Mind, Brain, and Education: A Discussion of Practical, Conceptual, and Ethical Issues

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Examples of Success in “Mind, Brain, and Education” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conceptual and Practical Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ethical Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Recent years have seen a tremendous growth in efforts to connect rapidly growing insights into how the brain learns to the field of education. Different names have been given to such efforts, including “Educational Neuroscience” and “Mind, Brain, and Education.” The aim of this chapter is to discuss these recent efforts and to provide an overview of the conceptual, practical, and ethical challenges faced by these novel, transdisciplinary efforts. To do so, the chapter begins with an overview of some examples of recent research efforts to connect research on Mind, Brain, and Education (MBE). To do so, the chapter begins with an overview of some examples of recent research in the emerging field of Mind, Brain and Education. Specifically, the chapter reviews evidence from the study of the neurocognitive processes of typical and atypical reading development in an effort to illustrate the merit of MBE. This is followed by a discussion of the conceptual and practical challenges that MBE needs to consider, such as the level at which evidence from the study of neurocognitive processes can influence education and how neuroscientists and educators can play complementary roles in the

D. Ansari Numerical Cognition Laboratory, Department of Psychology & Brain and Mind Institute, The University of Western Ontario, London, ON, Canada e-mail: [email protected]; [email protected] J. Clausen, N. Levy (eds.), Handbook of Neuroethics, DOI 10.1007/978-94-007-4707-4_146, # Springer Science+Business Media Dordrecht 2015

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construction of the field. Against this background, the chapter considers ethical challenges, including the need to effectively and accurately communicate evidence, to carefully consider the commercialization of neuroscience, including the use of brain stimulation, to enhance cognitive functions and for classroom application.

Introduction Recent decades of neuroscience research have witnessed an unprecedented growth in our understanding of the neural mechanisms that subserve human learning. Significant advances in our understanding of the neuronal machinery that allows humans to acquire complex skills such as reading, writing, mathematics, and problem solving have been made. Furthermore, our understanding of brain development and how experience changes brain function and structure has grown tremendously (Johnson 2001; Lenroot and Giedd 2006; Munakata et al. 2004). We are learning not only how the brain comes to process the content of the most classical domains of education, such as numeracy and literacy, but insights into the brain mechanisms underlying motivation, attention, and working memory are constraining our understanding and modelling of how children acquire new skills that are essential to their success in society. Against the background of these advances in basic research, there have been growing calls to apply knowledge from neuroscience to education. On the surface, it is a “no-brainer” that neuroscience should be capable of informing education. Without our brains, we cannot learn and therefore understanding the machinery (the brain) that underpins the ability of children and adults to learn in the context of educational settings should have implications for how to improve educational environments and pedagogy. A key concept here is “neuronal plasticity” – the ability of the brain to change as a function of experience. Early neurophysiological studies revealed that sensory deprivation or enrichment changes the brains of animals, showing that experience shapes the brain (Buonomano and Merzenich 1998). Today, we can study the effects of complex environmental and experiential differences, such as cross-cultural variability, on brain structure and function (Ansari 2012). Mounting research suggests that the brain is more plastic than we originally thought (though within constraints) and that our brains continue to be capable of functional and structural change (plasticity) in adulthood, which has potential implications for lifelong learning, a topic of much interest in many aging Western societies (May 2011). Plasticity is key to education. Teachers are the orchestrators of their students’ neuronal plasticity during classroom time. In order for knowledge to be acquired, the brain has to encode information, which involves changes in the connectivity between nerve cells (i.e., synaptic plasticity). The brain is not a static organ, but instead dynamically adapts to the environment. Education is a process of inducing brain plasticity through instruction in a social context. When children learn, for example, to read (for a greater discussion of this topic, see below), their brain changes from them seeing letters on the page as meaningless characters to the point at which they read with a flashlight at night and use these previously meaningless characters to follow stories and create meanings in their minds.

