Educational neuroscience (or neuroeducation, a component of Mind Brain and Education) is an emerging scientific field that brings together researchers in cognitive neuroscience, developmental cognitive neuroscience, educational psychology, educational technology, education theory and other related disciplines to explore the interactions between biological processes and education. Researchers in educational neuroscience investigate the neural mechanisms of reading, numerical cognition, attention and their attendant difficulties including dyslexia, dyscalculia and ADHD as they relate to education. Researchers in this area may link basic findings in cognitive neuroscience with educational technology to help in curriculum implementation for mathematics education and reading education. The aim of educational neuroscience is to generate basic and applied research that will provide a new transdisciplinary account of learning and teaching,
which is capable of informing education. A major goal of educational
neuroscience is to bridge the gap between the two fields through a
direct dialogue between researchers and educators, avoiding the
"middlemen of the brain-based learning industry". These middlemen have a
vested commercial interest in the selling of "neuromyths" and their
supposed remedies.
The potential of educational neuroscience has received varying degrees of support from both cognitive neuroscientists and educators. Davis argues that medical models of cognition, "...have only a very limited role in the broader field of education and learning mainly because learning-related intentional states are not internal to individuals in a way which can be examined by brain activity". Pettito and Dunbar on the other hand, suggest that educational neuroscience "provides the most relevant level of analysis for resolving today’s core problems in education". Howard-Jones and Pickering surveyed the opinions of teachers and educators on the topic, and found that they were generally enthusiastic about the use of neuroscientific findings in the field of education, and that they felt these findings would be more likely to influence their teaching methodology than curriculum content. Some researchers take an intermediate view and feel that a direct link from neuroscience to education is a "bridge too far", but that a bridging discipline, such as cognitive psychology or educational psychology can provide a neuroscientific basis for educational practice. The prevailing opinion, however, appears to be that the link between education and neuroscience has yet to realise its full potential, and whether through a third research discipline, or through the development of new neuroscience research paradigms and projects, the time is right to apply neuroscientific research findings to education in a practically meaningful way.
Several academic institutions around the world are beginning to devote resources and energy to the establishment of research centres focused on educational neuroscience research. For example, the Centre for Educational Neuroscience in London UK is an inter-institutional project between University College, London, Birkbeck and the Institute of Education. The centre brings together researchers with expertise in the fields of emotional, conceptual, attentional, language and mathematical development, as well as specialists in education and learning research with the aim of building a new scientific discipline (Educational Neuroscience) in order to ultimately promote better learning.
The potential of educational neuroscience has received varying degrees of support from both cognitive neuroscientists and educators. Davis argues that medical models of cognition, "...have only a very limited role in the broader field of education and learning mainly because learning-related intentional states are not internal to individuals in a way which can be examined by brain activity". Pettito and Dunbar on the other hand, suggest that educational neuroscience "provides the most relevant level of analysis for resolving today’s core problems in education". Howard-Jones and Pickering surveyed the opinions of teachers and educators on the topic, and found that they were generally enthusiastic about the use of neuroscientific findings in the field of education, and that they felt these findings would be more likely to influence their teaching methodology than curriculum content. Some researchers take an intermediate view and feel that a direct link from neuroscience to education is a "bridge too far", but that a bridging discipline, such as cognitive psychology or educational psychology can provide a neuroscientific basis for educational practice. The prevailing opinion, however, appears to be that the link between education and neuroscience has yet to realise its full potential, and whether through a third research discipline, or through the development of new neuroscience research paradigms and projects, the time is right to apply neuroscientific research findings to education in a practically meaningful way.
Several academic institutions around the world are beginning to devote resources and energy to the establishment of research centres focused on educational neuroscience research. For example, the Centre for Educational Neuroscience in London UK is an inter-institutional project between University College, London, Birkbeck and the Institute of Education. The centre brings together researchers with expertise in the fields of emotional, conceptual, attentional, language and mathematical development, as well as specialists in education and learning research with the aim of building a new scientific discipline (Educational Neuroscience) in order to ultimately promote better learning.
The need for a new discipline
The
emergence of educational neuroscience has been born out of the need for
a new discipline that makes scientific research practically applicable
in an educational context. Addressing the broader field of "mind, brain
and education", Kurt Fischer states, "The traditional model will not
work. It is not enough for researchers to collect data in schools and
make those data and the resulting research papers available to
educators", as this method excludes teachers and learners from contributing to the formation of appropriate research methods and questions.
Learning in cognitive psychology and neuroscience has focused on
how individual humans and other species have evolved to extract useful
information from the natural and social worlds around them.
By contrast, education, and especially modern formal education, focuses
on descriptions and explanations of the world that learners cannot be
expected to acquire by themselves. In this way, learning in the
scientific sense, and learning in the educational sense can be seen as
complementary concepts. This creates a new challenge for cognitive
neuroscience to adapt to the real world practical requirements of
educational learning. Conversely, neuroscience creates a new challenge
for education, because it provides new characterizations of the current
state of the learner – including brain state, genetic state, and
hormonal state - that could be relevant to learning and teaching. By
providing new measures of the effects of learning and teaching,
including brain structure and activity, it is possible to discriminate
different types of learning method and attainment. For example,
neuroscience research can already distinguish learning by rote from
learning through conceptual understanding in mathematics.
The United States National Academy of Sciences
published an important report, stressing that, "Neuroscience has
advanced to the point where it is time to think critically about the
form in which research information is made available to educators so
that it is interpreted appropriately for practice—identifying which
research findings are ready for implementation and which are not."
