Educational Neuroscience

Denis Mareschal, Brian Butterworth, Andy Tolmie, Denis Mareschal, Brian Butterworth, Andy Tolmie

• Publisher: Wiley-Blackwell
• Year: 2013
• ISBN:
  9781118315040
• Edition: 1
• Topic: Psychologie
• Subtopic: Éducation en psychologie

Educational Neuroscience presents a series of readings from educators, psychologists, and neuroscientists that explore the latest findings in developmental cognitive neurosciences and their potential applications to education.

• Represents a new research area with direct relevance to current educational practices and policy making
• Features individual chapters written collaboratively by educationalist, psychologists, and neuroscientists to ensure maximum clarity and relevance to a broad range of readers
• Edited by a trio of leading academics with extensive experience in the field

Chapter 1

Introduction

Brian Butterworth and Andy Tolmie

The Nature of the Discipline

Education is about enhancing learning, and neuroscience is about understanding the mental processes involved in learning. This common ground suggests a future in which educational practice can be transformed by science, just as medical ­practice was transformed by science about a century ago.

Report by the Royal Society, UK, 2011

The mission statement of the Centre for Educational Neuroscience in London, the affiliation of all but two of the lead authors in this book, states how this transformation can be brought about:

What: Our vision is to bring together three previously distinct disciplines ­[education, psychology and neuroscience] – to focus on a specific common problem: how to promote better learning. This will mean building a new scientific community and a new discipline, educational neuroscience.

Why: We now understand better how learning organizes and reorganizes the brain, but there is very little research so far that has had an impact on educational delivery. What is lacking is a body of researchers who are expert in education, psychology, and neuroscience, and to create these researchers is a primary aim of the project.

How: We believe we can do this by building on existing research collaborations and creating new initial training, post-graduate research, and continuing professional development opportunities for becoming expert in educational neuroscience.

Impact: Bringing education, psychology, and neuroscience together can help in designing better learning environments through the lifespan, and this will lead to more fulfilled and more effective learners.

Three Disciplines: Education, Psychology, Neuroscience

The goal of educational neuroscience is to work out how all learners can be helped to achieve their learning potentials and to make learning more effective for all learners. This has meant in practice that education seeks answers to two main questions.

What are the sources of individual differences in learning?

What are the optimal contexts for the learner?

In an attempt to answer these questions, educational neuroscience has evolved through three key phases of enquiry, which we discus in turn below. See Figure 1.1.

Phase 1. Education and psychology

Prior to the emergence of educational neuroscience as a separate discipline, in what we call Phase 1, educational research had a long history of collaboration with ­psychology in trying to achieve these goals. This is especially true in curriculum ­relevant areas such as learning to read and learning mathematics. Psychology first pointed to two main sources of individual differences in learning. First, there were differences in intrinsic cognitive capacity, for example as measured by IQ tests or tests of working memory, and more recently differences in cognitive styles. Another approach has revealed evidence for domain-specific cognitive differences in ­language acquisition (see Chapter 6), learning to read (see Chapter 7) and learning arithmetic (see Chapter 8). Second, psychological as well as sociological studies revealed experiential sources of individual variation, for example differences in home environment using socioeconomic status or parental education as proxy measures (e.g., Melhuish et al., 2008). Finally, with regard to optimal learning contexts, psychology has provided methodologies for investigating and comparing teaching methods, but it has also made proposals, mostly for mathematics and reading, and to some extent for science.

Figure 1.1 Three phases in the emergence of educational neuroscience.

In mathematics, there was the classic debate between Thorndike and Brownell. In The Psychology of Arithmetic, Thorndike (1922) took ideas from associationist theories of psychology, and emphasized drilling simple number bonds. In the 1930s, Brownell, in several important papers, applied psychological ideas about meaningful practice to how math should be taught. In the 1950s and 1960s, Piaget’s “constructivist” theories about the nature of cognitive development were very influential. Constructivism emphasizes the child’s construction of new schemas (accommodation) when new stimuli cannot be understood using existing schemas (see Chapter 8).