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Notwithstanding strong critics (Bruer 1997), over the past 15 years or so, the enthusiasm for a new science of learning and education that combines insights from cognitive science, neuroscience, and psychology has grown exponentially. Terms such as “Neuroeducation,” “Educational Neuroscience,” and “Mind, Brain, and Education” have been used to describe these efforts. The author of the present chapter prefers the term “Mind, Brain, and Education” (henceforth MBE) because it reflects the mutual and interactive influence of research from cognitive psychology, neuroscience, and educational research. New organizations such as the International Mind, Brain and Education Society (IMBES; www. imbes.org) and journals (e.g., “Trends in Neuroscience and Education” and “Mind, Brain and Education”) have been launched to attract research and theory that lies at the intersections between neuroscience, education, cognitive science, and psychology.” Interest in such new directions has extended beyond the realm of academia. Organizations such as the Organization for Economic Cooperation and Development (OECD) have convened expert groups to examine the relationship between Mind, Brain, and Education in an effort to find ways to improve education in OECD membership countries across the globe (OECD 2002). In addition, new graduate programs are being launched in many departments, the first of which was the Master’s in Mind, Brain and Education at the Harvard Graduate School of Education founded by Dr. Kurt Fischer (http://www.gse.harvard. edu/academics/masters/mbe/). As can be seen from the above, the field of MBE is growing rapidly. As with any new field, there are many conceptual, practical, and ethical issues to consider in order to facilitate the successful growth of the field. The aim of this chapter is to provide a critical reflection on and discussion of the potential of Mind, Brain, and Education. The chapter will commence with a discussion of examples from neuroscience research that are having implications for education and to illustrate some of the findings from neuroscientific research that are fueling the enthusiasm for Mind, Brain, and Education. The review of these findings will also consider how evidence from cognitive neuroscience might impact education now and in the future. The chapter will then turn to conceptual and practical challenges that are faced by this new, translational field. Against the background of having considered what MBE research looks like and what challenges face the field, the chapter will discuss the ethical challenges that the emerging field of Mind, Brain, and Education is and will be confronted with.

Examples of Success in “Mind, Brain, and Education” The aim of the following section is to provide the reader with some examples of recent interdisciplinary research that demonstrates the potential of the emerging field of Mind, Brain, and Education. This review does not aim to be comprehensive, but simply to illustrate through a few examples the potential significance of research that bridges the gap between cognitive neuroscience and education.

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Perhaps, the best example of how neuroscience research is shaping education comes from research in the domain of reading and the breakdown of reading abilities (i.e., Developmental Dyslexia). Noninvasive brain imaging methods such as functional Magnetic Resonance Imaging (fMRI) and Event-Related Potentials (ERPs) have enabled researchers to map out the brain regions involved in reading and to image the time course of neural activity associated with the process of reading. Through the use of such methods, it has become possible not only to study which brain regions are involved during reading, but how these change over the course of learning and development as well as what differences exist between the brain structure of typical readers and those with Developmental Dyslexia (for reviews, see: Gabrieli (2009); Schlaggar and McCandliss (2007)). The aim here is not to provide an exhaustive review of these studies but to highlight some findings that show how neuroscience can be used to constrain educational problems and inform educational practice. One area in which neuroscience is making great strides is in the prediction of reading success and failure. For example, several studies using ERPs to record the brain responses of neonates and infants, have revealed that infants brain responses to sounds predict individual differences in reading years later (Guttorm et al. 2001, 2010; Molfese 2000; Pihko et al. 1999). These are powerful data for a number of reasons. First of all, they reveal that the pre-reading brain of infants who will go on to experience difficulties in reading respond differently to those who will develop normal literacy skills. This draws attention to the early scaffolds of reading, resulting in many potential implications for early diagnosis and remediation. Secondly, these kinds of data are difficult to obtain with any other measure traditionally used in behavioral research with young infants and children, thereby demonstrating the added value of using neuroimaging methods. In studies with older children using both structural and functional neuroimaging, it has been demonstrated that structural variables, such as brain volume and white matter integrity, as well as functional measures of brain activation during readingrelated tasks (e.g., rhyming), predict significant variability in children’s reading scores. One might argue that this is hardly surprising and that it is far more costeffective to use traditional behavioral measures as predictor variables. However, Hoeft et al. demonstrated that the combined use of behavioral and neuroimaging measures as predictors of reading (specifically decoding skills) explains significantly more variance than either measure used in isolation (Hoeft et al. 2007). Thus, neuroimaging and behavioral measures each explain unique variance, which leads to overall better prediction of reading outcomes. These data speak against the notion that neuroimaging does nothing in addition to what can be gleaned from behavioral measures alone, but instead shows that such measures explain outcomes that cannot be captured by behavior alone. In a more recent study, Hoeft et al. showed another powerful way in which neuroimaging measures can be used to predict educationally meaningful outcomes. The authors asked whether neuroimaging data could predict who will go on to show gains in reading performance. In addition to a large battery of behavioral tests of reading, writing, and IQ, structural and functional brain imaging data was acquired from children with and without Developmental