In their book The Learning Brain, researchers from
London’s "Centre for Educational Neuroscience", Blakemore & Frith
outline the developmental neurophysiology of the human brain that has
given rise to many theories regarding educational neuroscience.
One of the fundamental pillars supporting the link between education
and neuroscience is the ability of the brain to learn. Neuroscience is
developing and increasing our understanding of early brain development,
and how these brain changes might relate to learning processes.
Early brain development
Almost all of the neurons in the brain are generated before birth,
during the first three months of pregnancy, and the newborn child’s
brain has a similar number of neurons to that of an adult. Many more
neurons form than are needed, and only those that form active
connections with other neurons survive. In the first year after birth
the infant brain undergoes an intense phase of development, during which
excessive numbers of connections between neurons are formed, and many
of these excess connections must be cut back through the process of synaptic pruning
that follows. This pruning process is just as important a stage of
development as the early rapid growth of connections between brain
cells. The process during which large numbers of connections between
neurons are formed is called synaptogenesis.
For vision and hearing (visual and auditory cortex), there is extensive
early synaptogenesis. The density of connections peaks at around 150%
of adult levels between four and 12 months, and the connections are then
extensively pruned. Synaptic density returns to adult levels between
two and four years in the visual cortex. For other areas such as
prefrontal cortex (thought to underpin planning and reasoning), density
increases more slowly and peaks after the first year. Reduction to adult
levels of density takes at least another 10–20 years; hence there is
significant brain development in the frontal areas even in adolescence.
Brain metabolism (glucose uptake, which is an approximate index of
synaptic functioning) is also above adult levels in the early years.
Glucose uptake peaks at about 150% of adult levels somewhere around four
to five years. By the age of around ten years, brain metabolism has
reduced to adult levels for most cortical regions. Brain development
consists of bursts of synaptogenesis, peaks of density, and then synapse
rearrangement and stabilisation. This occurs at different times and
different rates for different brain regions, which implies that there
may be different sensitive periods for the development of different
types of knowledge. Neuroscience research into early brain development
has informed government education policy for children under three years
old in many countries including the USA and the United Kingdom. These
policies have focused on enriching the environment of children during
nursery and preschool years, exposing them to stimuli and experiences
thought to maximise the learning potential of the young brain.
Can neuroscience inform education?
Although
an increasing number of researchers are seeking to establish
educational neuroscience as a productive field of research, debate still
continues with regards to the potential for practical collaboration
between the fields of neuroscience and education, and whether
neuroscientific research really has anything to offer educators.
Daniel Willingham
states that "whether neuroscience can be informative to educational
theory and practice is not debatable-it has been." He draws attention to
the fact that behavioural research alone was not decisive in
determining whether developmental dyslexia was a disorder of primarily
visual or phonological origin. Neuroimaging research was able to reveal
reduced activation for children with dyslexia in brain regions known to
support phonological processing, thus supporting behavioural evidence for the phonological theory of dyslexia.
While John Bruer
suggests that the link between neuroscience and education is
essentially impossible without a third field of research to link the
two, other researchers feel that this view is too pessimistic. While
acknowledging that more bridges must be built between basic neuroscience
and education, and that so called neuromyths (see below) must be
deconstructed, Usha Goswami
suggests that cognitive developmental neuroscience has already made
several discoveries of use to education, and has also led to the
discovery of ‘neural markers’ that can be used to assess development. In
other words, milestones of neural activity or structure are being
established, against which an individual can be compared in order to
assess their development.
For example, event-related potential
(ERP) research has uncovered several neural signatures of language
processing, including markers of semantic processing (e.g. N400),
phonetic processing (e.g. mismatch negativity) and syntactic processing
(e.g. P600). Goswami
points out that these parameters can now be investigated longitudinally
in children, and that certain patterns of change may indicate certain
developmental disorders. Furthermore, the response of these neural
markers to focused educational interventions may be used as a measure of
the intervention’s effectiveness. Researchers such as Goswami assert
that cognitive neuroscience has the potential to offer various exciting
possibilities to education. For special education, these include the
early diagnosis of special educational needs; the monitoring and
comparison of the effects of different kinds of educational input on
learning; and an increased understanding of individual differences in
learning and the best ways to suit input to learner.
A potential application of neuroimaging highlighted by Goswami
is in differentiating between delayed development and atypical
development in learning disorders. For instance, is a given child with
dyslexia developing reading functions in a totally different way from
typical readers, or is he/she developing along the same trajectory, but
just taking longer to do so? Indeed, evidence already exists to suggest
that in children with specific language impairments and dyslexia the
development of the language system is delayed rather than fundamentally
different in nature.
In disorders such as autism however, brain development may be
qualitatively different, showing a lack of development in brain regions
associated with a "theory of mind".
Goswami
also suggests that neuroimaging could be used to assess the impact of
particular training programmes, such as the Dore, an exercise based
programme based on the cerebellar deficit hypothesis that aims to
improve reading through a series of balance exercises. Some brain
imaging research is beginning to show that for children with dyslexia
who receive targeted educational interventions, their brain activation
patterns begin to look more like those of people without reading
disorders, and in addition, that other brain regions are acting as
compensatory mechanisms.
Such findings may help educators understand that, even if dyslexic
children show behavioural improvement, the neural and cognitive
mechanisms by which they process written information may still be
different, and this may have practical implications for the ongoing
instruction of these children.
Neuroscience research has evidenced its ability to reveal ‘neural
markers’ of learning disorders, most notably in the case of dyslexia.
EEG studies have revealed that human infants at risk of dyslexia (i.e.
with immediate family members who suffer from dyslexia) show atypical
neural responses to changes in speech sounds, even before they are able
to understand the semantic content of language.
