Crossing Mind, Brain, and Education Boundaries 1527590755, 9781527590755

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Crossing Mind, Brain, and Education Boundaries

Crossing Mind, Brain, and Education Boundaries By

Ali Nouri, Tracey Noel Tokuhama-Espinosa and Cynthia Borja

Crossing Mind, Brain, and Education Boundaries By Ali Nouri, Tracey Noel Tokuhama-Espinosa and Cynthia Borja This book first published 2023 Cambridge Scholars Publishing Lady Stephenson Library, Newcastle upon Tyne, NE6 2PA, UK British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Copyright © 2023 by Ali Nouri, Tracey Noel Tokuhama-Espinosa and Cynthia Borja All rights for this book reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the copyright owner. ISBN (10): 1-5275-9075-5 ISBN (13): 978-1-5275-9075-5

This book is dedicated to the memory of Kurt W. Fischer (1943-2020), transdisciplinary thinker and inspirational mentor.

TABLE OF CONTENTS

List of Figures and Tables .......................................................................... x Acknowledgements ................................................................................... xi Preface ...................................................................................................... xii What You Will Find in this Book Introduction ................................................................................................ 1 The Search for Why and How People Learn I. The History of Mind, Brain, and Education Science Chapter 1 .................................................................................................... 8 Early Contributions to Mind, Brain and Education Science Ancient Civilizations (3000 BCE–300 CE): Brain vs. Heart Hypothesis ....................................................................................... 8 Middle Ages (400–1300s): The First Universities and Illustrations of Human Brain Anatomy ............................................................. 11 The Renaissance (1400–1700): Development of the Modern Scientific Method .......................................................................... 13 Chapter 2 .................................................................................................. 16 The Industrial Age The First Industrial Revolution (1700–1849): Myth of “Localizationism” ............................................................ 16 The Second Industrial Revolution (1850–1900): Discovery of the Structure and Function of the Nervous System ................... 18 The Third Industrial Revolution (1900-1959): Establishment of the Relationships between Mind, Brain and Behaviour ............ 22 Chapter 3 .................................................................................................. 28 The Counter Culture Movement (1960–1999): Constructivist Thinking and the Decade of the Brain

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Chapter 4 .................................................................................................. 41 The Digital Age (2000–2010): Programs in Mind, Brain, and Education II. Current Directions and Debates Chapter 5 .................................................................................................. 50 Research in Mind, Brain, and Education: Some Methodological Considerations Models of Disciplinary Research ........................................................ 51 A Summary of Topics and Methodologies 2007-2018 ....................... 57 Current and Future Directions for Research in MBE .......................... 62 The Researcher-Practitioner Model in MBE....................................... 63 Communication among Mind, Brain, and Educational Scientists....... 64 Chapter 6 .................................................................................................. 67 The Name Debate Clarifying the Name Debate Over Time ............................................. 67 Research, Journal Names and Conference Affiliations ....................... 73 Arguments for the Name “Educational Neuroscience”....................... 75 Arguments for the Name “Mind, Brain, and Education” .................... 76 The Complexity of Human Teaching and Learning Requires Transdisciplinary Thinking ........................................................... 77 A New Research Approach ................................................................. 79 III: Mind, Brain, and Education’s Implications for the Future of Education Chapter 7 .................................................................................................. 88 Curriculum and Pedagogy: A Look from a Mind, Brain, and Education Perspective Changing How We Teach Students Based on MBE Knowledge ........ 88 Radical Neuroconstructivism .............................................................. 88 The Principles and Tenets of Mind, Brain, and Education Science: What MBE Tells us About Human Teaching and Learning.......... 90 The Influences of Technology on Mind, Brain, and Education .......... 97 Teacher Training Based on MBE Knowledge .................................... 99 Training Teachers ............................................................................. 100 Promoting Academic Professionalism .............................................. 101 Empowering Reflective Practitioners ............................................... 103 A Potential Curriculum for Teacher Development ........................... 104

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Chapter 8 ................................................................................................ 111 Mind, Brain, and Education Science: An International, Translational, and Transdisciplinary Perspective Aims of Education from a Mind, Brain, and Education Science Perspective .................................................................................. 112 Leaders in Mind, Brain, and Education Science ............................... 114 Moving Forward ............................................................................... 116 Appendix A ............................................................................................ 119 Mind, Brain, and Education Science Research, Practice and Policy Goals Appendix B............................................................................................. 123 Glossary of Mind, Brain, and Education Terms Appendix C............................................................................................. 136 Experts Invited to Participate in the 2020 International Survey on What We Have Learned From Mind, Brain, and Education Science Appendix D ............................................................................................ 215 QR Codes and Links for Timeline Illustration and Annexes Bibliography ........................................................................................... 218

LIST OF FIGURES AND TABLES

Figures Figure 5-1. Transdisciplinary Thinking .................................................... 52 Figure 5-2. MBE as a Transdisciplinary Research Field .......................... 55 Figure 5-3. Accumulative Model of Mind, Brain, and Education Science ................................................................................................ 56 Figure 6-1. Mind, Brain, Health and Education ....................................... 78

Tables Table 5-1. Distribution of Articles Published in MBE Journal in Terms of Topics ............................................................................................. 58 Table 5-2. Distribution of Articles Published in MBE Journal in Terms of Research Methods........................................................................... 60 Table 6-1. Articles Mentioning MBE, Educational Neuroscience and Neuroeducation 1970-2020 .......................................................... 74 Table 6-2 The Purpose, Mission, and Visions of the Field ....................... 80 Table 6-3. Mind, Brain, and Education within the Context of the Learning Sciences ............................................................................... 85 Table 7-1. Principles of Learning Supported by Mind, Brain, and Education Science According to 2020 Survey ............................. 91 Table 7-2. Tenets Supported by Mind, Brain, and Education Science According to 2020 Survey .................................................................. 94 Table 7-3. Key Concepts in MBE Teacher Knowledge Identified by the Participants in the 2020 Survey.............................................. 105 Table 7-4. A Proposed Curriculum for a Master’s Degree in MBE/ Educational Neuroscience ................................................................. 107 Table 8-1. The Six Main Aims of Education Based on Mind, Brain, and Education Science Identified by the Participants in the 2020 Survey ............................................................................................... 113

ACKNOWLEDGEMENTS

We wish to thank our colleagues around the world who participated in the 2020 survey conducted to evaluate what Mind, Brain, and Education science has taught us about teaching. They have challenged us, taught us, and helped us extend our thinking about learning sciences. This book would not be possible without the support received from several experts, most especially Professor David Daniel who contributed to the 2020 survey. We are grateful to all for their intellectual generosity.

PREFACE WHAT YOU WILL FIND IN THIS BOOK

This book is a journey through time, looking backwards in order to move forward. Historical thinking is defined by Seixas (2006) as organizing collective experiences of the past such that they form a meaningful way to think about the present. Historical thinking allows educators a path to consciously prevent the repetition of the mistakes made in earlier renditions of problem-solving (Eisner, 1994a; Ponder, 1974). This type of thinking is crucial for all practitioners, especially teachers (Shulman, 2005) as “those who cannot remember the past are condemned to repeat it” (Santayana, 1905, 284). Like other disciplines, Mind, Brain, and Education (MBE) science has its unique history; MBE has grown out of the intersection of neuroscience, education, and psychology (see Fischer, et al., 2007; Fischer, 2010; Gardner, 2008; Tokuhama-Espinosa, 2008, 2010, 2011, 2014, 2018, 2021), with historical roots grounded in philosophy and episiotomy. These strong roots lay the foundation for research, practice, and policy in the discipline at an important moment in education in which millions are rethinking the role of formal schooling due to revaluations during the global pandemic. The research for this book analysed and synthesized the literature on the history of Mind, Brain, and Education as it relates to turning points in the evolution of the discipline. A scoping review which, according to Xiao and Watson (2017), aims to extract as much relevant data from each piece of literature as possible, was conducted to provide a snapshot of MBE and a complete overview of what has been done. The present research initiated with a systematic search of English language publications around the terms “mind, brain, and education [history],” “neuroscience and education history,” “neuroeducation history,” and “educational neuroscience history,” on six databases: Google Books, Google Scholar, ISI Web of Science, PUBMED, ProQuest, and Scopus. This search led to the identification of a long list of articles and books. Because of the lack of a peer-review process or possible relevance to the research scope, many of the publications were excluded from the review as one of the goals of this work was to base all findings on solid evidence. Only five studies had investigated the history of the

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intersection between neuroscience, psychology, and education before this book, which builds from their excellent documentation. Through a snowball technique (Lodico et al., 2010) the citations from these five investigations were then used to identify further relevant literature. The search for additional studies stopped at the point of saturation, when each new set of citations in a publication began to repeat key references that had already been identified (Creswell, 2015). As the current lingua franca in science is English, the study was limited to this language. Key individuals mentioned repeatedly in the literature as being part of the formal construction of the International Mind, Brain, and Education Society (IMBES) from 1990 to the present were also interviewed or queried by email or teleconferencing about key events in recent history to confirm citations in the literature, and their recommendations for additional source material were included. A summary timeline of our findings is illustrated in the poster that can be accessed the hyperlink and/or QR code found in Appendix D. In Chapter 1 we look at what can be gleaned from Ancient Civilizations to establish not only key hypotheses about how the human brain and mind work, but also to show that where we come from, why we are how we are, and how we shape or succumb to our own circumstances, have always sparked human curiosity. We then document how humans wavered between their wish to leave everything in the hands of God and their desire to be in control of their destiny. Here we look at the Middle Ages and delve into the role of religion as an impetus for learning, as well as the establishment of the first universities. During this time, drawings of the brain created by brilliant minds, such as that of DaVinci, Vesalius, and Willis lead to the first shared definitions of brain parts. We close this chapter with a look at the way the Renaissance provided the backdrop for philosophy to stream into educational thinking, thanks to the likes of Descartes, Locke, and Rousseau. This was paralleled in time, but divided by intellectual chasms, with the way medical physicians and other scientists began to be more methodological, and the scientific method was born. Chapter 2 is devoted to homing in on specific scientific discoveries that catalysed very different theories of how the brain learns during the Industrial Revolution. On the one hand, ideas advanced by localizationists, or those who searched for a neat and clean division of brain functions, led to over-simplified interpretations of brain functions and to the pseudoscience of phrenology. On the other hand, some relished the new understandings of the electrical and chemical workings of the brain and ascribed to cell theory and a more micro analysis of brain functioning. The late 1800s brought with it new technologies, like better microscopes, which made the invisible visible and permitted a surge in more complex theories. We then look at the

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way the Second Industrial Revolution (1850–1900) brought a renewed, human-centric view to understanding learning. On the micro-level, specifically at the molecular and cellular level, neurons were better documented thanks to new technology developed by Golgi (from Italy) and used by Ramón y Cajal (in Spain) to establish the smallest unit of analysis for learning. At the macro, evolutionary level, animal observations–most notably by Darwin and Lamarck–led to hypotheses about human intellectual trait dominance, and the first intelligence tests were created. The “nature vs. nurture” debate, established back during Plato’s time, was renewed with Francis Galton’s ideas on eugenics, as was the postulation that some humans were naturally superior to others. The late 1800s firmly established the functioning of the nervous system and led to visions of how human learning is shaped by contact with the environment, including school settings. This is followed by a review of the remarkable consolidation of information about the workings of the human brain made possible through technology at the turn of the 20th century. A better understanding of neuroanatomy opened the door to the exploration of general cognitive functions, like memory. Modern educational practices, exemplified by the Dewey schools of the time, invited new theories based on a constructivist approach. The Third Industrial Revolution (1900–1950) was the first time the intersection of mind, brain, and behaviour was systematically studied, paving the way toward a more nuanced science of human learning focused primarily on early childhood development. In Chapter 3 we consider how the counter-culture movement in the 1960s united a surge of interest in how people learn to culminate in the Decade of the Brain in the 1990s. A new understanding of constructivism– how individuals build their knowledge based on prior experiences–combined with a growing understanding of how different environments influence learning created the shoulders upon which Mind, Brain, and Education could finally establish a footing. This time in history (1950–1999) was the perfect frame for three publications, which we explore in this chapter, which can be considered the foundational documents of MBE science. The Digital Age (2000–2010), explained in Chapter 4, used the elements of the perfect storm between technology, neuroscience, psychology, and education to give birth to Mind, Brain, and Education science, including a formal society, an award-winning journal, and a regular conference. New academic programs in Mind, Brain, and Education science emerged around the world, and there was a flood of new publications in the discipline. This leap to formality caused concern in many, some claiming that bridging hard and social sciences was not useful, easy, possible, and/or desirable. Others urged caution due to the unchartered territory, leading to a new area of Neuroethics. The Human Connectome Project was launched, which, among

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other things, documented the complexity of human thinking and learning, and the influence of teaching, leading to a new appreciation of the intricacies of the human brain, closing the chapter on simplistic theories, including localizationism, and the resulting in the demise of eugenics. Along with MBE’s debut and more global interest in the brain by people around the world came misinformation, however, and neuromyths flourished. In Chapter 5 we explore how research is being conducted in MBE. While MBE has an international society, a journal, and annual meetings, until the 2020s it could not lay claim to a specific methodology as neuroscientists, psychologists and educators have different types of ways of doing research. This chapter also looks at how MBE has evolved to include a “researcher-practitioner” model in which the ideal professional formation results in an individual who can walk the fence between neuroscience, psychology, and education in terms of basic knowledge, including teaching and researching skills. Additionally, while the critical role of technology on learning is mentioned throughout this book, the particularly interesting implications that it poses for Mind, Brain, and Education science are the focus of Chapter 5 as well. Interventions using knowledge gleaned from other learning sciences, including Artificial Intelligence, ushered in a different way to think of education spurred on by the analysis of “Big Data” and the first lab schools to monitor changes in children using measures from neuroscience, psychology and education simultaneously began a new age and established a unique methodology for MBE science. The growth of social media, online learning communities, and the collective intelligence of humanity began to corral neuromyths and counterpunch claims with evidence, elevating the general understanding of the brain. We close with a reminder that technology tends to lag behind human imagination, suggesting that interesting hypotheses about human learning may not currently have evidence or be visible with current tools, but they should be shelved rather than discarded. The unification of different sources of input into MBE meant that the lines between neuroscience, psychology and education have become blurred in the past few decades. In Chapter 6 we consider the semantics around the term “Mind, Brain, and Education” and the debate as to whether MBE is a discipline or a collection of concepts. Educational Neuroscience emerged as a formal discipline itself, increasing the need to distinguish what, if any, differences existed between the many learning sciences (neuroeducation, educational neuroscience, MBE science). Despite, or perhaps due to, the healthy debate about the borders between fields, new and exciting contributions have begun to emerge that benefit learners of all ages. In Chapter 7 we turn to MBE’s influence on has for teaching. Using data from the 2020 International

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Survey to gauge changes in education stimulated by MBE, we consider the Principles and Tenets of Mind, Brain, and Education science as agreed upon in this international consensus that greatly change pedagogy, as well as the influence this may have on teacher education. Projecting is just as much science as art; while the formula of the historical evolution of science appears to point to a clear trajectory–-toward the continued growth, popularity, use, and acceptance of MBE science–-it is unclear whether we may have hit a moment as Aristotle did in which current understandings stagnate for centuries, only to be revived when the time is ripe, or if MBE will continue to thrive and add new insights to educational practice. In Chapter 8 we look at three possible changes in educational research that might occur as the scientific value of MBE becomes better appreciated. A significant lesson from this historical review suggests that ideas that might have once appeared siloed or separate can now be unified to tell a different story with transdisciplinary hindsight. This historical perspective of Mind, Brain, and Education science, along with its sister disciplines–Educational Neuroscience, Neuroeducation, Cognitive Developmental Neuropsychology, Neuro-Psycho-Biology–outlines a clear, albeit complex period of gestation and birth, but also a promising early childhood and future development. From a global, historical perspective, several clear patterns have emerged. Some of the more outstanding relate to scientific advancements, information access, new academic programs and interventions, and the globalization and transdisciplinary focus of science today. This short book is meant for teachers and educators who value the history of science as a lens towards future practice. As a global overview, we acknowledge our work may not have done justice to each and every contribution towards the emergence of MBE over the past 5,000 years of history and invite further exploration on the part of the reader in other texts. The Soul Made Flesh (Zimmer, 2005) offers a wonderful narrative voice on the insights of human understanding about the brain. Seven and a Half Lessons about the Brain (Barrett, 2020) is a brief, how-to look at cognitive functions in a contemporary context. Immordino-Yang’s work on Emotions, Learning, and the Brain (2015) is a fabulous collection of our modern understanding of the link between feelings and thinking. Bordeau and colleagues’ “The Humanities in Medical Education: Ways of Knowing, Doing, Being” (2015) is an excellent reminder of how the hard and soft sciences can serve as compliments to one another. And for those interested in tracking the continually evolving refinement of teacher education, there is no better reference that Darling-Hammond and colleagues’ Educator Learning to Enact the Science of Learning and Development (2022).

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This book is different from the important contributions that have come before it in that it uses a macro-overview of multiple branches of the learning sciences – neuroscience, psychology, and education – to paint an historical overview in broad strokes to emphasize the collective contributions to our knowledge base and “ways of knowing” (Eisner, 1985) that are shaped by time, place and most importantly, culture and context. MBE is an international science, with contributions from nearly every country on earth. It is a transdisciplinary science, with contributions from nearly every learning science. And it seeks to share important messages about the human teaching-learning dynamic by translating evidence into useable knowledge. We hope the reader fills in the gaps between the broad strokes and digs deeper into the many facets of teaching and learning presented by the following pages, and that some may even use this book as a canvas for their own future work.

INTRODUCTION THE SEARCH FOR WHY AND HOW PEOPLE LEARN

Learning and teaching are complementary human activities. All animals learn, but few know how to teach, and only humans have made a science out of the teaching-learning dynamic (Battro, 2010). To teach well, one has to understand how learning occurs in brains and minds, and how this happens within and due to various contexts (National Academies of Sciences, Engineering, and Medicine, 2018). Indeed, throughout history, people have developed hypotheses about the means, mechanisms, and influences of and on human learning. The history of research on learning can be traced back to the efforts by early philosophers regarding a long debate over the place of the mind in the human body more than 5,000 years ago. Knowledge grew over time and the early illustrations of brain functions in the late Middle Ages created common starting points for speculation, discussion, and research across Europe, the Middle East, and Asia. During the Renaissance, researchers continued investigations to localize mental processes based on scientific evidence. This was intensified by the early 19th century with the establishment of the field of psychology. In the mid– 19th century, the theory of evolution had a profound influence on the understanding of the effect of learned behaviour on human evolution. Brainlateralization theory rose at the end of the 19th century, and, in the early 1930s, the evidence became available to show that neurons could communicate with each other, and that human experience changes their communication. By the 1960s, there were clear attempts to show the potential implications of brain research on education. The early 1990s coincided with both increased knowledge about the brain, but also a proliferation of misconceptions about learning, including neuromyths. In the first decade of the 21st century, many formal associations and academic programs were launched through a new discipline that emerged at the intersection of mind, brain, and education. Different labels have been used to describe such programs, such as Educational Neuroscience, Neuroeducation studies, and Mind, Brain, and Education.

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There continue to be vigorous debates in academic circles, however, as to whether differences between Mind, Brain, and Education (MBE) and other labels, such as Educational Neuroscience, are simply a matter of semantics, or if there are conceptual and philosophical foundations that distinguish them, which is explored further in Chapter 6. If viewed with 2020 hindsight, we might suggest that this process of development parallels that of a foetus growing towards early childhood, or at an even more macro level, of the moment in evolution when humans split from other apes to establish a new species. However, it is possible that like evolutionary tracks in general, clarity on this question will only emerge after more time has passed. As authors in MBE, we work with people around the world who we would quickly identify as “Mind, Brain, and Education scientists” including the past Presidents of the International Mind, Brain, and Education Society, Kurt Fischer (2004-2008), Antonio Battro (2008-2010), Marc Schwartz (2010-2014), Daniel Ansari (2014-2016), Mary Helen Immordino-Yang (2016-2018), Nora Newcombe (2018-2022), and Bert DeSmedt (20222024), and others whose research reflects MBE’s goals, such as Stanislas Dehaene, Michael Posner, Nienke van Attenveldt, Janet Dubinsky, Paul Howard-Jones, Daniel Willingham, David Daniel, Jay Giedd, Howard Gardner, among others. Most of these MBE thought leaders do not selfidentify as MBE researchers and often prefer to use more traditional fields of affiliation (“Neuroscientist”; “Psychologist”; “Educator”). This is an important stumbling block to growth in the discipline as we will explore further in Chapter 6, as most of the historical turning points in science are associated with key figures and thought leaders, which, if absent, lead to far more extended periods of gestation of ideas than would normally occur if promoted by a strong group of advocates. The complexity of MBE, its newness, and its slowly refining focus to laser in on the teaching-learning dynamic, is at once informed by and informs a new understanding of the brain and its place in educating about how we should teach to maximize each individual’s potential. The lack of societal affiliation is at once a symptom as well as a cause of its slow but steady speed of development. While the name itself is of little consequence–a rose by any other name would still smell as sweet–important opportunities to influence public policy as well as to globally improve education are likely lost without explicit identity to the discipline. After all, no discipline exists without membership and membership depends on identity. Having said that, this historical review shows that the pace of acceptance of MBE as a new discipline is actually far faster than the norm. Whereas it took Aristotle’s understanding of the role of the senses as the way we learn

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about our world hundreds of years to gain acceptance, MBE has grown from a concept to a reality in just two decades. Even good, solid, modern, and “obvious” ideas usually take more than a generation to take hold. For example, the need for a field like Cognitive Neuroscience seems obvious today, however, few remember that it was born conceptually in 1976 and challenged in 1998, that it debuted in university faculties in the late nineties, finally being established in textbooks in 2002, and eventually embraced by 2008. Yet practitioners, who are often deep in their research, and seldom have the time to raise their heads above their detailed silos to appreciate long-term development, may sometimes be impatient and fail to realize that new ideas in science rarely occur within a single lifetime, let alone within the span of a professional career. This makes the early abandonment of the professional affiliation with MBE much like someone playing the stock market. If you simply leave the investment alone over time, it inevitably grows, but many are spooked by reduced gains early on and pull out, thinking to cut their losses, only to find that their profits would have improved if they would have stayed in for the long haul. To establish a true understanding of the learning sciences would require a deft and complete review of what we know about human learning from multiple disciplines, ranging from the medical science to social sciences, with contributions from technology as well as from philosophy, morals, and ethics. There already exist a handful of excellent books that do this. Fischer, Hmelo-Silver, Goldman and Reimann’s International Handbook: The Learning Sciences (2018), the National Academies of Sciences, Engineering and Medicine of the United States’ consensus study report of How People Learn II: Learners, Contexts, and Cultures (2018), and Sawyer’s The Cambridge Handbook of the Learning Sciences (2022) are gold starreferences in this arena. Readers are encouraged to see these books for a more thorough understanding of our current knowledge of the complex phenomenon of learning. The goal of this humble book is slightly different and uses the learning sciences as an historical roadmap through humanity’s quest to know itself better. With a better understanding of from whence we came, we can more easily navigate towards more complex goals in human learning broadly speaking, and in education as a science in particular. Broadly speaking, the literature suggests human learning serves multiple goals. At its most basic level, the brain learns to ensure the body’s survival (Kempermann et al., 2010). At its most complex level, the brain learns to create and innovate (Yang et al., 2018). The human brain is the seat of all learning (Chang, 2014), and it is the focus of many of the main findings highlighted in this book. The brain bas been said to be “the last and grandest biological frontier, the most complex thing we have yet discovered in our

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universe” (Gordon and Koroshetz, 2021, para. 1) and “the most complex organ in the body—and perhaps the most complex object in the universe” (Ackerman, 1992, iii), which is only just beginning to be understood (Tokuhama-Espinosa, 2015). This means that what is shared here should be taken in historical context and with a mind open to continued development. In looking at the history of the learning sciences, we are guided by an overarching question: What useable knowledge for teaching comes from MBE and the learning sciences? Lessons from the original How People Learn (Bransford, Brown and Cocking, 2000) hint at key answers to this question. First, all learning hinges on knowledge (dates, facts, formulas, names, theories, concepts), skills (the ability to use the knowledge), and attitudes (value premises). Knowledge–such as the memorization of certain facts or formulas–is vital to learning but can be found on any Smartphone. This suggests that teaching should not only be focused on content alone. Skills can now be rehearsed based on personal needs using digital tools. This suggests that differentiation can be facilitated by technology. However, unlike knowledge and skills, attitudes, values and belief systems, require guided instruction from another human being. Deeper learning, not just the transmission of content, requires guidance from quality teachers (DarlingHammond and Oakes, 2021). Furthermore, one could argue that learning is a design problem. Leveraging prior knowledge (Witherby and Carpenter, 2021), giving time for reflection (Chen et al., 2017), and constructing learning contexts (García-Martínez et al., 2018) all help learning, and are only possible in the skilled hands of learning design specialists who are normally well-trained teachers (Darling-Hammond, 2017). The purposeful planning of classroom events (Stender et al., 2017), the balance of synchronous to asynchronous learning activities (Anderson, 2015), and the artful management of complex personalities in classrooms (Brophy, 2006) are all part of good instructional design. Finally, the most effective instructors know why their interventions work (Dome et al., 2005). That is, a better understanding of why leveraging prior knowledge (e.g., Witherby and Carpenter, 2021), time for reflection (e.g., Hodgkinson, 2021), and the design of learning contexts (e.g., Mandl, et al., 2005) work must be a part of every instructor’s preparation. This necessarily requires knowledge of how the human brain learns best (Tokuhama-Espinosa, 2018). These ideas were reaffirmed by TokuhamaEspinosa, Nouri and Daniels, 20 years after How People Learn was published, in an international panel to survey what teachers should be taught about the brain (2020). The consensus of 121 experts in the learning sciences from 29 different countries was that there are six principles in learning, –concepts that are evidence-based for all human brains, in all

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cultures, and all ages–which should be recognized as “basic” knowledge in the learning sciences. Experts also identified 21 tenets, which explain human learning, but which have to be considered within the broad range of human variability as no two people will leverage them identically. The tenets include things like motivation, which is a vital component for learning, but which is triggered by different stimuli for different people at different times in the learning process. This uniqueness exists because all new learning passes through the filter of prior knowledge, and no two people have identical life experiences. Guidelines about how humans learn best can be built upon these foundational consensus-driven ideas. This is no small feat. The history of the learning sciences reached this important level of understanding after more than 1,000 years of development, international cooperation, compromises in language, negotiation of communication media, and great advances in technology. To better appreciate the “shoulders of giants” upon which the learning sciences currently sit, this book will review some of those historical highlights which presently permit the use of the principles and tenets as evidence-based guidelines for teaching and learning practice. The information chosen for this book comes from all major branches of the learning sciences, including philosophy and history, and more modern constructs such as cognitive psychology and neuroscience. This book closes with the idea that the ultimate goal of the learning sciences is to improve teaching. Knowing that all animals learn, but only humans have made a science of teaching reminds all learning scientists, including teachers, trainers, coaches, and parents, that they can and should play a role in advancing knowledge through actions. Some readers will contribute by developing educational technology. Others will reach out to colleagues internationally. Some will improve their thinking processes through transdisciplinary insight. Readers may be inspired to move out of their comfort zones and learn the new language of learning for research. And others may have the imagination to create the next big insights into the human meaning-making and teaching exchange. All, hopefully, will commit to the rigour of being true to the learning sciences by using evidence-based information.

I. THE HISTORY OF MIND, BRAIN, AND EDUCATION SCIENCE

CHAPTER 1 EARLY CONTRIBUTIONS TO MIND, BRAIN AND EDUCATION SCIENCE

The history of the learning sciences spans back to the earliest records in civilization. The ancient Egyptians, Chinese, Greeks and Roman separately at first, and then later collectively through translation, used basic observation of behaviour to hypothesize the origins of complex thinking. This means the historical relationship between brain sciences, mind sciences, and educational sciences is not particularly new. Indeed, knowing how the brain acquires new information and how these learning processes are affected by age, emotion, and context are questions that have long fascinated scientists (Blakemore and Frith, 2001).

Ancient Civilizations (3000 BCE–300 CE): Brain vs. Heart Hypothesis The roots of humankind’s complex understanding about thinking can be traced back in written form from the Egyptians in Africa, the Chinese in Asia, and the Greek, and Romans in Europe, and in oral traditions and pictographs from the Mayans in the Americas. Some of the primary debates in these earlier times shared by all of these cultures were about whether mental processes are located in the brain or the heart (Newby-Watson, 1988), what drives will, motivation, and learning, and how this influences the teaching-learning dynamic (Tokuhama-Espinosa, 2014). Perhaps one of the most interesting contributions from this early time is the transdisciplinary vision with which the major actors considered philosophy, religion, medicine, neuroscience, and education to develop their theories. The first record of the neurobiological symptoms of brain injury was found in the Edwin Smith Papyrus reports written around 1700 BCE, nearly 4000 years ago, in which the first documented record of the word “brain” was mentioned. It is believed to be a copy of a much older treatise dating back to about 3000 BCE written by Imhotep, the famous Egyptian polymath and architect. It contrasts with most ancient subsequent medical writing

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which placed the heart, not the brain, as the seat of the mind and the centre of intellectual activity (Gross, 1987). Intellect and well-being, while complementary, were considered to be embodied in different physical structures of the body. Approximately 1,000 years after the Egyptian’s first mention of the brain, the great Chinese philosopher, Confucius (552– 479BC), contributed to what is now known as the Confucian theory of mind. His ideas influenced both theories about the nature of the human mind and methods of education, especially moral education. For Confucius, the mind was viewed as a mental substance that reflects, thinks, evaluates, and chooses. Confucius’ ideas exist today in modern neuroscience, though limitations in technology still hide the precise neural correlates for these basic functions. Mencius (371–289 BC) and Xun Zi (298–238 BC) followed Confucius to develop a better understanding of the mind from the moral point of view, emphasizing the mind as a mental substance of both moral and cognitive functions (Chen, 2016). These ideas are fundamental to modern developmental theories 2300 years later. Ancient Greek scientists also speculated about the anatomical seat of cognitive, motor, and sensory functions, and the origin of neural diseases (Crivellato and Ribatti, 2007). Around the same time as Confucius, Alcmaeion (500 BCE) was the first to identify the brain as a source of human consciousness and subscribed to what is now called “the brain hypothesis” or “encephalocentrism theory” (Stavros, 2014). Empedocles, another Greek, (490–430 BCE), located mental processes in the heart and subscribed to what is now called ‘‘the heart hypothesis” or “cardiocentrism theory” (Crivellato and Ribatti, 2007; Kolb and Whishaw, 2008; NewbyWatson, 1988). Empedocles explained that the blood around the heart is the most important vehicle of life and therefore, the source of human thoughts (Crivellato and Ribatti, 2007). Slightly after Empedocles, the more wellknown Hippocrates (460–370 BCE) recognized the role of the brain in human consciousness and argued for the brain hypothesis (Ferrari and McBride, 2011). According to Hippocrates’s view, there were four humours (blood, yellow bile, black bile, and phlegm) responsible for the states of health and illness, and mental insanity is a process of brain corruption induced by bile. The link between physical and mental wellbeing still exists today. For Hippocrates, the brain was not only considered the seat of intelligence, sensory perception, and motor control but it was also regarded as the source of pleasure and pain, the origin of emotions, and the font of moral judgment and artistic experiences (Crivellato and Ribatti, 2007), extending the physical and the mental to the ethical and aesthetical. Plato (427–347 BCE) proposed the concept of a tripartite soul (nutritive, perceptual, and rational) and placed its rational part in the brain because that

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was the part of the body closest to the heavens (Crivellato and Ribatti, 2007; Kolb and Whishaw, 2008). To Plato, the brain was a “mental wax” that becomes grooved as we learn and recall information over the same pathways and becomes a smooth surface once again as we forget the information. He also contributed to the distinctions between nature and nurture and attributed individual human differences to nature (NewbyWatson, 1988). In opposition to Plato’s opinion, Aristotle (384–322 BCE) recognized the heart as the source of mental processes because it is warm and active. The brain, which was cold and inert as Aristotle observed, served as a radiator to cool the blood. He also observed that, of all animals, humans had the largest brain relative to body size (which was later proven wrong; dolphins have the largest brain-to-body ratio of mammals) and interpreted this as evidence that our blood is richer and hotter than that of other animals and so requires a larger cooling system (Kolb and Whishaw, 2008). According to Aristotle, sensory input was the foundation of all knowledge (Newby-Watson, 1988). Just a half-century later, Aristotle’s belief about the heart was proven wrong while his beliefs about the senses were confirmed. Alexandrian physicians, Herophilus (335–280 BCE) and Erasistratus (310– 250 BCE) provided a remarkable contribution to the development of neuroscience with a modern approach to the dissection of the nervous system, the clear description of many neuroanatomical structures, the identification of cranial and spinal nerves, and the fundamental distinction between sensory and motor nerves (Sherrington, 1897). After the turn of the century, early Roman physicians, such as Galen (129–216 CE), devoted much experimental and theoretical work to the study of brain functions and argued strongly for the brain hypothesis (Crivellato and Ribatti, 2007; Kolb and Wishaw, 2008). Galen identified the cerebellum as the area involved in motor functions and the cerebrum as the area involved in sensory processing and was proven partially right centuries later (Voogd and De Zeeuw, 2020). Galen went to great pains to refute Aristotle, pointing out that pressure on the brain causes cessation of movement and even death, whereas pressure on the heart causes pain but does not arrest voluntary behaviour (Kolb and Whishaw, 2008). Despite Galen’s heroic efforts, the controversy between encephalocentrists (brain) and cardiocentrists (heart) continued well into the Renaissance and beyond (Newby-Watson, 1988). This first significant stage in the historical foundations of Mind, Brain, and Education science from ancient civilization can be referred to as foundational and purely functional. On the one hand, the physiological structure of the human body in the West, and, on the other hand, the exploration of inner consciousness in the East joined to form the core

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knowledge base upon which MBE stands today. The Middle Ages, channelled by religious zeal, moved attention away from the physical body and personal reflection towards the intangible soul, however, and as an extension, the beginning of the understanding of how humans learn and believe things about their world.

Middle Ages (400–1300s): The First Universities and Illustrations of Human Brain Anatomy In the Middle Ages, which lasted for about 1000 years (from 400 to 1300 CE), scientific investigations were almost always ignored except for a handful of theories proposed by clergy members who were, along with the rich and elite, the few educated people in society. During this period, philosophy and arts served to praise God and were used to stabilize the power of the Church (Foster-Deffenbaugh, 1996). God, rather than man, was the central force and the sole determinant of behaviour. As education was limited there was little reflection on pedagogical practices which were limited to oral traditions and direct instruction. The few universities that existed at the time looked very much like church congregations with an instructor up on high and the congregation below. The human body was assumed holy, and researchers had to steal the corpses from cemeteries to perform autopsies, which made research a dangerous and costly task (Hergenhahn and Olson, 2005). While not very advanced in other areas of human learning, Medieval thinkers did accept Galen and Herophilus postulations on ventricular localization of mental faculties (Scatliff and Clark, 1992). In the 4th and 5th centuries, a theory that became known as the “cell doctrine of brain function” proposed by early church fathers such as St. Augustine (354–430 CE), suggested that the faculties of the mind were contained within the ventricular system of the brain (Lanska, 2021). At the time, it was thought that there were three (rather than the current knowledge of four) ventricles in the brain. The lateral ventricles were thought to be one cavity or the first cell. This cell received information from the special senses (i.e., vision, hearing, balance, taste, and smell) and was known as the cavity of “common sense”. Images and ideas moved from this cell went to the second cell (third ventricle) where they were incorporated into “reasoning”. The third cell (or fourth ventricle) was attributed to “memory” functions (Scatliff and Clark, 1992). While there was little hands-on learning at the time, thought leaders showed an extraordinary amount of imagination and reflection on the little physical evidence they had as they united the body with their theories of intangible thought.