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Dyslexia. The same children were tested again 2.5 years later. Behavioral data suggested that while some children with Developmental Dyslexia exhibited significant gains in reading abilities, another group of children demonstrated no change on behavioral tests of reading competencies. By using the behavioral and neuroimaging data acquired at the outset of the study to predict who ended up showing reading gains compared to children who did not, the authors were able to show that structural and functional neuroimaging measures were able to predict which children ended up exhibiting gains in their reading abilities. In striking contrast, none of the behavioral variables were able to statistically predict which children exhibited gains (Hoeft et al. 2011). These findings provide strong evidence for the possibility of “neuroprognosis” and also demonstrate that, in some cases, neuroimaging measures (both structural and functional) may be a more sensitive way in which to predict later outcomes (given that the behavioral data did not exhibit such predictive power). In addition to providing strong evidence to suggest that neuroimaging measures can be used to predict change in educationally relevant outcomes (e.g., gains in reading ability), Hoeft et al. found that individual differences in the structure and function of the right inferior frontal cortex were particularly predictive of such gains. This is an interesting finding, as reading is mostly associated with a left-lateralized network of brain activity and structure. However, there have been other studies suggesting that the right hemisphere plays an important role in response to intervention and may represent compensatory neural mechanisms (Temple et al. 2003). Thus, individuals who are better able to use these right-lateralized compensatory mechanisms may show greater gains in reading ability. This finding provides a significant constraint on our understanding of the mechanisms that drive individual differences in improvements in reading abilities. It is not as though we necessarily see the normalization of disrupted brain circuits, but instead it appears that the recruitment of regions not typically associated with reading is what is associated with the recovery of impaired reading skills. This is not only important from the point of view of understanding the mechanisms underlying the recovery of reading abilities, but it may also help to constrain how reading interventions are designed. In other words, future efforts may be directed at better understanding what mechanisms drive the recruitment of such compensatory neural processes and how these might be optimally harnessed. In this way, neuroimaging provides novel constraint on recovery of cognitive function and by revealing the mechanisms can guide future intervention programs. Importantly, this is not an isolated case of “neuroprognosis.” Very recently, Supekar et al. (2013) showed a similar result for the prediction of response to intervention in the domain of math learning. These researchers demonstrated that measures of hippocampal volumes as well as functional connectivity between the hippocampus and other brain regions were a significant predictor of individual differences in response to a structured intervention for children with math learning difficulties. Furthermore, convergent with the data from reading reviewed above, the behavioral data acquired prior to the intervention were not able to predict individual differences in the response to intervention. Thus, these data