Not only does such research allow for the early identification of
potential learning disorders, but it further supports the phonological
hypothesis of dyslexia in a manner unavailable to behavioural research.
Many researchers advocate a cautious optimism with regards to the
marriage between education and neuroscience, and believe that to bridge
the gap between the two, the development of new experimental paradigms
is necessary and that these new paradigms should be designed to capture
the relationships between neuroscience and education across different
levels of analysis (neuronal, cognitive, behavioural).
Neuroscience and education: Sample cases
Language and literacy
Human language is a unique faculty of the mind and the ability to understand and produce oral and written language is fundamental to academic achievement and attainments. Children who experience difficulties with oral language raise significant challenges for educational policy and practice; National Strategies, Every Child a Talker (2008). The difficulties are likely to persist during the primary school years where, in addition to core deficits with oral language, children experience problems with literacy, numeracy and behaviour and peer relations.
Early identification and intervention to address these difficulties, as
well as identification of the ways in which learning environments can
support atypical language development are essential.
Untreated speech and language needs result in significant costs both to
the individual and to the national economy (ICAN, 2006).
Over the last decade, there has been a significant increase in
neuroscience research examining young children's processing of language
at the phonetic, word, and sentence levels.
There are clear indications that neural substrates for all levels of
language can be identified at early points in development. At the same
time, intervention studies have demonstrated the ways in which the brain
retains its plasticity for language processing. Intense remediation
with an auditory language processing program has been accompanied by
functional changes in left temporo-parietal cortex and inferior frontal
gyrus. However, the extent to which these results generalize to spoken and written language is debated.
The relationships between meeting the educational needs of
children with language difficulties and the findings of neuroscience
studies are not yet established. One concrete avenue for progress is to
use neuroscientific methods to address questions that are significant to
practice in learning environments. For example, the extent to which
language skills are attributable to a single common trait, and the
consistency of such a trait over development, are matters of debate. However, direct assessments of brain activity can inform these debates.
A detailed understanding of the sub-components of the language system,
and the ways these change over time may inevitably yield implications
for educational practice.
Mathematics
Mathematical skills are important not only for the national economy
but also for an individual’s life chances: low numeracy increases the
probability of arrest, depression, physical illnesses, unemployment.
One of the main causes of low numeracy is a congenital condition called
dyscalculia. As the Foresight report on Mental Capital and Wellbeing
puts it, "Developmental dyscalculia – because of its low profile but
high impacts, its priority should be raised. Dyscalculia relates to
numeracy and affects between 4-7% of children. It has a much lower
profile than dyslexia but can also have substantial impacts: it can
reduce lifetime earnings by £114,000 and reduce the probability of
achieving five or more GCSEs
(A*-C) by 7–20 percentage points. Home and school interventions have
again been identified by the Project. Also, technological interventions
are extremely promising, offering individualised instruction and help,
although these need more development." (Executive Summary, Section 5.3)
Understanding typical and atypical mathematical development is a crucial
underpinning for the design of both the mainstream mathematics
curriculum and for helping those who fail to keep up. Over the past ten years, a brain system for simple number processing has been identified and a handful of studies of children’s brains that throw a little light on its development.
An increasing convergence of evidence suggests that dyscalculia
may be due to a deficit in an inherited core system for representing the
number of objects in a set, and how operations on sets affect number and in the neural systems that support these abilities.
This core deficit affects the learner’s ability to enumerate sets and
to order sets by magnitude, which in turn make it very difficult to
understand arithmetic, and very hard to provide a meaningful structure
for arithmetical facts. Twin and family
studies suggest that dyscalculia is highly heritable, and genetic
anomalies, such as Turner’s Syndrome, indicate an important role for
genes in the X chromosome.
This suggestion that dyscalculia is caused by a deficits in a
core deficit in number sense is analogous to the theory that dyslexia is
due to a core deficit in phonological processing. Despite these
similarities in terms of the scientific progress, public awareness of
dyscalculia is much lower than it is for dyslexia. The UK's Chief Scientific Advisor, John Beddington,
notes that, "developmental dyscalculia is currently the poor relation
of dyslexia, with a much lower public profile. But the consequences of
dyscalculia are at least as severe as those for dyslexia."
The application of neuroscience to understanding mathematical
processing has already resulted in understanding beyond the early
cognitive theories. Cognitive neuroscience research has revealed the
existence of an innate ‘number sense’ system, present in animals and
infants as well as adults, that is responsible for basic knowledge about
numbers and their relations. This system is located in the parietal
lobe of the brain in each hemisphere. This parietal system is active in children and adults during basic numerical tasks,
but over the course of development it appears to become more
specialised. Furthermore, children with mathematical learning
disabilities (dyscalculia) show weaker activation in this region than
typically developing children during basic number tasks.
These results show how neuroimaging can provide important information
about the links between basic cognitive functions and higher level
learning, such as those between comparing two numbers and learning
arithmetic.
In addition to this basic number sense, numerical information can
be stored verbally in the language system, a system that neuroscience
research is beginning to reveal as qualitatively different at the brain
level to the number sense system.
This system also stores information about other well learned verbal
sequences, such as days of the week, months of the year and even poetry,
and for numerical processing it supports counting and the learning of
multiplication tables. While many arithmetic problems are so over
learned that they are stored as verbal facts, other more complex
problems require some form of visuo-spatial mental imagery.
Showing that these subsets of arithmetic skills are supported by
different brain mechanisms offers the opportunity for a deeper
understanding of the learning processes required to acquire arithmetic
proficiency.
