Educational Neuroscience

Development Across the Life Span

Michael S. C. Thomas, Denis Mareschal, Iroise Dumontheil, Michael S. C. Thomas, Denis Mareschal, Iroise Dumontheil

• Publisher: Routledge
• Year: 2020
• Print ISBN: 9781138240353
• eBook ISBN: 9781000040791
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Developmental Psychology
• Index: Biological Sciences

The field of educational neuroscience uses new insights about the neural mechanisms of learning to improve educational practices and outcomes. The first volume to bring together the latest knowledge on the development of educational neuroscience from a life-span perspective, this important text offers state of the art, authoritative research findings in educational neuroscience before providing evidence-based recommendations for classroom practice.

Thomas, Mareschal, Dumontheil, and the team of expert international contributors assembled in this volume thoroughly explore four main themes throughout the book. The first theme is individual differences, or what makes children perform better or worse in the classroom. The second theme is the nature of individual differences at different stages in development, from early years into adulthood. The third theme addresses cognitive enhancement, summarizing research that has investigated activities that might give general benefits to cognition. And the fourth theme considers the translation of research findings into classroom practices, discussing broader ethical issues raised by educational neuroscience, and what teachers need to know about neuroscience to enhance their day-to-day practice. Specific topics explored include neuropsychological perspectives on socioeconomic disparities in educational achievement, reading difficulties, phonological skills, executive function, and emotional development.

Educational Neuroscience is essential reading for researchers and graduate students of educational psychology, developmental science, developmental psychology, and cognitive psychology, especially those specializing in emotion regulation.

Section 1

Development and Variation

Genetic and Environmental Factors

3 What Has Behavioural Genetic Research Told Us About the Origins of Individual Differences in Educational Abilities and Achievements?

Georgina Donati and Emma Meaburn

Chapter Overview

The purpose of education is to prepare students for adult life by equipping them with the knowledge, character, and skills required to contribute to society and navigate their way in the world (Department for Education, 2015). However, as any teacher or parent can attest, children show remarkable differences in their appetite for learning, academic progress, and educational achievements. Why is it, for example, that some children in a classroom find learning to read so much harder than their peers, despite being taught by the same teacher in the same school, with access to the same learning resources and support? Behavior Genetics is a field of Psychology that uses genetic methods to query the origins of these individual differences. To what extent are the differences we observe in learning and academic outcomes between children due to genetic (nature) or environmental (nurture) factors? We each share a set of genetic instructions that are similar enough to build—from scratch—a highly complex organism that is characteristically human. Yet we differ in important and meaningful ways, including at the genetic level; if you were to pick any two unrelated individuals at random and examine their DNA sequence you would find that they differ at roughly 1 in every 1,200–1,500 DNA bases (or ‘letters’) (Auton et al., 2015). Given that the human genome is 3 billion DNA base pairs in length, this represents a substantial amount of genetic variability. How important are these genetic differences in accounting for the differences we observe between students? And how do they stack up against the importance of environmental influences such as the school the child attends, their home environment, neighborhood, and wider social and cultural factors? Several decades of behavior genetic research has robustly demonstrated that it is both nature and nurture and their interplay, and the focus now is on understanding the specific causes—which genes and which environments—that drive variability in traits and behaviors related to education (Knopik, Neiderhiser, DeFries, & Plomin, 2016). Charting the developmental dance between stable inherited DNA differences and dynamic environments will be critical for understanding the cellular, structural and functional mechanisms by which DNA shapes our learning, and will aid the identification of relevant educational environments and practices that cater to and accommodate our differences. Given that how well a child does at school is predictive of a wide range of important social, economic, and physical and mental health outcomes, understanding the specific contributions to individual differences in academic success is of fundamental importance both for the individual and for society (Cutler, Lleras-Muney, & Vogl, 2008; Ross & Wu, 1995).