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provide convergent evidence for the potential power of neuroprognostics from two domains: reading and mathematics. Another recent neuroscientific study of reading further illustrates the value added of neuroscience in addressing educational questions. One of the most hotly debated topic in special education is the use of so-called discrepancy criteria (Stanovic, 2005). Many researchers and practitioners define children as having specific difficulties in domains such as reading, writing, and arithmetic if they have below the normal range scores on the domain of interest but perform within the normal range on other tests of abilities. So, for example, according to the discrepancy criteria approach, a child with Developmental Dyslexia can only be defined as such if their reading abilities are both well below their general academic abilities and if their non-reading abilities are within the normal range. There have been many arguments against such stringent discrepancy criteria with researchers suggesting that children who have reading difficulties that are either discrepant or non-discrepant from their other intellectual and academic abilities have the same educational needs and are indeed indistinguishable from one another when it comes to measures of their reading ability (Fletcher et al. 1992). In a recent study, neuroimaging was used to constrain the question of whether children with and without a discrepancy between their reading and IQ scores showed different patterns of brain activation (Tanaka et al. 2001). The authors compared the brain activation of children with and without a reading-IQ discrepancy while they performed a reading-related task during functional neuroimaging (fMRI). Both univariate and multivariate analyses of the functional imaging data clearly demonstrated that both groups of children exhibited indistinguishable patterns of under activation (relative to non-impaired controls) of areas in the left hemisphere that are typically associated with successful reading. These findings show that the neurobiology underpinning reading does not differ between children with and without a reading-IQ discrepancy and therefore place a significant novel constraint on the special education debate surrounding the utility of using discrepancy based criteria to identify children with specific learning difficulties. Beyond the domain of reading, there are many other examples in other educationally relevant areas that can be characterized as success stories in the emerging field of “Mind, Brain, and Education.” For example, several studies, ranging from experiments with rats to functional neuroimaging studies with humans, have demonstrated the powerful effect that socioeconomic status and early experiences have on brain structure and function (Hackman et al. 2010). These data have revealed how early experiences and stress embed themselves into our biology and have long-term consequences for our health, well-being, and ability to learning. Without going into the details of the individual studies that demonstrate these powerful effects of early experience and socioeconomic status, these findings clearly have very important implications for education. They demonstrate the importance of early educational programs, especially in disadvantaged communities, in mitigating the profoundly negative effects of early, adverse experiences.

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Conceptual and Practical Challenges The above section provides a non-exhaustive discussion of some select examples (primarily from the study of the neurobiology of typical and atypical reading acquisition) of successful research in the emerging field of “Mind, Brain, and Education.” While such advances illustrate that there lies much promise in such transdisciplinary research, there are also many conceptual and practical challenges that lie in the path of such efforts. The aim of the following section is to discuss some of these challenges and potential ways of navigating such obstacles. Whenever different fields of both inquiry and application meet one another, a need for a common language and set of expectations emerges. One expectation that is prevalent when neuroscience and education meet is that neuroscience will have a direct impact on classroom instruction (Ansari and Coch 2006). In other words, scientists generate evidence, communicate this evidence to educators who will then go on to apply it. This expectation will inevitably lead to disappointment, as results from research cannot be directly applied, but instead need to be gradually translated through an iterative process that needs to involve multiple bidirectional interactions between the research laboratory and the classroom and requires individuals who are well versed in both cognitive neuroscience and education to facilitate the process of translation (Ansari and Coch 2006; Varma et al. 2008). Translation of evidence does not involve the presentation of recipes by researchers to educators, but must involve a collaborative effort that allows for the establishment of a common language and sets of expectations. In other words, to ensure successful transdisciplinary interactions between cognitive neuroscience and education, it is critical for expectations to be realistic and that a broader conceptualization of potential translations of insights from research into practice be adopted. Take the examples of studies, discussed above, revealing brain signals measured in neonates during language processing predict literacy impairments many years later. One may ask some of the following questions upon being presented with this evidence: what to do with this evidence in terms of practice? Does it mean that we can intervene very early in development or does it mean that the fate of children is determined from an early age onward and cannot be changed? If we can intervene, then how and when? What is the diagnostic utility of the eventrelated potential measurements for individual babies? Is it reliable enough to serve as a diagnostic tool? When considering these questions, it quite rapidly becomes apparent that research generates questions whose answers may lead to translation, but that the raw evidence often cannot be directly translated into practical applications. Evidence, whether from neuroscience or other scientific disciplines, is the beginning of a translational process. The expectation that research will be directly translated into application also reflects another common assumption: insights from the research laboratory will invariably change education. Visions of entirely new classrooms come to mind that are “brain friendly” or a complete revolution in the way in which certain subjects are currently taught. While it is indeed possible that new evidence will lead to