Neuroimaging studies of mathematical learning disabilities are
still rare but dyscalculia is an area of increasing interest for
neuroscience researchers. Since different neural mechanisms contribute
to different elements of mathematical performance, it may be that
children with dyscalculia show variable patterns of abnormality at the
brain level. For example, many children with dyscalculia also have
dyslexia, and those that do may show different activation of the verbal
networks that support maths, while those who have dyscalculia only, may
show impairments of the parietal number sense system. Indeed, the few
studies carried out on children with dyscalculia only point to a brain
level impairment of the number sense system.
Such evidence is beginning to contribute to a theoretical debate
between researchers who believe that dyscalculia is caused by a brain
level deficit of the number sense and those who believe that the
disorder stems from a problem in using numerical symbols to access the
number sense information. With the continued development of theoretical
models of dyscalculia that generate explicit testable hypotheses,
progress should be rapid in developing research which investigates the
link between mathematical learning disorders and their neural
correlates.
Social and emotional cognition
In the last 10 years, there has been an explosion of interest in the
role of emotional abilities and characteristics in contributing to
success in all aspects of life. The concept of Emotional Intelligence (EI)
has gained wide recognition and is featured in the Foresight report on
Mental Capital and Wellbeing. Some have made influential claims that EI
is more important than conventional cognitive intelligence, and that it
can more easily be enhanced.
Systematic research has yet to provide much support for these claims,
although EI has been found to be associated with academic success
and there is some evidence that it may be of particular importance for
groups at-risk of academic failure and social exclusion. In spite of the
weak evidence base, there has been a focus on promoting the social and
emotional competence, mental health and psychological wellbeing of
children and young people,
particularly in schools as the result of the investment in universal
services, prevention and early intervention (e.g., the Social and
Emotional Aspects of Learning (SEAL) project in the UK [DfES, 2005,
2007]).
The neural basis of emotional recognition in typically developing children
has been investigated, although there is little neuroimaging work on
atypically developing children who process emotions differently.
Males are commonly over-represented in these atypically developing
populations and a female advantage is commonly reported both on EI
measures and on most areas of emotion processing. In processing facial
expressions the female advantage appears best explained by an integrated
account considering both brain maturation and social interaction.
Prefrontal brain damage in children affects social behavior, causing insensitivity to social acceptance, approval or rejection.
These brain areas process social emotions such as embarrassment,
compassion and envy. Moreover, such damage impairs cognitive as well as
social decision making in real world contexts
supporting the Vygotskian view that social and cultural factors are
important in cognitive learning and decision making. This view
emphasizes the importance of bringing together neuroscientific and social constructionist perspectives, in this case in examining the influence of emotion on transferable learning.
However, there are currently many gaps in the attempt to bring
together developmental science and neuroscience to produce a more
complete understanding of the development of awareness and empathy.
Educational research relies on pupil's accurate self-report of emotion,
which may not be possible for some pupils, e.g., those with
alexithymia—a difficulty in identifying and describing feelings, which
is found in 10% of typical adults. Emotional awareness can be measured
using neuroimaging methods
that show that differing levels of emotional awareness are associated
with differential activity in amygdala, anterior insular cortex, and the
medial prefrontal cortex. Studies of brain development in childhood and
adolescence show that these areas undergo large-scale structural
changes.
Hence, the degree to which school-age children and young adults are
aware of their emotions may vary across this time period, which may have
an important impact on classroom behaviour and the extent to which
certain teaching styles and curriculum approaches might be effective.
Neuroimaging work is also beginning to help in the understanding
of social conduct disorders in children. For example,
callous-unemotional traits in children are a particularly difficult
problem for teachers to deal with, and represent a particularly serious
form of conduct disturbance. Jones et al. (2009)
showed that children with callous-unemotional traits revealed less
brain activation in the right amygdala in response to fearful faces,
suggesting that the neural correlates of that type of emotional
disturbance are present early in development.
Researchers from the Centre for Educational Neuroscience in
London have been instrumental in developing a research body that
investigates how social cognition develops in the brain. In particular,
Sarah-Jayne Blakemore, co-author of "The Learning Brain", has published
influential research on brain development related to social cognition
during adolescence. Her research, suggests that activity in brain
regions associated with emotional processing undergo significant
functional changes during adolescence.
Attention and executive control
Attention
refers to the brain mechanisms that allow us to focus on particular
aspects of the sensory environment to the relative exclusion of others.
Attention modulates sensory processing
in "top-down" fashion. Maintaining selective attention toward a
particular item or person for a prolonged period is clearly a critical
underpinning skill for the classroom. Attention is the key cognitive
skill impaired in ADHD resulting in difficulty in completing tasks or
attending to details.
Aspects of attention may also be atypical in children showing
anti-social behaviour and conduct disorders. From the perspective of
basic neuroscience, recent evidence suggests that attention skills may
be one of the human brain functions that respond best to early
intervention and training (e.g.).
Further, from a neuroconstructivist
perspective attention is a vital mechanism through which the child can
actively select particular aspects of their environment for further
learning. Executive functions include the abilities to inhibit unwanted
information or responses, to plan ahead for a sequence of mental steps
or actions, and to retain task-relevant and changing information for
brief periods (working memory).
Like attention, executive function abilities provide a critical
platform for the acquisition of domain-specific knowledge and skills in
an educational context. Further, recent studies show that preschool
training of executive skills may prevent early school failure.
Children with ADHD, anti-social behaviour, conduct disorders and autism
can all show atypical patterns of executive function. Basic
neuroscience studies have identified the primary brain structures and
circuits involved in executive functions, including the prefrontal
cortex, in adults. However, much research remains to be done to
understand the development of this circuitry, and the genetic and neural
bases of individual differences in executive function.
