I wrote this article in February 2015 as part of my PGCE Top-Up course at the University of Northampton. This is a course aimed at teachers who already have completed initial teacher training through the graduate training programme and gained QTS, but want to add on the university PGCE to this qualification.
Why publish it here? I have found that my own interests within Biology have developed hugely since I started teaching, taking me to academic areas that I never studied in my original Zoology degree. This is partly through trying to keep abreast with a subject whose post-16 content has changed and continues to change dramatically year on year and also partly through my own genuine interest in the subject. The brain and behaviour has been one of these areas.
As teachers we have a natural interest in how the mind works and how individuals learn. In one (very loose) sense teachers are Biologists because of this interest; we want to understand the mind of this species of hominid and how it develops.
My interest in educational neuroscience represents for me a cross over of these spheres of interest in my own professional life – biological science, specifically neuroscience and education.
Thoughts gratefully received.
On 19th October 1964 a paper was published in the journal Physical Review Letters. In it the author, Peter Higgs, hypothesised about the existence of a fundamental particle that was responsible for giving mass to other fundamental particles: the so-called Higgs Boson (Higgs, 1964). 47 years, 8 months and 15 days later, the European Organisation for Nuclear Research, CERN, confirmed that experimental physicists working at the facility had demonstrated the existence of the particle (CERN, 2015).
This story of discovery illustrates the wonderful interplay in science between scientific theory and scientific fact. The Higgs theory was just one of several competing models which had been proposed over 4 decades to explain how fundamental particles may interact. With the discovery of the Higgs Boson, the Higgs theory, with some modification, was proved to be the correct explanation.
In a similar way neuroscientific studies of the brain and its functioning could be used to constrain and validate psychological theories of learning. Educational practice uses psychological theories, developed over the past century or so, what if we attained physical evidence to illuminate which ones should be developed and which ones could be discarded?
Modern educational theory has diversified hugely with specialist areas devoted to studying different learning contexts e.g. classroom, outdoor, experiential, life-long, as well as at different developmental stages e.g. early years, school-age, university and adult (For a review see Illeris, 2009). It is only relatively recently that educational researchers have begun to try to forge links between education theory and neuroscience (Geake, 2009), while some have questioned the basic ability of these two fields to be bridged (Bruer, 1997).
I will review the evidence that educational neuroscience is yielding, and review the arguments for and against use of neuroscience in the context of education. Neuroscience still has much to learn about the brain but we already have an understanding that can inform educational practice on a variety of levels. I will begin by describing the development of psychological theories of learning before moving on to examine the contribution that modern neuroscientific or brain based theories of learning may yet make towards developing our understanding of how humans learn.
Humankind’s interest in learning and teaching could be said to go right back to the early days of our pre-history when, as a new species, we had to invent new ways to respond to a changing environment. Indeed learning is without doubt a very, but not solely, human trait; it is essentially what has allowed us to adapt to every environment on the planet.
Modern attempts to explain how humans learn have their roots in the psychological theories of the late 19th Century with the advent of cognitive psychology, behavioural science and ethology (Pritchard, 2009).
In the 20th Century behaviourists, notably Skinner (1958), developing the work of Ivan Pavlov, focussed on innate behaviour in animals and discovered the mechanisms of conditioning and reinforcement. Behaviourist approaches to understanding learning and human development view learning as the acquisition of new behaviour (Prichard, 2009).
In contradiction to behaviourism, constructivism views learning as the result of mental construction i.e. new learning is added to pre-existing knowledge. Piaget (1954) and Vygotsky (1997) separately developed their own particular brands of constructivism which differed fundamentally about how learning is constructed: Piaget viewed learning as being cognitively constructed and that students acted as lone scientists who learn through discovery; Vygotsky viewed learning to be socially constructed, with the teacher (and other students) having a significant contribution to play in scaffolding the work and setting the challenge for their students (Pritchard, 2009).