In the case of learning to read, perhaps the most striking impact of psychology is in differentiating dyslexic learners from other learners. Here careful psychological assessment revealed that some children found it hard to learn to read despite good vision, high general intelligence, appropriate teaching, and supportive home environment. Critically, it was found that dyslexic learners suffered from a deficit in analyzing the phonological structure of their language and indeed that phonological training could help (Bradley & Bryant, 1978).

Nevertheless, the debate continues as to whether there is a single underlying phenotype (Elliott, 2005) or whether there are a variety of separable causes of delays and differences in learning to read. Much ink has been spilled in the so-called “reading wars” about which method of teaching reading is most effective. Evidence, until recently, has been entirely based on psychological studies of reading performance. On one side, there are those who have proposed the whole-word or whole-language method, in which letter–sound associations are not drilled, but rather children are encouraged to recognize whole words, sound them out, and interpret them. On the other side, there is phonics, based precisely on drilling letter–sound correspondences (Ehri, Nunes, Stahl, & Willows, 2001) Unfortunately, many proponents of the two approaches appear to have a political agenda in which left-leaning child-centered proponents prefer the former, and conservative exam-focused proponents prefer the ­latter. Of course, in an orthography such as English, with many irregular and exceptional pronunciations, the learner needs to have a grasp of both letter–sound correspondences and whole-word pronunciations and meanings. Learners certainly need to know that pint is not pronounced to rhyme with print. It may be that it will be helpful for the teacher to encourage the learner to recognize whole letter strings, rather than simply insist on sounding out the letters. Nevertheless, children can and do learn to read irregular and exception words by “self-teaching”: that is, by using context to figure out what must be meant and thereby get a plausible pronunciation of pint, which will then be stored in the mental lexicon of meaningful letter strings (Share, 1995).

Phase 2. Psychology and neuroscience

This phase is characterized by the collaboration between neuroscience and the cognitive, affective, and developmental branches of psychology, to create cognitive neuroscience. In the course of this collaboration, questions arising from education were raised, notably in the neural basis of reading and its disorders, and in mathematics and its disorders, but also in more general issues of attention, executive function, and memory.

The neural underpinnings of cognition and learning in particular have also been the subject of studies of neurological patients. This is perhaps most striking in the case of learning and memory, where selective deficits in patients revealed much about the structure of memory, distinguishing short from long-term memory, declarative from procedural memory, encoding from retrieval, and so on. Even the first steps in revealing the neural bases of curriculum-relevant cognitive processes owe much to the study of patients. The identification of selective reading and spelling problems and evidence for their neural basis dates back to Dejerine in 1892, and modern multiroute models of normal reading were due initially to studies of patients (see Shallice, 1988, for the classic account). Similarly, the basic anatomy and functional organization of mathematical cognition was identified from studies of selective deficits in patients (Caramazza & McCloskey, 1987; Dehaene & Cohen, 1995; Warrington, 1982).

However, the critical impetus for the most relevant aspect of neuroscience for education, cognitive neuroscience, came with availability of in vivo imaging of neural processes as they happened (see Chapter 2 for a discussion of these methodologies). Neuroimaging has revealed important aspects of domain-general cognitive processes, such as performance on IQ tests, even the developmental trajectory of verbal and non-verbal IQ (Ramsden et al., 2011) and the neural basis of verbal working memory (Paulesu, Frith, & Frackowiak, 1993) and spatial working memory (Petrides, 2000; van Asselen et al., 2006). Other domain-general ­capacities that contribute to individual differences, such as attention and goal-directed behavior, social and emotional development are now better understood from neuroimaging studies (see Chapter 2). The capacity to understand other minds has also become clearer (see Frith, 2007, and Chapter 10).