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The early illustrations of brain function formed in the late Middle Ages used what was known of the physical body to explain brain functioning. In this context, though later proven imprecise, Jehan Yperman (1295–1351) identified three functional areas of the brain including the front, responsible for discrimination of visual, gustatory, and olfactory senses, the middle, dedicated to intelligence and hearing, and the posterior, devoted to memory (Clarke et al., 1996). To try and localize mental functions, John of Arderne (1307–1399) depicted the cranial cavity as being divided into anterior, middle, and posterior parts and Magnus Hundt (1449–1519) published anatomical illustrations depicting the brain as covering special senses and ventricular systems (Newby-Watson, 1988). Leonardo da Vinci’s (14521519) sketches of a centenarian brain and Andreas Vesalius’s (1514–1564) anatomical work not only created detailed visual records but also led to the consistent naming of specific brain areas, creating common terms of reference and vocabulary (Tokuhama-Espinosa, 2008; 2011). For the first time in the history of humanity, there was a consensus building process to try and share knowledge about the brain’s function. Among the most complete early versions of the brain were Christopher Wren’s engravings for Thomas Willis’ (1664) Cerebri Anatome (The Anatomy of the Brain) (Tokuhama-Espinosa, 2008, 2019), which provided an architecturally precise and proportional view of the brain. Later, it was shown that despite their accuracy, no two brain renderings were identical, which was not due to the inaccuracies of drawing quality, but rather because there are no two identical brains. The Medieval Age in Western Europe coincided with the Islamic Renaissance (7th–13th centuries) when Middle Eastern thinkers made great historical contributions about human learning (Clarke et al., 1996). In Persia, or modern-day Iran, prominent scholars such as Avicenna, Rhazes, and Jorjani established a new kind of medical practice based on observational data. Ali ibn Abbas Majusi Ahvazi, also known as Haly Abbas in the West, was a renowned Persian scientist of this era who wrote a large medical encyclopaedia entitled The Perfect Book of the Art of Medicine. The book was comprised of 20 chapters, including one on neurology, each of which began with anatomical discussions and provided not only the description of diseases and treatments but also offered detailed explanations of bodily structures, including that of cranial nerves and sutures. Al-Haytham (Latinized as Alhazen), (965–1039 CE), was an Iraqi mathematician, psychologist, and physicist of the Islamic Golden Age. Biographers call him “the first scientist” and the “inventor of the scientific method” who established that learning is generated by our sensory perceptions of the world (Ghassemi, 2020). In this process, our senses feed

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information to our memory, and we compare new with old, detect patterns and novelty, and base new learning on past associations (TokuhamaEspinosa, 2011). The Middle Ages established a key vision related to the processes by which knowledge could and should be gathered in MBE. As theories of learning were introduced, the scientific method was born to guide and organize thinking about the way new information was vetted not only in MBE but in all scientific disciplines. The reliance on evidence flourished in the third stage of development during the Renaissance.

The Renaissance (1400–1700): Development of the Modern Scientific Method Renaissance researchers sought to investigate the nature of the human mind based on scientific evidence. Scientists, as well as philosophers, continued to describe the localization of mental processes in the brain, influencing work in the field for centuries, only to be found to be only partially true 400 years later. Advances in technology through the invention of the microscope and the discovery of bioelectricity facilitated the study of brain structures. In 1628, William Harvey provided a significant contribution to the history of physiology when he recognized the circulation of blood in the human body (Harvey, 1628). René Descartes (1596–1650) replaced the Platonic concept of a tripartite soul with a single soul that he called “the mind” (Kolb and Wishaw, 2008). The mind, as Descartes saw it, was different from the body: the body operated on principles similar to those of a machine, while the mind decided what movements the machine should make. This idea implied that a person is capable of being conscious and rational only because the mind corralled the body’s instincts. Descartes’s dualism originated in what came to be known as the mind-body problem (Gorham, 1994). These were some of the first explicit references to the way the mind and brain controlled the body. In addition to being a dualist, Descartes ascribed functions to different parts of the brain, as an understanding of complex neuronal networks was not yet established at the time. He located the site of action of the mind in the pineal body, a small structure in the brainstem, today thought to take part in controlling seasonal rhythms (Lokhorst and Kaitaro, 2001). René Descartes’ proclamation “Cogito, ergo sum” (I think, therefore I am) in 1637 triggered a new reflection about the role of the individual mind and a new worldview that has forever influenced Western concepts of education (Tokuhama-Espinosa, 2010). In An Essay Concerning Human Understanding, first published in 1690, John Locke (1632–1704) established the link between developmental

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psychology and education, though psychology itself was still not known as a separate field at the time and was simply referred to as studies of the mind. Locke made calls for a philosophy of education that encouraged deeper selfregulation of metacognition and learning, which, even today, continues to impact the way students are taught and how we observe what is learned (Henson, 2003; Enkavi et al., 2019 ). Locke suggested that a key to good teaching is to help students reflect more on their thinking processes. By articulating their mental steps in solving a problem, for example, Locke believed that learners would become better thinkers. This reflective process is a modern cornerstone of critical thinking in which certain habits of mind such as self-reflection help students develop metacognitive skills (Costa and Kallick, 2008). Locke’s proposed curriculum emphasized starting with the fun of learning plain and simple ideas and building on children’s existing knowledge of how subjects are interconnected (Locke, 1880). Such ideas are still revered today, and “play” has taken on a prominent role in leveraging a modern understanding about the interaction of emotions and cognition (Immordino-Yang, 2015). Locke’s conceptualization of the mind as a “blank slate” that achieves knowledge due to contact with the external environment became the basis for the psychological thoughts of later scholars such as Charles Bonnet and George Berkeley (Lovejoy, 2017). For instance, in his 1755 Essay on Psychology, Bonnet specifically linked mind, brain, and education, but without proposing any educational program (Bonnet, 1755). In 1762, Jean-Jacques Rousseau (1712–1788), one of the great educational philosophers of the times, wrote the book Emile which cultivated the bases for a naturalistic philosophy of education and observational studies which remain the dominant methodology of educational research today. Rousseau’s conception of education was later accepted and developed further by Johan Henrich Pestalozzi (1746–1827), John Frederick Herbart (1776–1841), and Fedrick William August Froebel (1782–1853), who focused on education according to each child’s natural inclinations (Shrivastava, 2003), setting the first foundations of differentiated education started in early childhood. Thomas Reid (1710–1796) made influential contributions to philosophical topics including ethics, aesthetics, and the philosophy of mind, and offered perceptive and important criticisms of the philosophy of Locke, Berkeley, and especially Hume. He advocated an approach called Faculty Psychology which suggested the human mind was divided into over 43 faculties (such as consciousness, attention, perception, memory, judgment, and compassion) and that each of these faculties was assigned to certain mental tasks (Nichols and Yaffe, 2000). The views of faculty psychology were implicitly

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reconstructed in Franz Joseph Gall’s formulation of phrenology (Hergenhahn, 2009), which was later refuted, setting back the acceptance of the psychological divisions of the mind which are largely still agreed upon today. Immanuel Kant (1724–1804) was one of the first to recognize the cognitive processes of the mind and opened the door to Piaget and others who would further develop the ideas of complex cognition (DarlingHammond et al., 2001). The Renaissance showed the complementary nature of the mind and the body, as well as to suggest ways that they were mutually influential in the ability to learn. This period further advanced a more individualized vision of human learning by identifying the multiple factors that must be considered to personalize the learning experience, including a person’s interaction with others and with the environment. This led to some of the first publications of childhood developmental and educational interventions that supported learning contexts in the first Industrial Revolution.

CHAPTER 2 THE INDUSTRIAL AGE

The Industrial Revolutions of the 18th and 19th centuries ushered in a new approach to teaching and learning. Spurred on by new technology and tools, the efficiency of the industrial age drew awkward parallels about the goals of business and the goals of education, not the least of which was that learning could be optimized through automated, standardized processes. As measurements of brain functions became possible, overgeneralizations about findings lead to many neuromyths, some of which we are still trying to eliminate today. One such myth was that single brain parts were responsible for complex thinking or aspects of cognition. “Localizationism” was an over-simplified belief about the brain brought on by the factory output models during the 18th century in which each person, each machine, and each tool did just one thing, but did it well. If everything went to plan, the results were the production of standardized product, or in the case of education, student.

The First Industrial Revolution (1700–1849): Myth of “Localizationism” The last decades of the 18th century witnessed a growth of interest in the localization of brain functions. In 1792, Germans Franz Joseph Gall and J.G. Spurzheim advocated the idea that different brain regions were responsible for different behavioural and intellectual functions producing bumps and indentations on the skull. It was thought that the more highly developed areas would require more volume of the cortex and the part of the skull covering this area would bulge outward and create a bump on the person’s head (Fancher, 1979; Benjamin, 2008; Van Wyhe, 2002). Gall termed this doctrine “organology”, and it became extremely popular by the early 19th century. The term “phrenology” (derived from the Greek roots: phren: ‘mind’ and logos: ‘study/discourse’) came into general use around 1819–1820 in Britain after it was coined by the physician T.I.M. Forster in 1815 (Van Wyhe, 2002). Phrenology was promoted largely by the efforts of two brothers, Orson Fowler (1809–1887) and Lorenzo Fowler (1811–1896)

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who opened clinics in New York, Boston, and Philadelphia. They published a phrenological magazine for the public, wrote and published many books on the subject, and trained individuals in the “science” of phrenology, many of whom then opened clinics in various US cities or travelled the countryside with their “phrenological expertise” (Benjamin, 2008). The first phrenological society was founded in Edinburgh in 1820, and many more followed throughout Britain and America in later decades (Van Wyhe, 2002). Even during the peak of its popularity between the 1820s and 1840s, phrenology was always controversial and never achieved the status of an accredited science (Van Wyhe, 2002). In the late 1820s, Gall’s ideas were subjected to experimental analysis by the Pierre Flourens, who concluded that specific brain regions were not responsible for specific behaviours, but that all brain regions, especially the cerebral hemispheres of the forebrain, participated in every mental operation (Kandel, 1995; Kolb and Whishaw, 2008). Phrenology may seem obviously erroneous today, but similar neuromyths about other aspects of neural physiology still exist; people are attracted to simple explanations (Tokuhama-Espinosa, 2018). Phrenology was slowly replaced by an appreciation of the complex neural networks that worked to achieve different types of cognitive processes (Sporns, 2010). Facilitating this effort were new methods to understand human learning. By the time the Industrial Revolution was fully underway, human observation, dissection, and interventions became more commonplace. In 1749, David Hartley published Observations of Man, the first English work using the word psychology (Walls, 1982). Despite knowing about the mind from a Confucius perspective 2,000 years earlier, it was not incorporated into Western thought until the field of the study of the mind – psychology – was established, thanks in part to Hartley’s work. Not only was an understanding of human behaviour evolving through the incorporation of the mind and psychology, but in tandem, more knowledge was growing about the brain and neuroscience. A few years later, in Germany, Johann Gottlob Kruger authored a paper that suggested the use of electroconvulsive therapy for mental illness (Zuschrift an Seine Zuhörer by Kruger, 1754), indicating an advanced understanding of how human brains were controlled by electrical and chemical changes that resulted from environmental stimuli. Knowledge about the precise way cells changed due to electrical and chemical modifications grew at this time as well, building off on findings from 100 years earlier (Reynolds, 2010). Cell theory states that the cell is the basic unit of structure in all living organisms, including humans. Despite the discovery of the cell by Robert Hooke in 1665, cell theory was not developed for nearly another 200 years. A contemporary of Hooke’s in

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Holland, Anton van Leeuwenhoek, advanced the concept of cell biology by proving cells were living organisms and presenting his findings to the Royal Society in 1676 but it was not, until much later that Germany’s Jakob Schleiden (in 1838) and England’s Theodor Schwann (in 1939) each discovered individual units in plant and animal bodies which they called “cells,” that cell theory became known. Although cell theory quickly became popular after 1939 and remains so today, an explanation for the centuries’ long wait was that most of Hooke’s, van Leeuwenhoek’s, Schleiden’s and Schwann’s contemporaries were limited by the technology of the times and unable to see most cells with a naked eye. Because they couldn’t see the cells, they chose to believe in what was easily visible to the naked eye, namely the fibres running through the nerve tissues must be the key to how learning was processed in the brain (Evans-Martin, 2010). The nervous system, they thought, was a continuous reticulum, of fibres and was the real seat of learning, an idea that became known as reticular theory (Evans-Martin, 2010). They did now know what scientists understand today, which is that both fibres and cells can exist at the same time and are not mutually exclusive in their responsibilities for processing stimuli and facilitating learning. Discoveries of the Industrial Revolution advanced science to the point of making the invisible visible, and therefore, evidence based. Advanced tools and techniques developed at the opening of the 19th century created a marriage between invisible and observable. This, along with the extrapolation of findings in the animal kingdom to human behaviour, led to new speculations about how the brain and its cellular networks worked to achieve learning.

The Second Industrial Revolution (1850–1900): Discovery of the Structure and Function of the Nervous System By the mid-19th century, another theory of the brain and behaviour was proposed by two English naturalists, Alfred Russell Wallace (1823–1913) and Charles Darwin (1809–1892) who independently arrived at the same conclusion about the evolution of the species. Darwin elaborated further on the topic in his manuscript on the Origin of Species by Means of Natural Selection, published in 1859. Darwin’s ideas of natural selection were inspired by Jean-Baptiste Lamarck (1744–1829) who had theorized about the idea of the inheritance of acquired characters. This theory was then called the transmutation of species and implied that specific conditions were necessary for acquired changes to be conserved and transmitted successively to the next generation. However, it was Darwin who provided the additional

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evidence needed to explain how characteristics were acquired as the result of use and disuse and were transmitted from one generation to the next, though this remains disputed in evolutionary biology circles (Burkhardt, 2013). Darwin argued that all organisms, both living and extinct, are descended from some unknown ancestor that lived in the remote past (Darwin, 1859). Darwin believed that any change in internal conditions or environmental influences could affect any character of an individual and change it, something that is now referred to as epigenetics (Keverne and Curley, 2008). Epigenetics suggest that the genes an individual inherit remain the same, but some are potentiated by the interaction with the environment while others are not. Potentiation of genes occurs when the resulting gene expression is beneficial to survival. A modern understanding of epigenetics explains the importance of schools because only a small fraction of all our genes (approximately 10%) are actually stimulated by our environments (Cantor et al., 2021), meaning the quality of the environment determines learning potential. In the late 19th century, James Mark Baldwin began to formulate a hypothesis concerning what came to be known as the Baldwin Effect described in a paper entitled “A New Factor in Evolution” in 1896. The Baldwin Effect describes the significant impact of learned behaviour on evolution through natural selection. His biosocial theory of development is said to have influenced both Jean Piaget’s and Lev Vygotsky’s theories on cognitive development (Wozniak, 2009). This theory provided a profound contribution to the belief that learning is an inevitable phenomenon: humans learn to survive, and they survive because they learn. The evolution of the human brain has adapted to changes in context, like that of all animals. For example, Maryanne Wolf (2007) suggested how reading has changed the human brain through dramatic evolutionary processes, which Stanislas Dehaene (2009) explains using a “neuronal recycling hypothesis” or the reuse of evolutionary older areas of the brain for new needs. Epigenetic changes meant that things beneficial to humans, such as the ability to read, became more easily potentiated by subsequent generations. Another advancement that made the fundamental building blocks of learning observable came in 1873 when the Italian scientist Camillo Golgi discovered a special staining method that made neurons (nerve cells) easier to study under a microscope. Golgi staining suddenly made many once invisible structures visible. However, because his technique was not refined enough to show the connections between individual neurons, Golgi himself as well as many of his followers continued to adhere to reticular theory. He believed the nervous system was a vast network of cytoplasm with many nuclei. In 1886, Swiss researchers Wilhelm His and August Forel proposed

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that the neuron and its connections might be an independent unit within the nervous system (Evans-Martin, 2010), which was a stunning insight given the limitations of technology at the time. A few years later in 1888, the Spaniard Santiago Ramón y Cajal discovered the presence of strictly organized neuronal circuits as a fundamental characteristic of all brains (Llinás, 2003), an idea that would forever change our understanding of basic neurophysiology. Consequently, German anatomist Wilhelm Waldeyer coined the term “neuron” (cells in the nervous system) and introduced the neuron doctrine in 1891, known today as neuron theory. However, it was not until after the invention of the electron microscope in the early 1930s that definitive evidence became available to show that neurons could communicate between themselves (Evans-Martin, 2010) through network systems linked by synaptic connections. As shown throughout history, advances in the physiological construct of the brain paralleled advances in psychology. Sigmund Freud (1856–1939), better known as the founder of psychoanalysis was a contemporary of Ramón y Cajal and made an important contribution to early modern neuroscience by investigating studies of nerve cells and their connections. Freud postulated that there are separate sets of neurons for perception and memory (Kandel, 2006). Freud’s ideas had interesting and influential impacts on some educational theories as well. For instance, Harold Rugg and Ann Schumacher’s The Child-Centered School in 1928 was influenced by the desire to create educational institutions that addressed the covert, emotional life of the child, to which Freud paid much attention. Other educators, such as Alexander Sutherland Neill, a Scottish teacher known for the creation of the Summerhill Schools which celebrated individual freedom, and William Pinar, and Madeleine Grumet, educational theorists who sought to reconceptualize curriculum around individual needs (Eisner, 1994a; Pinar, 2004) were also deeply influenced by Freud’s work linking the brain and mind to personalized learning through individual experience and interpretation. Brain-lateralization theory also grew in the mid-19th century and suggested that the two hemispheres of the brain have different functions, which remained the pervasive thought until the early 2000s. According to this theory, the left brain (which is really a hemisphere; people have only one brain, something that also remained in dispute in the 1800s) is responsible for verbal and sequential abilities while the right brain is responsible for emotions and special holistic processing. The rightbrain/left-brain construct in which some individuals are considered more “right-brained” and others more “left-brained” is debunked as a neuromyth today but was widely prescribed well into the 21st century (Tokuhama-

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Espinosa, 2018). The work of Paul Broca (1862) was of pivotal importance in the localization of some higher cognitive brain functions relating language to the left hemisphere, thus inadvertently contributing to localizationism theory. He first reported that lesions to the caudal part of the inferior frontal gyrus were associated with expressive language deficits. Carl Wernicke (1874) discovered a second language area involved in the comprehension or understanding of language, also in the left hemisphere. Both findings seemed to suggest that language depended on these left-hemisphere areas, which today are recognized as key hubs or nodes. While vitally important in language processing, these hubs are not the location of language as a whole but are rather important and often vital networks through which electrical and chemical signals pass. Dozens of other networks for language that crisscross hemispheric lines have been documented, but these only became visible in the late 1990s (Tokuhama-Espinosa, 2018). For over 100 years, Broca and Wernicke’s Areas were the only language areas discussed in much of the literature, making the idea that language could be in any other part of the brain hard to accept, even today. As language has been used as a proxy for intelligence since the early 1900s, this limited understanding of the complex networks in the brain planted the seeds for controversies throughout the 20th century. How to measure intelligence grew remains a key question in education today and is studied by many fields, including through psychometrics. By the end of the 19th century, Francis Galton’s studies had provided the basis for a statistical approach to measuring mental abilities, including intelligence. Galton, an English polymath, explorer, sociologist, psychologist, statistician, and meteorologist, was enamoured with the normal distribution (bell curve), and its success in describing many physical phenomena, which persuaded him that it would permeate all manner of other measurements and in particular mental measurements (Goldstein, 2012). Following Galton’s work, researchers such as France’s Alfred Binet (1904) and Romanian-born David Wechsler (1939) developed instruments to measure mental abilities (see Tulsky et al., 2003), which were later considered the first intelligence tests. The belief at the time, which persists to some extent today, was that a multiple-choice test of language, math, working memory, and reasoning skills could be used as a proxy for intelligence. It was later found that no test, no matter how complex, measures all facets that comprise intelligence (Gardner, 1983; Tokuhama-Espinosa, 2018). During the last decade of the 19th century, Wilhelm Wundt, a German physician turned philosopher, wrote the “Principles of Physiological Psychology” (1873-1874) which introduced psychology as an independent science. He founded the first experimental psychology lab at the University

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of Leipzig in 1879. Another leader of psychology originally formed in philosophy, William James, began conducting experiments at Harvard in 1875 and introduced the practical applications of psychology in the classroom in a book titled Talks to Teachers in 1899. The creation of intelligence tests and the establishment of the field of psychology and psychometrics opened the door to the complex world of human behaviour and legitimized the measurement of intelligence with simple multiplechoice tools. Some took a broader look at intelligence, however. The latter half of the 19th century ushered in a renewed interest in the brain-mind understanding, and the desire to better understand the precise influences on neurological functioning which were not as easy to measure, but which many felt were a better reflection of intelligence as a whole.

The Third Industrial Revolution (1900-1959): Establishment of the Relationships between Mind, Brain and Behaviour The Third Industrial Revolution brought with it a new understanding of neuroanatomy including the unification of physical structures with observable behaviours or functions. This more nuanced understanding of learning made it clear that single measure tests (of language, math, working memory or reasoning) did not reflect the complex on-goings of the human thinking brain. Discoveries related to cortical function continued in the early 20th century. For instance, in 1908, Korbinian Brodmann, a Swiss-trained German physician, drew a cortical map of the brain based on comparative studies of the mammalian cortex. He identified 52 cortical areas grouped into eleven histological regions known today as Brodmann’s Areas (Brodmann, 1909). This mapping made it clear that the one-to-one correspondence of parts to functions (localizationism) was an insufficient model. The advancement of new technologies in the early 1900s assisted researchers in understanding the neural activity in the human brain, exposing new complexities. For example, in Germany in 1929, Hans Berger recorded the electrical activity of neurons using electrodes placed on the scalp and called the recorded signals ‘electroencephalogram’ (EEG) (Haas, 2003) a tool still used widely today. Seven years later in 1936 in England, Edgar Douglas Adrian verified that information was transferred between neurons via trains of electrical activity, which varied in frequency based on the intensity of the stimulus. This laid the foundation for the future discovery of electrical synapses, hypothesized by Golgi and Ramon y Cajal in 1909, well before they were established in the 1950s (Kandel et al., 2000). This also was the beginning of the bridge between electrical and chemical

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processes in the brain, which were later shown to be the construction of neural networks in the brain and the basis of all learning. The switch from localizationism to networks made psychometricians question their singular measures of intelligence, which planted the seeds for new theories which would come to light in the next decades, including Robert Sternberg’s Triarchic Theory of Intelligence (1985), and Howard Gardner’s Theory of Multiple Intelligences (1983). The early 1900s also coincided with valuable understandings of the connection between the physical structures of the brain and the psychological processes of learning and memory. Karl Lashley (1917-1964) proposed the theory of equipotentiality, which refers to the ability of any cortical area to execute the functions of the other parts of the cortex (Hergenhahn and Olson, 2005; Lashley, 1930), which was posed in stark contrast to the localizationalists of the time. The neurobiological bases of learning began being investigated in earnest by Canadian Donald Hebb in the first half of 1900s. According to Hebb’s discovery (1949) not only the neurons that were directly stimulated fired, but those near them also fired, resulting in the nowfamous proclamation made by his student Carla J. Shatz that the “[neurons] that fire together wire together,” (1992, 64) which explained the relationship of neuronal activity and challenged both Lashley’s and localizationalists’ ideas. Hebb was one of the first to suggest that neurons generally connected to their close neighbours, which began a new vision of neuronal networks as opposed to simple individual cell activity. This was only later shown to be true 60 years later by work on the Connectome Project (Sporn, 2011). This concept had valuable implications for classroom learning as it offered a neurophysiological explanation of why certain types of memories seemed to cluster together in recall activities. Aside from a better understanding of neural physiology, complementary findings were emerging from education and psychology in the first half 20th century. The remarkable influence of another philosopher-psychologistturned-educator, John Dewey (1907), on the value of learning by experience made an impact still felt today. He intelligently established the “laboratory school” model in 1896, at the University of Chicago to test his “educational theory of progressivism” which was the first structure designed to use empirical evidence to inform educational decisions (Dewey, 1899/1907). The lab school model contributed to MBE foundations by providing a framework that deploys the philosophy, psychology, and biology of learning. The establishment of the new field of educational psychology, celebrated by the first issue of Educational Psychology Journal in 1910, sought to explain the potential contributions of the formal discipline of psychology to education and paved the way for a greater transdisciplinary

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modality of thinking about problems in education (Davis and Sumara, 2014; Johnston, 1996). As psychology was now both linked to neuroscience and to education, it served as a natural bridge between fields that were very distinct just 100 years earlier. What knowledge is of most worth in society? This is one of the classic questions of curriculum theory that was first raised and answered by the English philosopher and sociologist Herbert Spencer in the late 19th century. For Spencer, what’s worth learning is the knowledge that the study of science provides (Spencer, 1860). Following Spencer, debates on this question became a part of curriculum discourse and different answers. According to Pinar (2004, 19), this is a question that must be asked constantly; the answers we provide “will change according to project, person, nation, and the historical moment”. In other words, there is no single lens or ideological orientation based on which to determine and justify what students need to know and what they do not need to know. Context changes what is valuable or useful information. With the discovery that most mammal brains were shaped relatively similarly, large numbers of studies began to be based on monkey, pig, dog, and mouse brains. This was controversial, some argued because memory systems in a mouse in a cage are arguably different than a child in a classroom. Animal studies are less ethically charge, argued others, and they are also less expensive and faster to compete (as you can sacrifice the animal and look at brain changes more immediately than waiting for a human to die) (Gallistel, 1981). This means that the beginning of the 20th century also ushered in multiple hypotheses about human learning based on animal research with is both illuminating and incomplete as definitive applications in the case of humans require more complex research methods (Pound et al., 2004). Russian psychologist Ivan Pavlov’s studies on reflexes in dogs lay the foundation for conditioning techniques in behaviour modification and classroom management. Pavlov’s work provided John Watson in the United States with a method for studying behaviour and a way to theorize how to control and modify it (Schultz and Schultz, 2015). Watson (1913) introduced the term behaviourism and served as the most vocal advocate for the behaviourist perspective for parents and teachers in the early part of the century. He promoted a method of research that described observable behaviour in objective terms to allow for it to be predicted and controlled. This extension of the scientific method into social science research laid the foundations for future methodologies in transdisciplinary contexts. It also, however, drew attention to the difficulties, complexities, and “messiness” of the classroom when conducting scientific research, a challenge to this day. Whereas the scientific method was designed to compare one variable’s

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impact on another, classroom settings are characterized by the presence of confounding or unidentified variables that are numerous, making it highly unlikely (if not impossible) for educational research in the classroom to measure a single variable’s effect on another (Peabody, 2019). For example, lab studies on behaviour modification with animals might measure the oneto-one correspondence between the speed of decision making and the availability of a certain type of information (e.g., Laueriro-Martinez and Brusoni, 2018), whereas real life would likely involve things like the bullying attitude of the person sitting next to the individual, the subject’s relationship with the teacher as well as whether they had a good night’s sleep before the task or not. The complexity of the teaching-learning dynamic, which always involves multiple variables, became the conundrum of education as it fought for a place among the other learning sciences without adequate tools for its context (Tokuhama-Espinosa, 2010). Among those looking for new tools to match new theories was Edward Thorndike, known to many as the father of educational psychology whose entire career was spent at Columbia University Teacher’s College in New York, sought to bridge the gap between laboratory research and classroom application. He created a theory of educational states which suggested that the extent to which information learned in one situation will transfer to another situation is determined by the similarity between the two situations: The more similar the situations are, the greater the amount of transfer will occur (Thorndike and Gate, 1929). This was labelled Principle of Identical Elements (Thorndike, 1927). This became a focal point of educational reforms in the 1960s as much of what is taught in schools was arguably unrelated to real life contexts. The combination of these early 20th-century findings created three bedrocks of modern education. First, the true measure of learning is the ability to transfer knowledge from one context to another. Second, learning is improved in authentic contexts. Third, what is authentic is necessarily complex, unique to the individual, and often difficult to measure, meaning comparable and replicable studies are almost impossible, despite being a gold standard for quality in other sciences (Tokuhama-Espinosa, 2014). B.F. Skinner used both Thorndike’s ideas and Watson’s classical conditioning to develop his concept of operant conditioning, or the idea that we can deliberately reinforce desired behaviours by rewarding them when they are practised and ignore undesired behaviours by not focusing on them (Skinner, 1963). The legacy of behaviourism in MBE was, in part, the explanation of how learning is affected by changes in the environment. While popular in some circles, by the 1960s behaviourism was not embraced by all.

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Behaviourism became the dominant movement from the 1920s through the 1950s, but it was challenged by serious criticisms. The major opposing view of behaviourism was cognitivism, a theory that is approximately as old as behaviourism. Gestalt theory is one of the earliest forms of cognitive theory that developed at about the same time as early behaviourism (Lefrancois, 2000). This theory was formulated by a group of psychologists in early 20th century Germany. Gestalt psychologists, including Wolfgang Kohler, Kurt Koffka, and Max Wertheimer, emphasized the process of perception in the solution of problems and contributed several concepts to the understanding of problem-solving. They rejected Thorndike’s trial-anderror explanations of human learning and in contrast explained that learning occurred through insight, which was defined as the perception of relationships among elements of a problem situation. Gestalt psychologists, therefore, believed that teachers could aid problem-solving by arranging elements of a situation so that students would be more likely to perceive how the parts relate to the whole (Gredler, 2009; Lefrancois, 2000; Schunk, 2012). Unfortunately, rather than see how both theories might possibly be true at the same time, they opposed one another. At the same time, Edward Tolman (1932) introduced his theory of purposive behaviourism. According to this theory, behaviour is goal-directed and is guided by expectancies, which are themselves related to goals. The expectations that underlie and guide behaviour are cognitions. These cognitions develop after experiences with stimuli and rewards. In effect, what is learned is knowledge of a link between stimuli and expectancies of acquiring a goal. Thus, it is this purpose or search for goals that directs behaviour, not the reward (Lefrancois, 2000). This boom in learning theory production was spurred on by the many creative thinkers of the time, and by a world unified by war that began to bring scientists from many backgrounds together. The communications research of World War II and computer simulations of human intellectual capabilities introduced a new paradigm to the study of mental operations based on machine learning. This paradigm is reflected in the information-processing descriptions of cognitive operations. Indeed, information processing is not the name of a single theory; it is a collection of various approaches to the study of cognitive functions. According to this paradigm, human memory is a complex system that actively seeks sensory data, transforms the data into meaningful information, and stores the information in long-term memory (Gredler, 2009; Schunk, 2012). By the 1950s the inextricable link between memory and learning became clear and many theorists began to refer to “how the brain learns” when they were really describing memory systems in the brain (e.g., Russel, 1959). Studies that measured human memory combined with perception that resulted in a

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processing speed began to replace the original intelligence tests. This changed the concept of intelligence of being about content to being about the speed of response. Many considered this trading one evil for another however, as it, too was seen as limited in the scope. Benjamin Bloom argued that most children – 90% by his estimate (1984) – could master learning in any classroom, if given enough time to do so, which contradicts using timed-tests or processing speed as an accurate evaluation of intelligence. Current views value both speed of processing and various types of intelligence but still acknowledge their limitations (e.g., Tourva and Spanoudis, 2020). Closely related to these advances in the study of memory, educators also made significant contributions to curriculum and pedagogy. In 1949, Ralph W. Tyler published The Basic Principles of Curriculum and Instruction, which became a standard reference for anyone working with curriculum development through the 2000s. Similarly, Bloom’s Taxonomy of Educational Objectives was formulated in 1956 by a group of researchers under the leadership of Benjamin Bloom. They identified three domains of educational activities and categorized them as the cognitive domain (knowledge), the affective domain (attitudes), and the psychomotor domain (skills) (Bloom, 1956). Later, Robert Gagné (1962) formulated one of the best-known instructional theories based on cognitive principles. He identified five types of learning outcomes: intellectual skills, verbal information, cognitive strategies, motor skills, and attitudes. According to Gagné, instructional design for each type of learning outcome differs in term of internal and external conditions. Internal conditions are prerequisite skills, and attitudes that will influence the new learning, and external conditions are stimuli in the environment that support the internal processes (Gagné, 1985). Gagné’s ideas continued to be revisited, especially during the global COVID-19 pandemic (2020–2022) in which the need to return to “fundamental” learning goals, including attitudinal, social, and emotional learning came back into focus in 2020. The first half of the 20th century is celebrated for the explicit integration of academic fields, such as psychology and education and psychology and neuroscience for the benefit of student learning in real classroom contexts, which paralleled discoveries in neurophysiology that focused on the functional aspects of the learning brain. The nearing of these disparate academic fields of education, psychology and neuroscience created fertile ground for the next step towards the truly integrated discipline of Mind, Brain, and Education science in the second half of the 20th century.