Foresight Mental Capital and Wellbeing Project specifically identifies
and highlights the importance of attention and executive function skills
in the future challenges for difficulties in learning (sections 2.2.4
and 2.4 in "Learning Difficulties: Future Challenges").
Neuroscience and education: A bridge too far?
Despite optimism from many who believe that neuroscience can make a
meaningful contribution to education and that the potential exists for
the establishment of a research field of educational neuroscience, some
researchers believe that the differences between the two disciplines are
too great for them to ever be directly linked in a practically
meaningful way. In 1997 John Bruer published a major critique of what he
called the "Neuroscience and education argument".
The ‘neuroscience and education argument’ as Bruer defines it, stems from three major findings in developmental neurobiology.
- Early childhood is characterised by rapid growth in the number of synapses in the brain (synaptogenesis), and this expansion is followed by a pruning period.
- There are so called experience dependant critical periods during which the developing brain is best suited to develop certain sensory and motor skills.
- A stimulus rich environment causes greater synaptogenesis. The essential argument is that children are capable of learning more at an early age when they have an excess of synaptic growth and peak brain activity.
The knowledge of early brain development afforded by neurobiology has
been used to support various arguments with regards to education. For
example, the idea that any subject can be taught to young children in
some intellectually honest form, due to the great adaptability and
learning potential of the young brain.
Alternatively, the idea that critical periods exist for learning
certain skills or knowledge sets appeals to the fact that in animal
studies, if the developing brain is deprived of certain sensory inputs,
the brain areas responsible for processing those inputs fail to develop
fully later in development, and thus "if you miss the window, you are
playing with a handicap".
One of Bruer’s major points of contention with reports in favour
of neuroscience and education is the lack of actual neuroscience
evidence. Reports such as Years of Promise: A Comprehensive Learning
Strategy for America's Children (Carnegie Corporation of New York, 1996)
cite many cognitive and behavioural psychology studies, but no more
than a handful of brain based studies, and yet draws dramatic inferences
with regards to the role of the brain in learning.
Bruer argues that behavioural science can provide a basis for
informing educational policy, but the link to neuroscience is "a bridge
too far", and the limitations of the application of neuroscience to
education stem from the limitations of neuroscience knowledge itself.
Bruer supports his critique by arguing the limitations of current
knowledge regarding the three key tenets of the neuroscience and
education argument.
Another problem is the discrepancy between spatial resolution of
imaging methods and the spatial resolution of synaptic changes that are
suggested to underlie learning processes. A similar problem is true with
regards to the temporal resolution. This makes it hard to relate
subcomponents of cognitive skills to brain function. However, the
primary flaw of the education neuroscience argument in Bruer’s opinion
is that it attempts to link what happens at the synaptic level to higher
order learning and instruction.
The terminology, "Mind, brain and education" alludes to the idea that if
we cannot bridge education and neuroscience directly, then we can use
two existing connections to inform education. These are the link between
cognitive psychology and education, and between cognitive psychology
and neuroscience.
Bruer contends that neuroscience in its current form has little
to offer educators at the practical level. Cognitive science on the
other hand, can serve as a basis for the development of an applied
science of learning and education. Other researchers have suggested
alternative bridges to the cognitive psychology suggested by Bruer. Mason
suggests that the gap between education and neuroscience can be best
bridged by educational psychology, which she outlines as being concerned
with "developing descriptive, interpretive and prescriptive models of
student learning and other educational phenomena".
Challenges to educational neuroscience
Despite Willingham’s assertion
that the potential for neuroscience to contribute to educational
practice and theory is already beyond doubt, he highlights three
challenges that must be overcome to marry the two disciplines
effectively.
The Goals Problem: Willingham suggests that education is a
so-called "artificial science" that seeks to construct an ‘artifact’,
in this case a set of pedagogic strategies and materials. Neuroscience,
on the other hand is a so-called "natural science", concerned with the
discovery of natural principles that describe neural structure and
function. This difference means that some goals set by education are
simply impossible to answer using neuroscience research, for example,
the building of character or aesthetic sense in children.
The Vertical Problem: Levels of analysis: Willingham
suggests that the highest level of analysis employed by neuroscientists
is the mapping of brain structure and activity onto cognitive function,
or even the interaction of cognitive functions (i.e. the impact of
emotion on learning). Within neuroscience research these functions are
studied in isolation for the sake of simplicity, and the nervous system
as a whole, functioning in its entirety with all its huge composition of
functional interactions, is not considered. For educators, on the other
hand, the lowest level of analysis would be the mind of a single child,
with levels increasing to incorporate the classroom, neighborhood,
country etc.
Thus, importing research about a single cognitive factor in
isolation, into a field in which context is essentially important
creates an inherent difficulty. For example, while rote learning may be
shown to improve learning in the research laboratory, the teacher cannot
implement that strategy without considering the impact on the child’s
motivation. In return, it is difficult for neuroscientists to
characterize such interactions in a research setting.
The Horizontal Problem: Translating research findings:
While education theory and data are almost exclusively behavioral,
findings from neuroscience research can take on many forms (e.g.
electrical, chemical, spatial, temporal etc.). The most common form of
data taken from neuroscience to education is the spatial mapping of
brain activation to cognitive function. Willingham (2009) highlights the
difficulty in applying such spatial information to educational theory.
If a certain brain region is known to support a cognitive function
relevant for education, what can actually be done with that information?
Willingham suggests that this ‘horizontal problem’ can be solved only
when a rich body of behavioral data and theories already exist, and points out that such methods have already been successful in identifying subtypes of dyslexia.