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changes in education, evidence can also play a critical role in affirming as well as speaking against what educators already do today and thereby strengthen certain approaches they adopt in their pedagogy every day. In this way, evidence may help to provide empirical grounding to certain educational approaches and techniques. In the above discussion of research on the neuroscience of dyslexia, powerful examples of how neuroscience can inform educational decision and help to arbitrate between different approaches was discussed. The study by Tanaka et al. demonstrates that the neural correlates of reading impairments do not differ between dyslexics who were diagnosed using a readingIQ discrepancy criteria and those who were not (who therefore showed impairments in reading and other cognitive functions). This confirms that discrepancy criteria used to diagnose children with developmental dyslexia do not appear to isolate a group of children who have qualitatively different neuronal deficits in reading from those who also have non-reading difficulties (Tanaka et al. 2011). This study therefore can be used to inform educational decision-making, in this case the method of diagnosing children with reading impairments. It does not change the way in which diagnoses are made, but instead provides critical information to guide decision-making. The use of evidence to confirm or disconfirm certain pedagogical choices is a powerful way by which evidence from the cognitive neuroscience laboratory can influence education and may indeed initially be the most realistic way in which education and cognitive neuroscience can be connected in the context of educational practice (Thomas 2013). A similar role of neuroscientific evidence was recently highlighted by Laurence Steinberg in a discussion of the role that neuroscience has played in US supreme court decisions regarding the criminal culpability of adolescents (Steinberg 2013; see also Johnson & Giedd, this volume). What Steinberg argues is that neuroscience most likely had an influence on the legal decision-making not by revealing something completely new that no other previous evidence, such as behavioral evidence, had shown, but by confirming common sense, intuition, and evidence from behavioral evidence. In other words, neuroscientific evidence played an important supportive role in the process of legal decision-making. One might argue that if the role of scientific evidence, such as data from cognitive neuroscience, plays only a supportive role, then one might as well ignore it. This argument, however, ignores the fact that confirmation of one set of opinions or intuitions is often accompanied by the rejection of alternative approaches where there either does not exist evidence to support their efficacy or evidence that demonstrate that such approaches are inefficacious. In this way, evidence provides a means by which to inform education. Rather than basing educational decisions on opinions and intuitions, a culture of evidence-based education uses evidence to make informed decisions. It follows from the above discussion that, if teacher education programs were to systematically train teachers in the evaluation of empirical knowledge during preservice training, then such individuals would be better equipped to use evidence to inform their pedagogical decision-making. This would allow teachers to become

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critical consumers of empirical evidence from a range of field of inquiry relevant to education, including but not restricted to evidence from cognitive psychology and neuroscience, and to seek out evidence to both confirm and reject particular educational approaches (Ansari 2005). Training teachers and other educational professionals in the language of science, how evidence is generated and evaluated, may hold the key to effective processes of translation. In the same way, cognitive neuroscientists generating evidence, which they hope will inform education, should become versed in pedagogy and approaches in educational practice and research. This will lay the foundation for translation that is supported by individuals from a multitude of backgrounds to ensue.

Ethical Challenges Having considered some, but certainly not all, of the practical and conceptual challenges faced by the field of Mind, Brain, and Education, the present discussion now turns to the ethical challenges that this field of inquiry has encountered as well as those that might lie in its future paths. This discussion will not consider ethical challenges associated with the use of neuroimaging methods to study the developing brain (for an excellent discussion of such challenges, see: Coch 2007). Instead the present section will consider broad ethical challenges that lie at the conceptual, rather than the methodological, level of Mind, Brain, and Education as a new field of inquiry. Recent years have seen an impressive increase in the public’s awareness and interest in neuroscience. Popular magazines are full of articles about the brain, and neuroscience is enjoying an unprecedented amount of public attention. While such attention is broadly welcome (at least from the vantage point of neuroscientists), it does also pose some significant challenges that require the attention of neuroscientists. One of these is the creating of a knowledge hierarchy. Specifically, because of the great attention paid to neuroscience, its informational merit, relative to other sources of evidence, may be judged too highly. As discussed above, the role of neuroscience is most frequently a complementary one. In other words, neuroscientific evidence can inform other areas, such as education, in conjunction with insights from other disciplines, such as the behavioral sciences. A set of recent studies have demonstrated that the great value assigned to neuroscientific evidence may not always lead to good conclusions about that evidence. One of these examined the influence of brain images on how individuals evaluate scientific evidence. Noninvasive imaging methods, such as functional Magnetic Resonance Imaging (fMRI), generate aesthetically pleasing images of brain “activation.” These images, of course, are not a direct representation of “activity” but rather represent color-coded statistical maps showing the probability of the “activation” (which in turn is represented by changes in blood flow that are thought to correlated with neuronal activity) in certain brain regions. These images provide powerful illustrations of data, but it turns out that their presence can also have a significantly negative influence on the way in which non-experts evaluate neuroscientific evidence (Weisberg et al. 2008). Specifically, Weisberg et al. presented both naı¨ve

