration through Science Education (CASE). After an introduction to the field of educational neuroscience, Part 2 will explore experiences of using two teaching resources from educational neuroscience: ‘The Brain-Targeted Teaching Model’ (Hardiman, 2012) and ‘Research-Based Strategies to Ignite Student Learning’ (Willis, 2006). Both approaches were selected for the case study research because of the strength of their scientific integrity, reliability and relatively substantial (and ongoing) empirical evidence.
Preprint
Full-text available
Almost without exception, adult second language (L2) learners fail to acquire an L2 to a comparable level of proficiency as their first language (L1). In part, traditional teaching approaches fail to address this issue or adapt to the equipotential brain. In light of this, this research attempted to explore language acquisition from a neuroeducation perspective. Accordingly, a neuroeducation program was developed which draws on concepts from neuroscience. The neuroeducation program was developed based on the LIRRA neuroeducational model which was proposed to automatize L2 and improve language acquisition for late learners. The program hinged on reiterative implicit exposure of lexical phrases in an attention- and reward- stimulating setting. This was to allow for procedural memory processing (like in L1) where L2 becomes automatized. In this regard, in a pre-post design, 30 English intermediate-level undergraduates were enrolled to the study. The program was a computerized online one encompassing 23 sessions and was implemented using a variety of engaging techniques such as games, riddles, and interactive readings. The outcomes were measured using a pre/post-test comprising three sections: a lexical-phrases production test, a reading proficiency test, and a writing test. The results revealed that the students showed a significant speed-up performance and considerable automaticity gains. Additionally, students showed a significant improvement in their acquisition of L2 lexical phrases and their reading proficiency. This research holds a promising future for the implementation of neuroeducation programs in language learning and for self-directed learning.
Article
Background: Many popular educational programmes claim to be ‘brain-based’, despite pleas from the neuroscience community that these neuromyths do not have a basis in scientific evidence about the brain. Purpose: The main aim of this paper is to examine several of the most popular neuromyths in the light of the relevant neuroscientific and educational evidence. Examples of neuromyths include: 10% brain usage, left- and right-brained thinking, VAK learning styles and multiple intelligences Sources of evidence: The basis for the argument put forward includes a literature review of relevant cognitive neuroscientific studies, often involving neuroimaging, together with several comprehensive education reviews of the brain-based approaches under scrutiny. Main argument: The main elements of the argument are as follows. We use most of our brains most of the time, not some restricted 10% brain usage. This is because our brains are densely interconnected, and we exploit this interconnectivity to enable our primitively evolved primate brains to live in our complex modern human world. Although brain imaging delineates areas of higher (and lower) activation in response to particular tasks, thinking involves coordinated interconnectivity from both sides of the brain, not separate left- and right-brained thinking. High intelligence requires higher levels of inter-hemispheric and other connected activity. The brain's interconnectivity includes the senses, especially vision and hearing. We do not learn by one sense alone, hence VAK learning styles do not reflect how our brains actually learn, nor the individual differences we observe in classrooms. Neuroimaging studies do not support multiple intelligences; in fact, the opposite is true. Through the activity of its frontal cortices, among other areas, the human brain seems to operate with general intelligence, applied to multiple areas of endeavour. Studies of educational effectiveness of applying any of these ideas in the classroom have failed to find any educational benefits. Conclusions: The main conclusions arising from the argument are that teachers should seek independent scientific validation before adopting brain-based products in their classrooms. A more sceptical approach to educational panaceas could contribute to an enhanced professionalism of the field.
Article
Full-text available
Educators are increasingly interested in applying neuroscience findings to improve educational practice. However, their understanding of the brain often lags behind their enthusiasm for the brain. We propose that educational psychology can serve as a bridge between basic research in neuroscience and psychology on one hand and educational practice on the other. We evaluated whether taking an educational psychology course is associated with increased neuroscience literacy and reduced belief in neuromyths in a sample of South Korean pre-service teachers. The results showed that taking an educational psychology course was associated with the increased neuroscience literacy, but there was no impact on belief in neuromyths. We consider the implications of these and other findings of the study for redesigning educational psychology courses and textbooks for improving neuroscience literacy.
Technical Report
Full-text available
This literature review on Early Childhood Education (ECE)/Inclusive Early Childhood Education (IECE) is part of the ‘Inclusive Early Childhood Education’ project, conducted by the European Agency for Special Needs and Inclusive Education. The project’s overall goal is to identify and analyse the factors that enable quality and effective pre-primary programmes for all children in inclusive early years settings. This review shows that international organisations and the European Union (EU) regard high-quality ECE/IECE as an essential foundation for lifelong learning. It is indispensable for success in modern knowledge-based economies. Participation in high-quality preprimary education has long-lasting positive effects on children’s development and the benefits are greater for children from a disadvantaged background (Frawley, 2014). In many cases, the early childhood stage is critical because many children’s different needs are detected once they become part of the education system. Therefore, one EU benchmark in the strategic framework for European co-operation in education and training (ET 2020) is that at least 95% of children between the age of four and compulsory school age should participate in ECE. At the same time, there are concerns about the accessibility and quality of ECE/IECE provisions. Despite its importance – especially considering the latest data about provisions for children with special educational needs (SEN) and/or at risk of social exclusion (e.g. due to poverty) in Europe from birth to seven years – the Organisation for Economic Co-operation and Development (OECD, 2004) reports that only one quarter of children with SEN are included in mainstream early education settings. This literature review aims to: • collect information about at-risk children and/or children with SEN in Europe at the pre-primary education level; • describe where those children are located during the pre-primary stages; • explore which resources are allocated to meet their needs; • describe the main characteristics of the educational contexts where these children are included. This document summarises major research and policy documents to analyse Early Childhood Education and Care (ECEC) services and programmes implemented for at-risk children and/or those with SEN.