Advances have also been made in curriculum-relevant cognitive capacities. For example, the reading network in the brain as revealed by neuroimaging clearly links visual recognition in the inferior temporal region with speech in the inferior frontal gyrus and with word meanings in the middle temporal lobe. This has enabled a better understanding of individual differences in the ability to learn to read in dyslexia. This has been shown to be related to abnormalities in this network: decreased activation in the left inferior temporal region (Paulesu et al., 2001) and abnormal structure in the left middle temporal lobe (Silani et al., 2005). These findings may help to resolve the skepticism that still surrounds the classification of learners as dyslexics.

Note that, without neuroimaging, it might be thought that learning different orthographies, such as alphabetic English or Italian as compared with ­character-based Chinese or Japanese, might depend on very different neural circuits. However, we now know from neuroimaging that all orthographies depend on similar neural networks (Dehaene, 2009) and indeed that dyslexia is due to similar neural abnormalities (Paulesu et al., 2001).

It has now become feasible to carry out large-scale studies of the development of the brain, and to understand better the genetic and environmental factors that affect it.

Phase 3. Emergence of educational neuroscience

Phase 3 is where we are now: we are seeking to use neuroscience to inform educational practice as a way to improve learning. In 1997, John Bruer famously argued that this was “a bridge too far.”

Currently, we do not know enough about brain development and neural function to link that understanding directly, in any meaningful, defensible way to instruction and educational practice. … There is a well-established bridge, now nearly 50 years old, between education and cognitive psychology. There is a second bridge, only around 10 years old, between cognitive psychology and neuroscience. This newer bridge is allowing us to see how mental functions map onto brain structures. When neuroscience does begin to provide useful insights for educators about instruction and educational practice, those insights will be the result of extensive traffic over this second bridge. Cognitive psychology provides the only firm ground we have to anchor these bridges. It is the only way to go if we eventually want to move between education and the brain.

Bruer based this position on critiques of three aspects of very basic neuroscience usually derived from studies of non-human species: the time course of ­synaptogenesis and synaptic pruning, critical periods for learning, and the role of enriched early environments. He quite sensibly notes that the evidence from these aspects is not sufficient to inform formal education. However, Since Bruer’s (1997) paper, there has been rapid expansion of the “pontoon” between the two bridges – cognitive neuroscience. This discipline deploys the resources of brain imaging to develop and refine our understanding of cognitive processes, including those that underpin educational attainment, such as working memory and learning processes, and also curriculum-relevant cognitions involved in language, reading, motivation, and mathematics. This in itself would still be the two-bridge solution that Bruer alluded to.

In 2005, Nature published a skeptical editorial questioning the contribution that even cognitive neuroscience could make to education. It warned

Researchers are planning to use magnetic resonance imaging to “look under the hood” at the development of skills such as numeracy and reading. It’s fascinating stuff, but how the results will inform educational practice remains, for now, largely a matter of speculation. Making meaningful connections between brain activity and behaviour is difficult, even under controlled lab settings. Brain imaging is seductive, and has an unfortunate tendency to spawn breathless, overreaching media coverage. Care will be needed to ensure that these projects don’t encourage ill-informed “experts” to design yet more pseudoscientific educational tools…. There’s also a strong case for putting the educational tools derived from research in neuroscience to more rigorous empirical tests. For instance, researchers who have evidence that dyslexics have problems with auditory processing have developed a program called Fast ForWord to help them learn to read. But the sc...

Table of contents

• Cover
• Title page
• Copyright page
• Dedication
• List of Contributors
• Preface
• Foreword: Imaging the Future
• Chapter 1: Introduction
• Chapter 2: Neuroimaging Methods
• Chapter 3: Computational Modeling of Learning and Teaching
• Chapter 4: Genetics for Education
• Chapter 5: Research Methods in Educational Psychology
• Chapter 6: Language Development
• Chapter 7: Literacy Development
• Chapter 8: Mathematical Development
• Chapter 9: The Development and Application of Scientific Reasoning
• Chapter 10: Social Development
• Chapter 11: Emotional Development
• Chapter 12: Attention and Executive Control
• Afterword
• Index