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adults, students in a neuroscience course and neuroscience experts with explanations of psychological phenomena. These explanations were varied in two ways: (1) They were either good explanations or invalid explanations. (2) They were either paired with or without neuroscientific evidence; however, this evidence was completely irrelevant to the logic of both good and bad explanations. The investigators found that this irrelevant neuroscientific evidence influenced the way in which the group of naı¨ve participants and the neuroscience students judged the explanations. Specifically, these participants were more satisfied with explanations that were paired with irrelevant neuroscientific evidence and, perhaps most alarmingly, they were less likely to recognize the bad explanations (i.e., found them more satisfying than bad explanations without irrelevant neuroscientific data contained within the explanation) when these were paired with irrelevant neuroscientific evidence. In other words, the presence of neuroscientific evidence appeared to make non-experts think more highly of bad explanations of scientific phenomena. The study by Weisberg et al. is a powerful explanation of how the current “hype” around neuroscience could lead to biases in the way in which individuals evaluate the validity of scientific evidence. However, it is very important to consider that the study by Weisberg and colleagues and related investigations of the effect of brain images on scientific evaluations (McCabe and Castel 2008) have recently not been replicated (Michael et al. 2013) in large-scale studies and therefore, it is unclear how reliable these effects are and how specific they are to brain images, as opposed to other stimuli that could bias the judgment of scientific data (Farah and Hook 2013). Regardless of whether the results are reliable and are specific to neuroscience, there are some general ethical implications for researchers in the field of MBE that go beyond the particulars of this research. Specifically, researchers in this emerging field of inquiry need to recognize that their understanding of the strengths and limitations of neuroscientific evidence is not necessarily at the same level of individuals who are not trained in neuroscience and therefore the way in which evidence is communicated becomes a critical ethical issue for researchers in MBE, particularly those who are generating neuroscientific evidence. Researchers in MBE must be aware of how their research results may be perceived by non-experts, such as teachers, and must therefore ensure that their findings are communicated in ways to avoid misunderstandings and the inappropriate use of the evidence. Researchers must think carefully about how they talk not only about the evidence they have generated but also about its implications for the classroom and to avoid overstating the potential for direct application. For example, teachers may not be aware that neuroscientific data is often based on averages and thus, a given finding may not be representative of every student or that must studies in cognitive neuroscience are conducted with adults participants and that the data may not be readily generalizable to children. Therefore, neuroscientists need training in how to communicate to and engage with the public in ways that are ethical and thereby avoid the creation of misconceptions (Illes et al. 2010). Effective communication and engagement is especially important when it comes to sharing neuroscientific evidence with educators. Many teachers are extremely enthusiastic about neuroscience and seek out opportunities to learn more about