CHAPTER 3 THE COUNTER CULTURE MOVEMENT (1960–1999): CONSTRUCTIVIST THINKING AND THE DECADE OF THE BRAIN

Transdisciplinary thinking, or the approach of educational problemsolving using many specialty frameworks rather than a siloed way, was furthered by the establishment of constructivism in which the learner builds his own knowledge through a series of life experiences and connections between them. This movement was led by two giants in educational psychology, Jean Piaget in Switzerland and Lev Vygotsky in the then Soviet Union. Following John Dewey work in the US, Jean Piaget explored the intricacies of a child’s cognitive development starting in the 1920s with seminal publications in the 1950s based on observation of the way children appeared to pass through clear, delineated mental stages, albeit within a broad range of time. Piaget’s theory of cognitive development was hugely influential, but not without criticism from neo-nativists (Lefrancois, 1991), who favoured focusing on domain-specific development (math, language, and other subject areas), rather than general cognitive development (e.g., memory, attention). Influenced by Piaget, Vygotsky demonstrated the focal role of social interaction in the construction of knowledge (1978). Whereas Piaget’s theory began from the “inside-out” and a child’s reflection about the world, Vygotsky favoured an “outside-in” model which gave a primary role to society’s influence on individual cognitive development. The approaches of Piaget and Vygotsky were later used in the 1990s as a basis for Kurt Fischer’s dynamic web of skills at Harvard University, which linked psychological theories of cognition with neural correlates underpinning that cognition in a global theory of human development that is at the forefront of current work in Mind, Brain, and Education (Bidell and Fischer, 1992, 1994, 1997, 2000; Fischer and Granott, 1995; Fischer, Knight, and Van Pays, 1993). Jerome Bruner (1960, 1996) also extended Piaget’s theory focusing on the contribution of cultural and social interaction and language

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as the medium of cognitive development. In contrast to Piaget, Bruner believed that any subject can be taught in a meaningful way to any child, regardless of their current stage of development. In turn, he advocated a spiral curriculum in which basic concepts and principles are revisited repeatedly with increasing depth and breadth (Bruner, 1960). In 1961, David Ausubel and colleague Donald Fitzgerald used the term “meaningful learning” to explain how individual cognitive structures are developed by assembling new knowledge based upon past experiences (Ausubel and Fitzgerald, 1961), extending the basic constructionist ideas of Piaget and Vygotsky. Meaning-making as a focus would become the centre of embodied cognitivist theories of learning in the 2000s (e.g., ImmordinoYang and Gotleib, 2017). Both Ausubel and Bruner drew new attention to the important role of the learning context and environment as the bases for the experiences that humans use to scaffold understanding. Norman Geschwind was responsible for a renaissance of understanding about the brain and learning through his carefully documented work on patients with lesions causing disconnection syndromes in the 1950s through the 1980s. Geschwind was one of the first examples of a modern transdisciplinary thinker. He had originally thought to study mathematics but pursued psychology and anthropology before beginning studies at the Harvard University Medical School where he initially began studies in psychiatry but finally settled in the field of neuroanatomy. Geschwind revived the localizationist ideas of the 1880s as he headed the Veterans Administration Hospital in Boston as the Chief of Neurology. His work shed new light on the neuroanatomy of cerebral lateral asymmetries related to aphasia and epilepsy and dyslexia (Geschwind and Galaburda, 1987), which contributed to what would become a renewed debate about the hemispheric dominance of skills, but even more importantly to reminding researchers to review all studies first hand as interpretations of evidence often left longterm gaps in historical understanding. Geschwind often paired his own observations of human behaviour with a return to primary source studies to see raw data instead of relying on other’s interpretations, which helped him forge simple but elegant proposals about the workings of the human brain (Damasio, 1985). He most famously used patterns of disturbed or changed networks in both epileptics (Geschwind, 1983) and in aphasics (Geschwind, 1970) to develop better hypotheses of what are considered “normal” neural networks for certain cognitive functions. He’s most lasting influence on Mind, Brain, and Education science is that his mentees, including Antonio Damasio, Albert M. Galaburda, Howard Gardner, and Maryanne Wolf all praised his keen insights as the father of “behavioural neurology,” a term he coined in the 1970s. Gardner later attributed Geschwind’s insights to be

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some of the most influential in his theories of learning, including that of multiple intelligences (personal conversation H. Gardner, 30 March 2019). The role of context and society in individual learning was furthered by Canadian American Albert Bandura who established “social learning theory” in 1977 based on work done earlier by Neil Miller and John Dollard (1946), Julian Rotter (1954), and most particularly Noam Chomsky, who refuted B.F. Skinner’s earlier work on conditioning as ignoring the important role of social interaction (Chomsky, 1959). Bandura and Chomsky put the spotlight back on “the whole child” and on the inadequacies of educational research which mainly depended on psychological laboratory techniques that measured just one variable at a time, while people, he argued, were always influenced by dozens if not hundreds of stimuli during social interactions, such as contact in a classroom. Bandura contributed by putting forth the idea that children learn through symbolic models with others that shape their behaviour. Bandura’s contributions extended into the transdisciplinary debate. According to Bandura (1989, 10) “thoughts are brain processes rather than separate psychic entities [but this does not mean that] psychological laws regarding cognitive functioning must be reduced to neurophysiological ones.” Rather, he believed, there was a dynamic process that permitted the individual actor to use the influence of their environment in both positive and negative ways that interacted to modify their learning outcomes in unique ways. Bandura’s ideas gave a microphone to earlier iterations of radical constructivism, first placed on the academic stage by Ernst von Glaserfeld in 1974. Von Glaserfeld, a Professor at the University of Georgia, used Piaget’s constructivist views as a scaffold for his vision of the dynamic cyclical process of experience combined with individual memory and reflection that results in new learning, which occurs in a never-ending iterative cycle. Von Glaserfeld’s ideas would lay the foundation of radical neuroconstructivism proposed by Tokuhama-Espinosa in 2019. Radical neuroconstructivism builds neural networks based on the constant exchange of the individual with stimuli, including others in the environment as well as one’s own prior experiences with the new learning content. The uniquely human process of interacting with the environment to change learning outcomes was contrasted with discoveries in neuroscience on animals. In 1958, Mark R. Rosenzweig and colleagues at the University of California at Berkeley published results of rat experiments that opened a new line of investigation related to the neurobiological basis for behaviour and the influence of “enriched” environments (Krech et al., 1962). Some rats in cages were given “toys” like running wheels, while others were given a bare environment. Unsurprisingly, when sacrificed, the rats’ brains with

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stimulation had more neural connections than those left in the less exciting environments. These earlier works were mistakenly seen as a defence for early stimulation classes for infants, when they were actually a condemnation of poor or deprived environments, such as those experienced by children living in poverty. Six years later, Marian Diamond and colleagues (1964), also at Berkeley, published their study which showed that exposure to “enriched” experiences changed the dendritic arborization and functional connectivity of brain cell networks in rats. Building off on Diamond’s work, William Greenough explored the plasticity of the brain or brain capacity to change with experience (Tokuhama-Espinosa, 2011). All these findings fed into the fervour for early childhood stimulation, which some took to mean cueing infants with flashcards to improve their vocabulary, despite the research being conducted on rats, not children. Roger Sperry (1968), a postdoctoral student of Lashley’s at Harvard and later professor at Cal Tech added more evidence for the plasticity of the brain. Likely informed, and perhaps even inspired, by Geschwind’s earlier work, he started his initial split-brain research to reduce the severity of epileptic seizures, which eventually led to a Nobel Prize in Medicine/Physiology in 1981 shared with David H. Hubel and Torsten N. Wiesel. His research demonstrated some degree of lateralization of function across the cerebral hemispheres, leading once again to the popular press suggestions that certain skill sets were in different halves of the brain and fuelling the “right-brain/left-brain” myth. Unfortunately, research on individuals with a single hemisphere who lived normal lives (e.g., Battro, 2006; Boatman et al., 1999) was not enough to keep the myth out of the popular press and belief in hemisphere “types” – right-brained people being creative and left-brained people being logical – still existed in the 2020s. Others understood that the new information about conditions under which the brain learns best could and should be more integrated with neurophysiological findings, leading some like William H. Gaddes (1968) to discuss the necessity and possibility of taking neuropsychological approaches to learning disorders. These foundational studies led to an avalanche of new hypotheses about learning and the brain, not only about where and how learning occurred in the brain, but when. These findings motivated Herman Epstein (1974a; 1974b, 1976) to proclaim that brain development occurs in spurts, and to hypothesize that these spurts in brain development are functionally related to the surges in mental growth, promoting a belief in critical periods for learning. McCall and colleagues (1988, 1990) reviewed and reanalysed the mental performance growth data from the several studies that Epstein (1974b) had cited in support of his theory and found that few data existed to demonstrate brain growth periodization related to practical mental and

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educational skills and performance in the same individual children, dismissing the idea of critical periods. Unfortunately, this analysis came too late for many who had already jumped on the critical period bandwagon that promoted this myth. There were still believers in this myth in the early 2000s thanks to textbooks that continued to reference critical periods for learning, though most have changed this to sensitive periods (TokuhamaEspinosa, 2018). At the same time, Project Zero, a research and development organization, was founded by the noted philosopher Nelson Goodman at the Harvard Graduate School of Education in 1967. The organization was created to develop an understanding of learning in and through the arts. David Perkins, Howard Gardner, Steve Seidel, Shari Tishman and Daniel Wilson have led the project for more than 50 years. Perkins and Gardner co-directed Project Zero for nearly 30 years and both were still actively involved into retirement (Alvarado, 2017). Three important works were published in the 1970s and 1980s that set in motion the formal move toward Mind, Brain, and Education science. In 1978, Jeanne Chall and Allan W. Mirsky edited the 77th Yearbook, Part II, of the United States National Society for the Study of Education dedicated to Education and the Brain. The book chapters were written by the noted neuroscientists interested in education including Timothy Teyler, M. C. Wittrock, Sebastian Grossman, Kenneth Heilman, Marcel Kinsbourne, Merrill Hiscock, Martha Denckla, Rita Rudel, and Paul MacLean, luminaries in what was then thought to be the cutting edge of understanding learning, and who can now be considered the forefathers and mothers of Mind, Brain, and Education science. The final chapter of the Yearbook by the editors, Chall and Mirsky, presented educational implications of the chapters’ themes of the volume. They intelligently cautioned educators of simplistic notions of brain development and hemisphericity or the idea that the two hemispheres controlled different behaviours. A second book titled Brain Research and Learning was published by the National United States Education Association (Claycomb, 1978), ushering in a new era of robust research specifically aimed at explaining childhood learning and at summarizing the implications of current research on the brain for educators. A third key publication came out just three years later in October 1981. Ron Brandt, the executive editor of Educational Leadership brought together Robert Sylwester, Jeanne S. Chall, M. C. Wittrock and Leslie A. Hart to present their perspectives on the possible educational implications to be gleaned from recent brain research. These three ground-breaking publications can be considered the Magna Carta or founding documents of what was to become Mind, Brain, and Education science, as they were the first to explore

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the outer boundaries of in-class implications of brain science on teaching practices. While the implications of neuroscience on teaching filled these books, and the psychological implications had already proceeded then, in parallel there was a new phenomenon of neuroscience exploring the implications of educational and socialization on development. The interdisciplinary field of cognitive science, a term coined by George Miller and Michael Gazzaniga (a student of Roger Sperry’s) in 1976 to designate the interface of system neuroscience, computational neuroscience, and cognitive psychology (Bruer, 2009), appeared in the curricula of colleges and universities and introduced in professional journals of the latter half of the 20th century. The birth of cognitive neuroscience as a field was followed by books such as The Handbook of Cognitive Neuroscience (Gazzaniga, 1984), which catalysed researchers’ motivation to focus on the contribution of neurosciences that would lead to a better understanding of learning. Sara Friedman, Kenneth Klivington and Rita Peterson’s 1986 book, The Brain, Cognition and Education, brought together neuroscientists, computer scientists, psychologists, and, refreshingly, educational researchers, to direct attention to the evolution of ideas about attention, knowledge acquisition and representation, cognitive and neural development (Friedman et al., 1986). In 1979, Elliot Eisner was invited by the John Dewey Society to give the John Dewey Lecture resulting, in 1982, in the publishing of the book titled Cognition and Curriculum: A Basis for Deciding What to Teach. It was revisited and developed in 1994 with the revised title of Cognition and Curriculum Reconsidered. In this book, Eisner argues that the separation of the mind from the body, a separation initiated by Plato and given a strong forward thrust by Descartes, has contributed to a narrow conception of cognition. According to Eisner, this problem stands out more clearly than when cognition is contrasted with affect. Affect is supposed to deal with feeling and not with knowing, while cognition supposedly deals with knowing and not with feeling. To Eisner, cognition and emotion needed to be discussed as a single system, not divided as neuroscientific laboratory studies had done in the past as such a narrow view of cognition legitimates a form of educational practice that limits what children have the opportunity to learn in school. He concluded that affect and cognition are not independent processes; nor are they processes that can be separated. There can be no affective activity without cognition; similarly, there can be no cognitive activity that is not also affective (Eisner, 1994b). The idea unifying social emotional awareness with cognition and mentalizing was further developed in the 2000s as the ways people come to know themselves best by reconciliating the thinking and feeling aspects of their being (Luyten and Fonagy, 2015; Immordino-Yang, 2019).

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Eisner supported Dewey’s constructivist idea (1938) that a human’s ability to know is based on the ability to build meaning from experiences. Eisner further argues that, while our sensory system is regarded as of marginal importance in human cognition, he shared Aristotle’s view that the senses are our primary information intake systems and provide the content through which our conceptual life takes form, an idea echoing von Glaserfeld’s first nod to radical constructivism. This means concepts initiate in the forms of experience that the visual, gustatory, olfactory, tactile, and auditory senses make possible. But concepts, regardless of the sensory form they take, are personal aspects of human experience, and although they might provide illumination for those who have them, they are private and cannot be shared until they are made public. As scholars would eventually agree 50 years later, all new learning passes through the filter of prior experience, and each lived experience is unique to the individual (Tokuhama-Espinosa, et al., 2020). The concepts are transformed and made public through a variety of forms of representation available in the culture. This public status might take the form of cultural artifacts such as words, pictures, music, mathematics, dance, and the like. Each of these forms makes it possible for individuals to both construct and experience particular kinds of meanings, Eisner suggested. Hence, students need to acquire different kinds of literacies or ways of knowing to construe meanings from these forms of representation. Accordingly, school programs should provide ample opportunity for children to become “literate” in a wide variety of forms as this will increase their meaning-making possibilities (Eisner, 1994b). This is an idea that resonated strongly with those seeking out “culturally responsive pedagogies” in the late 1990s (e.g., Ladson-Billings, 1992) who argued that current educational structures did not value or give voice to marginalized or minority populations. Eisner (1994a) acknowledges that many of the issues that he identified are closely related to Gardner’s (1983) work on multiple intelligences. However, their works have important differences. Gardner was interested in the developmental features of each of seven types of intelligence (an eighth added in 1995) and in the characteristics of the cultures that encourage the development of each. Eisner was concerned with matters of meaning and with the different kinds of meaning that different forms of representation make possible. According to Eisner, “the process of education itself has to do with the creation of mind. Mind, unlike brain, which is a biological given, is a form of cultural achievement. Schools are cultures. They are cultures for creating minds. Thus, the presence of different forms of representation is a presence that activates, develops, and refines mind” (Eisner, 1994a, x). However, Eisner’s work around cognition and education has become a

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significant reference point in debates around the design and evaluation of curriculum programs based on a cognitive pluralist perspective. The cognitive pluralists’ perspective highlights the idea that the school curriculum should foster multiple literacies in students by affording them the opportunities to learn and communicate their understandings through various forms of representation (Eisner, 1994a). Zaretta Hammond’s Culturally Responsive Teaching and the Brain (2014) was instrumental in linking the cultural debate with the MBE movement and was ahead of its time in offering a path for the integration of differentiation and inclusion within the MBE structure. Along with Eisner’s work, Leslie Hart’s Human Brain, Human Learning (1983) and Howard Gardner’s Frames of Mind (1983) were also milestones in educational theory in that they sparked a new interest among teachers in the connection between learning and the brain (Tokuhama-Espinosa, 2008; 2010). Gardner’s theory of multiple intelligences (1983) argued that teaching should adapt to individual differences. While controversial in neuroscience as the mapping of all the intelligences has proved yet illusive (Shearer et al., 2017), multiple intelligence theory drew a renewed interest in the uniqueness of the human brain and the need for educational practices to respond on a more personalized level. While acknowledging that human brains are more alike than they are different from one another, Gardner showed that a human’s individual life experiences did alter neural pathways that could change learning outcomes. This served as an important reminder that the sheer array of human experiences can alter the brain, but that within school parameters we often prize only a handful of those many experiences, namely those related to language and mathematical abilities. Gardner himself was a strong proponent of transdisciplinary thinking and of nurturing human potential in as many forms as possible and he was inspired by his mentor, Geschwind’s work in rehabilitating brains using a newfound understanding of neuroplasticity in therapeutic contexts. If people with brain lesions could learn to speak again through therapy, why couldn’t teachers change brains in classrooms through good instructional practice? Howard Gardner was also one of the original members of the International Mind, Brain, and Education Society founded in 2007. The other Founding Members of IMBES were: Kurt Fisher (USA), David Daniel (USA), Antonio Battro (Argentina), Usha Goswami (UK), Hideaki Koizumi (Japan), Juliana Paré-Blagoev (USA), Donna Coch (USA). The Advisors to the Board were: Daniel Cardinali (Argentina), Antonio Damasio (PortugalUSA), Kevin Dunbar (USA), John Gabrieli (USA), Tami Katzir (Israel), Kenneth Kosik (USA), Pierre Léna (France), Bruce McCandliss (USA), Laura-Ann Petitto (USA), David Rose (USA), Ann Rosenfeld (USA), Courtney Ross (USA), Manfred Spitzer (German), Paul van Geert (The

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Netherlands), Maryanne Wolf (USA), Namhee Wu (China).While most research in education, neuroscience and psychology was being published in journals from the US and Europe, IMBES founders wanted its membership to be global. The international aspect of the field showed a deep appreciation for a newly emerging field of cultural neuroscience which acknowledged the impact of cultural artifacts, like writing, on neural structures. This also opened a whole new sub-field of research in which cultural influences on learning could be compared with systems common to all humans. To explicitly show respect for this kind of research and to balance the world influence on new studies, IMBES chose that the second President of the organization after founder Kurt Fischer, would be Antonio Damasio, from Argentina. The second IMBES conference took place in China, and after being held in the US for four years, moved to Ecuador in 2013. After American Marc Schwartz’s presidency, Daniel Ansari, a Turkish-German Canadian took the helm, and a conference was held in Chile (2014). After Ansari, Mary Helen Immordino-Yang, followed by Nora Newcombe, both American women, were succeeded in 2024 by Bert DeSmedt from Belgium. It has been a goal of IMBES to try and balance the leadership between world representations and gender ever since. The transdisciplinary nature of MBE was reflected in the mission statements of many new organizations in the 1980s including the Economic and Social Research Council (ESRC) (United Kingdom [UK]) and the Medical Research Council (MRC) (UK) (Tokuhama-Espinosa, 2008). The first dissertation on neuroeducation, a close relative of MBE science, was written in 1981 (Odell, 1981), entitled Neuroeducation: Brain Compatible Learning Strategies and neuroeducation as a concept was first proposed by Cruickshank (1981) to introduce the application of knowledge about the brain to teacher education. Consequently, four years later, Jocelyn K. Fuller and James G. Glendening (1985) used the term “neuroeducator” to explain the need to train a new group of future professionals with expertise in both education and neuroscience capable of translating neuroscience research to educational platforms. In 1988, Gerhard Preiss published Neurodidáctica (neuropedagogy) and proposed creating a new discipline that would combine the study of brain processes with that of pedagogy to optimize human learning (Ferrari and McBride, 2011). The 1980s and 1990s served to call teachers closer to a scientific understanding of learning, but while new discoveries were being made about the human brain and learning, few teachers were privy to the information. At this time almost no teacher education programs offered any courses about the brain and human learning. Many US institutions in the 1990s were headed in a very different direction and taught teachers lesson

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planning and evaluations through standards-based testing. The knowledge from the Decade of the Brain took time to filter down to teachers, and in the meantime, several popular press authors tried to fill the growing gap between what teachers wanted to know about the brain, and the highly technical body of information that was being produced by neuroscientists (Tokuhama-Espinosa, 2008). Renate Caine and Geoffrey Caine (1991) published a popular book introducing the educational implications of brain research which has wildly considered by educators throughout the world and translated into several languages. Robert Sylwester (1995) also published a book aimed at providing educators with an introduction to the scientific understanding of the human brain and its processes. Eric Jensen’s book: Teaching with the Brain in Mind published in 1998, motivated many teachers to apply brain research in their classroom and sold to the thousands. Several of these books were later criticized by members of the International Mind, Brain, and Education Society who sought to safeguard the evidencebased standards of neuroscience being applied in education (TokuhamaEspinosa, 2008). While teachers were thirsty for more knowledge about the brain and learning, the supply was not always of high quality. Mixed among the contributing publications that launched the new discipline of Mind, Brain, and Education science, there were, unfortunately, also less serious publications and many opportunists who jumped on the bandwagon of “brain-based learning” to sell products. Critics of the terms “brain-based teaching” and “brain-based learning” considered their use to be a gimmick to promote self-serving work and went so far as to publicly explain that all learning is brain-brain based (Gardner, 1991). Paul Dennison and Gail Dennison’s book titled Brain Gym: Simple Activities for Whole Brain Learning was one such highly criticized programs. The book and accompanying classes organized in a pyramid scheme (in which people who took the class could then be certified as teachers within the program) guided parents and educators through the concept of “whole-brain learning” through movement “repatterning” and “brain gym activities” which they claimed enabled students to access those parts of the brain “previously unavailable” for them (Dennison and Dennison, 1986). While highly motivational and an impetus for parent involvement in early childhood learning, Brain Gym is now understood to be a neuromyth, or a claim about the brain and learning that was never been substantiated by research and which was promoted using self-published studies. Longitudinal studies now show there is no difference between kids who did Brain Gym and those who did not (Goswami, 2007). This example was a wake-up call to brain enthusiasts in education: Not everything promised about the brain and learning is supported by evidence. The early 1990s were host to a proliferation

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of misconceptions about the neuroscience of learning and commercial programs under the heading of “brain-based education”. This led the Organisation for Economic and Cultural Development (OECD), the International Mind, Brain, and Education Society and the Special Interest Groups of the American Educational Research Association to identify the need to debunk neuromyths as a priority within teacher education programs and within the public at large. The OECD (2007) took the initiative to call out false claims by the media and the promotion of neuromyths by making a monthly list of false headlines related to the brain and offering an explanation of the real science behind the misleading promises. It was not until 2018, however, that a complete catalogue of over 70 neuromyths commonly embraced by teachers was finally published (Tokuhama-Espinosa, 2018). As interest in the brain grew in the public, the United States declared the 1990s the Decade of the Brain. This announcement was accompanied by new funding and investment in the learning sciences as a whole, and in technology in particular. The advancement of new brain-imaging techniques (including refined functional Magnetic Resonance Imaging [fMRI]) profoundly influenced scholars to think about the practical applications of brain research for educational policy and practice. There were nearly 20,000 peer-reviewed articles published between 1990 and 2000 that used MRI or fMRI scans to measure some element of learning. Not all these studies focused on human learning, however. In fact, only a handful of studies during this time used human subjects, and even fewer were conducted on school-aged children. The lack of evidence directly gathered from school-aged children, along with the promotion of neuromyths prompted a new caution about the true utility of neuroscience research and teaching (Matejko and Ansari, 2015). The speed of change, the proliferation of “brain-based” commercial ventures and the inconclusive results comparing different units of analysis (brain cells to classrooms, for example), led some critics, including John Bruer (1997), to argue that neuroscience has nothing to offer the field of education. Bruer suggested that the relationship between brain science and education was made at a superficial level. He argued that the very different units of analysis – neurons and chemicals in the case of neuroscience, and children in classrooms in the case of education – were too distant to truly be comparable and suggested that cognitive psychology as a field and studies on consciousness were the best links to bridge the gap between neuroscience and education. The link between educational psychology, and between psychology and neuroscience were indisputable but linking education directly to neuroscience was problematic in Bruer’s view, which was

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reflective of many in cognitive neuroscience at the time (personal conversation with K. Hirsch-Pasek, 11 September 2019). While seemingly drawing a line in the sand with his article “A Bridge Too Far” (1997), Bruer’s article was one of the main motivators for many researchers to identify more formalized links between the fields of neuroscience, education and (cognitive) psychology. Whereas individual researchers such as Piaget, Vygotsky, Bruner, Bruer, Bandura and Ausubel led the 1950s–1970s vision, and teacherinspired publications drove the 1980s, institutional initiatives led the 1990s. The Brain, Neurosciences, and Education Special Interest Group (SIG) of the American Educational Research Association (AERA) was formed in 1988. This SIG of the AERA was originally formed as the Psychophysiology and Education SIG and is the oldest organizational entity specifically dedicated to linking research in the neurosciences and education in the United States (Tokuhama-Espinosa, 2010). By 1990, its membership had grown into the hundreds. In the late 1990s, many formal associations were launched around the emerging discipline of MBE to try and put parameters on quality-control questions related to research, policy, and teaching. At the institutional level, The Japan Neuroscience Society, the Centre for Neuroscience at Flinders University and the Australian Neuroscience Society were three pioneering neuroscience societies that were formalized in the late 1970s. These societies promoted new findings about the brain that were fuelled by growing information from improved imaging techniques (TokuhamaEspinosa, 2010). The workshop “Bridging the Gap between Education and Neuroscience” was held in Denver, Colorado on July 26–28, 1996. The workshop was cosponsored by the Education Commission of the States (ECS) and supported by a grant from the Dana Foundation. A group of 74 neuroscientists, cognitive psychologists, educators, policymakers, and practitioners brought together to explore the possible relevance of recent development in neuroscience and cognitive psychology to early childhood education and special education. Participants concluded that there is a chasm between what scientists accept as proven fact and what the public, teachers and policymakers believe as well as a similar chasm between what neuroscientists can measure and the complexities of human learning. The meeting was structured to foster communication and influence policymaking, by creating incentives and requirements for schools of education to understand, research and expand early childhood education (Education Commission of the States, 1996). The first “Learning and the Brain Conference” took place on the Harvard University and MIT campuses in 1997 and sought to elevate the calibre of teacher-neuroscientist encounters. In 1999, the first Learning Brain EXPO in San Diego gathered over 700 teachers and scientists, attesting to the

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popularity of anything labelled “brain-based” learning at the time (Tokuhama-Espinosa, 2010). The growth of the field of cognitive neuroscience, the gauntlet laid down by John Bruer to bridge the fields, massive advancements in technology, and a growing desire by teachers and teacher organizations all contributed to the final push in the birth of a new learning sciences sub-discipline: Mind, Brain, and Education science. Due to the demand from knowledge-hungry teachers and more refined research techniques within lab school environments such as the Queensland Brain Institute, which observed real children in real time doing real classroom learning and then analysed a myriad of data to reach inferences about brain functioning, the seeds were planted for the birth of Mind, Brain, and Education in the early 2000s.

CHAPTER 4 THE DIGITAL AGE (2000–2010): PROGRAMS IN MIND, BRAIN, AND EDUCATION

Academic programs that included brain sciences for teachers began to grow at the turn of the century. Columbia University Teachers College’s Neuroscience and Education program “was the first graduate program in the United States and Internationally to offer multidisciplinary training focused on the intersections of neuroscience and education,” and did so in the late 1990s (Teachers College, 2022, 1). After several years of planning (1997–2001), Harvard University launched its Master’s Program in Mind, Brain, and Education in 2001–2002 (Tokuhama-Espinosa, 2008). The MBE program was founded by the Graduate School of Education to prepare a new generation of researchers able to operate at the interface between neuroscience, cognitive science, and education. In 2021 it reverted to more traditional label of Human Development, though the courses remained. At around the same time, the University of Cambridge’s Program in Psychology and Neuroscience in Education started in 2004, as did the Transfer Centre for Neuroscience and Learning in Ulm, Germany (2004), Bristol University’s Centre for Neuroscience and Education (2005), and the Learning Lab in Denmark (2005), which were all landmark beginnings in an attempt to structure the emerging discipline. Other programs available in MBE science by 2005 included those at the University of Texas at Arlington, the University of Southern California, Beijing Normal University, and Southeast University in Nanjing (Tokuhama-Espinosa, 2010). Doctoral, Master’s and certificate programs in Mind, Brain, and Teaching (e.g., Johns Hopkins University; Munich Centre for Neurosciences, Mind, and Brain) became more commonplace, as did more transdisciplinary coursework expanding cognitive neuroscience, psychological neuroscience, educational neuroscience, and neuropsychology programs (e.g., Stanford University, Cambridge Centre for Neuroscience and Education; Universitat Pompeu Fabra, Barcelona; University College of London). The first decade of the 21st century coincided with the development of a signi¿cant body of literature on the neuroscience of learning. The National

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Research Council and Division of Behavioral and Social Sciences and Education published How People Learn: Brain, Mind, Experience, and School in 2000, which was aimed at teachers and educational policy makers with the goal to ensure the brain played a bigger role in teacher formation. In 2002, the OECD had 30 member countries which published work to introduce a new science of learning that integrated neuroscience and psychology with educational practice. This included its broadly cited book Understanding the Brain: Towards a New Learning Science based on its survey of multiple countries in the process of introducing the brain to teacher education. At this time, Kurt Fischer and others extolled the value of neuroscience research in education and began to lay the formal groundwork for an independent discipline of MBE (Fischer, Daniel, Immordino-Yang, Stern, Battro and Koizumi, 2007) by establishing a journal, a society, and regular meetings by 2007. In 2008 the Mind, Brain, and Education journal was acknowledged by the Association of American Publishers as the best new journal based in part on the way the publication deftly broached complex topics which had not been treated in a transdisciplinary way before. David Daniel, the journal’s first Editor along with Kurt Fischer, managed to develop what is now acknowledged as a different scientific genre. New mediums in social communication united the general public’s interest in learning more about the brain. In 2006, the Brain Science Podcast by Dr. Ginger Campbell began audio interviews with neuroscientists which were free and downloadable to the public. By 2015 she recorded more than 7.5 million downloaded recordings, indicating a thirst by the general public for topics ranging from In Search of Memory (Nobel laureate Eric Kandel), The Future of the Brain (by Steven Rose) Neuroplasticity (by science writer Sharon Begley), to Reading and the Brain (with Maryanne Wolf). The sheer volume of information shared by authors and researchers in the learning sciences directly with the public marked a significant shift in the translation of scientific information for the non-specialized learner. Podcasts and other mediums like peer reviewed journal “community” pages in which articles were translated for the general public began to create bridges to public understanding directly from the scientists themselves, enhancing the definition of translational research to include those who could cull direct communication from novice to laypeople. Despite the ground-breaking creation of the International Mind, Brain, and Education Society, John Bruer remained sceptical about the direct implications of neuroscience for education (Bruer, 2006) until he began one-on-one interventions with Latin American school teachers to measure the impact of neuroscientific training in 2014 (see Bruer, 2014 for a review).

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The conversion of Bruer, one of the most sceptical voices initially, was a dramatic force in propelling newer and more complex initiatives to the forefront. For the first time research was not just a one-way street from neuroscience to education, but rather also used psychology and education to form new neuroscientific theories. For example, research in education also showed that teacher beliefs about how humans learn influences their instructional practices (Lunn Brownlee et al., 2017), which in turn, influence a learner’s self-efficacy about their ability to learn (Johnston et al., 2001), and by extension, learning outcomes (Hattie, 2008). This research offered additional bridges from proven educational practices to neuroscience. Betts and colleagues (2019) established that professional development programs and journal reading in the learning sciences, specifically MBE, also improved teacher knowledge about evidence-based practice as well as knowledge about neuromyths. Rather than focus solely on new teacher formation, these exciting findings pointed to initiatives teachers could do as practicing professionals. To support K-12 teachers who were already in the classroom with high quality information from neuroscience, other initiatives arose. Janet Dubinsky began an innovative program to teach neuroscience to pre-kindergarten–Grade 12 teachers at the University of Minnesota in 2010 called BrainU with similar positive results. Dubinsky, along with colleagues Sashank Varma and Gillian Roehrig discovered that teaching teachers about neurobiology, specifically about brain plasticity, improved their instructional practices. Their unique BrainU structure included units on eight “Neuroscience Core Concepts” from the Society for Neuroscience (2008), which were used to “inform teaching and learning”, indicating that collaborative research between educators, neuroscientists, and psychologists could yield better learning outcomes for students (Dubinsky et al., 2013). Dubinsky later acknowledged, however, that this kind of training improves the knowledge base of teachers, but some of their long-held neuromythical beliefs might remain. As new research began to snowball and more children became involved in neuroscience studies, there was a growing concern about neuroethics (Tokuhama-Espinosa, 2008). In May 2002, the conference on “Neuroethics: Mapping the Field” was held in San Francisco. This conference was sponsored by the Dana Foundation to bring together scholars in neuroscience, biomedical ethics, the humanities, lawyers, public policy makers, and representatives of the media. The participants discussed four major themes: “Brain Science and the Self”; “Brain Science and Social Policy”; “Ethics and the Practice of Brain Science,” and “Brain Science and Public Discourse” (Marcus, 2002). While the intentions were noble and the conference managed to stir concerns, it could not yet offer few answers to

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the problems raised. Should people be able to use cognitive enhancers, or is this cheating? Should studies in cultural neuroscience that exploit innate bias based on race be funded? Should teenagers be let off for murder because their frontal lobes aren’t fully developed? Should young children use technology? The lack of definitive answers indicated that scientific advances were occurring much faster than policy measures could be developed. Some national bodies tried to respond to these new challenges by creating regulators to review these issues. For example, the “Brain and Learning Committee” was formed by the Organization for Scienti¿c Research in collaboration with the Netherlands’ Ministry of Education, Culture and Science in 2003. This committee organized an invitational conference on the international debate on “Brain, Learning and Education” in 2004, which led to a published report entitled Brain Lessons (Jolles et al., 2006). The first International Mind, Brain, and Education Society conference was held in 2007 and brought together an impressive line-up of speakers, including Kurt Fischer, Howard Gardner, Antonio Damasio, Mary Helen Immordino-Yang, and included participants from Holland, China, Japan, and Argentina as well as throughout the United States. Beyond information dissemination, the conference served to enhance communication between neuroscientists, psychologists, and educational researchers to achieve a common language for future research questions and to translate research into concrete educational applications (Tokuhama-Espinosa, 2008, 2010). In 2007, a group of scientists from around the world drafted the Santiago Declaration (now known as the Santiago Protocol), which became a focal point for the discussion of evidence-based educational practice. The Protocol summarized knowledge about child development and early learning, the benefits of embedding learning in meaningful social contexts, the importance of active rather than passive learning, the need for sensitive and responsive environments, and the need to instil concern about how, not just what, children learn (Hirsh-Pasek and Bruer, 2007). The initial signatories included Kathy Hirsh Pasek (Professor, Temple University), John Bruer (President, McDonnell Foundation), Patricia Kuhl (Professor, University of Washington), Susan Goldin-Meadow (Professor, University of Chicago), Elsbeth Stern (Senior Scientist, ETH Zurich Institute for Behavioral Sciences), Nuria Sebastian Galles (Professor, University de Barcelona), Albert Galaburda (Professor, Harvard Medical School, Boston), Marcella Pena (Professor, Catholic University of Chile), Laura Martignon (Professor, University of Education, Ludwigsburg), Ruth Campbell (Professor, University College London), Gerd Gigerenzer (Professor, Max Planck Institute for Human Development), Albert Rizzo (Research Scientist

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and Professor, University of Southern California), Elke Kurz-Milcke (Senior Researcher, Padagogische Hochschule Ludwigsburg) Bert DeSmedt (University of Leuven, Belgium), and Manuel Carreiras (Universidad de la Laguna, Spain). In 2008, an international Delphi panel of 20 experts from MBE and its sub-fields sought to create a framework for standards in MBE. The Scientifically Substantiated Art of Teaching: A Study in the Development of Standards in the Academic Field of Neuroeducation (Mind, Brain, and Education Science) (Tokuhama-Espinosa, 2008) brought many key questions from the backburner into the spotlight, most importantly, what were the research, practice, and policy goals of MBE? The experts debated these questions and more, resulting in a suggested list of Principles (things that are backed with significant evidence and appear to apply to all human brains, and which should be taught to teachers), Tenets (things that are supported by evidence, but which include a wide range of human variance) and Neuromyths (information that lacks evidence and is therefore rejected).The research, practice, and policy goals of MBE were scrutinized for a second time in 2017, and a third in 2020 and their current wording can be found in Appendix A. Other initiatives grew out of the worldwide movement to unify work from neuroscience, psychology, and education to explain learning. Having established MBE’s value to the educational process, the field began to focus on domain-specific influences. Work on the reading brain (e.g., Wolf, 2007), the math brain (e.g., Dehaene, 2011) complemented general texts for educators, such as Virginia Berninger and colleagues’ Brain Literacy for Educators and Psychologists (2002). The conference on “Learning, Arts, and the Brain” was held at Johns Hopkins in 2009 with the aim to bring together researchers who were eager to share their findings related to the link between arts and learning and identify areas of interest for future research (Hardiman et al., 2009). Many of these earlier initiatives were criticized, however, for continuing to make teachers the recipients of knowledge from neuroscience, rather than partners in research. The need for greater mutually beneficial research rose to a head by the first decade of the 21st century as neuroscience findings paralleled new advances in education, such as whole-child learning initiatives (Perkins, 2003), the promotion of Habits of Mind (Costa and Kallick, 2008) and a better understanding of growth Mindsets (Dweck, 2006), but without a clear coordinated effort among neuroscientists, psychologists, and educators. Despite telling similar stories–for example, that neuroplasticity explains why growth mindsets work–few translators were connecting the dots between research methods in the different learning sciences. Some notable exceptions (as Bruer

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predicted) were psychologists, such as Daniel Willingham to bridge neuroscience to education through psychology. The Internet, already decades old by the early 2000s, only became a functional tool for the average user with the advent of smart phones (19922010) and broader connectivity. People who had once relied on library visits, lectures by experts and books which often spent years in production, now had easy access to up-to-date information at their fingertips. More and more individuals became “brain savvy” (Hruby, 2013) as both scientific studies began to be published online, and as community initiatives and sharing sped up the transfer of knowledge from specialists to the general public through websites, podcasts and instant messaging. Some researchers from neuroscience began to extend invitations to the general public to use “brain training” software which took advantage of the Internet to provide gaming tools to improve certain areas of cognition like attention and memory. Some, such as BrainHQ (Posit Science) by Michael Merzenich, became well established and boasted “More than 100 published scientific papers show the benefits of BrainHQ exercises and assessments” according to their website (www.brainhq.com). These initiatives spread the use of information about the brain and protective factors for cognitive ageing, for example, to audiences who before knew little of the brain, but who were concerned about general well-being. This broadening of interest in the brain, and the practical applications promised by promoters increased public awareness of the brain and learning. Technology continued to change the information landscape, and along with it permitted laypeople greater access to information and scientists to greater collaboration possibilities. The Human Connectome Project (HCP), a US National Institutes of Health initiative, launched in 2009 to “construct a map of the complete structural and functional neural connections in vivo within and across individuals” (HCP, 2019, para.1) not only financed important international studies but the general public was also given a new view of the complexity of human thinking through the publicly available access to its findings (Elam et al., 2019; Van Essen et al., 2013 ). The Project included two primary teams (Washington University-University of Minnesota-Oxford University; Harvard University-Mass General Hospital-University of California at Los Angeles), and researchers from dozens of other institutions, including UC Berkeley, St. Louis University, Indiana University, D’Annunzio University in Italy, Warwick University in the UK, and Ernst Strungmann Institute in Germany. The HCP undertook a systematic effort to map macroscopic human brain circuits and their relationship to behaviour in a large population of healthy humans (Van Essen et al., 2013). By combining already existing neuroimaging tools into

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new, unified visual images, the Connectome created colourful, detailed neural circuitry maps that told the visual story of reading problems, how arithmetic is processed in healthy brains, and hundreds of other cognitive skills and sub-skills (e.g., Leergaard et al., 2012; Janssen et al., 2021) before invisible to the naked eye and inaccessible to the common person. The findings were made popular by a book made for the public called Connectome: How the Brain’s Wiring Makes Us Who We Are (Seung, 2012). In February 2011, an entire issue of Educational Philosophy and Theory was devoted to recent issues and initiatives in Educational Neuroscience. One year later, in January 2012, the first bilingual issue of the Neuroeducation journal was published by the Association for Neuroeducation Research in collaboration with the Université du Québec à Montréal (UQAM). Steve Masson, the editor of the journal introduced it as a bilingual (English and French) journal to facilitate the further development of the new field of Neuroeducation by providing a place for researchers to evaluate and share new knowledge (Masson, 2012). While there were multiple monumental milestones during the first decade of the 21st century for Mind, Brain, and Education science, perhaps the subtlest yet most significant was related to research. For an academic field to thrive, it must have a society, regular conferences, and a journal to measure the quality of new research (Tokuhama-Espinosa, 2008). The type of research coming out of IMBES from 2007 to 2010 established a transdisciplinary, international, and translational trend never before seen in science. For example, the Mind, Brain, and Education journal’s special issues on language, math, motivation and emotion–all approached with a transdisciplinary understanding of how the mind and brain interacted to influence educational initiatives–suggested a different way of approaching research. This, in turn, forced a parsing of research skills in the new MBE discipline. A Delphi panel of experts on Mind, Brain, and Education standards and practices suggested that researchers could be classified into three groups. There were “original” researchers (who posed new ideas, such as those related to math neural networks as seen in Stanislas Dehaene’s work), “collaborative” researchers (such as work done by Janet Dubinsky who joined neuroscientists with teachers and children to develop learning theories) and “translational” researchers, dedicated to helping people understand each other across disciplines (such as that done by Daniel Willingham, a psychologist who helps neuroscientists and teachers understand one another) (Tokuhama-Espinosa, 2017). In 2014, IMBES created an award to recognize and celebrate contributions to translational and transdisciplinary research.