The influence of these theories cannot be understated. Constructivism is the key idea in education, underpinning not only many modern theories of learning, but also curriculum models (like the International Baccalaureate, an inquiry-based curriculum model [IBO, 2015]) and classroom based pedagogical approaches. Today it is taken for granted that learning is constructed within the mind of the learner and therefore new learning builds upon prior learning and understanding. This is the overwhelming epistemological standpoint that underpins all of modern theories of learning (Samuels, 2009).
Neuroscience and Education
Much of the early research in neuroscience focused on the structure and function of neurons, the specialised cells that make up the brain and nervous system. These neurons, form connections (synapses) with each other. At these synapses individual neurons are able to generate or inhibit the “firing” of impulses within the other neurons that they are connected to. In this way neurons are assembled into neuronal groups or brain modules (Geake, 2009). It is these neuronal groups, their interconnectivity and how they may relate to pedagogical practice that is of interest in educational neuroscience.
An early neuroscientific model of learning, that is still robust today in terms of its explanatory power is that proposed by school-teacher turned neuroscientist Donald Hebb (1949). In Hebb’s model of learning it is the number of connections within the brain not the number of neurons that is important. He states that when a neuron stimulates or inhibits a signal in another neuron across a synapse, that synaptic connection is reinforced. Conversely when signals are not issued across a synapse very frequently, that junction between the two cells, is not preserved. Thus neurons that consistently communicate with each other have their synaptic connections maintained, while those that do not lose their connections.
Attempts to link the findings from neuroscientific research and formal educational practice date back to the 1980s (Bruer, 1997) and since that time, opinions of educational researchers have been divided on the usefulness of neuroscientific research in education (see Bruer, 1997, Geary 1998, Geake & Cooper, 2003, Goswami, 2004). However, recent writers are less pessimistic (Goswami, 2006, Varma et al., 2008, Samuels, 2009, Ansari et al., 2011, Howard-Jones et al., 2014, Howard-Jones 2014, Schenk & Cruickshank, 2014) and the trend in published articles becomes more positive. Indeed, it is telling that in the last decade we have seen the formation of the International Mind, Brain and Education Society (IMBES) along with the Mind, Brain and Education Journal. The Societies aim is to “facilitate cross-cultural collaboration in biology, education and the cognitive and developmental sciences” (IMBES, 2015). In addition there have been two formal reviews of the field, first by the Organisation for Economic Co-Operation and Development (OECD, 2008) and the second by the Royal Society (Royal Society, 2011). All of these developments suggest that the findings from neuroscience and education research are beginning to converge.
Many of the arguments questioning the usefulness of educational neuroscience have focussed either on the limitations of the methodologies employed in studying neuroscience or the extrapolations that education professionals (researchers, teachers, civil servants) have made about the results from neuroscientific studies resulting in the so-called “neuromyths”.
Bruer (1997) argues that neuroscience only has an explanatory power when viewed through cognitive psychology. He described the three fields of classroom instruction, cognitive psychology and neuroscience as being spanned by two bridges – one from instruction to cognitive psychology and a second from cognitive psychology to neuroscience and that only by contributing to our understanding of cognitive psychology could neuroscience hope to deepen our understanding of classroom learning. He describes using neuroscience to study learning as a bridge too far. His essay has been citied a great number of times and the arguments he makes are worthwhile to the classroom practitioner.
Bruer’s premise is that studying the mind is not necessarily informed by studying the brain. This argument is rebutted by Cruickshank & Schenck (2014) and Howard-Jones (2014) who argue that because the mind is created by the brain it must have biological correlates. The systems of processing in the mind must be reflected by systems in the brain. This is an idea that as a Biologist and Science Teacher I tend to agree with.
Bruer (1997) also describes at length the early work of neuroscience that was conducted on single neurons in rats, mice or monkeys. He demonstrates that much of the evidence from these studies has been extrapolated to humans and used to describe human neural development. He makes the valid argument that extrapolation from rats to humans is a large assumption. This extrapolation has formed the basis of many “neuromyths” – misconceptions about learner’s brains that have been adopted by the education community. These misconceptions tend to contain “nuggets” of truth which have been misunderstood or poorly applied (Howard-Jones 2014).