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neuroscience (Hook and Farah 2012). This enthusiasm represents a great opportunity for the field of Mind, Brain, and Education to grow and for dialogue between neuroscience and education to ensue. Without educators and “buy-in” from educators, the transdisciplinary field of MBE cannot succeed. However, such dialogue must be effective and avoid scenarios that lead teachers to construct misconceptions about neuroscience, or so-called neuromyths. Some so-called facts (neuromyths) about the brain, such as the idea that we only use 10 % of our brains or that some individuals are “left-brained” while others are “right-brained,” appear to be very persistent among teachers (OECD 2002). In a recent study of primary and secondary teachers in the Netherlands, it was found that around half of them believed neuromyths (Dekker et al. 2012). Moreover, and perhaps more alarming, the authors found that those teachers who were enthusiastic about neuroscience and read more popular science magazines were also those who were more likely to believe neuromyths. These data demonstrate the importance of providing teachers with better tools to evaluate scientific evidence in order to avoid misconceptions about neuroscientific (and other empirical) evidence that could be informative in terms of their pedagogy (Dubinsky 2010). Furthermore, it is important that researchers think carefully about how this evidence is going to be presented to teachers. The finding that those who read more popular science magazines were also more likely to believe in neuromyths provides a stark illustration that information itself is clearly not enough, but that the quality of that information and how it is delivered matters. It is likely that such training might be most efficient at the preservice level so that teachers enter their profession not only seeking evidence-based approaches to their pedagogy but also being capable of carefully evaluating evidence. The ethical challenge, for both neuroscientists and teacher education institutions, of addressing the prevalence and proliferation of neuromyths among educators, is further exacerbated by the commercialization of so-called brain-based programs. These programs are often advertised as being based on neuroscientific data, though a closer examination often reveals that such data are, at best, tangentially related to the commercial programs that are being advertised. Furthermore, the majority of such programs have not been evaluated in adequately controlled trials and therefore, it is unknown to what extent they will be efficacious. In a large-scale evaluation of computerized programs that purport to train certain brain functions, it was recently found that while training on such tasks improved task performance, there was no evidence of transfer of the trained abilities to other tasks, even if they involved very closely related neurocognitive functions (Owen et al. 2010). Thus, the promised effects of the “brain training” programs investigated did not hold. Furthermore, in some cases, the empirical evaluation of such programs reveals that they can actually lead to decrements in certain neurocognitive functions rather than improvements. In a study evaluating the effect of babies watching special “educational” programs on the infants language development, Zimmerman and colleagues found that greater consumption of such videos was associated with decrements rather than improvements in language development, as measured by a parental questionnaire regarding the child’s communicative abilities (Zimmerman et al. 2007). This is, of course, not to say that all so-called brain

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training programs will be either inefficacious or harmful, but these two studies demonstrate the importance of grounding such applications in empirical research and making sure that educators demand such evidence before investing financial and pedagogical resources into their application. Educators who are not trained in evaluating products and asking questions about the evidence base behind them, but who are, at the same time, highly enthusiastic about neuroscience may buy into such programs without reservations. To avoid the proliferation of such “brain-based” approaches in classrooms, it is important that individuals, such as administrators and classroom teachers who have the responsibility of choosing such programs, are trained in how to judge the efficacy of an educational program as well as the evidence base (or lack thereof) of any program that is being offered to them. The same applies to books written on “brain-based” education. If neuroscientists and teacher educators do not take action to prevent the spread of empirically unsupported programs and books, then this could lead to the further proliferation of neuromyths and the application of untested programs that may have no effect at all or, even worse, detrimental effects on neurocognitive functions. The field of MBE now needs an infrastructure for such training and ethical information sharing to take place. Training teachers and educational decision makers is going to be insufficient in preventing the proliferation of “brainbased” programs that have no supporting evidence. More and more such programs will flood the market as interest in neuroscience and its application to education increases. Neuroscientists and educators should therefore work together with politicians, funding agencies, and regulators to come up with guidelines. Eventually, given the critical role that education plays in society, there should be regulatory organizations, similar to those that exist to regulate medical products. Beyond considering neuroscientific evidence that has implications for education by virtue of showing how learning in certain domains affects brain structure and function, there exists a growing body of research that explores attempts to stimulate the brain in order to enhance cognitive functions (e.g., Cohen Kadosh et al. 2010; Hauser et al. 2013). Such studies are suggesting that the application of weak electrical current to the brain via scalp electrodes can lead to enhancements of cognitive functions through the induction of plastic changes in the neuronal architectures supporting these functions. These studies have received widespread attention in the media and it is foreseeable that commercialization of such approaches will take place shortly, if it is not already underway. One could imagine then, that it will not be too long before schools are offered packaged brain stimulators for their students that are to be applied during instruction to improve learning. This therefore raises a whole host of ethical considerations related to the potential, undesired, and uncontrollable side effects of such stimulation. In this context, it is important to consider that while the data suggesting that methods such as Transcranial Direct Current Stimulation (TDCS) are intriguing, the existing studies are exclusively conducted with comparatively small samples of adult participants, therefore making their generalizability to samples of children impossible to estimate. Children’s brains are developing and cannot be readily compared with those of adults. Therefore, the response of children’s brains to