Willingham suggests that what is essential for a successful union
of neuroscience and education is that both fields have realistic
expectations of one another. For example, educators should not expect
that neuroscience will provide prescriptive answers for educational
practice, answers for educational goals that are incompatible with
neuroscientific methods (e.g. aesthetic training), or levels of analysis
beyond the individual level. Finally Willingham suggests that
neuroscience will only be useful to educators when targeted at a
specific problem at a fine grained level of analysis, such as how people
read, but that these data will only be useful in the context of well
developed behavioral theories.
Other researchers, such as Katzir & Pareblagoev
have pointed out that neuroimaging methodology as it stands may not be
suitable for the examination of higher level cognitive functions,
because it relies primarily on the ‘subtraction method’. By this method,
brain activity during a simple control task is subtracted from that of a
‘higher order’ cognitive task, thus leaving the activation that is
related specifically to the function of interest. Katzir &
Pareblagoev suggest that while this method may be very good for
examining low level processing, such as perception, vision and touch, it
is very hard to design an effective control task for higher order
processing, such as comprehension in reading and inference making. Thus,
some researchers
argue that functional imaging technologies may not be best suited for
the measurement of higher order processing. Katzir & Pareblagoev,
suggest that this may not be a deficit of the technology itself, but
rather of the design of experiments and the ability to interpret the
results. The authors advocate using experimental measures in the scanner
for which the behavioural data is already well understood, and for
which there exists a strong theoretical framework.
Transforming challenges into opportunities
Another recent review of the educational neuroscience debate by Varma, McCandliss and Schwartz
focuses on eight primary challenges, divided into scientific challenges
and practical challenges, facing the field, and attempts to transform
those challenges into opportunities.
Scientific challenges
Methods:
Neuroscience methods create artificial environments and thus cannot
provide useful information about classroom contexts. Furthermore, the
concern is that if neuroscience begins to influence educational practice
too heavily, there may be a de-emphasis of contextual variables, and
solutions to educational problems may become primarily biological rather
than instructional. However, Varma et al. argue that novel experimental
paradigms create the opportunity to investigate context, such as brain
activation following different learning procedures
and that neuroimaging can also allow for the examination of
strategic/mechanistic developmental changes that cannot be tapped by
reaction time and behavioural measures alone. Furthermore, Varma et al.
cite recent research that shows that the effects of cultural variables
can be investigated using brain imaging (e.g.), and the results used to draw implications for classroom practice.
Data: Knowing the brain region that supports an elementary
cognitive function tells us nothing about how to design instruction for
that function. However, Varma et al. suggest that neuroscience provide
the opportunity for a novel analyses of cognition, breaking down
behaviour into elements invisible at the behavioural level. For example,
the question of whether different arithmetic operations show different
speed and accuracy profiles is the result of different efficiency levels
within one cognitive system versus the use of different cognitive
systems.
Reductionist Theories: Applying neuroscience terminology
and theory to educational practice is a reduction and is of no practical
use to educators. Nothing is gained be redescribing a behavioural
deficit in neuroscientific terms. Varma et al. point out that
reductionism is a mode by which sciences are unified, and that the
co-opting of neuroscience terminology does not necessitate the
elimination of education terminology, it simply provides the opportunity
for interdisciplinary communication and understanding.
Philosophy: Education and neuroscience are fundamentally
incompatible, because attempting to describe behavioural phenomena in
the classroom by describing physical mechanisms of the individual brain
is logically wrong. However, neuroscience may help to resolve internal
conflicts within education resulting from differing theoretical
constructs and terminologies used within subfields of education by
providing a measure of uniformity with regards to results reporting.
Pragmatic concerns
Costs:
Neuroscience methods are highly expensive, and the expected outcomes do
not justify the costs. However, Varma et al. point out that
educationally relevant neuroscience may attract addition funding to
education research rather than usurping resources. The essential claim
of educational neuroscience is that the two fields are interdependent
and that a portion of the funding allocated collectively to the two
fields should be directed towards shared questions.
Timing: Neuroscience, while expanding rapidly, is still in
relative infancy with regards to the non-invasive study of healthy
brains, and thus education researchers should wait until more data is
collected and distilled into succinct theories. Contrary to this, Varma
et al. argue that some success is already evident. For example, studies
examining the success of dyslexia remediation programmes
have been able to reveal the impact of these programmes on the brain
networks supporting reading. This in turn leads to the generation of new
research questions.
Control: If education allows neuroscience in the door,
theories will increasingly be cast in terms of neural mechanisms and
debates will rely increasingly on neuroimaging data. Neuroscience will
cannibalise resources and education research will lose its independence.
Varma et al. argue that the assumption of an asymmetric relationship
between the two fields is unnecessary. Education has the potential to
influence neuroscience, directing future research into complex forms of
cognition and education researchers can help Educational Neuroscience to
avoid naïve experiments and repetition of earlier mistakes.
Neuromyths: Thus far most of the neuroscience findings
applied to education have turned out to be neuromyths, irresponsible
extrapolations of basic research to education questions. Furthermore,
such neuromyths have escaped beyond academia and are being marketed
directly to teachers, administrators and the public. Varma et al.
respond that the existence of neuromyths reveals a popular fascination
with brain function. Appropriate translation of educational neuroscience
results and well established collaborative research can decrease the
likelihood of neuromyths.
A bidirectional relationship
Researchers such as Katzir & Pareblagoev and Cacioppo & Berntson (1992)
argue that as well as neuroscience informing education, the educational
research approach can contribute to the development of new experimental
paradigms in neuroscience research. Katzir and Pareblagoev (2006)
suggest the example of dyslexia research as a model of how this
bidirectional collaboration might be achieved. In this case, theories of
reading processes have guided both the design and interpretation of
neuroscience research, but the existing theories were developed
primarily from behavioural work. The authors suggest that the
establishment of theories, which delineate required skills and subskills
for educationally relevant tasks, is an essential requirement for
educational neuroscience research to be productive. Furthermore, such
theories need to suggest empirically testable connections between
educationally relevant behaviours and brain function.