Goswami (2006), Geake (2009) and Howard-Jones (2014) provide excellent up to date considerations of the neuromyths that have been adopted by the education community. They cite the ideas that learners are left or right brained; brains are male or female; the existence of brain buttons under the ribs; that there are critical periods for learning; that brains process information from different senses independently and that there are, consequently, individual learning preferences, as examples of neuromyths.
The prevalence of neuromyths cited within the literature and used to support various philosophies and policies of education is used by Bruer (1997) as evidence that neuroscience cannot, and should not, influence education. It seems to me that this argument is to misunderstand and misappropriate the role of science in society. It is precisely because neuromyths abound that systematic research needs to be conducted and communicated clearly to stakeholders. The reports from the Royal Society (2011) and the OECD (2008) along with Geake (2009) and many other authors now highlight the need for initial teacher training that provides some training in general scientific and neuroscience specific methods, as well as making an argument that deeper collaboration between the education and neuroscience academic communities is necessary so that educators and neuroscientists are able to better spot and counter these myths with biological evidence. Educational neuroscience has great potential to become a transdisciplinary area of collaboration with ideas from both fields influencing the other.
Bruer (1997) also writes about the problems with interpreting data from neuroimaging studies as well as the use of neuroimaging technology to study educational problems. In the 1990’s there was a huge expansion in development of technologies used to study the brain. For a review of these methodologies see Geake (2009) but it is important to note that the maps produced by scans of the brain are averages and do not necessarily represent individual brains. At that time neuroimaging technologies had very little ability to ask questions about classroom practice due to their size and cost, however these limitations are dramatically decreasing (Royal Society, 2011, OECD, 2008) and studies that actively image the brain during specific classroom based tasks are beginning to be published.
The relationship between neuroscience and the psychological study of literacy and the acquisition of language in school children is the oldest and most robust (OECD, 2008) and researchers in the field now have a good understanding of the neurological correlates for language learning which can inform the choice and timing of pedagogical activities. There is a sensitive but not critical timing for learning a second language in the early years of education (Geake, 2009 & Royal Society, 2011).
Educational neuroscientific research into the neurological correlates for numeracy and mathematical ability is newer, although important evidence is already emerging about how the brain processes the different mathematical information and learns specific mathematical skills (Geake, 2009 & Royal Society, 2011).
Perhaps the most interesting and important questions that educational neuroscience is addressing are those concerned with learning difficulties. Educational neuroscience research has now provided a biological basis for the causes of Dyslexia. Diagnosis of the condition can be made based on neurological evidence and when twined with an improved understanding of how the brain processes word forms and sounds, neurological evidence can suggest effective methods of treatment. Similar work on Dyscalclia is already underway (Geake, 2009 & Royal Society, 2011).
Several authors (OECD, 2008, Geake, 2009, Royal Society, 2011) provide a thorough overview of the key findings from neuroscience generally and how they may apply to educational practice. A key general understanding is that no two human brains are the same. This may seem trite but even identical twins, which are the same genetically, show differences in their brain structure. This illustrates how much the brain is shaped by the environment it interacts with. The Royal Society 2011 writes:
“The brain is constantly changing and everything we do changes our brain…the brain has extraordinary adaptability, sometimes referred to as ‘neuroplasticity’”
The report goes on to explain that this is due to the processes that strengthen synapses and the effect is present throughout life. Contrary to early ideas of brain development we now know that the brain can adapt, change and therefore learn throughout life even into old age (OECD, 2008). Throughout life new synapses grow and are pruned but this process of pruning and growth is most prevalent at certain sensitive periods, from early childhood to late teens and early twenties. Individual experiences and environments shape individual brains (Royal Society, 2011).