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stimulation may be quite different from what is currently being observed in adults. Moreover, though many study show improvements on behavioral measures following brain stimulation during learning, there also exists evidence to suggest that such stimulation can also have negative effects on cognitive processes (Iuculano and Cohen Kadosh 2013). Thus, it is clear that brain stimulation does not only affect the neurocognitive functions it is aiming to target but leads to side effects, the extent and magnitude of which is unknown. Generally, brain stimulation studies are very much in their infancy and little is known about the mechanisms through which brain stimulation exerts its effects on learning. Given this, researchers have an ethical responsibility to communicate about the potential of such methods to be applied in the classroom with caution. It is likely that such approaches and similar ones that try to modulate neurocognitive functions that are relevant to educational processes via stimulation or pharmacology are going to rapidly increase over the coming years and thus this will be a major frontier of neuroethics for MBE. On a broader level, it is the contention of this author that MBE must keep in mind that education is a deeply cultural activity. As such, education is not a fixed entity. Education varies across historical time, contexts, and cultures. The priorities of what children should be learning changes with the general shifts in our societies and cultures. It is brain plasticity that allows for these rapid adaptations to changing sociocultural demands and contexts. Often when discussing the role of neuroscience in education, the metaphor of a muscle is used. Specifically it is argued that the brain is like a muscle that needs to be exercised and that therefore education is a form of exercising your brain. In the opinion of the present author, this metaphor is overly simplistic and its implications may be misleading. While there is a range of ways in which you can exercise the muscles in your body, it does not by any stretch of the imagination resemble the diversity of how and what humans learn. Learning and education are not simply the acts of exercising a muscle in a particular way that can be replicated across cultures and contexts. Though neuroscience has great potential to provide information that could improve education and help us decide which educational approaches are most optimal (through systematic, evidence-based evaluation), it will never be able to inform us as to what we should be teaching our children. Neuroscience is and should be agnostic as to the specific goals of education. This will remain the purview and responsibility of societies. Therefore, the discussion around issues in MBE and the neuroethics of it should consider that efforts to bring neuroscience to bear on educational problems do not lead to normalization of education across time and context and a fixed view of what education means and what children should and should not learn.

Summary and Conclusions Evidence from neuroscience is increasingly discussed in the context of education. How can we use our growing insights into the mechanisms by which the brain learns across domains to improve education? This is a hotly debated question today.

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On the one hand, there is much to be enthusiastic about. The study of education is in many ways the study of brain plasticity. If our brains were unable to change in response to experience, education would not be possible. Every month, new studies are published that show how the brain changes as a function of learning across different domains, such as reading and mathematics. On the other hand, while the evidence base is steadily growing, efforts to translate such evidence into educational practice face significant conceptual, practical, and ethical challenges. There is a need to move beyond models of translation that focus on the direct translation of neuroscience laboratory research to the classroom and instead engage in a more iterative process of translation that involves neuroscientists, educational researchers, and practitioners. Furthermore, beyond changing education, evidence from neuroscience in conjunction with evidence from other domains has an important role to play in supporting what is already being implemented in education (thereby lending evidence to approaches that have previously not been evidence-based) and in using evidence to inform educational decision-making. The role of empowering educational professionals and decision makers through giving them tools to be critical consumers of evidence is discussed as both a conceptual and ethical challenge. Neuroscientists need to assume greater responsibility in ensuring that the information they generate is interpreted correctly and must guard against the proliferation of neuromyths, premature commercialization, and the use of neuroscientific approaches to enhance neurocognitive functions that have not been systematically tested in pediatric populations and for which side effects are currently understudied. Finally, while there is much reason to be enthusiastic about the emergence of MBE, it is important that society continues to discuss the direction of education independently of neuroscientific evidence. While evidence from neuroscience can inform which approaches work and why and perhaps help to optimize them, education and educational priorities remain deeply cultural activities.

Cross-References ▶ Ethical Implications of Brain Stimulation ▶ Human Brain Research and Ethics ▶ Neuroenhancement ▶ Neuroimaging Neuroethics: Introduction ▶ Research in Neuroenhancement

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