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The first decade of the 21st century can be seen in many ways as the birth of an academic discipline after centuries of gestation. The formalization of the discipline with the creation of new academic programs, the establishment of international conferences hosted by a formal society, and the creation of a journal that sought to celebrate a new scientific genre using transdisciplinary thinking that was shared through translational research all confirmed the arrival of Mind, Brain, and Education science on to the world stage and carved a distinct niche in policy, practice, and research. This academic space was not guaranteed, however, and the second decade of the 21st century brought both typical and atypical challenge. Typically, new movements need establish wider membership, eke out a space in public policy discussions, and encourage more research. Atypically, MBE faces challenges due to its non-traditional tripart design (mind-brain-education). Most important of these challenges were the debates about the “turf wars” with the emerging field of Educational Neuroscience. Also important was that neuroethics continued to be in the spotlight. A new area, itself a hybrid of bioethics, medical ethics and education called educational neuroethics, grew in response to the increasing number of challenges being faced by teachers and schools related to information about the brain (Hardiman et al., 2012; Lalancette and Campbell, 2012; Zocchi and Pollack, 2013). Should (imperfect) neuroimaging techniques be admissible as evidence of learning deficits? Should controversial studies about gender differences in brain structure be shared with the general public (even if they resulted in no difference in academic performance)? Should commercial products that promise “brain training” be purchased by schools? The Journal of Neuroethics dedicated a special issue to a discussion about these matters in August 2012. Governments also began to listen to the multiple promises as well as cautions being generated by MBE scholars. The Royal Society in the UK published Neuroscience: Implications for Education and Lifelong Learning to motivate MBE research beyond the childhood years, as well as to document the promises and possible perils of applying neuroscience to education. All in all, MBE arrived on the academic stage with a powerful presence. To continue its growth into the future, refinement of research and methodological processes became the focus of its second decade of existence, as will be explored in Part II.

II. CURRENT DIRECTIONS AND DEBATES

CHAPTER 5 RESEARCH IN MIND, BRAIN, AND EDUCATION: SOME METHODOLOGICAL CONSIDERATIONS

Debate and open discussions are key contributors to the development of science (Shilatifard, 2022). Given the transdisciplinary and translational nature of Mind, Brain, and Education science, since its founding there have been heated debates as to just what constitutes a research methodology in this discipline. Defining the nature and meaning of theory and theory building of a discipline are at the heart of defining a scientific discipline. The importance of these issues has already been discussed by leaders within IMBES. For instance, Immordino-Yang (2011) suggested that, For education to truly bene¿t from these neuroscienti¿c ¿ndings in a durable, deep way, for the full implications to become apparent, educators must examine closely the theory on which good practice is built, to reconcile the new and exciting evidence with established educational models and philosophies. (102)

One key debate was brought to light by the first Delphi panel in 2008 in which the core research question was whether MBE was the combination or the intersection of standards in Mind (psychology), Brain (neuroscience), and Education (Tokuhama-Espinosa, 2008). The evolution of MBE from a conceptual framework in the 1990s into a young discipline in 2019 illustrates similar trajectories in the history of science. This does not mean using MBE instead of, but rather in addition to, other disciplines. While celebrating new inroads made by professionals who have decided to work at the intersection of the fields, the historical evolution of the discipline suggests there is also the necessity for continued research in the parent fields of psychology, neuroscience, and education. For example, new neuroscientific knowledge about the specific neural underpinnings of decision-making (which itself is based on underpinnings in memory and affect-cognition) (e.g., Yau et al., 2020) is important and can inform psychology and education. However, it is equally important to consider additional studies that intentionally approach decision-making from a transdisciplinary

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perspective as they simultaneously interpret decision-making from a Mind, Brain, and Education science view (e.g., Meyer, 2021). The same suggestion can be made for domain area studies in math and language, as well as general cognitive abilities, such as memory, attention and executive functions, or characteristics beneficial to learning, such as motivation, metacognition, and social-emotional learning. In the simplest of evaluations, two primary camps exist when discussing the theoretical framework of the field. It should be noted, of course, that there are a lot of grey stances in between these two extremes, and that this is also a friendly rivalry as both camps appreciate and value the work of the other. The first camp is comprised of those who see MBE research as being an accumulative understanding of the research that comes from Neuroscience, Psychology, and Education of themes of common interest. The second are those who believe that “true” MBE research is conducted at the crossroads of the three parent disciplines and must necessarily involve practitioners trained in each of them. This chapter has three parts. First, we will clarify “transdisciplinary research” in the MBE context. Second, we will consider the existing research methodologies and topics in MBE by looking at a review of the MBE literature from 2007 to 2018. Finally, this chapter will look at what is needed of a professional in MBE science who is both a researcher and a practitioner.

Models of Disciplinary Research Figure 5-1 shows four models of research, all of which have contributed to MBE over its first decade. The first is of traditional, disciplinary thinking, where separate researchers investigate the (a) mind perspective, (b) the brain perspective, and the (c) education perspective. This unidisciplinary view is what existed before Mind, Brain, and Education science arrived onto the scene.

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Figure 5-1. Transdisciplinary Thinking

Source: Borja and Tokuhama-Espinosa, 2021, based in part on Darian-Smith and McCarthy, 2016

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This is followed by multi-disciplinary thinking in which the researchers may take information from each of the fields and try and develop coherent theories by uniting the information. This is what occurred in the early years of MBE when there were no professionals who worked in all the MBE parent fields. This accumulative model of research in MBE seeks out existing research on a topic of common interest to Neuroscience, Psychology, and Education, and then translates findings between them. For example, the topic of “Motivation” is studied in Neuroscience, Psychology, and Education separately. This presumes that MBE is a discipline that is nurtured by all learning sciences but with different levels of analysis. In this divided model, practitioners rarely work together, although they may use each other’s research. That is, a neuroscientist conducts their research in the laboratory, reports in their specialized journals (e.g., Trends in Neuroscience), attends their conferences (e.g., Society For Neuroscience), and may or may not use findings from the other learning scientists, in the same way, an educator would conduct their research in the classroom, report in their specialized journals (e.g., Educational Researcher), attend their conferences (e.g., American Educational Research Association), and may have little exposure to the other learning sciences. Psychologists would act in much the same way, conducting research in their settings, publishing in their journals (e.g., Psychological Review), and attending their conferences (e.g., American Psychological Association) but not necessarily refer to the work from the other learning sciences. This multidisciplinary lens is the least disruptive way to begin to use the MBE framework in research. This is followed by interdisciplinary thinking, in which research is used from the intersections of the disciplines (a) mind-brain, (b) braineducation, (c) education-mind to piece together a coherent understanding of a topic or problem. Interdisciplinary thinking does not only consider what the neuroscientist, psychologist, and educator think in their own spaces, publications, and gathering but would also extend into the “hyphenated fields” such as that of “neuro-education”. These hyphenations imply that two fields are bound, though one usually plays a subservient role as that of a sub-area of a dominant field. For example, in “neuro-psychology” neuroscience is a sub-area of psychology; in “educational-neuroscience” education is a sub-area of neuroscience; in “psycho-biology” psychology is a sub-field of biology, and so on. These compounded visions are generally superior to single disciplinary thinking because they take into consideration a broader range of evidence and ensure multiple disciplinary lenses. Hyphenated fields also invite a hierarchical understanding of the research and problem-solving, however, which generally prioritizes the

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dominant field’s vision. That is, when considering a problem of student motivation, for example, an educational psychologist will likely feel obliged to prioritize their psychological understanding of the problem, rather than the educational. Similarly, an educational neuroscientist is more likely to see education as the context for the application of neuroscientific findings, rather than as a potential variable in the problem itself. Despite these challenges, the interdisciplinary perspective shows many advantages over single disciplinary views, which often place scholarly boundaries on acceptable interventions. This means that many current researchers in MBE are often professionally trained in “neuro-psychology” (“psychobiology”), “neuro- education” (“educational neuroscience”), or “educational psychology” (“psycho-pedagogy”), but ensure their perspectives include and value the other interdisciplinary studies that can contribute to findings. Finally, some would argue that the best idea for problem solving would be to use transdisciplinary thinking in which the researcher habituates an approach to understanding in which both the intersection of sub-disciplines, as well as global intersection of all of the fields in considered. In figure 51, the transdisciplinary view values the research in each of the singular “parent” disciplines of (a) mind, (b) brain, and (c) education, plus the interdisciplinary intersections of (d) mind-brain, (e) brain-education, (f) education-mind, as well as the global intersection of (g) mind-brain-healtheducation (Figure 5-2). MBE has increased the space for transdisciplinary thinking, and for a great appreciation of problem resolution approached from multiple lenses. All problems in education ranging from topics as different as student motivation, or whether creativity can be taught, to learning how the brain learns to read, to how self-regulation is developed, can find more complete, long-term and transferable answers through transdisciplinary thinking (see Figure 5-3). As a transdisciplinary discipline itself, MBE serves as a constant reminder to educators that a habituated multi-pronged approach is a superior problem-solving strategy.

Research in Mind, Brain, and Education Figure 5-2. MBE as a Transdisciplinary Research Field

Source: Tokuhama-Espinosa, 2019. Used with permission of the author.

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Neuroscientific evidence [on Motivation] Psychological evidence [on Motivation]

Educational evidence [on Motivation]

MBE View [of Motivation]

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Figure 5-3 Accumulative Model of Mind, Brain, and Education Science

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While the conceptual framework of MBE leaves little doubt about the approach to research as a process, there is less clarity about MBE’s methodological tools.

A Summary of Topics and Methodologies 2007-2018 Research methods in MBE in the early years did not (and could not) respond to the call for transdisciplinary thinking due to limits in technology. The Mind, Brain, and Education journal was founded in 2007 to publish high-quality studies in all areas of the learning sciences. A document analysis was employed to examine the topics, the types of articles and the research methodology of published studies in the journal. All the issues of the first decade of the journal (2007 to 2018) were included in the analysis using a systematic procedure of review. First, the abstracts of articles were reviewed, and a rubric form was developed as the data collection tool. This rubric form consisted of pre-defined categories of topics and methods of research. Then, each article in every issue of the journal was analysed and the data were coded using the rubric. While analysing the articles, some new categories emerged, and these categories were added to the rubric and the analysis phase restarted. After finalizing the list of topics, frequencies for each category were calculated and recorded in the rubric. For the reliability and validity of the study, the coding of the data was carried out using a constant comparison procedure in which the researcher generates and connects categories by comparing incidents in the data to other incidents, incidents to categories, and categories to other categories (Creswell, 2015). The distribution of the articles published according to the topic is given in Table 5-1. As can be seen in Table 5-1, 21 different topics were published in Mind, Brain, and Education in this period. The most frequent topics were: (a) Learning and Development (n=28); (b) Social and Emotional Development (n=27); (c) Language and Literacy (n=27); (d) Research and Development (n=27); (e) The Nature of the Discipline (n=25); (f) Curriculum and Pedagogy (n=24); (g) Attention and Executive Control (n=23); The Relevance of Neuroscience to Education (n=21); and Mathematics Learning (n=21). The less frequent topics were: Learning Games (n=4); Nutrition and Learning (n=4); Physical Education (n=4); Embodied Cognition (n=3); and ICT and Pedagogy (n=2). The second section of categorization related to methodology, as seen in Table 5-2.

Chapter 5

The main Topics

Items

2 2

6

1 2

3

1

4

3

1

9

6

2

3

2

1

4

26 7

2009

1

1

31 3

19 3

Frequency The Nature of the Discipline The Relevance of Neuroscience to Education Genetics and Education Science Education Mathematics Learning Social and Emotional Development Language and Literacy Attention and Executive Control Learning Disabilities and Developmental Disorders Educational Chronobiology

2008

2007

Year of publication

1

3

4

2

23 1

2010

2

1

1

1

1

27 4

2011

4

3

4

7

3

31 2

2012

1

1

3

6

2

31

2013

8

1

1

1

1

25 1

2014

Table 5-1. Distribution of Articles Published in MBE Journal in Terms of Topics

58

1

2

1

1 7

1

1

31 2

2015

2

3

1

24 1

2016

1

2

5

4

5

22

2017

1

3

1

2

1 3

1

22 1

2018

16

13

23

27

27

6 21

11

21

312 25

Total

Learning and Development Curriculum and Pedagogy Educational Neuroethics Research and Development Criticizing Brainbased Learning and Neuromyths Neuroaesthetics and Learning Learning Games Embodied Cognition Nutrition and Learning ICT and Pedagogy Physical education

1

1

2 1

1

1

4

2 1

1

5

1

8

5

1

1

1

1

1

5

1

9

2

5 1

1

3

1

3

1

3

4

Research in Mind, Brain, and Education

1 1

3

5

2

3

2

1

1

4

9

1

3

1

1 1

1 1

1

2

1

1

2 4

4 3 4

10

9

27

8

24

28

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Methods and tools

Items

1

Quantitative survey research Longitudinal

Genetic measures Single subject Cross-cultural Correlational/ predictive Action research exploratory study Case study Behavioural and Electrophysiological

1 1

1

19 1

Frequency Experimental

Systematic literature review fMRIဨ and fieldဨ based observations fMRI

2007

Year of publication

1

1 1 1 3

3

1

31 1

2008

1 1 1 1

2

26 5

2009

1

1

1

3

1

23 2

2010

1

1

2

27 6

2011

3

3

1

1

2

2

31 2

2012

4

1

1

2

31 2

2013

2

1

2

1

2

25 1

2014

3

1

1

1

2

31 1

2015

Table 5-2. Distribution of Articles Published in MBE Journal in Terms of Research Methods

60

1

4

1

1

6

1

24 3

2016

1

1

2

1

3

22 9

2017

1 1

3

1

2

1

22

2018

4 1 7 7

2 2 1 21

7

4

26

7

10

312 33

Total

15

14

17

17

19

12

7

19

Not stated

13

1

1 17

4

2

2

1

1

1

1

156

2 9

1

2 1 2 1

1

1

1 1

1 3

3

2

1

1

1

1 3

1

Psychometric/ Measurement Eyeဨmovement study Mixed method Causal comparative Qualitative survey research Historical research Observational Classification fMRIဨ behavioural and eye-movement MEG

1

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The results showed that studies in MBE mostly employed experimental designs (n=33); systematic literature review (n=26); and correlational/predictive method (n=21). Only 12 of the total 312 studies employed fMRI studies, the most common neuroimaging used in neuroscientific studies, and just nine used other types of neuroimaging technology. Surprisingly, of the 312 studies, only 156 indicated any methodology at all, reinforcing the idea that methodological boundaries have been less defined in MBE than in other fields. This literature review suggests that the methodologies of Mind, Brain, and Education science might not have been as precise as in other journals as they were hostage to the technology of the times. This began to change in the 2010s.

Current and Future Directions for Research in MBE Tools determine what can be measured, and what can be measured is often considered “evidence” in the learning sciences. This means that technological advancements have also changed what we consider to be the measure of learning itself. Good, accurate and nuanced technologies are expensive. For example, experiments in which students use wearable technology to measure brain waves, heart rates, sweat and cortisol levels as they learn in a real classroom are very accurate, but also expensive. To scale the measurement of learning, many schools and businesses use simple technology. The consequences of this conundrum are that simple tools, like multiple-choice tests, are used to make big decisions, such as who is considered intelligent enough to go to university (Morgan, 2016). Not everything that can be measured is important, nor is everything that is important measurable with current tools and technology. There exist two basic barriers to measuring the learning brain. First, there are limited physical variables that can be measured with current technology. Currently, learning can be measured in the brain in four basic ways, the first is electrically by placing probes on the scalp and tracking brain waves (i.e., Magnetoencephalography [Cohen, 1972] Magnetic Resonance Imagining [Information, Reed Business, 1978]). Second, we can measure chemical changes in the brain. This can be done by drawing blood, through urination or saliva. Third, we can also measure brain structure, which was first tried with x-rays (Dandy, 1918), and then Computed Axial Tomography, discovered in 1971 by Godfrey Hounsfield. Fourth, we can measure brain activity through oxygenation, which has produced the greatest number of neuroimaging machines to date (Dick et al., 2014). This meant that for over 100 years research has been limited to the isolated use of either electrical, or chemical, or oxygenation, or structural aspects of the

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brain. It was not until the Human Connectome Project that combinations of these techniques were used that a more complex picture of the learning brain emerged. Beginning in 2018 a new methodological approach using wearable technology emerged on the scene. This new technology, often used by combing both EEG as well as fNIRS as well as eye-tracking software, enables researchers the most complete, naturalistic approach to MBE research ever in the history of science. The newness of this technology, being both wearable and more affordable, opened an exciting new range of findings. Some of the leading researchers in this area include Ido Davidesco at the University of Connecticut. Perhaps one of the most exciting additions to educational research due to this new technology is the ability to move beyond quantitative, explicit measures of learning, such as measured by test scores, and to delve into internal processes and implicit learning (DahlstromဨHakki et al., 2019). Second, the technology that exists is limited in its use in real classrooms with real learners during real learning events. Perhaps the most important and impressive advances in the second decade of the 21st century were in research and the publication of some of the first studies that directly gathered neuroscientific data in real live classrooms with real children using both psychological and observational methods as well as molecular/neuroscientific tools. Studies by researchers at the Queensland Brain Institute in Australia, for example, replicated Dewey’s Lab School Model in a modern context and research multiple aspects of learning such as “Brain-to-Brain Synchrony and Learning Outcomes [that] Vary by Student-Teacher Dynamics: Evidence from a Real-world Classroom Electroencephalograph” (Bevilacqua, et al., 2019). Such ground-breaking research appears to directly cross John Bruer’s “bridge too far” by explicitly showing the benefits of neuroscientific research combined with psycho-social interactions in real classrooms. This was expanded further with the application of “wearable” technology in the classrooms in which real students put on headband-like apparatus that could measure blood flow and electrical signals which track students’ eye movements (Brockington et al., 2018; Peitek et al., 2018).

The Researcher-Practitioner Model in MBE The 2020 International Survey showed that there are many professional tracks for MBE among them Teacher Educators, Instructional Designers, and Consultants as well as Administrators, Educational Materials Developer, including EdTech and AI and Curriculum and Psychologists or Counsellors. Others may go the research route towards Graduate School or

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University Position, Researcher and Policy Makers, while another group may help expand the new areas within of Translational Communication. Of all the options, however, the most mentioned is that of a teacher who is well versed in research skills. The current reality within MBE is, however, that few teachers research well and few researchers teach well. That is, the researcher-practitioner model remains relatively rare. This suggests more work is needed to nurture a new type of professional at the crossroads not only of mind (psychology), brain (neuroscience), and education, but also at the intersection of research and teacher practice. Crossing researchers-practitioner boundaries requires a new generation of individuals who can walk the fence between neuroscience, psychology, and education in terms of basic knowledge, including teaching and researching skills. While there is no official professional profile of an MBE teacher-practitioner exists, however, one key characteristic has been mentioned related to the translational abilities of such practitioners.

Communication among Mind, Brain, and Educational Scientists To improve both research and practice in MBE, and to enhance to probability of policy changes based on the evidence, communication needs to improve. There is an urgent need to facilitate international networks between MBE researchers and practitioners. While important in ancient times, more than ever, international networks have been the spark for discovery and its recent increase and encouragement in the 21st-century has expanded the applicability of findings to broader audiences. The ability of people all around the world to cooperatively resolve learning issues has never been greater (de Wit and Altbach, 2021). The field of international comparative education, a fledging sub-area of education in the 1980s, has grown exponentially in the 2020s, with much of the best research coming out of joint institutional efforts in which ideas can be compared in multiple contexts and approached from different perspectives (Carnoy, 2019). The International Mind, Brain, and Education Society, and the Global Science of Learning Network, as well as the editorial staff of most major journals, boast contributions from around the globe, which serves both to enhance scientific knowledge as well as to speed up the understanding of context and culture in learning. The international nature of collaborative learning has also encouraged growth in inter-, multi-, and transdisciplinary thinking. Transdisciplinary research depends on a shared language. A commonly accepted vocabulary has yet to be agreed upon by Mind, Brain, and Education scientists, neuroscientists, psychologists, and educators to

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facilitate exchange. Despite the proposal of such a vocabulary in 2013 by Ansari, Varma, and Tokuhama-Espinosa (cited in Tokuhama-Espinosa, 2014), there has been no “official” acceptance of the glossary which can be found in Appendix B, despite Daniel Ansari’s role as a past president of the IMBES Board. To make matters more challenging, few people have taken on the role of translators to facilitate communication between established fields and the emerging MBE science. As mentioned earlier, translational research is fundamental to the growth of the discipline. Like the role of earlier pioneers who ventured into unknown territory as they explored looking for new opportunities, translational researchers benefit both those who remain in the established lands and those who choose to forge into new ones. New online publications, such as the Nature Partner Science of Leaning journal and its accompanying online community launched in 2016 created the possibility of translating studies among the different learning sciences fields. By 2018, such online communities, albeit small with only a few hundred members, created a meeting space to exchange ideas between neuroscientists, psychologists, and educators. These and other new technologies permitted online, open access, translational research from classrooms to laboratories and back, and by 2019, began to point to best practices in the teaching-learning dynamic that can be publicly debated by a global community. The researcher-practitioner model in MBE is one that is also celebrated in the mission statements of other fields, such as Educational Neuroscience. Indeed, many of the goals in terms of research endeavours are shared by MBE and sister fields such as Neuroeducation and even Cognitive Neuropsychology. These shared goals have created a tension about the name “Mind, Brain, and Education” which will be explored in chapter 6. To move MBE towards a transdisciplinary model of research, several questions must be answered. The transdisciplinary model of MBE differs from the accumulative model in two specific ways. First, contributions from all the parent disciplines, as well as their hyphenations, are valued equally. That is, there is no “sub-field”. Mind (psychologists), Brain (neuroscientists), and Education (teachers) have equal value and contributions. This then begs the question as to whether such collaborative ventures exist, and they do, but in far smaller a number than purist research opportunities. A second natural question is then, must there be multiple specialists to complete research in MBE, or is it possible that one person or small group of lab experts, could combine the skill sets needed to embark on research? These options are explored below.

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Option 1: International, cooperative investigations between research specialists with shared goals Option 2: (Small) labs with specialists in the parent disciplines with shared agenda Option 3: Individuals with the skill sets needed to conduct research in MBE The second decade of the 21st century can be considered the early childhood years of MBE science and can metaphorically be seen to have been nurtured by advances in its parent disciplines (psychology, neuroscience, education, and, to some extent, health) that spoon-fed it. But by the 2010s, MBE also began with new, transdisciplinary research of its own using a unique combination of tools and perspective as it tried to feed itself. Technology and social media appeared to tip the balance in favour of informal exchanges on research findings, broadening the base of learning scientists who offered input about the future of the discipline and the topics for research, which ranged from sleep hygiene, gifted learning, technology, and the brain, neuromyths, social contagion, creativity, genetics, and motivation, among others. This leads to the description of a new researcherpractitioner model in MBE. Currently, there are groups working within each of these three types of structures, and all should be welcomed as their findings contribute to the collective betterment of teaching. Options 1 and 2 have been the working model for the past 100 years, but more recently there is a new type of professional, as suggested by Kurt Fischer’s initial vision, who can manage a combination of skill sets that cross into the three parent disciplines of neuroscience, psychology, and education seen in Option 3. This new kind of formation is primarily focused on educators, as seen in the program at Harvard and Johns Hopkins, though there are other programs which reach more broadly into the “grey” area of crossdisciplinary specialists, such as those at Columbia University and the University College of London. All three professional formations are welcome. But as suggested by the expert panel in 2020, if one of the main aims of MBE is the improvement of educational practices, it is hoped and even presumed that most teacher formation will begin to embrace the guidelines proposed throughout this book.

CHAPTER 6 THE NAME DEBATE

Throughout this book we have called the new science of teaching and learning “Mind, Brain, and Education science” but this is not without its controversies. Since its formation in 2004, the founders of MBE have debated the term around the world with friends and colleagues. In most cases, participants in these discussions, like the experts in the 2020 International Survey, remain on the fence conceptually, or diplomatically proclaim there “isn’t really any difference” between these labels and choose to focus on more substantive content issues. The name debate of the discipline is important, however, as it helps refine parameters and explains boundary crossings. This chapter seeks to summarize the articles that have tried to bring clarity to the name debate in Mind, Brain, and Education.

Clarifying the Name Debate over Time As documented in previous chapters, the efforts to understand the neurological bases of learning and education date back to about 5,000 years BC, but the translation of these bases into policies and practices that can be used in the educational context did not begin until the 1970s when the terms “brain-based” or “brain-compatible teaching” came on the scene (Hart, 1978). While "brain-based education" or "brain-based learning" promised a meaningful transformation in education and was attractive to teachers, some criticized the term for being a tautology, as all learning is based on brain functions (Braunger and Hart-Landsberg, 1994). During the 1980s, 1990s and early 2000s, it became clear that while some embraced “brain-based” teaching and learning, others who came from more traditional fields preferred to use conventional labels, such as Neuropsychology and Educational Neuroscience. For example, in 1988 Darlene Newby-Watson described the historical evolution of the Neuropsychological foundations of behaviour and the possible applications of the tenets of this conception to curriculum design. She concluded that while technological advances had revolutionized brain imaging, the science of neuropsychology was still in its infancy, and applications to school contexts were limited as evidenced by the existence

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of just one teacher training program, the Neuroscience and Education Program, founded in 1988 at the Teachers College at Columbia University in New York. By her measure, while the Teachers College was ahead of the curve in perceiving the utility of bringing more neuroscience to teacher education, the future of the discipline would depend on whether others also joined in. Another study on the developing relationships between Neuroscience and Education, conducted by Susan Koop Fazio (1989), considered the complementary nature of neuroscience and education but did not suggest they could be unified as a single discipline. The 1990s’ Decade of the Brain triggered important research about how the brain learns and was accompanied by many popular press books, most of which totted the “brain-based” label (e.g., “Reinventing Schools Through Brain-Based Learning” [Caine & Caine, 1995]; Brain-Based Teaching and Learning [Jensen, 1995]; How the Brain Learns [Sousa, 1995]) and were associated with large for-profit conferences and products. Indeed, “the allure of brain science ensures that these ideas will often find a substantial and accepting audience,” wrote John Bruer in his 1999 chapter in the JosseyBass Reader on the Brain and Learning called “In Search of…Brain-Based Education” (53). He went on to elaborate indicating that “‘these ideas are easy to sell to the public, but it is easy to take them beyond their actual basis in science,’” (Bruer, 1999, 53) quoting Joseph LeDoux. Stretching ideas beyond what the scientific evidence says has many consequences, Bruer argued, not the least of which was the promotion of neuromyths and false ideas about how human learning occurs. To more successfully bridge neuroscience and education, Bruer recommended using cognitive psychology to connect the two fields (Bruer, 1997). This suggestion to bridge neuroscience to education through psychology was the first clear call that a more complex view of the teaching-learning dynamic was transdisciplinary, not just a two-way conversation between neuroscience and education. The broader reach of transdisciplinary thinking meant that the international community, speaking through the OECD’s research, chose to use “the learning sciences” rather than “neuroscience and education” or “brain-based learning”. This was a deliberate action to try and broaden the conversation about the true science behind learning (OECD 2002; 2007). Due to the evolution of this “new science of learning” (OECD, 2002), many advocates of brain-based learning stopped using the term as it began to be associated with commercial ventures (for example, see Brandt, 2012). While “the learning sciences” proved broadly acceptable, it did not resolve the definition of the discipline at the intersection of neuroscience, education and psychology, as suggested by Bruer. Since the early 2000s there have been several articles in which this has been discussed.

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Some, like Denis Brandt and Usha Goswami (2007), refuted John Bruer’s idea that neuroscience and education shared “A Bridge Too Far” (1997) as they argued there were already practical applications of neuroscience in education within studies on mental representations. Many took their work to indicate that Educational Neuroscience could be used to can expand knowledge about learning and teaching by showing teachers the physical evidence for learning in the brain. While this was true, others, like Paul Howard-Jones (2008) suggested that the philosophical underpinnings of neuroscience and education were the true roadblocks to integration. That is, while there were practical ways that neuroscience was already contributing to teacher knowledge, many teacher colleges had not yet included these ideas due to philosophical differences that often created “common transgressions in sense-making with dualist and monist notions of the mind-brain relationship,” (Howard-Jones, 2008, 361). He then goes on to point out that once people can move beyond thinking in narrow silos of understanding of single disciplines or even interdisciplinary thinking (e.g., neuroscience and education), they can then extend to “a brain-mindbehaviour model from cognitive neuroscience to include a greater emphasis on social interaction and construction,” (361). The ability to consider the social construction of learning in addition to mind, brain, and behaviour permits educators to examine “the potentially complex interrelationships between the different learning philosophies,” (361). Howard-Jones breaks down the complex relationships, similarities, and differences between the historical, epistemological, and methodological foci of “Mind, Brain, and Education,” “Neuroeducation,” “Educational Neuroscience, and “Brain and Education,” and acknowledges that “although these names may come to represent some differentiation in approach, all these initiatives share a common goal: to combine our educational understanding with our biological understanding of brain function and learning” (361). While the goals might be shared, he footnoted this observation with John Bruer’s idea and the bridge of psychology: “Although sometimes absent from the name of the enterprise, it is worth noting that an understanding of the mind, as provided by psychology and/or cognitive science, is usually seen as essential in attempts to build conceptual bridges between neuroscience and education” (378). Tracey Tokuhama-Espinosa’s thesis (2008) dedicated a section of “The Scientifically Substantiated Art of Teaching: A Study in the Standards of Neuroeducation (Mind, Brain, and Education science” to gaining consensus on the discipline’s name. In fact, the thesis began focused solely on Neuroeducation, but the title was changed before the final submission to reflect the strong arguments made by the Delphi panel participants. The

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panellists shared unanimous opposition to “brain-based teaching” and “brain-based learning” which many felt was a way to dupe unsuspecting teachers into purchasing books, routines, activities or packets that were often unsupported by evidence, and in some cases, even tinted with neuromyths. After four rounds of debate and six months of exchanges, the 20-member panel showed a preference for the term Mind, Brain, and Education. Many within Educational Neuroscience did not bother to take the time to participate in a defence of their discipline’s name, and several presumed the focus of “EdNeuro” to be self-evident. Those who did examine Educational Neuroscience’s scope called it an interdisciplinary field, which served the practical role of improving education (e.g., Feiler and Stabio, 2018). In 2012, Ali Nouri conducted a study to define the state and scope of the field of Neuroeducation in terms of its own discipline-specific terminology. While, in general, there was consensus among experts regarding the concepts, methods, and scope of the field, their responses regarding the name of the field showed relatively few but serious disagreements. Those who favoured Mind, Brain, and Education were more prolific in their publications to defend the MBE name. While there were many articulate arguments, perhaps the best explanations in defence of the use of the term “Mind, Brain, and Education” came from Paul Van Geert and Henderien Steenbeek (2008), who seemed to build off on Howard-Jones’ ideas reflecting the growing complexity of our understanding about human learning and the need to have increasingly complicated theories to reflect the growing understanding of the brain. In their chapter “Understanding Mind, Brain, and Education as a Complex, Dynamic Developing System: Measurement, Modeling, and Research,” which appeared in the book Antonio Battro, Kurt Fischer and Pierre J. Léna’s The Educated Brain: Essays in Neuroeducation, the authors argue that something as complex as human learning merits more than a single disciplinary view. They argued that “human development and education can benefit from a framework that analyses behavior and brain change as involving dynamic systems processes,” (2008, 71) primarily because studies limited to a single timeframe or group cannot possibly explain the complex systems that make up human learning. They suggest that thinking about learners in contexts, with pasts and histories, would provide “a dynamic approach [that] promises to provide useful tools for understanding the complex individual changes that occur during education and child development” (71). In the opening chapter of The Educated Brain: Essays in Neuroeducation, the editors (Battro, Fischer and Léna, 2008) also discuss the name debate.

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One name for this effort is neuroeducation (Bruer, this volume), which emphasizes the educational focus of the transdisciplinary connection. Another is educational neuroscience, where the focus is on neuroscience, to which education connects. We use the name ‘‘mind, brain, and education’’ to encompass both of these focuses and others that bring together cognitive science, biology, and education. On one side, this emerging field touches on all levels of modern neuroscience: from molecules to genes, from synapses to artificial neural networks, from reflexes to behaviors, from animal studies to human brain imaging (Dawson & Fischer, 1994). On the other side, the term ‘‘education’’ is as vast as human culture itself. Because of the process of globalization, which intermingles so many different cultures, languages, and beliefs, the field of mind, brain, and education is becoming increasingly complex and necessarily diverse. (3-4)

This suggests that the complexity of human learning is the main reason justifying “Mind, Brain, and Education science” over “Educational Neuroscience.” The complexity of human learning came up again in later research. In 2010, Tokuhama-Espinosa asked once again if “a rose by any other name” would still smell as sweet, alluding to Shakespeare’s lines about whether the fact that Romeo and Juliet belong to rivalling families should matter in the love affair between the two. In the end, both in Shakespeare and in Mind, Brain, and Education, it seems that words and their meanings do matter. The key distinction suggested that all the disciplines are concerned with learning, whereas the main focus of MBE is teaching. The intersection among education, neuroscience, and psychology has been referred to in many ways and through many labels over the past three decades. Some of the terms used to describe this intersection are brain-based learning (which is mainly commercial packaging of information about the brain for teachers); educational neuroscience (which is primarily information about learning grounded in laboratory research but that uses more technical terms than teaches are typically comfortable with); educational neuropsychology (whose origins in psychology are substantiated by neuroscience and then seen in light of learning situations); educational psychology (whose origins on psychology are an attempt to explain learning in terms of observable behavior), cognitive neuropsychology (whose origins in psychology are substantiated by neuroscience and then seen in light of thinking processes), and neuroscience (which is the study of the nervous system and often includes studies on how nonhuman organisms learn). These disciplines all add to the knowledge about the learning process as conceptualized in MBE science, but they are not identical to it. The biggest distinction among these labels is in the way they embrace learning, whereas MBE gives equal playtime to teaching. (16-17)

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After 2010, the reasons for this naming protocol began to gain clarity. Michel Ferrari and Hazel McBride (2011) examined the history of Mind, Brain, and Education from the development of the discipline and helped move what had been loosely labelled Cognitive Science, Educational Psychology, and Educational Neuropsychology into the single discipline of Mind, Brain, and Education science, which significantly emphasizes the importance of examining not only the learning sciences but rather the teaching-learning continuum. Teaching, not just learning, made MBE stand out from the other disciplines. Also in 2011, Daniel Ansari (former IMBES President), Donna Coch and Bert DeSmedt (in-coming IMBES President) wrote an interesting article entitled “Connecting Education and Cognitive Neuroscience: Where will the journey take us?” in which they suggest that one of the primary ways to make Education and Cognitive Neuroscience applicable is via Mind, Brain, and Education. In yet another study, the former President of the International Mind, Brain, and Education Society, Marc Schwartz (2015), provided an understanding of the recent history and present status of Mind, Brain, and Education science. He described the evolution of the discipline in three phases. The first phase was initiated in the late 1980s, through formal and informal forums exploring how a new interdisciplinary e൵ort could (or could not) address educational issues through neuroscience. The potential connections between Education and Cognitive Neurosciences came into sharper focus in the 1990s during the Decade of the Brain. The second phase emerged by the early 2000s, through the development of new certi¿cate or masters’ programs developing connections between Mind, Brain, and Teaching. The third phase is currently underway and is framed as a “challenge in collaboration” between all vested partners. The focus on teaching, and the eye on complex, transdisciplinary research, seemed to set MBE apart. In 2016, Rockey Knox summarized the main reasons that Mind, Brain, and Education is distinct from Educational Neuroscience based on its transdisciplinary approach to identity, scope and method, which were different. This echoed earlier ideas from Battro, Fischer and Léna (2009), and others who believed that MBE was more appropriate because it was more complex and encompassing than Neuroeducation or Educational Neuroscience. While the new appreciation of the complexities of human learning started to filter into teacher education programs, such as those run by the Deans For Impact around 2016, there was still confusion about whether MBE was a discipline or not. In 2017, an international Delphi panel survey study sought consensus from 41 experts in 11 countries (TokuhamaEspinosa, 2017; 2018) to document key advances and current challenges to

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Mind, Brain, and Education over its first decade of existence. Many of the Delphi panellists were unsure if MBE should be called an academic discipline, if it was a scholarly field, or if it was an educational movement. One of the recommendations at the close of the study was that “a separate study be conducted that looks at the history and evolution of scientific fields to settle this question whether MBE is, indeed, a distinct discipline (or field or movement)” (Tokuhama-Espinosa, 2017, 286). Beginning around 2018 several authors from educational backgrounds wrote articles to sternly defend the Mind, Brain, and Education discipline name by presenting new evidence from the frontlines of teaching. Different from Educational Neuroscientific studies, those in Mind, Brain, and Education embraced the complexities of the dynamic student-teacher exchange. Ian Kelleher and Glenn Whitman’s article “A Bridge No Longer Too Far: A Case Study of One School’s Exploration of the Promise and Possibilities of Mind, Brain, And Education Science for the Future of Education” suggests that Mind, Brain, and Education is the bridge in Bruer’s “Bridge Too Far” (1997). Others aggressively defended how education alone is insufficient to meet current educational needs, and that more complex theories are needed to address issues like social justice (Pirayesh, 2018) where MBE plays a role in developing “curriculum relevance” that goes “beyond the tensions between science and education as described in the MBE literature, to assume an ‘itinerant position” (Pirayesh, 2011, 128).