The role of educators
Kurt
Fischer, director of Harvard University’s Mind, Brain and Education
graduate program states "One of the reasons there is so much junk out
there is that there are so few people who know enough about education
and neuroscience to put the thing together".
Educators have been reliant upon others’ expertise for the
interpretations from Neuroscience hence have not been able to discern
whether the claims made are valid or invalid representations of the
research. Without a direct access to the primary research educators may
be at risk of misusing results from neuroscience research.
The need for so called ‘middlemen’ in the translation of research to
practice has led to a situation where the application of cognitive
neuroscience research findings is running ahead of the research itself.
In order to negate the need for middlemen, some researchers have suggested the need to developed a group of neuro-educators,
a specially trained class of professionals whose role would be to guide
the introduction of cognitive neuroscience into educational practice in
a sensible and ethical manner. Neuro-educators would play a
pivotal role in assessing the quality of evidence purporting to be
relevant to education, assessing who is best placed to employ newly
developed knowledge, and with what safeguards, and how to deal with
unexpected consequences of implemented research findings.
Byrnes & Fox (1998)
have suggested that developmental psychologists, educational
psychologists and teachers generally fall into one of four orientations
with respect to neuroscientific research "(1) those who readily accept
(and sometimes over interpret) the results of neuroscientific studies;
(2) those who completely reject the neuroscientific approach and
consider the results of neuroscientific studies meaningless; (3) those
who are unfamiliar with and indifferent toward, neuroscientific
research; and (4) those who cautiously accept neuroscientific findings
as being a proactive part of the total pattern of findings that have
emerged from different corners of the cognitive and neural sciences".
Greenwood (2009)[85] suggests that as the body of knowledge
available to educators increases, and the ability to be expert in all
areas diminishes, the most productive standpoint would the fourth
outlined by,[87] that of cautious acceptance of neuroscientific findings and proactive collaboration.
Bennett & Rolheiser-Bennett (2001)
point out that "teachers must be aware of and act on the science within
the art of teaching". They suggest that educators must become aware of
other methods and incorporate them into their practice. Furthermore,
Bennett and Rolheiser-Bennett suggest that specific bodies of knowledge
will play an important role in informing educators when making important
decisions with regards to the "design of learning environments". The
bodies of knowledge discussed include multiple intelligences, emotional
intelligences, learning styles, the human brain, children at risk and
gender. As the authors explain these and other areas are just "lenses
designed to extend teachers’ understanding of how students learn, and
from that understanding, to make decisions about how and when to select,
integrate, and enact items in the … list".
Mason
supports calls for a two-way constructive collaboration between
neuroscience and education, whereby, rather than neuroscience research
simply being applied to education, findings from neuroscience research
would be used to constrain educational theorizing. In return, education
would influence the types of research questions and experimental
paradigms used in neuroscience research. Mason also gives the example
that while pedagogical practice in the classroom may give rise to
educational questions regarding the emotional bases of performance on
school tasks, neuroscience has the potential to reveal the brain basis
of higher-order thinking processes and thus may help to understand the
role that emotion plays in learning and open new areas of study of
emotional thought in the classroom.
Neuromyths
The term "neuromyths" was first coined by an OECD report on understanding the brain.
The term refers to the translation of scientific findings into
misinformation regarding education. The OECD report highlights three
neuromyths for special attention, although several others have been
identified by researchers such as Usha Goswami.
- The belief that hemispheric differences relate to different types of learning (i.e. left brain versus right brain).
- The belief that the brain is plastic for certain types of learning only during certain "critical periods", and therefore that learning in these areas must occur during these periods.
- The belief that effective educational interventions have to coincide with periods of synaptogenesis. Or in other words, children's environments should be enriched during the periods of maximal synaptic growth.
Left versus right brain
The idea that the two hemispheres of the brain may learn differently has virtually no grounding in neuroscience research.
The idea has arisen from the knowledge that some cognitive skills
appear differentially localised to a specific hemisphere (e.g., language
functions are typically supported by left hemisphere brain regions in
healthy right handed people). However, massive amount of fibre
connections link the two hemispheres of the brain in neurologically
healthy individuals. Every cognitive skill that has been investigated
using neuroimaging to date employs a network of brain regions spread
across both cerebral hemispheres, including language and reading, and
thus no evidence exists for any type of learning that is specific to one
side of the brain.
Critical periods
The critical periods neuromyth is an overextension of certain
neuroscience research findings (see above) primarily from research into
the visual system, rather than cognition and learning. Although sensory
deprivation during certain time periods can clearly impede the
development of visual skills, these periods are sensitive rather than
critical, and the opportunity for learning is not necessarily lost
forever, as the term "critical" implies. While children may benefit from
certain types of environmental input, for example, being taught a
second language during the sensitive period for language acquisition,
this does not mean that adults are unable to acquire foreign language
skills later in life.
The idea of critical periods comes primarily from the work of Hubel and Wiesel.
Critical periods generally coincide with periods of excess synapse
formation, and end at around the same time that synaptic levels
stabilise. During these periods of synaptic formation, some brain
regions are particularly sensitive to the presence or absence of certain
general types of stimuli. There are different critical periods within
specific systems, e.g. visual system has different critical periods for
ocular dominance, visual acuity and binocular function
as well as different critical periods between systems, for example, the
critical period for the visual system appears to end around the age of
12 years, while that for acquiring syntax ends around 16 years.
