Educational neuroscience

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.

== Early history of the field == Scholars, such as Herbert Walberg and Geneva Haertel, trace the beginning of Educational neuroscience to the era between 1800 and 1850 when the scientific study of sense organs began to make advancements. It was during this time that Galen's dictum, which held that the mind was located in the brain, gained acceptance. The study of reflex action during this era triggered a debate over conscious and unconscious states. Mental chronometry that studied the processing speed or reaction time of the brain also began during this period, and was used to infer questions about temporal sequencing of mental operations. By the late 1800s all these developments were categorized as the "new psychology." An early milestone for the development of Educational neuroscience was the offering of a course in Educational Psychology in 1839 at the University of Nebraska. By 1886 similar courses were offered at the State University of New York at Oswego, the Normal School Department of University of Iowa and the Department of Pedagogy at Indiana University. In 1895 the University of Nebraska went on to found a professorship of educational psychology. By the 1900s disputes among schools of education grew over the content of undergraduate educational psychology courses. (Disagreement between professionals about the definition of Educational neuroscience, has always been part of the field and continues to this day.) Despite arguments about how the field should be defined, there is widespread agreement that American psychologists William James, Edward Thorndike, and James McKeen Cattell are important figures in its advancement in the early decades of the 1900s. Another milestone for the field of Educational neuroscience was the publication in 1910 of the first issue of the Journal of Educational Psychology. Since then, philosophical and scientific movements (such as cognitive theory) have influenced the development of the field. As the field has matured it has played a part in shaping policy during periods of educational reform.

== 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 US 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 regard 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 with 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 regard 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 shed 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 ...

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