Research, Journal Names and Conference Affiliations Before 2007, most scientific research that supported education came from cognitive behavioural science and educational psychology. The name debate changed after the launch of the Mind, Brain, and Education journal in 2007. Books with “mind, brain, and education” in their titles began to emerge (e.g., Schwartz and Paré-Blagoev, 2017; Sousa, 2010; Tokuhama-Espinosa, 2010; 2014) and some publishing houses (e.g., W.W. Norton, Columbia University Teacher College Press, and Association for Supervision and Curriculum Development [ASCD]) went so far as to establish reading lists and multiple titles based on Mind, Brain, and Education science as readers were hungry for anything with “brain,” or “neuro” in it. Research and publications in MBE began to grow in other parts of the world as well, with attendance at European conferences equalling or surpassing that of United States initiatives. Research and publications increased during the Decade of the Brain.

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Table 6-1. Articles Mentioning MBE, Educational Neuroscience and Neuroeducation 1970-2020 Number of articles mentioning the term

1970-1980 1981-1990 1991-2000 2001-2010 2011-2020

Mind, Brain, and Education 2 8 16 977 10,100

Educational Neuroscience 10 5 17 369 4,040

Neuroeducation 4 19 25 231 2,810

An informal search in the Google Scholar’s database showed that between 1990-2000, only 17 articles were published with the term “Mind, Brain, and Education,” 17 in “Educational Neuroscience”, and 27 in “Neuroeducation.” From 2001-2010 “Mind, Brain, and Education,” yielded 977 results, 369 in “Educational Neuroscience,” and 231 in “Neuroeducation.” In 2011-2020, “Mind, Brain, and Education” yielded over 10,000 results, “Educational Neuroscience” had 4,040 results, and 2,810 in “Neuroeducation”. These seems to suggest that while all the fields have grown significantly, the greatest number of articles have come from Mind, Brain, and Education. In 2010, several educational researchers came together in Zurich to participate in the first meeting of the Special Interest Group (SIG) of Neuroscience and Education under the organizational structure of the European Association for Research on Learning and Instruction (EARLI) to establish and strengthen the bridge between neuroscience and education. The second biannual meeting of this SIG was held in London in 2012, the third was held in June 2014 at GeorgဨAugustဨUniversity, in Göttingen Germany, the fourth in Amsterdam in 2016, and the fifth in London in June 2018. The conferences were composed of keynote lectures, oral presentations and over 60 posters presented to discuss the theoretical and methodological issues in the discipline (EARLI SIG 22 Neuroscience and Education, 2014), which attested to the growth of the discipline and in particular, the popularity of the academic interest by younger professionals in newly formed academic programs in Educational Neuroscience throughout Europe. The conference aimed to reflect on the recent advances in the various fields from learning and instruction, mathematics, reading, language development, science learning, motivation, emotion, creative thinking, and general cognitive abilities. Both the IMBES and EARLI conferences highlighted the

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need for the emerging discipline to respond responsibly to challenges in education, while cautiously using research being generated in the other learning sciences. The choice of the European initiatives to label the field Educational Neuroscience rather than Mind, Brain, and Education science created a crisis of identity for the emerging discipline of MBE science. Another professional journal, Trends in Neuroscience and Education first published in December 2012, aimed to bridge the gap between the increasing basic cognitive and neuroscience understanding of learning and the application of this knowledge in educational settings. It “provide[d] a forum for original translational research on using systems neuroscience findings to improve educational outcomes, as well as for reviews on basic and applied research relevant to education” (Trends in Neuroscience and Education, 2019, para. 1). In 2016, the journal Educational Neuroscience also made its debut (Brown and Daly, 2016). The formalization of concepts like “Neuroscience and Education” and “Educational Neuroscience” confirmed the space in academia for conjoining visions from these two disciplines, but also furthered the debate about the role of Mind, Brain, and Education and precisely how the fields differed. The American counterpart to EARLI’s Neuroscience and Education Special Interest Group was labelled “Brain, Neurosciences and Education,” and proceeded both IMBES and EARLI beginning in 1978. This name side-stepped the name debate by including the brain as an overarching unifier of information from neuroscience and education.

Arguments for the Name “Educational Neuroscience” Those on the side of “Educational Neuroscience” made strong arguments that “mind” and “brain” were concepts or entities in the body, rather than disciplines, whereas both neuroscience and education were already established fields. The term “Mind, Brain, and Education” was also challenged at some US conferences, such as the American Education Research Association which created the Special Interest Group on Brain, Neuroscience, and Education (2014) and considered MBE to be a Harvard program of study, rather than its own discipline comprised of the three areas of psychology, neuroscience, and education (Tokuhama-Espinosa, 2017). The unconventional name “Mind, Brain, and Education science” was far less readily recognizable than Educational Neuroscience, Cognitive Neuroscience, or Developmental Neuroscience, forcing many leaders in the MBE movement, including IMBES board members, to self-identify as “neuroscientists” or “developmental cognitive neuropsychologists” rather than label themselves as “MBE scientists” because of the additional

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explanations required. Some went so far as to separate themselves professionally from the term after the initial years as the confusion about disciplinary origins cost them research and work opportunities (D. Daniels, personal conversation 20 Jan 2019). Furthermore, MBE did not adhere to typical hybrid parameters for disciplines or fields, in which one area is always considered a sub-area of another: Educational Neuroscience makes Education a sub-area of Neuroscience; Neuroeducation makes Neuroscience a sub-area of Education.

Arguments for the Name “Mind, Brain, and Education” The counterargument of those in MBE was three-fold. First, the name “Mind, Brain, and Education” was purposeful, discipline-related, and placed all three sciences (psychology, neuroscience, and education) on an even keel where no area was a sub-field of any other. That is, mind (psychologists), brain (neuroscientists), and education (educators) were equal in their contributions to research, practice, and policy goal formation. Second, MBE proponents argued that the discipline of psychology was lost in the “Educational Neuroscience” label unless it was presumed to be a subdiscipline of neuroscience, which was controversial in and of itself. Third, while Educational Neuroscience and MBE were both undisputedly learning sciences, the research being done as reflected in the articles produced in the Mind, Brain, and Education journal appeared to pay more attention to teaching, teachers, teaching interventions, and the unique dynamic of the classroom than Educational Neuroscience, which favoured the explanation of neural correlates for cognitive processing over teaching. A 2013 Wikipedia definition of Educational Neuroscience indicates that it is “a component” of Mind, Brain, and Education science, but offered no clear justification for this label and appeared to be authored by someone from the Harvard MBE program. The 2017 Delphi panel survey on MBE science had to add an appendix to relay the debate of the participating professionals some of who vehemently argued for positions on both sides of the name of the discipline being researched (Tokuhama-Espinosa, 2017). However, in the 2018 IMBES and EARLI conferences, the terms Educational Neuroscience, Neuroeducation, and Mind, Brain, and Education science seemed to be used interchangeably, creating further confusion but little discord, which was welcomed. In 2022 EARLI and IMBES joined forces to sponsor a single conference under the “International Mind, Brain, and Education Conference,” suggesting that EARLI was not opposed to the MBE label.

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The Complexity of Human Teaching and Learning Requires Transdisciplinary Thinking This disruptive new discipline brought a kind of scholarly dissonance to academia. Whereas traditional fields of inquiry often relied on siloed visions of conceptual understanding, MBE pushed a transdisciplinary vision. Whereas traditional scholarship meant peer review within a single discipline (Tennant et al., 2017), MBE requires perspectives from multi-disciplinary professionals (D. Daniel, personal conversation Jan 2019). Whereas traditional insights and advancements in a discipline were normally led by a society (Schwartz as cited in Tokuhama-Espinosa, 2010), MBE seems to be shaped by the multitudes who were now opinionizing thanks to social media (Sonne and Alstrup, 2019). In 2010, to broaden the appeal of the concept of Mind, Brain, and Education beyond the master’s program established in 2004, Kurt Fischer, Director of the MBE master’s Program at Harvard University, agreed to launch a course at the Harvard University Extension School. Together with Stephanie Peabody, they designed a semester-long, global overview of Mind, Brain, and Education for Harvard Extension students and the general public. Peabody added “Health” to the Mind, Brain, and Education title in the effort to incorporate the influence of the physical body into the discipline (“Mind, Brain, Health, and Education”), an addition Fischer was opposed to as it only further complicated the scope of the discipline, which was already beginning to feel challenged by other “neater” programs in Educational Neuroscience. Despite Fischer’s opposition and withdrawal from the program, it grew in popularity. Tracey Tokuhama-Espinosa was asked to join Peabody in 2013, and eventually, when Peabody withdrew from participation in 2015, took over the course as the sole instructor of the Neuroscience of Learning: An Introduction to Mind, Brain, Health and Education, which continues to be taught (2023). This course provides the learner with a unique instructional design that leverages technology in ways that improve outcomes by personalizing content through individualized resources, the development of a strong learning community, and the chance to learn from one’s mistakes through a liberal re-write policy. It was one of the first courses to use what is known about the human brain and learning to create the instructional design of an online course about the brain and learning from an MBE transdisciplinary framework.

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Figure 6-1. Mind, Brain, Health and Education

Source: Tokuhama-Espinosa, 2019

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In 2016 the Dean’s for Impact consortium of teacher colleges in the United States decided to join efforts to respond to the need to integrate more information about the brain and biology into their university teacher training curricula calling it the science of learning. This can be acknowledged as the first effort to respond to the need to include more information about human variability and learning based on individual brains as well as the collective understanding of how humans learn. In 2017, the OECD published a report in which they suggested that two areas of necessary growth for teacher education included technology and neuroscience (Guerrerio, 2017). This echoed the Deans for Impact’s call for better teacher preparation in the learning sciences. This call was matched by an offering from the major peerreview journals to create community spaces in which scientific articles about human learning were made more accessible to the general public. The Global Science of Learning Network, started by Bob Wise and Andrea Chiba began work in 2017 to bring together people from IMBES, AERA, EARLI and other organizations as a “network of networks” to facilitate conversations around poverty and the developing brain; whole education systems; and pedagogies that work for online, hybrid and face-to-face learning. Many in GSoLen were less concerned about the name hierarchy and more concerned about the impact of evidence-informed research. This created a circular problem, however.

A New Research Approach For research to advance, researchers need to target specific problems for resolution depending on the theoretical framework. To improve education, this usually means targeting specific questions. Each one of these questions can be answered in dozens of ways depending the theoretical framework used. A discussion of “motivation” even if limited to classroom settings, looks very different depending on whatever your view it through a disciplinary lens, a multi-disciplinary lens, an inter-disciplinary lens, or a transdisciplinary lens. All this is to say that the theoretical framework changes the unit of analysis as the lenses used to study topics change. Uni-, multi-, inter-, and transdisciplinary research frameworks differ in the number of perspectives used to respond to research questions. They also differ in research methodologies, the most elaborate to date involving real children in real classrooms in real-time meaning multiple variables simultaneously. This suggests that the most accurate understanding of human learning comes from the most elaborate design, which is not surprising given that it involves the most complex object in the known universe (Ackerman, 1992, iii; Gordon and Koroshetz, 2021, para. 1), the

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brain. Given the newly celebrated appreciation for complexity, a new host of questions emerges when moving this work into practice. The organizations debating the name of the field include IMBES; AERA, EARLI and GSoLeN. Their mission statements are surprisingly similar (Table 6-2). Table 6-2 The Purpose, Mission, and Visions of the Field Organization IMBES (https://imbes. org/about)

Purpose, Mission, Vision The mission of the International Mind, Brain and Education Society (IMBES) is to facilitate cross-cultural collaboration in biology, education and the cognitive and developmental sciences. Science and practice will benefit from rich, bi-directional interaction. As research contributes to usable knowledge for education, practice can help to define promising research directions and contribute to the refinement of testable hypotheses. Our objectives are: Ɣ To improve the state of knowledge in and dialogue between education, biology, and the developmental and cognitive sciences. Ɣ To create and develop resources for scientists, practitioners, public policy makers, and the public. Ɣ To create and identify useful information, research directions, and promising educational practices. To accomplish these objectives, we: Ɣ Share ideas, critiques, insights, and issues through a journal and other publications. Ɣ Organize symposia, workshops, and conferences as forums to promote dialogue. Ɣ Promote collaboration between researchers and practitioners in neuroscience, genetics, cognitive science, and education.

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IMBES and EARLI 2022 Conference: EARLI SIG 22 Neuroscience and Education (https://www.earli. org/node/45)

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“Our mission is to facilitate cross-cultural collaboration in biology, education and the cognitive and developmental sciences.” Identity The SIG brings together researchers from the fields of educational research, cognitive (and developmental) psychology and (cognitive) neuroscience as well as interdisciplinary people with training in each of these fields, all of which investigate human learning and development. Taking interdisciplinarity as a basic principle, the SIG conceives the relation between educational research and neuroscience as a two-way street with rich bi-directional and reciprocal interactions between educational research and (cognitive) neuroscience. Aims The SIG wants to explicitly focus on empirical research at the intersection of both educational research and neuroscience. A key aim is to build fundamental knowledge about the ways that children and adults learn and develop, thereby using neuroscientific approaches in combination with behavioral approaches. Research that deals with the effects of different learning environments on the neural correlates of learning and relates the latter to outcomes in learning (and development) is among the priorities of the SIG. In addition, there is also room for theorizing about the general relation between both disciplines, thereby providing a forum to address and discuss on the promises and pitfalls of this new interdisciplinary field. In this respect, theoretical contributions dealing with, for example, issues related to ecological validity, optimal combination of behavioral and neural data, etc. are welcome. The SIG aims to organize thematic symposia, workshops and conferences as forums to

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promote dialogue and collaboration between researchers in education and neuroscience. It also seeks to stimulate the visibility of EARLI on international neuroscientific forums, by means of symposia organised by SIG members at neurosciences conferences. Particular attention will be given to the training of young researchers in both education and neuroscience. This training is conceived to be crucial for a successful interdisciplinary field of education and neuroscience. AERA SIG 14 Brain, Neurosciences and Education (https://www.aera.net /SIG014/BrainNeurosciences-andEducation)

The purpose of the Special Interest Group on Brain, Neuroscience, and Education (SIGBNE) of the American Educational Research Association (AERA) is to lead and promote the design, implementation, and dissemination of empirical and theoretical work that articulate how brain and neuroscience knowledge can inform knowledge about education - and vice versa. This SIG “provides a venue for research in the neurosciences that may inform and inspire educational research, and for rigorous educational research thus informed.” To this end, we seek to support members in identifying, using, and producing high-quality, evidence-based information about topics at the intersection of education, neuroscience, psychology, and other learning sciences. The SIG-BNE aspires to be the “go-to” place for real dialogue between brain researchers, cognitive scientists, and educational researchers, so that our colleagues around the world can share ways to improve crossdisciplinary research necessitated for this dialogue

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GSoLeN (https://gsolen. ucsd.edu/about/)

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VISION To elevate learning around the world by providing a science of learning network of networks for collaboratively building a global scientific infrastructure to address the increasing learning needs of children and young people and the teaching practices necessary to address them in a fast-changing future. MISSION The mission of the Global Science of Learning and Education Network (GSoLEN) is to achieve maximum worldwide benefit from science-based strategies designed to meet the learning needs of our global future and to overcome the impact of systemic inequities on learning. GSoLEN promotes a deep understanding of Science of Learning (SoL) and the extent to which it can be generalized and implemented in practice. Through this process, network participants develop and share best practices for learning, education, and policy resources that consider for whom, at what developmental stage, under what conditions, and in what context SoL can be implemented in the world’s distinctive cultures and conditions. Grounded in an environment of trust and co-invention, this Global Science of Learning Network is fertile ground for training the very best interdisciplinary scientists, technologists, information brokers, practitioners, and policymakers to lead the innovation of SoL in education to benefit students in their global contexts.

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The missions, visions, and statements of purpose of these different organizations show a large area of overlap. This suggests that academic, research organisations, as well as global bodies, all see the benefits of transdisciplinary work in the learning sciences. Happily, all these organizations are working diligently towards the improvement of education, albeit using different methodologies. Another way to envision the name issue is through a global overview of the Learning Sciences and its many sub-disciplines. As can be seen in Table 6-3, the Learning Sciences is an overarching field, which includes studies on humans and animals. It also researches teaching and learning, and tends to approach learning through a single discipline at a time. While most respondents in the 2020 International Survey did not think there was an important difference between Mind, Brian, and Education science, and Educational Neuroscience (or “EdNeuro” as some call it), there were four important differences as alluded to earlier. First, Educational Neuroscience does not include Psychology. Second, in Educational Neuroscience, Education is a sub-field of Neuroscience. Third, Mind, Brain, and Education science considers equal contributions from the sub-fields of Psychology, Neuroscience and Education. Fourth, Mind, Brain, and Education science is part of the learning sciences and primarily bases its work on human studies from both single field perspectives (psychology, neuroscience and education), as well as from the intersection of fields. While not a definitive answer to the name question, these four points help identify the boundaries of MBE. Having said that, there are others who define these fields differently in terms of the level of analysis. For instance, Han and colleagues (2019) have defined Educational Neuroscience as a transdisciplinary field, incorporating findings, theoretical frameworks and methodologies from education, and cognitive and brain sciences. They have presented a multilevel framework for educational neuroscience, which argues for the integration of multiple levels of analysis, some originating in brain and cognitive sciences, others in education, as a roadmap for the future of educational neuroscience with concrete examples in mathematical learning and moral education.

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Table 6-3. Mind, Brain, and Education within the Context of the Learning Sciences

© Tokuhama-Espinosa 2019, revised with input from Nouri and Borja in 2022

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The name debate has not yet been resolved but the parameters of the discussion have been refined. The deeper our understanding of the complexities of human learning, and the clearer we become in understanding transdisciplinary thinking, the more accurate our classroom interventions can become. This suggests a host of new implications for education, which we turn to next in Part III.

III: MIND, BRAIN, AND EDUCATION’S IMPLICATIONS FOR THE FUTURE OF EDUCATION

CHAPTER 7 CURRICULUM AND PEDAGOGY: A LOOK FROM A MIND, BRAIN, AND EDUCATION PERSPECTIVE

In this chapter, we look at curriculum and pedagogy from a Mind, Brain, and Education perspective and speculate on the areas that are likely to change in the future. What and how we teach, where and when learning occurs, and who participates in education are all changing thanks to MBE. We begin with a look at how teaching is impacted by MBE, and end by discussing how teachers should be trained to best implement MBE.

Changing How We Teach Students Based on MBE Knowledge How we teach is as important as what is taught. In the 2020 survey, experts agreed that education requires several changes to truly allow all learners to reach their potentials. Some suggestions from the experts are that there is a need for a change of focus “from teacher-centred learning to learner-centred pedagogies”; others suggest that education should be “designed around the basic general cognitive functions” of attention, memory, and executive functions, “not around subject areas”; others said the curriculum needs to go from fixed, predetermined, age-based objectives and evaluation to “more flexible mastery-based” assessments; and yet others said there needs to be a “greater focus on the socio-emotional” domain of learning as well as cognitive aspects (Tokuhama-Espinosa, Nouri and Daniel, 2020, 79-84). All these suggestions have merit, but they are also challenging to put into practice.

Radical Neuroconstructivism One MBE evidence-based teaching approach that may contribute to more insightful instruction is radical neuroconstructivism. Students build

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their knowledge based on contact with the world combined with their memories and first-hand knowledge of the past. Learning in the brain is evidenced by new neural connections and reinforced neural pathways, also known as neuroconstructivism. The interaction of the student with their world, further modified by interaction with their teacher, their classmates, and their prior experiences, changes the way they know, which is “radical,” as opposed to static. Radical neuroconstructivism changes based on the student-teacher and student-student dynamics, and other human exchanges converging with what the student already knows about the information mediated by the pedagogical choices of the instructor. Radical neuroconstructivism reflects the teaching-learning dynamic as an ongoing exchange following the construction and strengthening of neural pathways for basic cognitive functions before more complex ones (TokuhamaEspinosa, 2019). This dynamic exchange is created by a student who comes to class with past lived experiences as well as their genetic potential, along with the exchanges they have with their teacher, including the pedagogies that are used and the labels that are applied, all of which influence their learning. This back-and-forth between student knowledge and teacher instruction suggests that the human brain changes with every teaching intervention, modifying its potential for learning in subsequent interventions (Tokuhama-Espinosa, 2019; Erbeli et al., 2019; Petrill and Justice, 2007; Kovas et al., 2012, 2014) Some dictums in MBE might include ideas such as “the more you know, the more you can know” and “what you already know influences what you can learn next” (TokuhamaEspinosa, 2022). This means new learning is based on what the student already knowns, how s/he interacts with others around the information, and the quality of the pedagogical choices around instruction. Rather than a simple “Teach A-Learn A” scenario, MBE teachers appreciates that learning is complex, and influenced by multiple factors. MBE practitioners understand that: (a) students come to class on an uneven playing field due to genetic inheritance; (b) students don’t share the same prior experiences; (c) what the student already knows influences how they learn; (d) how knowledge, skills, and attitudes influence learning; (e) the student’s relationship with the other learners influences learning; (f) the student’s relationship with the teacher influences learning; (g) the teacher’s execution of the methodology, strategy or activity influences learning;

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(h) the learner’s self-perception in the class context/environment influences learning; (i) what else is vying for the student’s attention can influence learning. These different actors, actions, reactions, and interactions can all influence learning outcomes. One way for teachers to use information from MBE science is to learn these basic ideas about radical neuroconstructivism. A second way to use MBE is to learn the core Principles and Tenets of MBE.

The Principles and Tenets of Mind, Brain, and Education Science: What MBE tells us About Human Teaching and Learning The “primary goal of [Mind, Brain, and Education science] is to join biology with cognitive science, development, and education so that education can be grounded more solidly in research on learning and teaching” said Kurt Fischer, one of the co-founders of IMBES (Fischer, et al., 2010, para. 1). To determine the fundamental aspects of evidence-based teaching in MBE, the panel members of the 2020 survey (Tokuhama-Espinosa, et al., 2020; Tokuhama-Espinosa and Nouri, 2020) were asked to review six statements that are listed as the principles of learning (Tokuhama-Espinosa, 2017) and the accompanying (hyperlinked) evidence to journal articles that had been provided in the previous research. A principle is a “concept which is ‘universal’ and has robust evidence for human brains independent of age, gender, or culture” (TokuhamaEspinosa, Nouri and Daniels, 2020, 65). A tenet is “a concept that is true for all people but with a large degree of human variation either due to culture, genetics, or prior experience” (Tokuhama-Espinosa, Nouri and Daniels, 2020, 66). The panellists were asked to answer if they agreed, disagreed, or had no basis to reply and were also invited to comment after each statement, and if they chose, to provide additional or counterevidence for their thinking. The evidence supporting the principles supplied by the 2017 Delphi panel and updated by the authors in June 2020 can be found in Annexe A which can be accessed using the hyperlink and/or QR code found in Appendix D. Modifications to the original principles of learning supported by MBE were made based on participant comments, evidence, and suggestions, resulting in new statements presented in Table 7-1.

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Table 7-1. Principles of Learning Supported by Mind, Brain, and Education Science According to 2020 Survey What Principles of Learning are Supported by Mind, Brain, and Education Science? Principle 1. Human brains are unique as human UNIQUENESS faces. While the basic structure of most humans’ brains is the same (similar parts in similar regions), no two brains are identical. The genetic makeup unique to each person combines with life experiences and free will to shape neural pathways. Principle 2. Each individual’s brain is differently DIFFERENT prepared to learn different tasks. POTENTIALS Learning capacities are shaped by the context of the learning, prior learning experiences, personal choice, an individual’s biology and genetic makeup, pre-and peri-natal events, and environmental exposures. Principle 3. PRIOR New learning is influenced by prior EXPERIENCE experience. The efficiency of the brain economizes effort and energy by ensuring that external stimuli are first decoded, compared, both passively and actively, with existing memories. Principle 4. The brain changes constantly with CONSTANT experience. The brain is a complex, CHANGES IN THE dynamic, integrated system that is BRAIN constantly changed by individual experiences. These changes occur at a molecular level either simultaneously, in parallel, or even before they are visible in behaviour. Principle 5. The brain is neuro-plastic. NEUROPLASTICITY Neuroplasticity exists throughout the lifespan though there are notable developmental differences by age.

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Principle 6. MEMORY SYSTEMS AND ATTENTION SYSTEMS ARE NEEDED FOR LEARNING

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Learning involves multiple cognitive processes, including memory and attention. There is no new learning without some form of memory and some form of attention. Learners are not always conscious of these processes. Most school learning requires wellfunctioning short, working and long-term memory systems and conscious attention. However, other types of learning can occur without conscious attention (e.g., procedural learning, habituation, sensitization and even episodic memory).

Other organizations have offered their own principles for MBE, including the Center for Transformative Teaching and Learning headed by Glenn Whitman and Ian Kelleher and Glenn Whitman (2018). Several of the CTTL principles overlap with those agreed upon by the experts though some appear to be tenets or instructional guidelines more than principles. Nevertheless, they offer a firm rudder around which to organize teaching and learning. Others have suggested that MBE principles should be the sum of principles from Mind (psychology), Brain (neuroscience) and Education. This would potentially join the Top 20 Principles from Psychology For PreK–12 Creative, Talented, and Gifted Students’ Teaching and Learning (Brody et al., 2017) with the Society For Neuroscience’s Brain Facts for Kids (Dubinsky, 2010), and perhaps John Hattie’s top 20 interventions according to effect size (Hattie, 2008). While an interesting exercise, this accumulative list does not seem necessarily more inclusive that the current decision to use the six principles and 21 tenets shared here based on the international consensus of experts and the evidence they shared, which is openly available to the reader and should remain under scrutiny as new evidence becomes available. The participants in the 2020 international survey (see QR codes in Appendix D) were asked if they would like to add any new principles to the six listed in the original list. Fifty-seven per cent (57.32%) said yes. It is interesting that in the 2008 Delphi survey most experts queried were hesitant to say that there were any principles at all, and in the current survey more than half feel that the six principles mentioned were not enough.

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Most suggestions made by the participants were to add a principle about concepts that were included in the MBE list, but labelled tenets (not principles) in this study. This shows that there is support for core ideas about teaching and learning, but that most participants did not distinguish between the concept of a principle– “true” for all learners independent of age and culture– and tenets– “true” but with a broad human variation. For example, most Delphi panellists believed motivation was a key component of learning. Motivation is considered a tenet in MBE because what motivates one person does not necessarily motivate another. This means motivation plays a role in education, but functions differently for different people which is why it is not a principle. It should be noted that the authors agree that there are no “truths” in science, but rather evidence or lack thereof. The use of the word “true” is to establish acceptance rather than an epistemological foundation. Of the most suggested additions was about the role of emotions in learning. Emotions are, however, already contemplated in the MBE list of tenets as emotive states are highly personal (e.g., what triggers stress varies from person to person). Similarly, emotions was closely followed by the role of social context, situated learning and classroom design for learning. There were also comments about the role of motivation, and metacognition. All these suggestions are already included but as tenets. Once the Principles were debated, a similar process occurred concerning the 21 Tenets in Mind, Brain, and Education science. The evidence supporting the tenets supplied by the 2017 Delphi panel and updated by the authors in 2020 can be found in Annexe B which can be accessed using the hyperlink and/or QR code found in Appendix D. The final tenets statements, resulting from modifications made to the original statements based on participant comments, evidence and suggestions can be found in Table 112.

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Table 7-2. Tenets Supported by Mind, Brain, and Education Science According to 2020 Survey What Tenets of Learning are Supported by Mind, Brain, and Education Science? Tenet 1. Motivation influences learning. However, MOTIVATION what motivates one person and how may not influences learning. motivate another in the same way. Tenet 2. Emotions and cognition are mutually EMOTIONS AND influential. Not all stimuli result in the same COGNITION are affective state for all people. mutually influential. Tenet 3. STRESS Stress influences learning. However, what influences learning. stresses one person and how may not stress another in the same way. Tenet 4. ANXIETY Anxiety influences learning. However, what influences learning. causes anxiety in one person may not cause anxiety in another. Tenet 5. Depression influences learning. However, DEPRESSION what causes depression in one person may influences learning. not cause depression in another. Tenet 6. Learning is Learning is influenced by both challenge and influenced by both threat as perceived by the learner. What a CHALLENGE AND person finds challenging or threatening is THREAT. highly individualized as are their reactions to the stimuli. Tenet 7. Reactions Reactions to facial expressions are both to FACIAL universal in that there are six or seven EXPRESSIONS are emotional states recognized by all humans, universal as well as as well as highly individualized in that a highly person’s culture as well as their own past life individualized. experiences condition responses to faces. Tenet 8. The brain The brain interprets human voices interprets HUMAN unconsciously and almost immediately. The VOICES perception of tones and inflexions of human unconsciously and voices are both universal in that basic almost immediately. emotional states, such as anger, are recognized by all humans, as well as highly individualized in that a person’s culture as well as their own past life experiences condition responses.

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Tenet 9. SOCIAL INTERACTIONS influence learning. Tenet 10. ATTENTION is a complex phenomenon.

Tenet 11. Most LEARNING IS CYCLICAL. Tenet 12. Learning involves CONSCIOUS AND UNCONSCIOUS PROCESSES. Tenet 13. Learning is DEVELOPMENTAL (nature and nurture) as well as EXPERIENTIAL (nurture). Tenet 14. Learning engages the BODY AND BRAIN. Tenet 15. SLEEP AND DREAMING influence learning in different ways.

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Social interactions influence learning. Humans are social beings who learn from and with each other. Different amounts of social interactions around learning are desired by different people. Attention is a complex phenomenon comprised of multiple systems supporting functions such as metacognition, selfreflection, mindfulness, states of high alertness, selective attention and focused attention. These systems work to different degrees in different people. These systems also have different relationships with one another in different people. Most learning is cyclical and advances and recedes based on stages of growth, reflection, consolidation, and the amount of repetition to which one is exposed. Learning involves conscious and unconscious processes, which may differ by individuals based on their training and other individual experiences. Learning is also described as implicit (passive or unaware processes) and explicit (active or aware processes). Learning is developmental (nature and nurture) as well as experiential (nurture). A person’s age, cognitive stage of development and past experiences all contribute to learning and do so differently for each person. Learning engages the body and brain, which is sometimes called embodied cognition. Sleep and dreaming influence learning in different ways. Sufficient sleep allows the brain to pay attention during wakeful states and both sleep and dreaming (normally rapid eye movement [REM]) sleep contributes to memory consolidation. The amount of sleep and dreaming individuals need can vary based on cultural norms and habits, circumstances, motivation, genetics and rehearsed sleep hygiene practices.

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Tenet 16. NUTRITION influences learning.

Tenet 17. PHYSICAL ACTIVITY influences learning. Tenet 18. When it comes to cognitive abilities you either USE IT OR LOSE IT. Tenet 19. FEEDBACK about learning progress influences learning outcomes.

Tenet 20. Embedding skills and facts in individually RELEVANT AND MEANINGFUL CONTEXTS enhances memory retrieval. Tenet 21. Brains detect NOVELTY and seek out PATTERNS.

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Nutrition influences learning. Basic nutritional needs are common to all humans, however, the frequency of food intake, the gut-brain axis and microbiome balance, and some dietary needs vary by individual. Children cannot learn well when they are hungry in the moment, or systematically malnourished. Physical activity influences learning. However, different individuals need different amounts of physical activity to perform optimally. Interspersing physical and cognitive activity may improve learning. Use it or lose it. Brains that remain active cognitively help development and can also stave off cognitive decline in the ageing brain. Individual variations including experiences and genetic predispositions influence the final outcomes of interventions, however. Feedback about learning progress influences learning outcomes. Feedback itself can be a source of learning. The type, frequency and use of feedback can influence learning outcomes, which vary by individual. Different tasks require different types of feedback, and the degree to which it is attended to, perceived, and interpreted correctly depends on the context. It is easier to retrieve memories when facts and skills are embedded in individually relevant and meaningful contexts. However, what is relevant or meaningful varies by individual.

Brains detect novelty and seek out patterns. However, what is novel to or recognized as a pattern by one individual may not be novel or may not be recognized as a pattern by another.

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The review of the Tenets undertaken with the expert panel revealed that many researchers had deep and nuanced understandings of their own fields, and often had little or no information about fields beyond their immediate realm of study. For example, experts on attention or memory might not understand the role of sleep or motivation in learning. This suggests two important ideas. First, a deeper reliance on the literature should be made to complement the opinions of the panellists. Second, and perhaps more importantly, the transdisciplinarity valued in Mind, Brain, and Education research is not necessarily practiced by current professionals. This appears to be changing, however, as the 2020s ushered in a new wave of research that depends on the cross germination of disciplines. A third big idea of related to teaching has to do with the use of digit tools and educational technology.

The Influences of Technology on Mind, Brain, and Education Most advances in the learning sciences have been due to two kinds of technology. The first has helped our ability to visualize learning in the brain (neuroimaging technology), which was discussed in chapter 5. The second has facilitated learning itself, which are the digital tools that complement the teaching and learning dynamic, which we will explain here. Many digital tools were created to save teachers time. For example, there are numerous tools built into Learning Management Systems (learning platforms) that provide self-graded quizzes, word counts on written submissions, and analytics that show how long a student spends on an activity and how many attempts they took to get a perfect score (Sottilare et al., 2018). New learning tools such as adaptive technology (e.g., Sottilare, et al., 2018), data analytics (e.g., Lee and Cheung, 2020), and individual learning apps (e.g., Kim et al., 2021) have exploded on the educational landscape in the past decade, enhancing the focus on truly personalized and adjustable technologies (Xie et al. 2019). Other digital tools are designed to increase self-paced rehearsal of content and accompany students to personalized learning by using algorithms to adjust to individual needs. For example, apps for learning a foreign language (e.g., Duolingo), or video explanations on how to do a specific type of math problem (e.g., MathPhoto), permit autonomous learners the ability to learn at their own pace. Two of the newest areas of digital learning technologies are virtual reality and gamification. Both show a great deal of promise for expediting learning objectives (Loureiro et al., 2020).

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Several high-quality teaching interventions based on neuroscientific research already exist. For example, the neuroscientifically-based reading tool RAVE-O (retrieval, automaticity, vocabulary, engagement with language, orthography) (Wolf, Miller and Donnolley, 2000); math programs like the Numbers Race (Wilson, et al., 2006); and cognitive processing programs like FastForWord (Gillam, et al., 2008) and BrainHQ Posit Science (Merzenich, 2017), are used successfully in classroom settings. Educational technology was a $6-billion-dollar industry in 2018 (Entertainment Software Association, 2018) and continues to gain territory in classrooms, with a strong spike during the 2020 pandemic (Iivari et al., 2020). In the past decade, educational gaming has become a new learning medium to improve general cognition, such as working memory (e.g., Melby-Lervåg and Hulme, 2013), attention (e.g., Posner, Rothbart and Tang, 2015), and inhibitory control (e.g., Karbach, 2015). Some technological apps aid learning by supporting general health and well-being. These tools are dedicated to mindfulness practice (Gál et al., 2021), sleep hygiene, (Grigsby-Toussaint et al., 2017), and the habituation of wellness activities, including physical movement (e.g., He et al., 2021) and improved nutrition (e.g., Hsu et al., 2018). Others seek to improve mental well-being (Renfrew et al., 2020) and social-emotional learning (Corcoran et al., 2018), and promote growth mindsets (Devers et al., 2016). Technology has always existed in education, but only recently has its power to save time and personalize learning advanced so rapidly and been used by so many (Lai and Bower, 2020). The primary lessons learned from the global pandemic and technology centred on human relationships. During the COVID outbreak and school shut down in 2020-2022, some believed that student learning could advance just as efficiently online. These people were right, in part. Those teachers who learned how to leverage the tech tools successfully to design courses that used digital tools to save teachers time on the repetitive activities (like grading quizzes, for example), and then used the free time to be more person with students, exceeded student learning outcome expectations. On the other hand, schools that thought they could replace teachers one with online, self-paced learning modules did not do so well. One of the most important lessons from the rapid on-ramping of technology during the pandemic was that human relationships remained at the core of education. Whereas technology could tell students what they did wrong on a math problem, history test or writing assignment, technology could not replace the human aspect of teaching which motivates student to try again and do better the next time. Only humans could make students care. The role of teachers in the MBE context celebrates aspects of teaching and learning we have been aware of for centuries: personalization matters. To be a good MBE teacher

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includes the belief that “you can’t teach them if you don’t know them”. Core teacher knowledge is the focus of the second half of this chapter.