The aim of this chapter is to introduce teachers and educational neuroscience students to how behavior genetic research has contributed to our understanding of the genetic contributions to individual differences in educationally relevant traits and outcomes. We focus primarily on intelligence (or general cognitive function; ‘g’), how long you stay in education (‘educational attainment’), and how well you do (‘educational achievement’) as these are the areas where the majority of research has been conducted, and the most progress has been made. We also limit our focus to cognitive and academic traits within the normal range of function; readers interested in the genetic basis of marked intellectual disability, or specific learning disabilities such as dyslexia and specific language impairment are referred to excellent recent reviews (Bishop, 2015; Reader, Covill, Nudel, & Newbury, 2014). During the course of the chapter we highlight what we consider to be the three key areas of progress, the immediate implications of these insights, and how they might practically be used to improve children’s learning and educational experiences. Along the way we hope to highlight some of the current issues or debates in the field before finally considering likely future directions for behavior genetic research in education. Where possible we have minimized the use of jargon, but some terminology is unavoidable: Terms in bold are defined in the glossary at the end of this book.

Educational Phenotypes

Before we jump to what we consider to be the most robust scientific findings, we first provide a brief overview for the uninitiated of how intelligence and educational outcomes are typically operationalized in behavior genetic research. If you are already familiar with the concept of intelligence and psychometric testing of cognitive functions, you may wish to skip this section.

One of the main phenotypes used by behavior genetic researchers is intelligence, also known as general cognitive ability or ‘g’ (Spearman, 1904). Intelligence or ‘g’ is a statistical construct that captures what is in common between diverse ability tests; that is, it describes the fact that if you do well on a specific cognitive test (e.g., a test of numerical reasoning or memory), you also tend to do well on other cognitive tests (e.g., vocabulary or spatial awareness). A nuanced discussion of what intelligence might represent both at the cognitive and neurological level is beyond the scope of this chapter, but broadly speaking it can be thought of as a general measure of problem-solving ability and information processing (Carroll, 1993; Deary, 2012). As you might well expect, intelligence and educational outcomes are closely interconnected. The relationship is not perfect, but in general people who score higher on intelligence tests tend to stay in school longer, and vice versa (Deary, Strand, Smith, & Fernandes, 2007). As we shall see in later sections, this relationship is at least partly explained by shared genetic effects (Johnson, Deary, & Iacono, 2009). More recently there has been a move to studying educational attainment (length of time spent in formal education), and educational achievement (typically, the highest academic qualification achieved) directly (Rietveld et al., 2014a). One critical benefit of studying very broad social phenotypes such as these is that they are easily measured in very large samples of individuals for relatively low cost, which is necessary to detect specific genetic influences. However, how well you do in school is undoubtedly influenced by facets of cognitive function other than intelligence, in addition to emotional behaviors, personality, creativity, motivation, resilience, and social and economic circumstance. All of these more specific phenotypes have been studied in a behavior genetic framework (although typically on a smaller scale), and we touch on them where appropriate.

Twin Studies: Dissecting the Origins of Individual Differences in Educational Phenotypes

When considering the origins of individual differences in educational phenotypes, how do we know if genetic influence is important? Fundamentally, we can infer genetic effects by contrasting the phenotypic similarity between related individuals with their genetic similarity; if genes contribute to a trait we can predict that the resemblance between pairs of relatives will increase with increasing genetic relatedness. However, familial resemblance could also be due to shared environmental exposures and experiences (e.g., the number of books in the home, parenting style) as well as shared genes. Fortunately, twin studies are able to tease apart the relative influence of genetic (variation in DNA sequence) and non-genetic factors (variation in environments) by exploiting the fact that identical twins (monozygotic or MZ) and non-identical or fraternal twins (dizygotic or DZ) share the same family environmental experiences but differ in their genetic similarity. Specifically, MZ twins develop from one egg (or zygote) and share 100% of their DNA sequence, while DZ twins develop from two separately fertilized eggs and share on average only 50% of their segregating genes (just like regular siblings with the same parents). Working under the assumption that within twin pair prenatal and postnatal environmental variation is similar for both MZ and DZ twins (the ‘equal environments assumption’), genetic influence can be quantified by the extent to which MZ twins are more similar for a trait than DZ twins by virtue of their greater genetic similarity (Knopik et al., 2016); doubling the difference between MZ and DZ correlations for a measured phenotype (such as educational attainment) provides an estimate of genetic influence known as twin heritability.