Book
Caffeine is the most popular psychoactive substance in the world, and one of the widest-traded commodities in the forms of coffee, tea and cola soft drinks. But is consumption of caffeine safe in terms of physical and mental health? Addressing this question, the author traces how caffeine consumption evolved as well as how caffeine is absorbed, distributed and metabolized in our bodies. He then discusses the effects of caffeine on: psychomotor and cognitive performance; psychological well-being; blood pressure and cardiovascular health; carcinogenic potentials; pregnancy and perinatal health; athletic performance; and diagnostic and therapeutic applications. The book addresses the question of whether caffeine is a drug of abuse, and summarizes the main conclusions to be drawn from the vast body of relevant science.
Book
Psychologists have been trying to understand the factors that underpin children's success and failure in different educational domains for many years. One psychological function that has been found to play an important role in educational achievement is 'working memory', the processes involved in the temporary maintenance and manipulation of information. This book provides the reader with an up-to-date review of the research that has identified how working memory relates to academic attainment in: reading, reading comprehension, arithmetic and writing, as well as looking at how children with difficulties relating to hearing impairment and attention deficits differ in terms of their working memory. Other chapters focus on how working memory is called upon in classroom settings, how working memory can be assessed, and approaches to remediation. The opening chapter of the book provides an account of working memory from the architect of the model that has dominated psychological theory for over two decades. This book is a valuable resource for psychologists, educationalists, and anyone seeking to understand more about the cognitive basis of educational achievement in children.
Article
Problem Statement: Emotions have effects on learning. Learning becomes more effective in emotionally non-threatening environments. The power of emotions should be taken into account when designing, developing, and implementing learning environments. Emotions have a key role in accelerated learning; an instructional model which emphasizes learning will enhance knowledge without anxiety, stress, and prejudices. Accelerated learning claims that learning occurs both at conscious and subconscious planes and that working principles of the human brain should also be considered during instruction. Purpose of the Study: The basic aim of the study is to compare the effects of accelerated learning in a classroom environment with the effects of accelerated learning in a computer environment, and also with effects of expository teaching. Methods: The research is an experimental study. It was carried out using a science and technology lesson. The research was conducted with 73 students studying in the 5th grade in a primary school in Ankara. Three groups were randomly assigned a learning environment. The first group learned with accelerated learning in a classroom environment. The second group learned with accelerated learning in a computer environment. Finally, the third group learned through expository teaching. Throughout the research, data regarding the students' achievement was collected. Student and teacher opinions were also collected. Data was analyzed using percentages, t test for paired samples, ANOVA and ANCOVA tests. All hypotheses were tested at a .05 significance level. Finding and Results: The findings of the study showed that both accelerated learning environments had a more positive impact on student achievement than did expository teaching. However, accelerated learning in a classroom environment and accelerated learning in a computer environment were equal in effecting student achievement. Student and teacher opinions indicated students preferred accelerated learning. Conclusions and Recommendations: According to the results, accelerated learning should be considered for an instructional model in science education. Accelerated learning principles could be employed in educational software design to increase the retention of knowledge and student motivation.
Article
A long-awaited book from developmental disorders expert John Morton, Understanding Developmental Disorders: A Causal Modelling Approach makes sense of the many competing theories about what can go wrong with early brain development, causing a child to develop outside the normal range. Based on the idea that understanding developmental disorders requires us to talk about biological, cognitive, behavioral and environmental factors, and to talk about causal relationships among these elements. Explains what causal modelling is and how to do it. Compares different theories about particular developmental disorders using causal modelling. Will have a profound impact on research in the fields of psychology, neuroscience and medicine.
Article
This study evaluated a 10-week behavior training program for parents of children with Attention-Deficit/Hyperactivity Disorder (ADHD) and also examined whether the inclusion of an intervention provided to children's classroom teachers would result in additional behavioral benefits. Parents and teachers of 30 children with ADHD were randomly assigned to the Parent Group Only or Parent Group plus Teacher conditions. Results indicate that the program is effective in improving child behavior in the home setting. More importantly, a greater reduction in children's ADHD symptoms was observed when both parents and teachers received the intervention. This suggests that the teacher component was a simple, time- and cost-effective way of increasing the beneficial effects of an ADHD parent training program.
Article
We recoil at the idea of people taking drugs to enhance their intelligence. But why?