Teacher Training Based on MBE Knowledge More people of more diverse educational, geographical, social, and economic backgrounds now have access to information from the learning sciences than ever before in the history of the world (GSoLeN, 2021). This has led to significant democratization of knowledge access and more widespread sharing of quality information. However, this phenomenon also makes it clear that “a little bit of knowledge is a dangerous thing”. Scientific literacy in the general public has always lagged behind scientific advancements as seen in this historical review (Strasser et al., 2019). This points to the current challenges in the discipline laid out within neuroethics, as policy and law-making also seem to continually play catch-up with discoveries about the brain. Greater socialization of basic core knowledge in MBE includes not only an understanding of the principles and tenets, but also off the many neuromyths and false beliefs about the brain and learning that still exist. A list of more than 70 neuromyths, explanations about their origins, and current research about why they are now categorized as myth was shared in Neuromyths: Debunking False Ideas about the Brain (Tokuhama-Espinosa, 2018). This information was written for the public at large and teachers in particular to explain the harm done by myths, such as believing boys are better at math than girls, that people are either right or left-rained, or have learning styles, or that some use just 10% of their mental capacities. Many on the 2020 International Survey expressed concern that educational texts often abbreviate concepts, use multiple metaphors and overuse acronyms rather than dig into the depth of knowledge necessary to understand the workings of the human brain. Short, abbreviated statements can never capture the complexity of the science behind them, yet books for teachers about the brain often do just that. Several people on the 2020 survey agreed that helping teachers have better access to information was important, but that this should not be done through “edible science” as one put it, which are short sound bites that are easy to hear, but often also easy to confuse with mythical information. One neuroscientist suggested that writing for a general audience always puts the integrity of the science at risk. Several initiatives can help here, including more and better researcher-practitioners in the discipline, improved scientific literacy by all teachers, and a change in attitude that embraces complexity over quick fixes in teacher education. This places a very

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important role on the translators and teacher trainers that use this information, who must do so responsibly and based solely on the evidence. Once teachers understand the neuromyths, principles, and tenets, they should also learn something about base brain structure. According to several participants in the 2020 survey, there is a need to balance attention around the unique aspects of human learning with the globally similar aspects of human learning. This means that teachers should be taught both that humans as a species are remarkably similar in how we learn to read or do math problems, while at the same time appreciate how and why we also differ in learning these skills. Both the similarities of human minds and brains, as well as the differences, should play a role in teacher education. Indeed, most of the remarkable imaging research over the past decade calls attention to how amazingly similar neural pathways are for estimating the non-symbolic magnitude, common nutritional needs to fuel thinking, or learning how to read, for example. Similar is not identical, however. This means that while the differences between human brains must be acknowledged to tailor the learning experience to the individual, so should teachers be taught about the ways brains are the same so that they can take advantage of “typical” learning trajectories. The MBE discipline has motivated a deeper understanding of how people evolve over time and how their brains are prepared to do things based on what they have already been exposed to. That is, what people know influences what they can know in the future, and both nature (one’s genetic make-up) and nurture (one’s life experiences) combine to react to the teaching experience and create the final learning outcomes that are achieved. MBE reminds teachers of the importance of learning in context, including differences in development. This discipline has called attention to the quickly evolving content knowledge that comes from the learning sciences to inform pedagogical practice. The increased quality of knowledge now available has exposed many misunderstandings teachers have about how brains learn. This is due in part to initial teacher formation which rarely includes information about the brain, as well as continual professional development which does not keep pace with the science. MBE reminds us that basic teacher education should include information about how the brain learns best based on the strongest evidence possible.

Training Teachers Continual professional development in education takes on many forms. In some cases, it is focused on content knowledge (improving math skills or art skills). Other times it is related to pedagogical content knowledge, of

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ways of teaching content. In modern teacher education, teachers should also learn about technology and learn about how the brain learns. According to the OECD, the modernization of the teaching profession depends on content knowledge, pedagogical knowledge, technology and learning about the brain (Guerriero, 2017).

Promoting Academic Professionalism The growth of the interest in the interface of mind, brain, and education science has led to the establishment of postgraduate courses at leading universities such as Johns Hopkins, Dartmouth, London, Bristol, and Amsterdam. These academic programs are labelled with titles such as “Mind, Brain, and Education” (Fischer et al, 2007; Stein and Fischer, 2011; Schwartz and Gerlach, 2011;), or “Mind, Brain, and Teaching” (TokuhamaEspinosa, 2010; 2017), “Educational Neuroscience” (Geake, 2009; Patten and Campbell, 2011; Thomas, Ansari and Knowland, 2019) and “Neuroeducation Studies” (Ansari, DeSmedt and Grabner, 2012; HowardJones, 2011; Gardner, 2008; Nouri; 2013; Nouri and Mehrmohammadi, 2012). The increased number of Master’s and Doctoral programs in all these learning science fields associated with Mind, Brain, and Education will be a strong indicator of the advancement of the discipline-based on-demand from up-and-coming researchers. Expanded course offerings in the MBE and MBE-related fields will also promote better communication as is necessitated by transdisciplinary research. Different from theoretical research programs, MBE programs usually generate usable knowledge which connects research with practice and policy in education, and trains professionals to create a new world in which research on the mind and brain relates directly to practice and policy in education (Fischer et al., 2010; Schwartz, 2015; Tokuhama-Espinosa, 2014). The future is open for MBE research to contribute to developing and implementing MBE-supported interventions for typical and atypical learning and test them in the field of education according to evidence-based principles to optimize learning for all students (Tokuhama-Espinosa, 2017). Some of the more recent interventions address the needs of typical children as well as those with attention deficit, dyslexia, dyscalculia, developmental language disorder, executive function disorders, and social and emotional disorders. As this process unfolds, educators can take an active role in shaping the discipline by striving to be critical consumers of educational products (Pasquinelli et al., 2021; Tokuhama-Espinosa, 2018), collaborating with researchers (Ansari and Coch, 2006), becoming researchers (Sylvan

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and Christodoulou, 2010), participating in the research (e.g., Dubinsky, 2010), and leading research (e.g., Tokuhama-Espinosa, 2017) in this area. Improved professionalism, especially guidance in transdisciplinary thinking, is needed. Some participants in the 2020 survey either over -or under-estimated the impact of certain scientific findings on learning. It was not uncommon to find a participant acknowledging something as being true, but then labelling it as “unimportant in education.” For example, one scientist said that it was true that facial expressions conveyed emotions but then commented that it was unclear how this had any role in education, apparently ignoring the huge impact social contagion plays in educational exchanges. Similar comments were made about the ways that sleep and dreaming, physical activity, and challenges and threats are related to learning. Such comments suggest many people remain unaware of how the teaching-learning dynamic can potentially be shaped by the mind-body interface. This suggests that MBE trained teachers must explicitly benefit from better information across a broad range of human behavioural topics, including the effects of facial expressions on communication and the role of sleeping on learning. The experts in the 2020 survey also acknowledged that MBE science pushes teacher education programs to include research-skills training, and to help teachers identify and use evidence-informed studies upon which to base choices in educational interventions. While some of the participants made it clear that most of the ideas shared were “common knowledge,” to scientists, they have not yet made their way into many teacher training programs around the world. Despite having support from the experts as well as from evidence for the principles and tenets derived from a review of more than 4,200+ documents, this information is not yet a part of all teachers’ knowledge training. And despite some very good initiatives that are underway right now that promote the conscientious understanding, research, and application of evidence-based practices about human learning, there remain close to a 100 neuromyths that are commonly sprinkled throughout teacher professional development, which are promoted by unknowing or unscrupulous teacher trainers. This means that rather than being told what to include, teachers should learn how to select information for themselves. The teacher-as-researcher-practitioner suggested earlier is a key aspect of teachers’ new pedagogical knowledge (Guerriero, 2017).

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Empowering Reflective Practitioners Educational practitioners, specifically teachers, are increasingly interested in applying neuroscience findings to improve educational practice (Betts et al., 2019). There is little scepticism within the educational community on the benefits of neuroscience to improve the practice of teaching (Serpati and Loughan, 2012). However, the rush to include “brain-based learning” means that there are some teachers who are increasingly willing to apply several seductive concepts that are scientifically invalid and educationally irrelevant (Hook and Farah, 2013; Howard-Jones and Fenton, 2012; TokuhamaEspinosa, 2018; Weisberg et al., 2008). Lack of scientific literacy may result in educational policymakers and practitioners wasting money and time pursuing unsubstantiated interventions. In the worst case, this also violates the first rule educators share with physicians: To do no harm (TokuhamaEspinosa, 2010), resulting in poor teaching and learning (Hardiman et al., 2012; Howard-Jones and Fenton, 2012; Tokuhama-Espinosa, 2017). This means that MBE science is vulnerable if the public in general and teachers in particular are not able to think critically about the evidence they use to create teaching interventions. They must become more conscientious consumers of information about the brain and learning (Tokuhama-Espinosa, 2010, 2018). In this context, MBE researchers have a significant role to play in debunking such misconnections by responsibly engaging in translating research findings into educational applications and producing new knowledge that will contribute to the improvement of educational policy and practice (Tokuhama-Espinosa, 2018). Researchers, therefore, have a serious obligation to consider ethical issues in their research more than any other role; experiments on childhood learning are not the same as experiments on lab animals. Researchers need to be aware of and anticipate ethical concerns, dilemmas, and conflicts that may arise throughout the research process, from defining the research problem, to collecting and analysing the research data, interpreting the results and suggesting the theoretical and practical solutions. This requires MBE scholars to find the best ways to help teachers to understand what is currently known about brain mechanisms and learning processes. One possible solution that would improve the researcher-practitioner model is the establishment of interdisciplinary and collaborative partnerships between educational researchers, practitioners and policymakers (TokuhamaEspinosa, et al., 2020; Tokuhama-Espinosa and Nouri, 2020). Scientists and educators need to collaborate to build a strong research foundation for analysing the black box of biological and cognitive processes that underpin

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learning to create usable knowledge that has great practical value (Fischer et al., 2010). They also must facilitate policymakers’ use of scientific evidence to improve the efficiency and validity of educational policies (see Appendix A).

A Potential Curriculum for Teacher Development In 2020, the expert panel indicated that one of the necessary changes in education is to integrate MBE courses in educational sciences curricula and teachers’ professional programs. Presently, we are moving towards the potential of integrating educational, neuroscientific, and psychological approaches in our developing understanding of learning. The key to the future development of MBE depends on training and empowering future teachers and researchers with critical, reflective thinking skills that will enable them to collaboratively contribute to creating valid and relevant educational knowledge, and reforming curriculum and pedagogy. While there is no set curriculum that all these programs follow, there are some key documents produced from some of the seminal programs which identify core knowledge in the discipline. Gardner and suggested a “first course” syllabus for MBE that included the basics of memory, attention and emotions, as well as a deep dive into literacy and mathematics (Blake and Gardner, 2007). Tokuhama-Espinosa’s syllabus for the course Neuroscience of Learning: An Introduction to Mind, Brain, Health and Education (2022) offers a global overview of 15 topics (functional neuroanatomy; plasticity and epigenetics; neurodevelopment; mindfulness and the default mode network; metacognition and theories of how the brain learns; affective neuroscience; language, executive functions, attention, memory, mind-body connection [sleep/dreaming, physical exercise, nutrition], theory of mind and cultural neuroscience; and neuroethics). Other programs prefer to spend an entire semester on memory, another on attention, another on emotions, and so on (Johns Hopkins, 2019). Others spread the learning out over several summers (e.g., Brain U at the University of Minnesota). While the time and depth vary, most of the core topics are similar. A suggested curriculum follows. To better understand what teachers should know about Mind, Brain, and Education topics, participants of the 2020 survey were asked, “What is important for teachers to know?” From their responses, 18 concepts were identified as key notions in MBE knowledge that all teachers should know. If divided by category, and role, the Key Conceptual Knowledge needed by all teachers can be seen in Table 7-3.

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Table 7-3. Key Concepts in MBE Teacher Knowledge Identified by the Participants in the 2020 Survey Category

Role

Foundational Knowledge:

Definition

Objective

Neuromyths

General Cognition

Attention Memory

Executive Functions Foundational Beliefs

Development

Neuroplasticity

MBE Practitioners: 18 Areas of Teachers’ Conceptual Knowledge 1. Neuroscience, Psychology, Education, and other cognitive and learning sciences have come together to form the foundations of MBE. 2. Teaching environments should meet the physical, social, emotional, spiritual, moral, and aesthetic needs and interests of the whole child. 3. Neuromyths and their origins should be understood, and they should then subsequently be debunked. 4. The brain’s attention networks can improve as a result of training. 5. There are multiple memory systems and attention systems which process information in different ways. 6. Executive functions can improve through integrating and teaching these skills as part of the curriculum. 7. The human brain undergoes enormous development across the lifespan. 8. There is a reciprocal interaction between nature (genes) and nurture (environment) during development. 9. The brain is neuroplastic and can change as a result of learning experience. 10. Human variance and individual differences should be respected using differentiated instructional strategies.

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Context

Affect DomainSpecific Cognition

Subject area knowledge

Direct Classroom Applications Do Exist:

Instructional practices

11. Neurodevelopmental disorders are impairments of brain function that can affect learning and be remediated with interventions. 12. Intelligence is a stable inherited trait which shows malleability in the face of educational interventions. 13. All cognition is embodied due to the interaction of the mind, body, and environment. 14. Cognition develops within a social and cultural context of learning. 15. Affective and cognitive processes are inextricably linked. 16. Neurobiological bases of domain-specific learning (e.g., school subject matters mathematics, language, literacy, arts, and so on) should inform effective pedagogies. 17. As they evolve, instructional practices should be informed by the learning sciences. (e.g., active memory retrieval as experienced through frequent, low-stakes testing can improve memory and boost learning; affect and social contagion can influence learning; interleaving for memory enhancement improves learning outcomes; d. spaced versus massed practice should be used for better retrieval; some psychological interventions, like growth mindsets, are supported by neuroscientific evidence, like neuroplasticity; memory is enhanced by authentic learning within context).

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18. Learning can be measured using neurotechnology in real class settings, though this is not yet common in most studies. Most brain research is conducted in laboratories, not in schools. Only a small amount of research is conducted on school-aged children, though this is increasing with the use of wearable technologies.

This list may be considered as the key standards to design effective teacher professional development on Mind, Brain, and Education. Based on this, we propose the following Curriculum for a Master’s Programme in MBE and/or Educational Neuroscience (see Table 7-4). Table 7-4. A Proposed Curriculum for a Master’s Degree in MBE/Educational Neuroscience Time

Semester I

Course title Foundational Knowledge in MBE

Human development

Syllabus Definitions, Terminology in MBE Research, Practice and Policy Objectives History of MBE Psychological foundations Biological foundations Philosophical foundations Educational foundations Technological foundations Brain development Physical development Cognitive development Language and literacy development Moral development Emotional development Social development

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Human cognition

Human learning Technology and the Measurement of Human Learning Information processing

Semester 2

Mind-Body interactions

Neuro diversity

Teaching

Sensation Perception Consciousness Cognition Metacognition Cognitive modelling Artificial intelligence, cognitive ontology and Algorithmic thinking Learning theories Intelligence theories Motivation theories Neuroimaging fMRIs, PET, fNIRS, EEG, MEG, SPEC Connectome Wearables Attention Memory Executive Functions Social perception Social cognition Gut-brain axis Nutrition Exercise and physical education Chronobiology Social-emotional learning Emotion and Cognition Individual differences ADHD Autism Dyslexia Dyscalculia Giftedness and Genius Creativity Synaesthesia Pedagogies supported by MBE

Curriculum and Pedagogy

Cultural epigenetics

Research Methods and Statistics Semester 3

Language and literacy

Mathematics education

Science education

Arts and aesthetics

Semester 4

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Nature, nurture and decision making Genetic analysis Learning environments Plasticity, transgenerational trauma Cultural neuroscience Quantitative methods Qualitative methods Mixed methods Advanced statistics Language development Neural networks of literacy Socio-cultural bases of literacy and cultural artefacts ICT and Literacy Mathematical development Neural networks of mathematics Socio-cultural bases of mathematics and cultural artefacts ICT and Mathematics Neuroconstructivism of scientific conceptual knowledge Scientific reasoning ICT and Science Neuroaesthetics Arts and education Arts and learning Cognitive functions of arts Arts curriculum

Dissertation

This overview is intended to give researchers, educators, and practitioners a succinct synopsis of Mind, Brain, and Education training. An understanding of where a field comes from, and its current state can point to future directions in terms of research, practice, and policy. The curriculum has 16 key areas of instruction: (a) Foundational Knowledge in MBE; (b) Human Development; (c) Human Cognition; (d) Human Learning; (e) Technology and the Measurement of Human Learning; (f)

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General Cognition; (g) Mind-Body Relationship; (h) Neurodiversity; (i) Teaching; (j) Cultural Epigenetics; (k) Research Methods and Statistics; Language and Literacy; (m) Mathematics Thinking; (n) Science Education; (o) Arts and Aesthetics; and (p) Research Methods and Statistics. This curriculum should make graduates highly employable and help them to take their understanding of the discipline into the educational workplace at any level of teaching or administration, as an educational researcher, or within a university context. This idea is one of many possible scenarios and combinations of courses leading to a degree in MBE. Some might argue for more neuroscience, others for more psychology, and yet others for more educational context. What all programs should consider, though not et aa common occurrence, is to ensure at least one course be taken at different institutions, hopefully in another country. Part of the IMBES mission is to design programs that promote transdisciplinary thinking which is useable and translatable, but which is spurred on through international and global exchange. We close this book with a reminder of why MBE’s special role in academics is shaped by these three core pillars.

CHAPTER 8 MIND, BRAIN, AND EDUCATION SCIENCE: AN INTERNATIONAL, TRANSLATIONAL, AND TRANSDISCIPLINARY PERSPECTIVE

By definition, a child is a young person below the age of adolescence. However, as anyone who has ever been a child likely knows, a child is so much more than this simple definition. A child is a young person below the age of adolescence who has wishes, thoughts, desires, fears, likes, dislikes, experiences, a life history, worldviews, and complexities beyond imagining. Similarly, while by definition Mind, Brain, and Education science is “a careful selection of only the best information [from neuroscience, psychology, and education] that can inform the new science of teaching and learning. The development of MBE science results in a new and innovative way to consider old problems in education and offers evidence-based solutions for the classroom” (Tokuhama-Espinosa, 2011, 4), there are many complexities underlying this definition. As a transdisciplinary science, MBE intertwines principles and concepts from several disciplines and sciences such as psychology, neuroscience, education, biology, chemistry, mathematics, sociology, anthropology, and philosophy to better understand not only the human learning process but also what that means for teaching and the learning-teaching dynamic. The survey conducted in 2020 by Tokuhama-Espinosa, Nouri and Daniels counted on the participation of experts identifying with 19 different fields, including but not limited to philosophy, mathematics, educational administration, physiology, cognitive neuroscience, neuropsychology, clinical psychology, public policy, and education, evidencing the transdisciplinary nature of Mind, Brain, and Education science. Another key characteristic of Mind, Brain, and Education science is that is an international discipline. MBE has not emerged as the result of isolated efforts from a single country; on the contrary, through the ages, it has come to be due to individual and collaborative efforts of scholars and laymen alike from around the world. From its earliest history, MBE is rooted in the contributions made by great thinkers in ancient civilizations like Egypt,

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China, Greece, Rome, Persia, and India, to name a few, and modern regional efforts like those in the United States, Europe and Latin America. Today, MBE continues to be an international discipline as evidenced by the 2020 survey which was led by three investigators in three different countries, and which had the participation of experts from 29 different countries (see Appendix C), and this book with three different researchers, one from the Middle East, one from the United States, and one from Latin American. Finally, Mind, Brain, and Education science is a translational discipline. MBE has come about as the culmination of thousands of years of human curiosity about how people learn and what that means for the teaching and learning dynamic. As a translational discipline, MBE does not seek to answer questions about teaching and learning by focusing only on information emerging in the laboratory setting. Instead, it seeks to involve researchers, practitioners, and the wider community, to “translate” findings from the laboratory into the classroom and from the classroom into the laboratory.

Aims of Education from a Mind, Brain, and Education Science Perspective From a Mind, Brain, and Education perspective education has at least six main aims as suggested by the 2020 international participants (Tokuhama-Espinosa, et al., 2020; Tokuhama-Espinosa and Nouri, 2020) which are summarized in Table 8-1. One aim of education from an MBE perspective is to develop translational and transdisciplinary approaches to research and education where scientists, teachers, and policymakers use what we know about the teaching and learning dynamic to improve education. The second aim of education from an MBE perspective is to move towards becoming evidence-informed and grounded on scientific research. It also seeks to offer a more comprehensive view of education to practitioners, researchers, and policymakers so that they may shift from a vision where education is a one-way transmission of knowledge, skills, and attitudes, to a consideration of the individual and their context as a whole. Additionally, it aims to bring the mind-body connection to the forefront of educators’ understanding. The fifth aim of education from an MBE perspective is to help improve teacher education and professional expertise. Finally, it seeks to maximize the potential of every learner through better teaching.

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Table 8-1. The Six Main Aims of Education Based on Mind, Brain, and Education Science Identified by the Participants in the 2020 Survey What are The Main Aims of Education Based on Mind, Brain, and Education Science? 1. To develop translational and transdisciplinary approaches to research 2. To ground education in scientific research 3. To offer a more comprehensive view on education-to-education practitioners, researchers and policy makers 4. To better understand the mind-brain connection 5. To enhance teacher expertise 6. To maximize the potential of every learner To meet all these aims requires the concerted efforts of MBE professionals from around the world. This book offers a brief but critical look into the past, present, and future of Mind, Brain, and Education science in light of the existing initiatives and concerns. According to TokuhamaEspinosa (2010), MBE science had experienced a pendulum swing. From the time of the Greeks through the Decade of the Brain in the 1990s there was a demand to ground teaching in science, or more specifically, in information about the brain. Around the start of the 21st century, there was a change, however. Many scientists reminded the discipline that it was “losing its mind in favor of the brain,” (Siegel, 1999, xii) and that a move toward “biological determinism” (Allen, 1984, 141) was unbalanced, at best, and dangerous, at worst. These observations returned a more human face to the emerging discipline and demanded a happy medium between research and practice as well as between the laboratory and the classroom. This pendulum swing brings the balance back to the middle and values both the science as well as the art of teaching. At present, there are peer-reviewed scientific journals, academic societies, graduate programs, conference series, forums and special interest groups that all exemplify the vitality and dynamic advancements of the discipline (KaygÕsÕz, 2022; Nouri, 2013; Nouri and Mehrmohammadi, 2014). To continue to grow and thrive, scholars are encouraged to review history and use this knowledge to project the future trajectory of MBE. In the best-case scenario, MBE will continue to grow in popularity (membership), research (new combined MBE methodologies), scope (add “health” to its foundations), and influence (policy-wise). We also anticipate that transdisciplinary research, along with complexity theory and radical neuroconstructivism, will further broaden the scope of MBE to include health and a greater role

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for artificial intelligence and algorithmic thinking (Wenjie et al., 2021). Several programs around the world from the United States. (e.g., MIT’s Integrated Learning Initiative), Germany (e.g., German Aerospace Center) and Japan (e.g., the University of Kyoto) are establishing firmer links between what can be known about human thinking and what can and cannot be carried over into the future of AI-assisted learning. We also anticipate that the growing international vision will be strengthened by easier transnational cooperation (such as seen in this book with authors from Iran, the United States, and Ecuador working together). Furthermore, we sense that as more concrete, evidenced-based results are confirmed using MBE interventions, greater standardization of research paths and the formalization and professionalization of MBE scientists will increase.

Leaders in Mind, Brain, and Education Science Over the past 20 years, there has been growing consensus about where Mind, Brain, and Education should head, who should lead, and what should be taught to teachers. While the role of the regulatory body is clear, who should lead remains open. In the past, the International Mind, Brain, and Education Society has been a promising venue for supporting faculties of education throughout the world to systematically incorporate training in both MBE and Educational Neuroscience into their curricula. Blake and Gardner (2007) suggest that The future of the field clearly lies in the hands of those students and young scholars who are motivated to undertake fresh lines of research as well as interventions that hold promise. A major vehicle for attracting such students is the courses that are being offered at colleges and universities. As the courses improve, the quality of researchers and practitioners is likely to be enhanced; and these full-blown neuroeducators will, in turn, contribute to further improvement in curricula and pedagogy (61).

MBE departments should train future teachers on the formulation and implementation of new learning interventions. The role of IMBES in supporting the direction of newer programs in established institutions has yet to be exploited as both IMBES and universities appear to be waiting for the other to make the first move. Bold leadership on both sides is needed to advance the conversation. Should IMBES serve as a regulatory body? This has been discussed for years by the Board and rejected time and again as IMBES does not see itself as reprimanding, but rather inspiring interest in MBE. Should IMBES offer a seal of approval to “good programs” or “recommended literature” or facilitate “bridging research to practice”?

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These ideas have also been debated for years without resolve. Some have argued that in its goal to remain neutral, IMBES risks becoming irrelevant. The area of least resistance appears to be related to promoting research opportunities. Should IMBES help broker scientist-teacher relations? The belief has always been a resounding yes, but the mechanisms by which this should occur have been less than definitive. Schools, the perfect settings for testing specific interventions, have yet to foster learning communities that empower teachers to actively engage in MBE research projects. To remedy this divide, the EARLI Special Interest Group on Education and Neuroscience formed a working team in 2018 to create an online brokering service to join researchers with schools and teachers. The prototype is currently being tested, and shows promise, suggesting that bodies other than IMBES may lead the way to better communication between actors in the discipline. One area IMBES has had no trouble supporting is in calling out the negative influences of neuromyths. As in other moments in the historical evolution of the discipline, it appears that it is easier to say what incorrect information is rather than to make proactive suggestions for precise teaching interventions. This is changing, slowly but surely, however. Teaching interventions that appear to leverage neuroscience to improve teaching and learning based on evidence are rare, but when they become established, IMBES embraces them as well. The advancement of technology has changed our understanding of brain functions, and in turn, influenced educational thought and practice. An understanding of the role of the senses in all learning took more than 1,200 years to take hold. Belief in humours that determined the quality of life and learning existed for 1,000 years. The belief in “localizationism” and skillsets being in a specific part of the brain rather than in networks lasted for 500 years. Phrenology lasted 100 years. While the shelf-life of neuromyths appears to be shortening, there are still many misunderstandings about the brain yet to be refuted by science (Scurich et al., 2014; Tokuhama-Espinosa, 2019). This suggests that much of what we now believe to be true may not be so accurate in the future (Bergen and Coscia, 2001) as technology advances and our understanding of the brain improves. Additionally, the greater integration of increased technology adds a new factor to the discipline, suggesting that the maturity of Mind, Brain, and Education has yet to be completed. The development of the discipline continues to grow due to the speed of access, the number of people conducting research, intellectual generosity, and the increased formalization of Mind, Brain, and Education science. This leads to an important pattern seen in the history of the learning sciences. The history of science shows that many interesting yet unsustainable hypotheses are usually put forward

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before good hypotheses are proven (Tokuhama-Espinosa, 2019). Heartcentric visions of human learning turned into brain-centric, then neuroncentric theories, and will likely continue to be refined as technology deciphers the more than 350 different neuronal cell types in the brain identified in 2019 (Cervantes, et al., 2019). Right-brain/left-brain ideas and belief in superior races due to eugenics have ceded space to lab school measurements of student brain functioning to dispel multiple neuromyths. While history is riddled with hypotheses that were proven wrong over time, it is clear that outright rejection of ideas can prolong acceptance and integration and slow the pace of scientific advancements. Neither blind faith acceptance nor immediate rejection seems appropriate where science is concerned. Aristotle’s understanding of the role of sensory perception in learning took hundreds of years to take hold, as did Robert Hooke’s “cell theory” because they were considered wild hypotheses at the time of their inception but are now the cornerstone of modern theory. This points to the necessity of researchers to be open to new ideas but also to be cautious while expediently vetting those new ideas. The history of MBE indicates that it usually falls on the personal responsibility of society members as both idea generators as well as gatekeepers to advance the discipline at a steady pace as well as to call attention to issues worthy of policy change (Chiong, 2020). Unlike other civil society institutions in which playing the judge, jury and sentence-maker is condemned, academia is one of the few structures in which the inception, promotion, and survival-destruction of its products depend on individuals who are often in competition with one another. One new up-and-coming concept that may test the fragile structure of idea acceptance relates to algorithmic thinking models and artificial neural networks (Pardos et al., 2019).

Moving Forward The history of MBE is long and fascinating, and knowing where we have come from can point us in the direction we should be headed. Advancements, even in the past decade, are notable. Between 2007–2017 experts celebrated that MBE had grown in terms of (a) better research tools; (b) discoveries about the brain; (c) improvements in teacher education and public knowledge about the brain; (d) improvements in communication mechanisms; and (d) increased opportunities to learn about the brain thanks to growing academic programs. Progress in these areas continues to snowball along with the expansion of the MBE transdisciplinary science, promising further growth in the coming decades.

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After reviewing 5,000 of history, it is clear that MBE science is still a very young discipline. Its history tracks a parallel development around the world borne out of studies in psychology, education, and neuroscience, which eventually became a single transdisciplinary vision and a development that became an integrated effort in the 1990s and a new academic discipline around 2004–2006 (Tokuhama-Espinosa, 2008, 2010). When viewed through this holistic lens and with hindsight, the evolution of MBE shows an ever-increasing interplay between neuroscience and psychology with educational practice. The overarching umbrella of the learning sciences that includes MBE science reinforces the benefits of transdisciplinary thinking, international cooperation, and a progressively complex appreciation of the teaching-learning dynamic. However, history is merely that, “his” story, meaning it is open to interpretation. Despite basing the conclusions on solid research, the interpretation of the findings is the choice of the authors. This points to a final lesson from the history of science, which is that it is hard to write history when you are in the middle of making it. Several important historical advances were all but ignored in their time, simply because their impacts could not yet be felt, or their historical relevance in the evolution of the discipline was not visible. Mind, Brain, and Education science is and will remain an evolving discipline for generations to come. This means this first draft of history serves to document, but not to define, the discipline. Knowledge from the past widens our imaginations to establish conceptual frameworks of the discipline. For example, in a new incarnation of Dewey’s original idea of laboratory school, Schwartz and Gerlach (2011) suggest “The Research Schools Network” as a framework for realizing the MBE mission of creating useable knowledge, identifying educational challenges, developing experimental methodologies and ethics, clarifying research ¿ndings, interpreting conclusions, and monitoring suitable applications of results. Further building off these ideas, the Brain and Behavior labs were developed by Pankaj Sah at the University of Queensland to observe changes in specific neural mechanisms as children learned in real time (see https://qbi.uq.edu.au/), and Ido Davidesco in the University of Connecticut now goes into regular classrooms with wearable technology (Davidesco et al., 2021), an idea only dreamed about a mere decade ago. The past can, indeed, inform the future. We invite the reader to reflect on their role in this continual development of the emerging Mind, Brain, and Education science. Rome wasn’t built in a day and disciplines are not built in decades. It will take individual, institutional, and national initiatives to move Mind, Brain, and Education science forward, and with it, improve the likelihood of fulfilling its research,

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practice, and policy goals that will contribute to better human teaching and learning.

APPENDIX A MIND, BRAIN, AND EDUCATION SCIENCE RESEARCH, PRACTICE AND POLICY GOALS

The Delphi panel (2017) also ratified a set of research, practice and policy goals, by amending an initial set of the same from 2008. As edited in 2017, these goals are as follows.

Research The RESEARCH goals of the emerging discipline of Mind, Brain, and Education Science are to: a. Establish a working understanding of the dynamic relationships between how the brain processes and organizes information and constructs new learning, and how we educate. b. Study how the developing, changing structures and functions of the brain contribute to education and learning across the lifespan. c. Study relationships between human development and the biology of the brain, including the genetic contributions to individual factors that can influence plasticity and the parameters of critical/sensitive periods. d. Develop, implement and assess interventions of neuroscientific and cognitive scientific determinants of typical and atypical learning and test them in the field of education according to evidence-based principles. e. Study how biopsychosocial factors (such as sleep, nutrition, physical exercise and stress) can modulate learning and can influence teaching. f. Study context and psychosocial factors (such as socioeconomic factors, levels of parental education, intellectually stimulating environments, and culture) as they interact with biological influences on learning, including those in actual classroom settings.

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g. Determine how and why certain pedagogical practices are successful. h. Study teaching and learning through transdisciplinary, mutlidimensional relationships that are meaningful for advancing scientific knowledge and educational practice by establishing better research ties including, but not limited to, those among educators, psychologists and neuroscientists and among the fields of educational psychology, teacher education and neuroscience. i. Study the best ways to help teachers and students understand what is currently known about brain mechanisms and learning processes. j. Study life-long learning in the context of ‘the developing teacher,’ including how teacher self-efficacy impacts students learning; how teacher experience contributes to classroom experiences; what changes in information processing occur in teachers at different ages; how humans develop their capacity to teach; how brains are changed in the teaching process; how motivation to teach influences learning outcomes; and how the biopsychology of teaching influences learning. k. Study how human self-regulation, metacognition and thinking skills can be best developed by applying evidence from psychology and neuroscience.

Practice The Practice goals are to: a. Align teaching with how human beings are biologically and psychologically organized for learning, taking into account individual variation. b. Reciprocally connect research with practice on processes of learning and teaching. c. Systematically apply neurobiological and psychological principles to the theory and practice of education. d. Study and evaluate how findings from research in neuro -and cognitive sciences can support educational theory and practice, including field research across the spectrum of abilities related to brain development and learning. e. Use research findings in cognitive neuroscience and psychology to develop field research in classrooms that will inform the development of new educational theory, policy, and practice.

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f. Use successful classroom experiences and questions proposed by teachers as points of departure for continued research in the learning sciences. g. Teach pre-service and in-service educators about neuromyths and how to be critical consumers of brain research claiming educational application. h. Consider all levels of analysis, including student voices as well as laboratory research findings when making instructional decisions. i. Increase the dialogue between neuroscientists and teachers. a. Help improve teachers’ and other stakeholders’ literacy of basic neuro and cognitive science, including the limitations of current knowledge and methods of inquiry; thereby helping them to differentiate valuable science from neuromyth. b. Help neuroscientists, psychologists and other MBE researchers understand the complexities of real classrooms and real students. j. Apply evidence-based practice to improve teachers’ understanding of why and how affect plays a role in learning. k. Apply evidence-based practice to improve teachers’ understanding of the importance of teaching subjects based on hierarchical organization, neuroconstructivism and developmental neuroscience. l. Apply evidence-based practice to improve teachers’ understanding of why and how different memory systems are vital to learning. m. Apply evidence-based practice to improve teachers’ understanding of how to leverage different attention systems for better learning. n. Apply evidence-based practice to improve teachers’ understanding of social cognition and social contagion. o. Promote the translation of research findings among neuroscientists, psychologists and educators. p. Co-construct scientific practices appropriate for the classroom within the MBE framework. q. Leverage the knowledge of teachers to enhance collaborative research with neuroscientists and psychologists.

Policy The Policy goals of MBE as stated by the Delphi panel in 2017 are as follows: Inform educational policy and practice with research on the science of learning, including helping policymakers understand the limits of brain research and the need for teachers and students to understand what we know and do not know about the brain.

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a. Improve the efficiency and validity of educational policies, both for normal and at-risk children, by relying on scientific principles of how the learner’s brain/mind operates, both for the design and for the evaluation of education strategies. b. Continually encourage the pursuit of neuroscientifically substantiated beliefs founded in educationally-inspired research questions, the results of which have potential application to educational practice or thought. c. Discourage the pursuits of brain-based beliefs not supported by the evidence (neuromyths). d. Provide neuroscientists with the opportunity for direct experiences in educational settings. e. Require courses for all pre-service and in-service teachers that would improve their literacy in neuro -and cognitive sciences. f. Offer definitions of evidence-based practice/theory/information and guidance on how to evaluate and use such information. g. Inform educational policy and practice with research on the science of learning with particular reference to changes in learning capacities from the very earliest years throughout childhood and into adulthood and old age. h. Provide the opportunity for teachers to learn about neuroscience and the scientific method to assess the quality of research. i. Suggest that those interested in Mind, Brain and Education Science learn about all three parent (neuroscience, psychology and education) and related fields independent of the original field of academic formation. j. Do No Harm.

APPENDIX B GLOSSARY OF MIND, BRAIN, AND EDUCATION TERMS

Developed in 2010 with Daniel Ansari, Sashank Varma and Tracey Tokuhama; updated in 2014 by Julia Volkman.