Rather than talking of a single critical period for general
cognitive systems, neuroscientists now perceive sensitive periods of
time during which the brain is most able to be shaped in a subtle and
gradual fashion. Furthermore, critical periods themselves may be divided
into three phases. The first, rapid change, followed by continued
development with the potential for loss or deterioration, and finally a
phase of continued development during which the system can recover from
deprivation.
Although there is evidence for sensitive periods, we do not know
whether they exist for culturally transmitted knowledge systems such as
educational domains like reading and arithmetic. Further, we do not know
what role synaptogenesis plays in the acquisition of these skills.
Enriched environments
The enriched environment
argument is based on evidence that rats raised in complex environments
perform better on maze tasks and have 20-25% more synaptic connections
than those raised in austere environments.
However, these enriched environments were in laboratory cages, and did
not come close to replicating the intensely stimulating environment a
rat would experience in the wild. Furthermore, the formation of these
additional connections in response to novel environmental stimuli occurs
throughout life, not just during a critical or sensitive period. For
example, skilled pianists show enlarged representations in the auditory
cortex relating specifically to piano tones, while violinists have enlarged neural representations for their left fingers.
Even London taxi drivers who learn the London street map in intense
detail develop enlarged formations in the part of the brain responsible
for spatial representation and navigation.
These results show that the brain can form extensive new connections as
the result of focused educational input, even when this input is
received solely during adulthood. Greenough’s work suggests a second
type of brain plasticity. Whereas synaptogenesis and critical periods
relate to experience-expectant plasticity, synaptic growth in complex
environments relates to "experience-dependent" plasticity. This type of
plasticity is concerned with environment specific learning, and not to
features of the environment that are ubiquitous and common to all
members of the species, such as vocabulary.
Experience dependent plasticity is important because it does
potentially link specific learning and brain plasticity, but it is
relevant throughout the lifetime, not just in critical periods.
"Experience-expectant plasticity", suggests that the environmental features necessary for fine tuning sensory systems
are ubiquitous and of a very general nature. These kinds of stimuli are
abundant in any typical child's environment. Thus, experience-expectant
plasticity does not depend on specific experiences within a specific
environment, and therefore cannot provide much guidance in choosing
toys, preschools, or early childcare policies. The link between
experience and brain plasticity is intriguing. No doubt learning affects
the brain, but this relationship does not offer guidance on how we
should design instruction.
Bruer also warns of the dangers of enriching environments on the
basis of socio-economic value systems, and warns of a tendency to value
typically middle class pursuits as more enriching than those associated
with a working class lifestyle, when there is no neuroscientific
justification for this.
Synaptogenesis
In addition some critics of the Educational Neuroscience approach
have highlighted limitations in applying the understanding of early
physiological brain development, in particular synaptogenesis to
educational theory.
Synaptogenesis research has primarily been carried out on animals
(e.g. monkeys and cats). Measures of synaptic density are aggregate
measures, and it is known that different types of neuron within the same
brain region differ in their synaptic growth rates. Secondly, the
purported "critical period" of birth to three years is derived from
research on rhesus monkeys, who reach puberty at the age of three, and
assumes that the period of synaptogenesis in humans exactly mirrors that
of monkeys. It may be more reasonable to assume that this period of
neural growth actually lasts until puberty, which would mean until early
teenage years in humans.
Periods of intense synaptogenesis are typically correlated with
the emergence of certain skills and cognitive functions, such as visual
fixation, grasping, symbol use and working memory. However, these skills
continue to develop well after the period that synaptogenesis is
thought to end. Many of these skills continue to improve even after
synaptic density reaches adult levels, and thus the most we can say is
that synaptogenesis may be necessary for the emergence of these skills,
but it cannot account entirely for their continued refinement. Some other form of brain change must contribute to ongoing learning.
Additionally, the types of cognitive changes usually seen to
correlate with synaptogenesis revolve around visual, tactile, movement
and working memory. These are not taught skills but rather skills that
are usually acquired independent of schooling, even though they may
support future learning. How these skills relate to later school
learning is, however, unclear. We know that synaptogenesis occurs, and
that the pattern of synaptogenesis is important for normal brain
function. However, what is lacking is the ability of neuroscience to
tell educators what sort of early childhood experiences might enhance
children’s cognitive capacities or educational outcomes.
Male versus female brain
The idea that a person can have a "male" brain or "female" brain is a
misinterpretation of terms used to describe cognitive styles by
when attempting to conceptualise the nature of cognitive patterns in
people with autism spectrum disorder. Baron-Cohen suggested that while
men were better "systemisers" (good at understanding mechanical
systems), women were better "empathisers" (good at communicating and
understanding others), therefore he suggested that autism could be
thought of as an extreme form of the "male brain". There was no
suggestion that males and females had radically different brains or that
females with autism had a male brain.
Learning styles
A common myth in the field of education is that individuals have different learning styles,
such as 'visual' or 'kinesthetic'. Many individuals will state
preferences for the way in which they want to learn, but there is no
evidence that matching a teaching technique to a preferred style will
improve learning, despite this hypothesis being tested multiple times.
There may even be harms associated with the use of learning styles,
wherein learners become 'pigeonholed', perceiving that they may not be
suited to types of learning that are not matched to their 'learning
style'
(e.g. so-called visual learners may not wish to learn music). Despite
this lack of evidence, a 2012 study demonstrated that a belief in the
use of learning styles is widespread amongst teachers, and a 2015 study showed that the majority of research papers in higher education research mistakenly endorse the use of learning styles.