Twin studies of many hundreds of families use the principle just described and structural equation models to partition observed variance in the phenotype being studied into a) additive genetic effects (heritability), b) shared (or common) environmental effects and c) non-shared (or unique) environmental effects (Neale & Cardon, 1992). Within the twin model framework, shared environmental effects are considered to be any non-genetic influences that are shared by twins in the same family and serve to make them more similar, such as characteristics of the home environment (e.g., number of books or social-economic status), prenatal environment, and neighborhood. In contrast, non-shared environmental factors are taken to be any aspects of the environment that are experienced differently by twins in the same family and serve to make them different, and includes idiosyncratic events such as individual-specific illnesses, random biological noise, differential treatment (either real or perceived) by teachers, parents or peer group members, and good old-fashioned luck (Plomin, 2011). Like all research paradigms, twin studies come with important qualifications and assumptions and these have been extensively tested and critically discussed elsewhere (e.g., see (Rutter, 2006; Kendler, Neale, Kessler, Heath, & Eaves, 1993)).

Individual Differences in Educational Phenotypes Are Heritable

So what do twin studies tell us about the importance of genes in explaining the relative gaps that we see between students’ abilities and educational achievements? One of the most consistent and replicable findings to emerge is that individual differences in educationally relevant traits and behaviors—whether measured in childhood or adulthood—are heritable (Plomin & von Stumm, 2018). Figure 3.1 provides a roadmap of the key research papers published in the last 12 years that have been critical to our understanding of the nature and magnitude of genetic contributions to educationally relevant traits. Whilst exact heritability estimates vary across twin studies, they all find that a sizable proportion of the differences we see between students can be attributed to genetic differences that exist between them. For example, intelligence or ‘g’ has a heritability estimate of ~40% in childhood, rising to ~60% in adulthood (Haworth et al., 2010; Trzaskowski, Yang, Visscher, & Plomin, 2014). Twin study research has also demonstrated that academic achievement is heritable, whether considering standardized achievement scores during childhood, or high-stakes exam outcomes in late adolescence. For example, a large representative UK-based study of ~10,000 twin pairs (Haworth, Davis, & Plomin, 2013) has reported heritability estimates of 68% for literacy and 66% for numeracy at age 7 (Kovas, Harlaar, Petrill, & Plomin, 2005; Kovas et al., 2013), 52–58% for performance in core General Certificate of Secondary Education (CGSE) exams at the end of compulsory education at age 16 (Shakeshaft et al., 2013), and 59% for average performance in A-level exams at age 18 (Rimfeld, Ayorech, Dale, Kovas, & Plomin, 2016; Smith-Woolley, Ayorech, Dale, von Stumm, & Plomin, 2018). The Rimfeld et al. study also demonstrated that genetic influence extends beyond achievement and influences the choice of academic subject studied; the authors reported heritability estimates of 50–80% for A-level subject choice, suggesting that a reciprocal relationship exists across development between ability, previous achievement, and academic interests. Similarly high heritability estimates have also been reported in non-UK twin cohorts (e.g., (Schwabe, Janss, & van den Berg, 2017), and a recent meta-analysis of 61 studies reported a heritability estimate of 66% for educational achievement (de Zeeuw, de Geus, & Boomsma, 2015). Notable genetic influence has also been found for psychological and behavioral correlates of academic achievement such as self-efficacy (Krapohl et al., 2014; Waaktaar & Torgersen, 2013), personality traits such as neuroticism (Docherty et al., 2016; Power & Pluess, 2015), and perseverance for long-term goals (‘grit’; (Rim...

Table of contents

• Cover
• Half Title
• Series
• Title
• Copyright
• Contents
• Contributors
• Introduction
• Section 1 Development and Variation: Genetic and Environmental Factors
• Section 2 Discipline-Specific Abilities: Literacy, Numeracy, and Science
• Section 3 Discipline-General Abilities: Executive Functions, Social and Affective Development
• Section 4 Leading Methods for Cognitive Enhancement
• Section 5 Into the Classroom
• Conclusion
• Index