Acetylcholine

Action potential

Active learning

Affect and learning

Affective neural network

A neurotransmitter that activates muscles and is a major neurotransmitter in the autonomic nervous system; associated with memory. Measure in excitable cells that indicate the transfer of knowledge; often referred to as a nerve impulse, spike, or the “firing” of the membrane. Discovery learning in which the proponent of the learning is the learner herself (as opposed to the teacher); often includes physical movement. The interaction between feeling or emotion and learning. Medial brain regions are where we process and generate emotions. This network drives our attention. When people are emotionally engaged in learning, they are better able to translate that learning to real world applications. People are more likely to remember emotional events. Deep engagement and interest with a subject matter can empower us to overcome severe deficits or learning obstacles.

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Amygdala

Angular gyrus Anxiety and learning Autotelic experience Attention and learning

Authentic assessment

Axon

Basal ganglia

Behaviourism

Brain development Brainstem

Broca’s area

Appendix B

Almond-shaped groups of neurons (one in each lobe) located in the medial temporal lobes and part of the limbic system related to the processing of emotional memory. Brodmann area 39 located in the parietal lobe involved in language and cognition. The interactions between the physiological, cognitive somatic, emotional and behavioral states and impact on learning Synonymous with the Flow experience The cognitive process of selectively concentrating on a single aspect of one’s surroundings while ignoring other things. Evaluation methods that measure significant learning experiences; often mentioned in contrast to typical multiple-choice tests. A long, slender projection of a nerve cell, or neuron that conducts electrical impulses away from the neuron’s cell body. A group of nuclei in the brain interconnected with the brainstem, thalamus, and cerebral cortex related to motor control, cognition, emotions and learning. A philosophy of psychology in which learners are analysed through the experimental analysis of their behaviours. The cellular and molecular mechanisms by which the nervous system emerges throughout life. The lower part of the brain, adjoining and structurally continuous with the spinal cord. Area in the brain associated with language processing, speech or sign production and comprehension located in the inferior frontal gyrus of the left frontal lobe.

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Cerebellum

Cerebral cortex

Cerebral hemispheres

Chunking of information

Cingulate gyrus Cognition

Cognitive development

Cognitivism

Consciousness

Constructivism

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Area of the brain related to sensory perception, motor control equilibrium, attention and motor learning located in the inferior posterior portion of the head. Grey matter the brain enveloping the surface of the brain that plays a role in memory, attention, perceptual awareness, thought, language and consciousness. The two regions of the brain that are united by the corpus callosum and delineated by the body’s median plane (left hemisphere and right hemisphere). Strategy in cognitive psychology and mnemonics in which more efficient use of short-term memory is achieved through recoding of information. An integral part of the limbic system in the medial part of the brain which is involved with emotion formation and processing, learning, memory, and executive control. Thinking, information processing. A theory in cognitive psychology, which concerns the growth of intelligence, which for some means the ability to accurately represent the world and to perform logical operations on representation of concepts, grounded in interactions with one’s surroundings. A psychological approach to understanding the mind, which supposes that mental functions can be understood through scientific methods. A state of subjective experience that involves thoughts, sensations, perceptions, moods, emotions, dreams and an awareness of self. A theory of learning in which new knowledge is built upon past experiences.

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Cooperative learning activities

Corpus callosum

Cortex Cortisol Critical period

Critical thinking (higher order thinking skills)

Declarative knowledge

Dendrites

Differentiated instruction Direct Instruction Divergent thinking

Dopamine

Appendix B

The purposeful mixing of often heterogeneous groups of students for the purposes of enhanced learning experiences. A structure connecting the right and left cerebral hemispheres which is the largest white matter structure in the brain responsible for inter-hemispheric communication. The outer most layer of the brain, divided into motor, prefrontal, visual and cerebellar regions. A hormone normally associated with stress. A limited time that an event can occur, usually resulting in transformations or changes in behaviour. Mental processes of analysis, evaluation, discernment, interpretation, inferences and self-regulation; considered by many as one of the most important goals of education. Awareness and understanding of factual information about the world; often considered knowing what in contrast to knowing how. The branched projections of a neuron that conduct the electrical stimulation received from one neural cell to the cell body of another. Individual instructional strategies based on the needs of diverse learners. Explicit teaching methods, including lectures. Thought processes or a method of thinking in which idea generation, creativity, problem solving or innovation results. A hormone and neurotransmitter related to cognition, motor activity, motivation and reward, inhibition sleep, mood, attention and learning.

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Knowledge is not linear. Over time, it is built, falls apart, and is reconstructed. This cycle of predictable advances and declines repeats until we achieve mastery. Repetition and support (e.g., from teachers, peers, Dynamic skill development books) aids in developing mastery of a topic. When we are supported, performance improves. We can increase the level of support offered by allowing and encouraging learners to build peer relationships. A form of validity in a study or experiment in which the methods, materials, subjects Ecological validity and settings of an experiment must approximate the real-life situation that is under study. A brain imaging device to measure the EEG electrical activity produced by the brain (Electroencephalograph) recorded by electrodes placed on the scalp. The ability, capacity or skills to perceive, Emotional intelligence assess and manage one’s emotions. Emotions and learning See affect and learning. The process of transforming information Encoding from one format to another. Polypeptides produced in the pituitary gland Endorphin during exercise, excitement and orgasms, resembling opiates. The study of the development of an organism as influenced by and influencing Epigenetics the activation and deactivation of genes without any change in DNA sequence Memories that refer to events, times, places Episodic memory and their associated emotions. Systems in which competing influences are Equilibrium/disequilibrium balanced or in which a dynamic working balance exists among interdependent parts. Brain imaging technique that measures the Event-related potentials electrophysiological response to a stimulus (ERPs) related to thought or perception.

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Executive functions

Experiential learning (hands-on learning/discovery learning) Explicit learning

Appendix B

Cognitive control in which the brain processes thought and behaviour in accordance with internally generated goals; often known as the “control centre” of the brain. Inquiry-based learning.

Making meaning from direct experience. The conscious, intentional recollection of Explicit memory previous experiences and information. Brain imaging technique that measures the fMRI (functional magnetic hemodynamic (blood flow and oxygenation) resonance imaging) responses related to neural activity in the brain or spinal fluid. A self-reflective process in which teacher Formative assessment feedback is used by the learner for improvement. Located at the front of each cerebral Frontal lobe hemisphere and related to executive functions. The complete genetic information of an Genome organism typically represented by the four Taco Bell ingredients/building blocks of DNA Situations in which a student feels secure, Good learning respected, has a degree of self-regulation, environments paced challenge, active learning, and receives feedback. Grey matter Neuronal cell bodies; See cerebral cortex A type of non-associative learning in which there is increased repetition of a stimulus Habituation results in a progressive decline of behavioral response probability.

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Hormones Imagery Imitation Impact of self-efficacy on learning

Implicit learning

Inhibition, memory

Innate Interference theory

Learning by teaching

Learning styles Levels-of-processing framework

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Part of the forebrain located in the medial temporal lobe and belonging to the limbic system; plays a role in short term and working memory and spatial navigation. Also associated with long-term memory consolidation. Chemical messengers that carry signals from one cell to another. The invention or development of mental representations in the mind to reflect experience. A behaviour in which an individual replicates another’s actions. An understanding of how a teacher’s belief that he has the capabilities to execute actions required to teach impact a student’s learning itself. Unannounced and often passive learning experiences in which exposure to information results in learning (as opposed to overt, explicit or active learning processes). The ability not to remember irrelevant information, which is an effective aspect of functional memory. Innate (intrinsic) motivation needs no external incentives; associated with high educational achievement. A theory of forgetting; certain things interfere with the recall of others. Classroom activity in which the student-asteacher structure improves the learning process. Based on Seneca’s idea “by teaching we are learning.” A method of teaching in which individual’s particular learning preferences are taken into account. Memory recall of stimuli is a function of the depth of mental processing.

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The name for the joint reference to the hippocampus, amygdala, anterior thalamic Limbic system nuclei and limbic cortex, related to emotions, behaviour and long-term memory. Memory stored as meaning that can last between a few days to decades, differing Long-term memory structurally and functionally from working memory and sort-term memory, related to the natural forgetting process. The long-lasting enhancement in Long-term potentiation communication between neurons that results from simultaneous stimulation. The process by which information, which Memory consolidation and enters short-term or working memory, is learning crystallized into long-term memory. Awareness or knowledge of one’s own cognitive processes and the use of selfMetacognition awareness to self-regulate these cognitive processes. The scientifically substantiated art of teaching, or the confirmation of best Mind, Brain, and pedagogical practices with studies on the Education science human brain. Also known as educational neuroscience, neuroeducation, and in the popular press as brain-based learning. When we perceive (by any sense) that someone else is doing something, the motor network in our brain becomes active in the same way as if we were doing it ourselves. Mirror neurons As such, imitation is an important aspect of learning. Learning is facilitated when we demonstrate in context what we are teaching. If our actions do not match our instructions, learning is more difficult. The reason(s) for engaging in a particular Motivation behaviour. Area of the cerebral cortex involved in Motor cortex planning, control and execution of voluntary motor functions.

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Myelin

Negative transfer, knowledge Neural network Neurobiology

Neurochemistry Neuroeducation Neuroethics Neurogenesis Neuron

Neuroplasticity

Neurotransmitter Occipital lobe Parallel processing

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Myelin is an insulating layer, or sheath that forms around nerves, including those in the brain and spinal cord. It is made up of protein and fatty substances. This myelin sheath allows electrical impulses to transmit quickly and efficiently along the nerve cells [Medline Plus]. The applicability of knowledge to a new domain in an incorrect fashion. Circuits of neurons The study of cells of the nervous system and the organization of these cells into functional circuits that process information and mediate behaviour. A branch of neuroscience devoted to the study of chemicals. See Mind, Brain, and Education science. A subcategory of bioethics related to neuroscience. The process by which neurons are created. Excitable cells in the nervous system that process and transmit information. Refers to the changes that occur in the organization of the brain as a result of experience; Young children (before age 6) have dramatically changed brains—their plasticity is effortlessly induced. Older humans have slower changing brains—to induce plasticity as we age, requires greater effort and repetition but it is possible to invoke plasticity throughout the lifespan. Chemicals that are used to relay, amplify and modulate signals between neurons. The visual processing centre of the brain located in Brodmann area 17. The ability of the brain to simultaneously process incoming stimuli.

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Parietal lobes Peptides PET (positron emission tomography) Plasticity

Prefrontal cortex

Primacy-Recency effect (serial position effect) Priming Problem-based learning activities Procedural knowledge (memory)

Pruning

Reasoning

Appendix B

Area of the brain superior to the occipital lobe and posterior to the frontal lobe that is responsible for sensory information related to spatial sense and navigation. The link between amino acids. A nuclear medicine imaging technique which produces a three-dimensional image or map of functional processes in the body See neuroplasticity The anterior part of the frontal lobes of the brain, lying in front of the motor and premotor areas implicated in planning complex cognitive behaviours, personality expression, and moderating correct social behaviour. Recall accuracy is highest for items presented first, last, then those in the middle. A teaching technique by which a stimulus is used to sensitize students to a later presentation of the same stimulus. A student-cantered instructional strategy in which students work together to find a collaborative solution. The knowledge of how to perform some task The autopsies (reabsorption) of dendritic and axonal pathways that suffer from underuse; a healthy aspect of a developing brain that is overcrowded with neural pathways (if development has proceeded typically) and, thus, inefficient at communication; neural proliferation and pruning occur throughout life but to a greater extent in childhood. The cognitive process of looking for beliefs, conclusions, actions or feelings often by using introspection.

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Recognition neural network

Retrieval, information

Scaffolding

Schemas

Self-concept Self-directed learning

Self-efficacy Self-empowerment Semantic memory Sensitive period Sensory store (short-term store)

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“What is being taught?” There is a network of lateral and posterior brain regions that we use to receive and interpret input from our senses. To activate this network, we can: Ɣ Provide varied sensory input (e.g., visual, auditory, kinaesthetic) Ɣ Present the same information in different ways Assist learners in internalizing new perceptions (e.g., active memorization, pausing) Memory recall. Helpful interactions between instructors and learners, or between children who have different levels of knowledge about a topic, to provide sufficient support for achievement. A mental structure that represents an individual’s view of the world; an organized network of knowledge devised in abstract mental structures. The way in which one views oneself, based in terms of self-assessment of feelings An instructional practice in which the learner is given latitude to structure (in part) his own didactic experiences. Belief that one is capable of performing in a certain way and/or of attaining certain goals. Personal self-image or transformation in which one feels capable. Memory of meanings, understandings, and other concept-based knowledge unrelated to specific experiences. Important periods in childhood development important to acquire certain abilities. Very short-term form of memory that holds sensory input for a few seconds.

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A neurotransmitter in the central nervous system which plays an important role Serotonin modulating anger, aggression, body temperature, mood, sleep, sexuality and appetite. Short-term memory See sensory store How people process social information Social cognition based on existing mental schema. An instructional practice designed to use Social-Emotional Learning social interaction and emotional connections (SEL) to information to enhance learning experiences. Parameters that (a) define common terminology accepted in the field; (b) determine the rules for evaluating quality Standards information; (c) confirm how producers, users and receivers of Mind, Brain, and Education science information are defined and how they are treated. an agent (such as an environmental change) that directly influences the activity of a living organism or one of its parts (as by Stimulus exciting a sensory organ or evoking muscular contraction or glandular secretion) [Merriam Webster Dictionary] Reason(s) behind student behaviour often based on needs (including acceptance, food, Student motivation desired object, goals, state of being, ideas, etc.) Educational approach in which the student Student-cantered learning is the protagonist of the learning activity. Evaluation that refers to assessment of the Summative assessment learning and summarizes the development of learners at a given stage of instruction. Specialized junctions through which neurons signal to each other and to nonSynapse neuronal cells such as those in muscles or glands. Synaptogenesis Formation of synapses.

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Temporal lobe

Theory of Mind

Transcranial magnetic stimulation Vigilance

Wernicke’s area

White matter

Working memory

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Part of the cerebrum, involved in speech, memory, and hearing, located beneath the lateral Sylvian fissure. A specific cognitive capacity to attribute mental states to oneself and others in order to understand that others have beliefs, intentions, desires, etc., different from one’s own. A non-invasive method to excite neurons in the brain and measures changing magnetic fields (electromagnetic induction) The process of paying close and continuous attention; watchfulness. Area of the brain encircling the auditory cortex on the Sylvian fissure (Brodmann area 22), located in the left hemisphere and related to receptive language comprehension. The tissue through which messages pass between different areas of grey matter within the nervous system, composed of myelinated nerve cell processes, or axons; Myelinated axons; see myelin Processes used for temporarily storing and manipulating information dependent on the frontal cortex, parietal cortex, anterior cingulate, and parts of the basal ganglia

APPENDIX C EXPERTS INVITED TO PARTICIPATE IN THE 2020 INTERNATIONAL SURVEY1 ON WHAT WE HAVE LEARNED FROM MIND, BRAIN, AND EDUCATION SCIENCE

Ackerman

Philip

Albro

Elizabeth

Aldrich

Richard

Alvarez

Doris E.

1

Philip Ackerman, professor at Georgia Institute of Technology. His research spans several related research areas of differential, educational, cognitive, applied experimental, and industrial and organizational psychology, the nature of adult learning, personality, and motivation. Current research projects focus on physiological correlates of cognitive effort and fatigue. Elizabeth Albro, Institute of Education Sciences. Commissioner of Education Research. Specialty in Reading and Writing. Richard Aldrich is Professor at the University of London and researches neuroscience, education and the evolution of the human brain. Doris E. Álvarez is Director of the Educator Network in San Diego, CA. Dr. Alvarez’s distinguished educational career includes being named National Principal of the Year by the National Association of Secondary School Principals in 1997.

This is list is accurate through March 2020 when the list was compiled.

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Greg Anderson is the Dean of the College Gregory M. of Education, Temple University. Founding member of Deans For Impact. Dr. Anderson has advanced the college’s prominence as a national centre of excellence in research and teaching. Mike Anderson is a Professor of Psychology and Director of the Anderson Mike Neurocognitive Development Unit in the School of Psychology at the University of Western Australia. His research is based around his theory of intelligence and development and focuses most recently on the influence of the developing brain on intellectual functions in children O. Roger Anderson is Chair of the Department of Mathematics, Science and Anderson O. Roger Technology at Teachers College and a Senior Research Scientist at Columbia University, New York. His research in education has particularly focused on cognitive and neuroscientific perspectives on teaching and learning, especially in science education. Daniel Ansari is a Professor and Canada Research Chair in Developmental Cognitive Ansari Daniel Neuroscience in the Department of Psychology and the Brain and Mind Institute at the University of Western Ontario in London, Ontario, where he heads the Numerical Cognition Laboratory He is the former President of the International Mind, Brain, and Education Society. Cora Bagley Marrett is the Chair in the Bagley Marrett Cora Department of Sociology, University of Wisconsin–Madison. She is a Fellow of the American Academy of Arts and Sciences and the American Association for the Advancement of Science. Anderson

Appendix C

138

Bandura

Albert

Barkley

Jordan

Baron-Cohen

Simon

Basile

Carole

Albert Bandura OC is a CanadianAmerican psychologist who is the David Starr Jordan Professor Emeritus of Social Science in Psychology at Stanford University. Bandura has been responsible for contributions to the field of education and to several fields of psychology, including social cognitive theory, therapy, and personality psychology, and was also of influence in the transition between behaviourism and cognitive psychology. He is known as the originator of social learning theory (renamed the social cognitive theory) and the theoretical construct of self-efficacy, Jordan Barkley is the Dean at the College of Education, Tarleton State University. Member of Deans For Impact. Jordan Barkley currently serves as a dean of the College of Education and a professor of Curriculum and Instruction at Tarleton State University, where he, along with his associate deans, provides leadership for the departments of Curriculum and Instruction, Educational Leadership and Technology, Psychological Sciences, and the School of Kinesiology. Simon Baron-Cohen is Professor of Developmental Psychopathology, University of Cambridge, a Fellow at Trinity College and Director of the Autism Research Centre in Cambridge. He is a Fellow of the British Academy, VicePresident of the National Autistic Society, and President of the International Society for Autism Research. He was Chair of the NICE Guideline Development Group for Autism (Adults) and is co-editor in chief of the journal Molecular Autism. Carole Basile is the Dean of the Mary Lou Fullerton Teachers College at Arizona State University. Member of Deans For Impact.

Crossing Mind, Brain, and Education Boundaries

Battro

Antonio

Bauer

Patricia J.

Bavelier

Daphne

Beamon Crawford

Glenda

Begley

Sharon

139

Antonio M. Battro is a medical doctor and psychologist, graduated from the University of Argentina (medicine) and Paris (psychology). He also studied math and logic in Freiburg. Founding member of IMBES and second President. Patricia J. Bauer is a professor in the Department of Psychology, Emory University and serves as Senior Associate Dean for Research in Emory College. Her research focuses on the development of memory from infancy through childhood, with special emphasis on the determinants of remembering and forgetting; and links between social, cognitive, and neural developments and age-related changes in autobiographical or personal memory. Daphne Bavelier is a professor at the University of Geneva, who studies cognitive neuroscience. She obtained her PhD in Brain and Cognitive Sciences from the Massachusetts Institute of Technology, Boston, MA and trained in human brain plasticity under Helen Neville at the Salk Institute. Her lab investigates how new media, such as video games, can be leveraged to foster learning and brain plasticity. Glenda Beamon-Crawford is the author of Brain-based teaching with adolescent learning; Managing the adolescent classroom; Differentiation for the adolescent learner Sharon Begley is an American journalist and scientific writer. Her topics include the neuroplasticity of the brain, issues affecting science journalism, education, and other topics she has researched during her career. She has appeared on radio and television to discuss the topics covered in her articles and books.

Appendix C

140

Bell

Philip

Bergen

Doris

Berkman

Elliot

Berninger

Virginia

Bernstein

Jane Holmes

Philip Bell is professor in the Learning Sciences and Human Development, University of Washington and is executive director of the UW Institute for Science and Math Education. He studies everyday expertise and cognition in science and health, the design and use of novel learning technologies in science classrooms and has a background in human cognition and development, science education, computer science, and electrical engineering. Doris Bergen is Distinguished Professor Emeritus of Educational Psychology at Miami University in Ohio and author of Brain Research and Child Education. Elliot Berkman is an Associate Professor of Psychology at the University of Oregon. His research is about the motivational and cognitive factors that contribute to success and failure real-world goals, as well as the neural systems that support goal pursuit. Recipient of the UCLA Distinguished Teaching Award. His blog, The Motivated Brain, is published within Psychology Today. Virginia Berninger is Emeritus Professor in the Psychology Department of the University of Washington. Until recently she was the Coordinator and Director of the Learning Sciences and Human Development program; Director of the University Brain Education Technology Center (UBET); and Coordinator of studies on Learning Disabilities. She specializes in writing and the brain. Jane Holmes Bernstein, a staff Neuropsychologist at Boston Children’s Hospital who has helped to develop, apply and teach a “whole-child” assessment model for the behavioural observation of children with learning and behavioural disorders. She

Crossing Mind, Brain, and Education Boundaries

Betts

Bialystok

Bishop

Blake

Blakemore

141

is the co-editor of Mind, Brain and Education in Reading Disorders, and is the namesake of the annual Jane Bernstein Lecture in Neuropsychology at Boston Children’s. Kristen Betts, Professor at Drexel Kristen University, Educational Leadership and Management. Dr. Betts teaches courses in instructional design and supports novel learning in online contexts. Ellen Bialystok is a Distinguished Research Professor at York University, in Toronto, Ellen and is also an Associate Scientist at the Rotman Research Institute of the Baycrest Centre for Geriatric Care. She is a Canadian psychologist and professor and specializes in research on the bilingual brain. Dorothy Vera Margaret Bishop is a British psychologist specializing in Dorothy developmental disorders, specifically, developmental language impairments. She is Professor of Developmental Neuropsychology and Welcome Trust Principal Research Fellow in the Department of Experimental Psychology at the University of Oxford. Peter R. Blake is a Professor in the Peter R. Department of Psychological and Brain Sciences at Boston University, where he studies children’s perception and how they develop a sense of fairness. Sarah-Jayne Blakemore is Professor of Psychology and Cognitive Neuroscience at Sarah-Jayne the university of Cambridge and Honorary Professor at the Institute of Cognitive Neuroscience, University College London. She is co-director of the Welcome Trust PhD Programme in Neuroscience at UCL. Her research focuses on the development of social cognition and decision-making during human adolescence.

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142

Blasi

Anna

Booth

Julie

Booth

Walter

Bowers

Jeffrey

Boyd Ratzer

Mary

Anna Blasi, Centre for Brain and Cognitive Development, Birkbeck University of London. Her research interests are centred on functional aspects of human physiology and include development of technology, data collection and analysis. Julie Booth is an Associate Professor in the Psychological Studies in Education department at Temple University, where she also currently serves as the Associate Dean of Undergraduate Education for the College of Education. Her research interests lie in translating between cognitive science and education by bringing laboratory-tested cognitive principles to real-world classrooms, identifying prerequisite skills necessary for learning, and examining individual differences in the effectiveness of instructional techniques based on learner characteristics. Walter Boot is professor at Florida State University. Research in visual cognition, training, and transfer of training. Currently investigating video games to improve perceptual and cognitive abilities. Other research interests include visual search, attention capture, eye movement control, and visual attention across the lifespan. Jeffrey Bowers is a Professor at Bristol where he studies Memory and Language. He received his degree in psychology (BSc) at the University of Toronto (1987) and completed a Ph.D. with Daniel Schacter and Kenneth Forster at the University of Arizona (1993) on the topic of long-term priming. Mary Boyd Ratzer is a certified secondary school educator and librarian and media specialist in New York. She is member of the American Library Association and National Council of Teachers of English, New York State Academy for Teaching, and

Crossing Mind, Brain, and Education Boundaries

Bransford

John D.

BrookmanByrne

Annie

Bruer

John T.

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grant recipient. Co-Author of Think Tank Library: Brain-based learning plans for new standards, grades 6-12. John D. Bransford is known for his work with the National Academies on How People Learn. Bransford served as Co-Chair of several National Academy of Science committees. He holds the Shauna C. Larson University Professor of Education and Psychology at the University of Washington in Seattle and is Co-Principal Investigator and Director of the Learning in Informal and Formal Environments (LIFE) Center, a National Science Foundation (NSF) Science of Learning Center. Annie Brookman-Byrne is the Deputy Editor of The Psychologist, of the British Psychological Society and was an educational neuroscience researcher at Birkbeck, University of London. She investigated the cognitive and neural bases of science and maths reasoning in adolescence, using behavioural, neuroimaging, and classroom-based methods, working closely with teachers in school. She aimed to ensure that my research was both scientifically rigorous and educationally relevant. John T. Bruer, President Emeritus, McDonnell Foundation, author of “A Bridge Too Far,” distancing neuroscience and education. John Bruer holds degrees in philosophy from the University of Wisconsin, University of Oxford, and the Rockefeller University. After work as a research fellow and associate director in the Health Science Division of the Rockefeller Foundation, he joined the Josiah Macy, Jr. Foundation and administered programs in the public understanding of science and medical education.

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144

Bullock

Ann

Bunge

Silvia

Busso

Daniel S.

Butterworth

Brian

Ann Bullock is the Dean of the School of Education at Elon University is a Member of Deans For Impact. Bullock worked at East Carolina University where she worked on a Teacher Quality Grant that redesigned the outcomes of ECU’s teacher education programs through assessment -based innovations and on the implementation of the edTPA performance -based assessment for teacher candidates, both recognized nationally as innovative projects. Silvia Bunge is a Professor at University of California, Berkeley, Department of Psychology and Helen Wills Neuroscience Institute. She runs the Building Blocks of Cognition Laboratory, and her research interests are in brain mechanisms, development, and plasticity of higher cognitive functions in humans; basic cognitive/neural processes that underpin reasoning, learning and memory, and goal-directed behaviour; and the effects of education and home environment on cognitive development. Daniel Busso received his EdD in Human Development from the Harvard Graduate School of Education. His research interests include the impact of early adversity (maltreatment, trauma and poverty) on developmental, educational and mental health outcomes in children. He is interested in using the tools of neurobiology and cognitive science to better address questions of educational practice and policy. Brian Butterworth FBA is emeritus professor of cognitive neuropsychology in the Institute of Cognitive Neuroscience at University College London. His research has ranged from speech errors and pauses, short-term memory deficits, dyslexia, reading both in alphabetic scripts and Chinese, and mathematics and dyscalculia.

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Caine

Calero

Campbell

Campbell

145

Renate Caine, Professor Emeritus of Education at California State University in San Bernardino (CSUSB), is an education Renate researcher, learning theorist, writer, and consultant. She is the Executive Director of the Natural Learning Research Institute, whose mission is to disseminate research and information on neuroscience and learning. She. Is the Executive Director of the University’s Centre for Research in Integrative Learning and Teaching. Her work with schools has been featured on Teacher TV and Wizards of Wisdom. Cecilia Calero runs the Neuroscience Laboratory, Universidad Torcuato Di Tella Cecilia and is Co-Director ‘Little Teachers’ at the Neuroscience Laboratory (Torcuato Di Tella University), which focuses on how teaching skills are developed since very early ages. She is Her group seek to understand the relationship between the ability to teach and the learning experience itself, the importance of peer tutoring and the impact of other cognitive skills, such as metacognition and empathy, in the way we teach. Ruth Campbell is an Experimental Psychologist and Neuropsychologist who is Ruth especially interested in the psychology and neuroscience underlying lipreading (speechreading), and how the face is used in sign language. Her projects include imaging the deaf brain, and perception of movement in autism. Stephen R. Campbell is Associate Professor and Director of the Educational Neuroscience Laboratory in the Faculty of Stephen R. Education at Simon Fraser University. His scholarly focus is on the historical and psychological development of mathematical thinking from an embodied perspective

146

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informed by Kant, Husserl, and MerleauPonty. His research incorporates methods of psychophysics and cognitive neuroscience as a means for operationalizing affective and cognitive models of math anxiety and concept formation.

Campos

Cardinali

Carew

Carey

Ana Lucia Campos is the General Director for Latin America of Cerebrum, the IberoAna Lucia American Institute of Neuroscience, Education and Human Development, a commercial teacher educator institution which gives certificates in educational neuroscience and tries to bridge neuroscience and pedagogical practice. Daniel P. Cardinali, Director of Department of Teaching and Research, Daniel P. Faculty of Medical Sciences, Pontificia Universidad Católica Argentina, and Professor Emeritus, University of Buenos Aires, Department of Physiology, School of Medicine. His research areas include the educational implications of chronobiology of learning, sleep, physiology and pharmacology of melatonin and biologic rhythms. Thomas J. Carew formerly of the Department of Neurobiology and Behavior, Thomas J. Center for the Neurobiology of Learning and Memory, Department of Education, University of California. Currently serves as Dean of the Faculty of Arts and Sciences at New York University, and has research interests in the behavioural, cellular, and molecular analyses of learning and memory. Susan Carey is in the Department of Psychology at Harvard University and Susan researches the development of concepts in the child and adult (i.e., over ontogenesis), and the cultural construction of concepts over history. Carey has concentrated on a process she calls “Quinian bootstrapping.”

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147

Current case studies include representations of abstract relations and logical connectives, and conceptual changes within intuitive theories of biology and physical reasoning

Carreiras

Carstensen

Cassasola

Chomsky

Manuel Carreiras, Professor at the Basque Center on Cognition, Brain, and Language. Research on reading, bilingualism, visual word recognition, sentence processing, sign language, neurodegeneration of language. Laura L. Carstensen, professor in the Laura L. Department of Psychology, Stanford University. Her most current empirical research focuses on ways in which motivational changes influence cognitive processing. Laura is director of the Stanford Center on Longevity. Marianella Casasola, professor at Cornell University researches infant cognitive Marianella development and early word learning with a particular interest in the interaction between thought and language during the first few years of development. She is especially interested in the emergence of spatial concepts, the early acquisition of spatial language, and the interplay between spatial cognition and spatial language in infants and young children. Avram Noam Chomsky holds a joint appointment as Institute Professor Emeritus Noam at the Massachusetts Institute of Technology (MIT) and laureate professor at the University of Arizona. He is an American linguist, philosopher, cognitive scientist, historian, social critic, and political activist and called "the father of modern linguistics" as well as a founder of the field of cognitive science. Manuel

Appendix C

148

Christodoulou

Joanna

Chudler

Eric

Chun

Marc

Church

Mark

Joanna A. Christodoulou leads the Brain, Education, and Mind (BEAM) Team research lab located in the Center for Health and Rehabilitation Research at Mass General Hospital, which conducts research to improve student learning outcomes by investigating risk factors in reading. Her primary research focus has been on the brain-behaviour dynamic underlying development of reading and related skills. Eric Chudler is a professor of Bioengineering and Anaesthesiology and Pain Medicine and the Executive Director of the Center for Sensorimotor Neural Engineering Neuroscience Focus Group: Behavioral Neuroscience, Brain-Computer Interface at the University of Washington where he runs the webpage Neuroscience For Kids. Marc Chun previously worked at the RAND Corporation, Stanford University, UCLA, and the Council for Aid. He holds a PhD in education from Stanford University, completed a postdoctoral fellowship in sociology and education at Teachers College/Columbia University, and holds three master’s degrees in sociology, education, and administration and policy analysis. His research focuses on the development of the Deeper Learning strategy. Mark Church is co-author of Making Thinking Visible and a consultant with Harvard Project Zero. He helps teachers examine opportunities for student thoughtfulness, use thinking routines as supports and scaffolds, to interact with students in ways that demonstrate interest in and respect for students’ thinking, to send clear expectations about the importance and value of thinking in learning.

Crossing Mind, Brain, and Education Boundaries

Churches

Clay Clement

Coch

Cohen Kadosh

Coltheart

149

Richard Churches is co-author of Neuroscience for Teachers and the lead adviser for education reform and evidencebased practice at the Education Development Trust in the UK. Kurt Kurt Clay is the Superintendent, Dela County Colorado School District and an MBE practitioner. Neville D. Neville Clement is professor at the University of Newcastle, Callaghan, Australia looking at the link between neuroscience and education. Donna Coch is a Professor of Education at Dartmouth University and runs the Reading Donna Brains Lab. Her areas of expertise are Mind, Brain, and Education and the development of reading, which she approaches through an interdisciplinary, evidence-based approach to education, learning, and discovery. Kathrin Cohen Kadosh is a Senior Lecturer in Developmental Cognitive Kathrin Neuroscience at the University of Surrey. She researches how children and adolescents learn to make sense of the social world and how this is reflected in the improving social cognitive abilities and the underlying brain networks changes. She is also investigating the role of the microbiome on behaviour and brain function in development. Max Coltheart is Emeritus Professor of Cognitive Science at Macquarie University. Max He specializes in cognitive neuropsychology and cognitive neuropsychiatry. He is a fellow of the Australian Academy of Science and the Academy of the Social Sciences in Australia and is currently a Chief Investigator in the Australian Research Council’s Centre of Excellence for Cognition and its Disorders at Macquarie University. Richard

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150

Commissar

Lia

Compton

Donald

Connell

Michael

Conyers

Marcus

Lia Commissar, M. Ed at the University of Cambridge. Lia leads the Welcome Trust’s Education and Neuroscience Initiative. After studying neuroscience at the University of Nottingham, Lia became a secondary school biology teacher for six years, where she noted a disconnect between the education community and the neuroscience/psychology research, which she is working hard to amend. Donald Compton is professor at Florida State University in the Florida Center for Reading Research. Compton is experienced in designing, managing, analysing, and disseminating data from cross-sectional and longitudinal studies as well as randomized control studies. His research involves modelling individual differences in the development of children’s reading skills and the identification and treatment of children with reading disabilities. Michael Connell is Visiting Research Associate at the Southwest Center for Mind, Brain, and Education. Connell holds a doctorate in Education from Harvard University and an M.S. in Computer Science from MIT and was a design engineer at Microsoft Corporation. He is currently an educational consultant on instructional design, assessment design, and learning analytics to schools, non-profit organizations, the federal government, and corporations Marcus Conyers, a pioneer in the field of Brain-Based Leading and Learning for more than three decades, is lead developer of the world’s first doctoral minor in BrainBased Leadership and co-developer of the first NCATE accredited EdS and MS degree programs in Instructional leadership/BrainBased Learning in partnership with Nova Southeastern University.

Crossing Mind, Brain, and Education Boundaries

Cooper

Melanie

Costa

Arthur L.

Cozolino

Louis

Crowley

Kevin

151

Melanie Cooper is professor in the Department of Chemistry, Michigan State University. She develops evidence-based approaches to teaching, learning and assessment. She assess both what students know and how they use their knowledge to develop curriculum materials and evaluate the effects of transformation efforts both within and across disciplines. Arthur L. Costa is Emeritus Professor of Education at California State University, Sacramento, and cofounder of the Institute for Intelligent Behavior in California. He has written and investigated Habits of Mind for over 30 years and served as a classroom teacher, a curriculum consultant, an assistant superintendent for instruction, and the director of educational programs for the National Aeronautics and Space Administration. Louis Cozolino, author of The Social Neuroscience of Education, is a professor of psychology at Pepperdine University and a private practitioner. He is a researcher and author on healthy aging, relationships, and the neuroscience of psychotherapy. Cozolino holds degrees in philosophy and theology, in addition to his doctoral in clinical psychology. Kevin Crowley is a professor of Learning Sciences and Policy at the University of Pittsburgh, where he also directs the University of Pittsburgh Center for Learning in Out-of-School Environments (UPCLOSE) and is a Senior Scientists at the Learning Research and Development Center. Crowley works in partnership with museums, community organizations, and other informal educators to develop innovative learning environments.

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Csikszentmihalyi Mihaly

Daley

Samantha G.