While Individuals show differences in the structure of their brains this does not mean that there is evidence for individual learning styles of preferences. Due to the massive interconnectivity within the brain between individual neurons and between brain modules we know that information is processed across a wide variety of areas of the brain and that these areas are overlapping and interlinked. The ideas of learning styles –that learners learn exclusively through one sensory modality are false (Kratzig & Arbuthnott 2006). For example the areas of the brain that process speech overlap with those that process movement. The idea that an individual processes visual information in isolation from any other sense is another example of a neuromyth (Geake, 2009). In fact the interconnectedness of different sensory areas within the brain supports the notion of multisensory teaching i.e. approaching subject matter and skills through a variety of sensory inputs as this will enable more robust networks of neurones to form in the same manner as may be expected from repetition.
Geake (2009) defines the purpose of education as enabling the individual to gain transferable life skills from a variety of contexts. He also points out that learning in the form of memory formation of skills and concepts requires directed attention from working memory i.e. the engagement of the prefrontal cortex and the areas associated with working memory. Evidence shows that learners need to be guided. The brain can just as easily learn incorrect skills and content, but unlearning them is difficult because it requires the pruning of connections in the brain. Thus there are implications for inquiry based teaching methods and the idea that gifted students are able to teach themselves. Adult guidance and encouragement along with appropriate intellectual challenges should therefore be a central strategy for schools (Geake, 2009, Krishner et al., 2006).
Geake (2009) highlights the need for repetition within the learning environment of an individual. Repetition over time reinforces synaptic connections and allows the effective transference into long term memory. He illustrates this argument with the example of learning music. Hours of practice of the correct finger movements on an instrument allow the motor cortex to develop the neural networks that control the movement sequences. He does not advocate repetition in the sense of drilling exercises but suggests that spiral curriculums where individuals meet related concepts throughout their school experience, each time at a deeper and deeper level, along with lower pupil rations and immediate feedback from assessment to correct errors in processing would be beneficial for learners.
Educational neuroscience has also highlighted the interdependence of intellectual and physical wellbeing and much work has highlighted the importance of emotional wellbeing for learning (OECD, 2008). We now know how stress can inhibit learning because the centres of the brain that deal with emotion affectively inhibit the areas that help to regulate activity across the brain and are used in learning.
Modern theories of learning build firmly upon constructivist ideas (Samuels, 2009), but precisely because there is such a plethora of modern learning theories means that they cannot all be right (Geake, 2009).
Gardner’s (1983 & 1999) theory of multiple intelligences, a retelling of Plato’s ideal curriculum, is one such educational theory that must be qualified. It has been widely cited in educational policies and led to many misinterpretations such as labelling all children in a school as gifted by definition Geake (2009). Howard-Jones (2014) and Waterhouse (2006) argue that there is no neural evidence to support the idea of multiple intelligences but that there is evidence to suggest that there is a general cognitive ability underpinning all the possible dimensions of intelligence.
While massive differences exist in brain structure, the interconnectivity of the brain does point to a single underlying intelligence factor. Intelligence does have a genetic and environmental component in the same way that an individual heights do. Genetically, intelligence is brought about through the interaction between many genes; each of which have an individually small effect. The environment also has a role to play in unlocking the brains potential as diet, toxins and social interactions all up-regulate or down-regulate the effects of genes. A good social educational environment will enable an individual brain to reach it full intelligence potential (Geake 2009).
At this stage educational neuroscience may not have the resolution to inform specifically about many aspects of classroom pedagogy (e.g. in science teaching) or classroom contexts but it is able to inform us about generalities that may inform curriculum planning on a whole school and regional basis. E.g. sleep patterns and gender differences, developmental differences, as well as serving to identify the psychological theories that may be most robust.
Obviously if we were to remove an individual’s brain we would soon find that they had lost the ability to learn altogether! Therefore is it unreasonable to be able to expect the workings of the mind to be understood through a deeper understanding of the brain?
The beauty of educational neuroscience is in its potential ability to underpin and constrain psychological theories of learning. Like Higgs with his Boson and the experimental physicists that validated its existence, educators are on the cusp of not only being able to identify a psychological intervention that works but also able to explain why it works, thanks to the evidence derived from educational neuroscience. To enable this we need better communication between the education and neuroscience communities.
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