Damasio

Antonio

Darling Hammond

Linda

Mihaly Csikszentmihalyi is Author of Flow and Creativity. Csikszentmihalyi is Claremont Graduate University’s Distinguished Professor of Psychology and Management and the founder and codirector of the Quality of Life Research Center (QLRC), a non-profit research institute that studies positive psychology, the study of human strengths such as optimism, creativity, intrinsic motivation, and responsibility. Samantha Daley holds appointments across three program areas at the University of Rochester’s Warner School in teaching and curriculum, counselling and human development, and educational policy. Her research focus is on inclusion and disability from a range of perspectives and in all aspects of human learning and flourishing. Antonio Damasio is an adjunct professor at the Salk Institute and the David Dornsife Professor of Neuroscience at the University of Southern California. He Directs the Brain and Creativity Institute, and is Professor of Psychology, Philosophy, and Neurology. He is a leader in understanding the biological origin of conscious and researches affective neuroscience. He is the author of several hundred scientific articles and the recipient of many prestigious awards. Linda Darling-Hammond is the Charles E. Ducommun Professor of Education, Emeritus, at Stanford University. She is the founding president of the Learning Policy Institute and is past president of the American Educational Research Association. She was executive director of the National Commission on Teaching and America’s Future, whose 1996 report What Matters Most: Teaching for America’s Future was named one of the most

Crossing Mind, Brain, and Education Boundaries

Dawson

Geraldine

de Haan

Michelle

DeSmedt

Bert

Deater-Deckard Kirby

153

influential reports affecting US In 2006, Darling-Hammond was named one of the nation’s ten most influential people affecting educational policy. Geraldine Dawson is Professor in the Departments of Psychiatry and Behavioral Sciences, Pediatrics, and Psychology and Neuroscience and Director of the Duke Center for Autism and Brain Development at Duke University, North Carolina. Dawson’s awards include a Lifetime Achievement Award from the Association for Psychological Science for outstanding contributions to the area of applied psychological research that addresses a critical problem in society at large. Michelle de Haan is Professor in the Infant and Child Development program at the University College of London’s Great Ormond Street Institute of Child Health. Michelle’s research applies neuroimaging and neuropsychological methods to examine the brain underpinnings of typical and atypical cognitive and social development. Bert DeSmedt is an associate professor in Educational Neuroscience at Faculty of Psychology and Educational Sciences at University of Leuven, Belgium. His primary interest is in understanding individual differences in children’s mathematical skills. His team uses both behavioural and brain imaging methods to understand how children develop arithmetical skills and what neurocognitive mechanisms underlie this typical and atypical numerical development. Kirby Deater-Deckard is a developmental psychologist who is Professor of Psychological and Brain Sciences at the University of Massachusetts Amherst, as well as director of the Healthy Development

Appendix C

154

Dehaene

Stanislas

Dekker

Sanne

Della Sala

Sergio

Initiative at the UMass Center in Springfield. He studies child and adolescent cognitive and social-emotional development, and the role of parenting and peer environments on developmental outcomes. Stanislas Dehaene is a professor at the Collège de France and, since 1989, the director of INSERM’s "Cognitive Neuroimaging" Department where he researches numerical cognition, the neural basis of reading and the neural correlates of consciousness. Dehaene is an associate editor of the journal Cognition, and a member of the editorial board of several other journals, including NeuroImage, PLoS Biology, Developmental Science, and "Neuroscience of Consciousness". He is also known for the concept of the human brain’s “Number Sense”. Sanne Dekker works at the Department of Educational Neuroscience at the Radboud University Nijmegen in the Netherlands. She is best known for her work to dispel neuromyths, adolescent development, processing speed, information processing efficiency and self-regulation. Sergio Della Sala is Professor of Human Cognitive Neuroscience in the Psychology Department at the University of Edinburgh and holds an adjunct chair at the Psychology Department of the University of Western Australia. His research focuses on memory and memory impairments and on the cognitive deficits associated with brain damage. He is the Editor of the Elsevier Encyclopedia of Behavioral Science.

Crossing Mind, Brain, and Education Boundaries

della-Chiesa

Bruno

Delvin

Keith

Devonshire

Ian

Diamond

Adele

155

Bruno della Chiesa is a linguist of Italian, French and German descent, who describes himself as an "engaged cosmopolitan". He teaches at Harvard University and is considered one of the main founders of educational neuroscience, is known to have coined the terms "neuromyth" (2002) and "neuro-hijacking" (2013) and has established theories on the "motivational vortex" (2007) and on the “tesseracts in the brain” (2008). Keith J. Devlin is a British mathematician and co-founder of Stanford University’s Human-Sciences and Technologies Advanced Research Institute (2006), a cofounder of Stanford Media X universityindustry research partnership program, and a Senior Researcher in the Center for the Study of Language and Information (CSLI). He is a commentator on National Public Radio’s Weekend Edition Saturday, where he is known as "The Math Guy" and acknowledged as a leader in scientific translation for the general public. Ian Devonshire is Senior Training and Competency Officer at the Faculty of Medicine and Health Sciences at the University of Nottingham. Devonshire is a neuroscientist, author and science communicator and is currently the Chief Experimental Officer in the Bio-Support Unit. He is also an Associate Lecturer in Neuroscience and Mental Health at the Open University and is a Chartered Scientist (CSci) registered with the Royal Society of Biology. Adele Diamond is Professor of Developmental Cognitive Neuroscience at the University of British Columbia, a Fellow of the Royal Society of Canada, and was recently listed as one of the 15 most

156

Doidge

Dommett

Donlan

Dougherty

Appendix C

influential neuroscientists alive today. She is one of the pioneers in the field of Developmental Cognitive Neuroscience, and researches executive functions. Norman Doidge, FRCP(C), is a Norman psychiatrist, psychoanalyst, and author of The Brain that Changes Itself (2007) and The Brain’s Way of Healing (2015). The former describes some of the latest developments in neuroscience and became a New York Times and international bestseller. Eleanor Dommett is a Senior Lecturer in Biological Psychology and Neuroscience at Eleanor J. the Institute of Psychology, Psychiatry and Neuroscience, part of King’s College London. Her research focuses on models of Attention Deficit Hyperactivity Disorder and mechanisms of action of therapeutic drugs in this condition. She is a Fellow of the Higher Education Academy. Chris Donlan, Division of Psychology and Language Sciences, University College of Christina London is co-author of the chapter on Language Development in Educational Neuroscience. Donlan studies Specific Language Impairments (SLI) in childhood and how they inhibit cognitive development in non-linguistic domains such as math. Her current work explores the neural substrates and factors affecting variability in SLIs. Michael Dougherty, Chair in the Department of Psychology at the University Michael of Maryland, is a cognitive scientist interested in complex cognition. Dougherty believes truly transformative research requires that the basic research eventually be scaled-up to address practical problems. His research seeks to identify questions that are of both practical and theoretical interest.

Crossing Mind, Brain, and Education Boundaries

Doyle

Terry

Dubinsky

Janet

Duncan

Greg J.

Dunlosky

John

Duplice

John

157

Terry Doyle is co-author of The New Science of Learning. Terry is the CEO of Learner Centered Teaching Consultants and is working on a new book for college teachers titled Engaging Students in the Learning Process: Understanding How Research Is (or should be) Revolutionizing the Way We Teach with his co-author Todd Zakrajsek. Janet M Dubinsky, Professor of Neuroscience at the University of Minnesota (UMN), directs the BrainU professional development program for secondary science teachers and teaches graduate and undergraduate neuroscience. She is the winner of the 2009 Society for Neuroscience Science Educator Award and serves on the Society’s Public Education and Communication Committee. Greg J. Duncan is Distinguished Professor at the School of Education at the University of California, Irvine and an adjunct faculty member at the Institute for Policy Research at Northwestern University. His current research is on children’s early skills and behaviours relate to later-life outcomes, and a meta-analysis of the impacts of early childhood intervention programs. John Dunlosky is professor in the Department of Psychological Sciences at Kent State University. His research program focuses on understanding three inter-related components of self-regulated learning: (1) monitoring of learning, (2) control of study time, and (3) the application of strategies during learning, which fall under the rubric of metacognition. John Duplice is an educator and MBE practitioner in Japan.

158

Dweck

Eccles

Eddy

Edelenbosch

Egan

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Carol S. Dweck is the Lewis and Virginia Eaton Professor of Psychology at Stanford Carol University. Dweck is best known for her work on the mindset psychological trait and her book on Growth Mindsets. She taught at Columbia University, Harvard University, and the University of Illinois before joining Stanford University in 2004. Jacquelynne Eccles is professor in the Department of Psychology, University of Jacquelynne Michigan. He research includes family and school influences on development; development in high risk settings; development of self -esteem, activity preferences, and task choice; adolescent development; identity formation; transition into adulthood; biosocial influences and development; gender role development; and role of ethnicity in development and socialization. Marianna D. Eddy is co-author of The Marianna Reading Brain in Sousa’s Mind, Brain, and D. Education: Neuroscience implications for the classroom. Eddy is a Team Leader at the Cognitive Science and Applications at Combat Capabilities Development Command Soldier Center in Massachusetts. Rosanne Edelenbosch, Athena Institute for Rosanne Research on Innovation and Communication in Health and Life Sciences at the University of Amsterdam. Her areas of expertise are in teacher education and bridging the gap between neuroscience and education. Egan Kieran is a Professor in the Kieran Department of Education, Simon Fraser University, Canada. His areas of interest include educational and curriculum theory, conceptions of development in education, and the way cognitive tools shape our learning and understanding.

Crossing Mind, Brain, and Education Boundaries

Eisenhart

Margaret

Elder

Linda

Elish-Piper

Laurie

Erlauer

Laura L.

Falik

Louis H.

159

Margaret Eisenhart is a University Distinguished Professor of Educational Anthropology and Research Methodology at the University of Colorado Boulder. Dr. Eisenhart specializes in educational anthropology and ethnographic research methods. Her research focuses on the social and cultural experiences of students in US schools. Linda Elder is an educational psychologist and a prominent authority on critical thinking. Elder has taught psychology and critical thinking at the college level and has given presentations to more than 50,000 educators at all levels. She is author of Liberating the Mind: Overcoming Sociocentric Thought and Egocentric Tendencies. Laurie Elish-Piper is Dean of the College of Education at Northern Illinois University and Distinguished Engagement Professor and a Distinguished Teaching Professor in the Department of Curriculum and Instruction (CI). Elish-Piper has provided leadership to professional organizations, including her service as the president of the Association of Literacy Educators and Researchers. Laura Erlauer is author of The BrainCompatible Classroom: Using what we know about learning to improve teaching. Drawing on her experience as a teacher and principal, Erlauer summarizes current brain research and shows how teachers can use this knowledge in the classroom every day. Louis H. Falik is Professor Emeritus at San Francisco State University and co-author of Beyond smarter: Mediated learning and the brain’s capacity to change.

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Farah

Martha J.

Feiler

Jake

Fern-Pollak

Liory

Ferrari

Michel

Ferrero

Marta

Martha Julia Farah is a cognitive neuroscience and researcher at the University of Pennsylvania. She received a lifetime achievement award from the Association for Psychological Sciences for work on mental imagery, face recognition, semantic memory, reading, attention, and executive functioning Jacob B. Feiler, a doctoral student at the University of Alabama, College of Education, in Educational Psychology and concentrating in Educational Neuroscience. His research interests include examining how neuroscience can be utilized to understand why some students find challenges in learning science and math and how this information might lead to innovative student interventions. Liory Fern-Pollak, is a Senior Teaching fellow at the University College of London Institute of Education where she investigates the neural correlates of multilingual language processing, reading and dyslexia in adults and children. She is co-author of Literacy Development in Mareschal, Butterworth and Tolmie’s Educational Neuroscience. Michel Ferrari is an Associate Professor in the Department of Developmental Psychology and Education at the Ontario Institute for Studies in Education at the University of Toronto. He is also director of the Wisdom Identity Center. His research interests include personal wisdom in people of different ages and from different cultures around the world. Marta Ferrero is a researcher at the University of Deusto in Bizkaia, Spain and the Universidad del País Vasco where she writes about evidence-based teaching and learning in reading, writing and mathematics.

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Fischer

Frank

Fischer21

Kurt W.

Fisher

Doug

Fisher

Phil

161

Frank Fischer is Professor of Educational Psychology, Ludwig Maximilians Universität, with a Professorship in Empirical Education and Educational Psychology. He is the Editor of the International Handbook of the Learning Sciences. Kurt Fischer was the founding president of the International Mind, Brain, and Education Society and creator of the Harvard University Graduate School of Education MBE Program. Kurt W. Fischer is an educator, author, and researcher in the field of neuroscience and education. Until his retirement in 2015, he was the Charles Bigelow Professor of Education and Director of the Mind, Brain, and Education Program at Harvard Graduate School of Education. Fischer studies cognitive and emotional development and learning. Douglas Fisher is Professor and Department Chair of the College of Education at San Diego State University. He is also a teacher and administrator at Health Sciences High and Middle College. He has served as a teacher, language development specialist, and administrator and works closely with San Diego’s public schools. Philip Fisher is the Philip H. Knight Chair and a Professor of Psychology at the University of Oregon. His research focuses on developing and evaluating early childhood interventions in socially and economically marginalized communities, and on translating scientific knowledge regarding healthy development under conditions of adversity for use in social policy and programs.

2 Honorarily invited though unable to participate. Sadly, Kurt Fischer passed just prior to the publication of the 2020 study results.

Appendix C

162

Fiske

Susan T.

Fitzpatrick

Michelle

Fletcher

Jack M.

Fogarty

Robin J.

Fornaguera

Jaime

Susan T. Fiske is Chair in the Department of Psychology and Woodrow Wilson School of Public and International Affairs, Princeton University. She is a social psychologist known for her work on social cognition, stereotypes, and prejudice. Michelle Fitzpatrick received her Master’s in Education from Harvard’s Mind, Brain, and Education program and has an MA in literature and creative writing from the University of Houston. She has co-authored many nonfiction books, including international bestsellers. She is the co author, with Vanessa Rodriguez, of The Teaching Brain: The Evolutionary Trait at the Heart of Education (The New Press) Jack M. Fletcher is the Associate Department Chair of Psychology at the University of Houston. He is also affiliated with the Texas Center for Learning Disabilities, Development, Cognitive and Behavioral Neuroscience and Clinical Psychology. He is a board-certified child neuropsychologist and researches spina bifida, traumatic brain injury, developmental learning, and attention disordersRobin Fogarty has a doctorate in curriculum and human resource development from Loyola University in Chicago. She is co-author of Twelve Brain Principles That Make the Difference and Supporting Differentiated Instruction. Her book The Right to Be Literate was named the 2017 Teachers’ Choice Award Winner for Professional Development. Jaime Fornaguera is a Professor of Physiology at the University of Costa Rica and involved in teacher education. Jaime currently works at the Neuroscience Research Center at the University of Costa Rica. Fornaguera does research in genetics

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Francisco

Joseph

Frey

Nancy

Friedman

Sarah L.

Frith

Uta

163

and neuroscience and is currently studying microglial response to chronic stress Joseph Francisco is the former Dean of the College of Arts and Sciences at the University of Nebraska at Lincoln and current chemistry professor at the University of Pennsylvania. He researches atmospheric chemistry and chemical kinetics. Nancy Frey is a professor in the Department of Educational Leadership at San Diego State University. She had previously served in the School of Teacher Education beginning in 2003 as a professor of literacy. She is the recipient of the 2008 Early Career Achievement Award from the National Reading Conference. Sarah L. Friedman is a developmental psychologist with post-doctoral training at the National Institute of Mental Health. Her research focuses on (a) the effects of preterm birth on cognitive, educational and social development of children; (b) the interface of brain, cognition and education; (c) the development of planning skills; (d) longitudinal follow -up research strategies; (e) environmental influences on psychological development; and (f) childcare and children’s psychological and health development. Uta Frith is a psychologist working at the Institute of Cognitive Neuroscience at University College London. She has pioneered much of the current research into autism and dyslexia and has written several books on these two subjects moving these conditions out of the psychological realm and into the neuroscience field of study. She is also interested in ensuring that neuroscience research remains relevant to education and lifelong learning.

Appendix C

164

Fugelsang

Jonathan

Fullan

Michael

Fuster

Joaquín

Gaab

Nadine

Jonathan Fugelsang, Department of Psychology, University of Waterloo. Jonathan is co-author of The Development and Application of Scientific Reasoning in Mareschal, Butterworth and Tolmie’s Educational Neuroscience. His research in cognitive psychology and cognitive neuroscience, and higher level cognition and complex decision making using neural imagery. Michael Fullan, Global Leadership Director for New Pedagogies for Deep Learning. He is a worldwide authority on educational reform. Fullan is a former Dean of the Ontario Institute for Studies in Education (OISE) of the University of Toronto, and currently advises policymakers and local leaders around the world to provide leadership in education. Joaquin M. Fuster is Professor of Psychiatry and Biobehavioral Sciences at UCLA’s Semel Institute for Neuroscience and Human Behavior. He researches the neural structures underlying cognition and behaviour, particularly related to memory and the prefrontal cortex. He is a resident fellow of the American Academy of Arts and Sciences Nadine Gaab, an Associate Professor of Paediatrics at the Boston Children’s Hospital/Harvard Medical School and a member of the faculty at the Harvard Graduate School of Education. She is a faculty adjunct at Brandeis University. Her research within the Laboratories of Cognitive Neuroscience focuses on the brain correlates of reading development in typical and atypical children as well as possible premarkers of developmental dyslexia in preschoolers and infants.

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Gabrieli

John

Galaburda

Albert

Gamoran

Adam

Gardner

Howard

165

John Gabrieli, Professor of Cognitive Neuroscience at MIT, Grover Hermann Professor, Health Sciences and Technology and Professor of Brain and Cognitive Sciences. Gabrieli uses imaging and behavioural tests to understand how the human brain powers learning, thinking, and feeling. Albert Mark Galaburda is Professor of Neurology and Neuroscience at Harvard Medical School, the Director of the Office for Diversity, Inclusion, and Career Advancement at Beth Israel Deaconess Medical Center, Boston, and Co-director of the Harvard University Interfaculty Initiative on Mind Brain and Behavior. His research is specifically focused on the biologic bases of developmental cognitive disorders. Adam Gamoran is President of the William T. Grant Foundation. He was previously the John D. MacArthur Professor of Sociology and Educational Policy Studies and director of the Wisconsin Center for Education Research at the University of Wisconsin-Madison. His research focuses on inequality in education and school reform. Among his recent books are, Standards-Based Reform and the Poverty Gap: Lessons for No Child Left Behind. Howard Earl Gardner is a developmental psychologist and until May 2019, was the John H. and Elisabeth A. Hobbs Research Professor of Cognition and Education at the Harvard Graduate School of Education at Harvard University. He is currently the senior director of Harvard Project Zero, and the co-director of The Good Project. He is best known for his theory of multiple intelligences, as outlined in his 1983 book Frames of Mind: The Theory of Multiple Intelligences.

Appendix C

166

Gazzaniga

Michael

Geary

David C.

Giedd

Jay

Gigerenzer

Gerd

Michael S. Gazzaniga is a professor of psychology at the University of California, Santa Barbara, where he heads the new SAGE Center for the Study of the Mind. He is one of the leading researchers in cognitive neuroscience, the study of the neural basis of mind. He is a member of the American Academy of Arts and Sciences, the Institute of Medicine, and the National Academy of Sciences David C. Geary is a cognitive developmental and evolutionary psychologist with interests in mathematical cognition and learning as well as the biological bases of sex differences. Geary is a Thomas Jefferson Fellow in the Department of Psychological Sciences and Interdisciplinary Neuroscience Program. His research spans cognitive, developmental, and evolutionary psychology, education, biology, and medicine. Jay N. Giedd, M.D. is adjunct Professor at John Hopkins’ School of Public Health and Chief of the Brain Imaging Section at the Child Psychiatry Branch of the National Institute of Mental Health. His research involves large scale longitudinal study combining brain imaging, genetics, and psychological/behavioral assessments to explore the path, mechanisms, and influences on brain development in health and illness, especially during the adolescent years. Gerd Gigerenzer is director emeritus of the Center for Adaptive Behavior and Cognition (ABC) at the Max Planck Institute for Human Development and director of the Harding Center for Risk Literacy. He is a psychologist who has studied the use of bounded rationality and heuristics in decision making. Gigerenzer investigates how humans make inferences about their world with limited time and knowledge.

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Gillis Furukawa Amanda

Glannon

Walter

Gleichgerricht

Ezequiel

Goldin-Meadow Susan

Goldman

Susan R.

167

Amanda Gillis Furukawa is a Professor at Kyoto Sangyo University. And an MBE practitioner in Japan. Walter Glannon is Professor of Neuroethics, Philosophy of Mind, and Bioethics at the University of Calgary. His main area of research is neuroethics where he has published over 150 articles and 10 books. Ezequiel Gleichgerricht is an Associate Professor at Favaloro University (Argentina) and a guest lecturer in several universities across the Latin American region. He conducts research in cognitive neurology and neuroscience with a strong focus on neuropsychiatric diseases involving the frontal lobes and a particular interest for affective and social processes in the brain. Susan Goldin-Meadow is the Beardsley Ruml Distinguished Service Professor in the Departments of Psychology, Comparative Human Development, the College, and the Committee on Education at the University of Chicago. She is the principal investigator of a 10-year program project grant, funded by the National Institute of Child Health and Human Development, designed to explore the impact of environmental and biological variation on language growth. Susan R. Goldman is Professor of Learning Sciences and Technology at the University of Illinois. She conducts research on subject matter learning, instruction, assessment, and on roles for technology, especially in literacy and mathematics. Goldman is widely published in discourse, psychology and education journals. A particular focus of her current research is on understanding the literacy demands in different disciplinary contexts and the implications of these demands for supporting learning.

Appendix C

168

Goldstone

Robert L.

Goleman

Daniel

Golinkoff

Roberta Michnick

Gorham

Thomas

Goswami

Usha

Robert L. Goldstone is a professor in the Department of Psychological and Brain Sciences at Indiana University. His research goal is to apply complex adaptive systems models to understanding on individual people learn and perceive, and how groups of people organize themselves into emergent structures which none of the individuals in the group may understand or even perceive. Daniel Goleman is an author and science journalist. For twelve years, he wrote for The New York Times, reporting on the brain and behavioural sciences. His 1995 book Emotional Intelligence was on The New York Times Best Seller list for a year-and-ahalf, a best-seller in many countries, and is in print worldwide in 40 languages. Roberta Michnick Golinkoff is the Chair of the School of Education at the University of Delaware and a member of the Departments of Psychological and Brain Sciences and Linguistics and Cognitive Science. She founded and directs the Child’s Play, Learning, and Development Laboratory which investigates how young children learn their native language and the importance of play. Thomas Gorham is a doctoral student at the University of Kyoto and is studying the relationship between complex systems, artificial intelligence, and human learning while being an MBE practitioner in Japan Usha Goswami is a researcher and professor of Cognitive Developmental Neuroscience at the University of Cambridge and the director of the Centre for Neuroscience in Education at St. John’s College. Goswami’s work is primarily in educational neuroscience with major focuses on reading development and developmental dyslexia

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Grabner

Graesser

Grossmann

Guerriero

Gutiérrez

169

Roland H. Ronald H. Grabner is a University Professor for Biochemistry at the Institute of Molecular Biosciences, at the University of Graz in Austria. Arthur C. Graesser, professor in the Arthur C. Department of Psychology and direct the Institute of Intelligent Systems at the University of Memphis and an honorary Research Fellow at the University of Oxford. He is best known for his research on intelligent tutoring systems. Tobias Grossmann is an Associate Professor of Psychology at the University of Tobias Virginia. He studies the early development of the social and affective abilities that enable us to interact with others and make sense of their social behaviour. In particular, he is interested in the brain processes that underpin social interaction and cognition during infancy. Sonia Guerriero is a Senior Education Specialist in Teacher Development at Sonia UNESCO. She studies the early development of the social and affective abilities that enable us to interact with others and make sense of their social behaviour. In particular, she is interested in the brain processes that underpin social interaction and cognition during infancy. Kris Gutierrez is a Professor of Educational Policy and Language, Literacy Kris and Culture at the University of California, Berkeley. Gutiérrez currently holds the Carol Liu Chair in Educational and formerly held the Inaugural Provost’s Chair at University of Colorado, Boulder. Her primary areas of research are literacy, learning sciences, and interpretive and design-based approaches to inquiry.

Appendix C

170

Hakuta

Kenji

Hammond

Zaretta

Handley

Caroline

Hardiman

Mariale

Hattie

John

Kenji Hakuta is a Professor in the School of Education at Stanford University in Educational Policy, Literacy and Language, Psychology, Standards and Teachers and Teaching. He is renowned for his work on bi -and multilingual education. Zaretta Hammond is a lecturer at St. Mary’s College’s Kalmanovitz School of Education in Moraga, California and author of Culturally Responsive Teaching and the Brain. Zaretta Hammond is a former classroom English teacher who has been doing instructional design, school coaching, and professional development around the issues of equity, literacy, and culturally responsive teaching for the past 18 years. Caroline Handley is a teacher and an MBE practitioner in Japan Mariale Hardiman is Professor, Cofounder and Director of Johns Hopkins’ Neuro-Education Initiative (NEI) and doctoral programs in Mind, Brain, and Teaching, an innovative cross-disciplinary program that provides educators with relevant research from the learning sciences. Her research and publications focus on enhancing educational practices through techniques that foster innovation and creative problem-solving, instructional practice, pedagogy, special education programming and exceptional children, including gifted education. John Hattie is Professor of Education and Director of the Melbourne Education Research Institute, Australia. Hattie undertook the largest ever synthesis of meta-analyses of quantitative measures of the effect of different factors on educational outcomes. His book, Visible Learning, is the result his PhD thesis at the University of Toronto in 1981. His research interests

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Haworth

Claire M.

Hays-Jacob

Heidi

Hinton

Christina

Hirsh-Pasek

Kathy

171

include performance indicators and evaluation in education, as well as creativity measurement and models of teaching and learning. Claire Haworth is a Professor at the University of Bristol. Her work focuses on why people are different from one another, specifically, what factors influence our mental health and wellbeing across the life course. Claire uses a range of techniques to investigate individual differences, including genetically informative studies that tell us about the role of nature (genes) and nurture (environments) in creating these differences between us. Heidi Hayes Jacobs is an author and internationally recognized education leader known for her work in curriculum mapping, curriculum integration, and developing 21st century approaches to teaching and learning. Christina Hinton is the Founder and Executive Director of Research Schools International and a faculty member at Harvard Graduate School of Education. Hinton is a neuroscientist and educator committed to bridging the gap between interdisciplinary research on learning and education practice. Kathy Hirsh-Pasek is the Stanley and Deborah Lefkowitz Professor of Psychology at Temple University in Philadelphia, where she directs the Temple University Infant Language Laboratory. She is also a Senior Fellow at the Brookings Institution’s Center for Universal Education, and the current president of the International Congress of Infant Studies. Her work has been dedicated to bridging the gap between developmental and educational research and applications.

172

Hmelo-Silver

Hoeft

Honey

Appendix C

Cindy Hmelo-Silver is Professor of Education and Technology, Indiana University Bloomington and Editor of the Cindy E. International Handbook of the Learning Sciences. She focuses on how people learn about complex phenomena and how technology can help support that learning. As part of this work, she studies problembased learning, collaborative knowledge construction, and computer supported collaborative learning and the role of technology to support social knowledge construction and collaborative learning and problem-solving. Fumiko Hoeft is a Professor of Child and Adolescent Psychiatry and Weill Institute for Neurosciences at the University of Fumiko California, San Francisco School of Medicine. She directs the UCSF Developmental Cognitive Neuroscience Laboratory and is Deputy Director of UCSF Dyslexia Center, and Executive Director of UC Office of the President’s Multicampus Precision Learning Center. She is a psychiatrist, neurophysiologist, as well as a developmental cognitive and systems neuroscientist. Margaret A. Honey, of President and CEO of the New York Hall of Science. She is Margaret A. widely recognized for her work using digital technologies to support children’s learning across the disciplines of science, mathematics, engineering and technology. She was also the architect of numerous large-scale projects in the National Science Foundation, the Institute for Education Sciences, The Carnegie Corporation, The Library of Congress, and the US Department of Education.

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Horvath

Jared Cooney

Howard-Jones

Paul

Ilgen

Daniel R.

Illes

Judy

173

Jared Cooney Horvath is an Educational Neuroscientist in the Melbourne Graduate School of Education at University of Melbourne. He is an expert in the field of Educational Neuroscience with a focus on learning, memory, and attention. He currently serves as Director of The Science of Learning Group: a team dedicated to bringing the latest brain and behavioural research to teachers, students, and parents. Paul Howard-Jones is a Professor in the School of Education at the University of Bristol. His areas of research include applying our understanding of cognition and neuroscience to enhance child and adult learning. His research explores the benefits offered to education by emerging technologies, aided by a critical consideration of underlying cognitive processes. For information and resources from the Neuroeducational Network (NEnet). Daniel R. Ilgen is professor in the Department of Psychology, Michigan State University. His research is primarily in the areas of industrial and organizational psychology, and specifically on the behaviour of groups including schools and businesses. Judy Illes, CM, Ph.D., FRSC, FCAHS, is Professor of Neurology and Canada Research Chair in Neuroethics at the University of British Columbia. She is Director of the National Core for Neuroethics at UBC, and faculty in the Brain Research Centre at UBC and at the Vancouver Coastal Health Research Institute. She is well known for her work in many areas, not the least of which is neruoethics.

174

Appendix C

Mary Helen Immordino-Yang is a Professor of Education, a Professor of Immordino-Yang Mary Helen Psychology at the Brain and Creativity Institute, and a member of the Neuroscience Graduate Program Faculty at the University of Southern California. She studies the psychological and neurobiological bases of social emotion, self-awareness and culture and their implications for learning, development and schools and is past president of the International Mind, Brain and Education Society. David Istance is a non-resident senior fellow at the Center for Universal Istance David Education. He was the editor of the 2007 OECD volume Understanding the Brain: the Birth of a Learning Science. His current research focuses on innovation, including the international Innovative Learning Environments (ILE) project, the 2015 follow-up Schooling Redesigned: Towards Innovative Learning Systems, and now Innovative Pedagogies for Powerful Learning. Jaeger Paige Paige Jaeger is co-Author of Think Tank Library: Brain-based learning plans for new standards, grades 6-12 Rebecca Torrance Jenkins is a doctoral Jenkins Rebecca student at the University College of Torrance London’s Department of Curriculum, Pedagogy and Assessment where she specialises in cognitive and neuroeducational pedagogy, particularly in translating research into classroom practice, and a science teacher. Jensen Eric Eric Jensen is a “brain-based teacher” and author who popularize the idea of teaching teachers more about the brain and learning.

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Johnson

Mark H.

Jolles

Jelle

Jones

Alice

Kalbfleisch

Mary Layne

Kallick

Bena

175

Mark H. Johnson, Centre for Brain and Cognitive Development, Birkbeck University of London. Mark is co-author of Developmental Cognitive Neuroscience. He researches how specialized cognitive functions emerge within particular brain regions during development. Within this approach his research focuses on the perception and cognition of the social and physical world over the early years. Jelle Jolles is Director of the Amsterdam Centre for Brain and Learning. University Professor, Faculty of Behavioural and Movement Sciences and LEARN! -Brain, learning and development. Alice Jones directs the Unit for School and Family Studies at Goldsmiths in the Department of Psychology of Goldsmiths College, University of London. Her work uses inter-disciplinary methods to focus largely on school behaviour and mental health; understanding the influences on socio-emotional development and functioning across a child’s school life. Layne Kalbfleisch is an Associate Professor of Education and Human Development at George Mason University. Her laboratory, KIDLAB, studies two aspects of learning “twice exceptional,” children and how the environment influences reasoning and attention systems in the brain using behaviour, psychometrics, virtual world platforms, gaming techniques, and functional magnetic resonance imaging (fMRI). Bena Kallick is co-author of Thinking-Based Learning. Kallick is the co -director of the Institute for Habits of Mind and program director for Eduplanet21, a company dedicated to online professional learning and curriculum development based on the Understanding by Design® framework.

176

Kandel

Kaneft

Kanfer

Kanwisher

Karpicke

Appendix C

Eric Richard Kandel is a medical doctor who specializes in Psychiatry and is a Eric R. Neuroscientist and University Professor of Biochemistry and Biophysics at the College of Physicians and Surgeons at Columbia University. He was a recipient of the 2000 Nobel Prize in Physiology or Medicine for his research on the physiological basis of memory storage in neurons. Brent Brent Kaneft is a teacher in Park Tudor Indiana and an MBE practitioner. Ruth Kanfer, professor in the School of Psychology, Georgia Institute of Ruth Technology. Her research examines the role of motivation and self -regulation in work and achievement settings and looks at motivational dynamics over time, the influence of adult development and change on motivation and self-regulation, and motivation in and of teams. Nancy G. Kanwisher, professor in the Nancy G. Department of Brain and Cognitive Sciences, and an investigator at the McGovern Institute for Brain Research at the Massachusetts Institute of Technology. She studies the neural and cognitive mechanisms underlying human visual perception and cognition. Jeffrey D. Karpicke is Professor of the Department of Psychological Sciences at Jeffrey D. Purdue University. His areas of research include human learning and memory, especially retrieval processes; cognitive science and education; complex learning, comprehension, and knowledge application; learning and cognitive strategies in children; metacognition and self -regulated learning; and educational technology and computerbased learning.

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Katzir

Tami

Kelly

Curtis

Kharrazi

Kamal

Kiecolt-Glaser

Janice

Kim

Sung-il

177

Tami Katzir directs the Mind Brain and Reading Lab at the University of Haifa. She received her PhD in Applied Child Development at Tufts University and was an Assistant Professor at the Harvard Graduate School of Education in the Mind, Brain and Education program between 2002 and 2006. She joined the Edmond J. Safra Brain Research Center for the Study of Learning Disabilities in 2006 and had been a senior lecturer in the Faculty of Education since 2008. Curtis Kelly is one of the founders of the FAB conferences, the JALT BRAIN SIG, and producer of the MindBrainEd Think Tanks, a magazine that connects brain science to language teaching. He is an MBE practitioner in Japan. Kamal Kharrazi is Emeritus Professor of Education and Psychology in the University of Tehran and Institute of Cognitive Science Studies. He is the president of the board of trustees at the Institute for Cognitive Science Studies. Janice Kiecolt-Glaser is Professor of Psychology at the Ohio State University College of Medicine and the Director of the Institute for Behavioral Medicine Research. He research is in psychoneuroimmunology where she has demonstrated the important health consequences of stress. She also studies how personal relationships influence immune and endocrine function, and health. Sung-il Kim is a Professor of education and director of Brain and Motivation Research Institute (bMRI) at Korea University. He currently serves as the President of Korean Mind, Brain, and Education Society (KMBES). His recent research interests revolve around interdisciplinary approach on interest and motivation, including

178

Klahr

Klingberg

Knowland

Koedinger

Appendix C

neuroeducational approaches on interest and motivation, motivationally adaptive tutoring agent, and designing fun and exciting learning environment. David Klahr is professor in the Department of Psychology, Carnegie Mellon University. David Dr. Klahr’s most recent research has investigated the cognitive processes that support children’s understanding of the fundamental principles underlying scientific thinking. He has worked in a wide variety of schools in the Pittsburgh region, focusing on the relative effectiveness of different instructional methods for teaching children how to design and interpret simple experiments Torkel Klingberg is a professor of Cognitive Neuroscience at the Karolinska Torkel Institute in Stockholm, Sweden. He is the author of The Overflowing Brain: Information Overload and the Limits of Working Memory, and The Learning Brain: Memory and Brain Development in Children. He is executive director of Cognition Matters, a project that provides free digital cognitive training tools for children worldwide. Victoria Knowland, is interested in Victoria language development, works in York University, and has written one chapters for the book titled Educational Neuroscience. She recently published “Educational neuroscience: progress and prospects”. Kenneth R. Koedinger is a professor of Human Computer Interaction and Kenneth R. Psychology at Carnegie Mellon University. Using his multidisciplinary background, he researches the understanding of human learning using creating educational technologies that increase student achievement. His research has contributed

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Koizumi

König

Korthagen

Kovalþíková

179

new principles and techniques for the design of educational software and has produced basic cognitive science research results on the nature of student thinking and learning. Hideaki Koizumi is an Honorary Fellow of Hitachi, Ltd. Koizumi is also recognized worldwide as an early proponent and major Hideaki advocate of the new transdisciplinary field of Mind-Brain Science, proposing such novel concepts as "Brain-Science and Education," and "Trans-disciplinarity (TD)". His work has been recognized through many honours including an audience with the late Pope John Paul II in 2003 following an invited presentation at the 400th Anniversary of the Pontifical Academy of Sciences (PAS) at the Vatican. Johannes König is a Professor in the Faculty Johannes of Human Sciences at the University of Cologne. His research focuses on teacher education and the teaching profession. He has presented on TED on the topic of “Teacher Education and Development Study: Lessons and Validation”. Franciscus Korthagen is Emeritus Professor in Education, Utrecht University. Studies in Franciscus Social and Behavioural Science, Educational and Pedagogy and Education. His expertise is in teacher education. His specialties are reflection and self-management as central aspects of professional development. He is co-developer of the core reflection approach, Quality from the Inside. Iveta Kovalþíková is the Vice-Rector of the Iveta University of Presov, Slovak Republic. Her main areas of research are Cognitive education, Cognitive stimulation programs, Practical intelligence and adaptive capabilities, Educational research methodology.

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180

Kovas

Yulia

Krein

Derek

Lach

Michael

Ladson-Billings Gloria

Larrison

Abigail

Yulia Kovas is Professor of Genetics and Psychology at Goldsmiths; honorary professor at Moscow State University; visiting Professor at University of Sussex, New York University in London, Tomsk State University and Higher School of Economics. She directs InLab and co directs the International Centre for Research in Human Development and studies mathematical development in the Twins Early Development Study and leads project IDEA (Individual Differences in Education and Achievement) at the Educational Centre for gifted adolescents. Derek Krein is a teacher at the Tabor Academy and an MBE practitioner. Michael Lach is professor at the Urban Education Institute, University of Chicago and Director of STEM Education and Strategic Initiatives. Previously, he was appointed by Secretary Arne Duncan to lead science and mathematics education efforts at the U. S. Department of Education. Gloria Ladson-Billings, professor in the Department of Curriculum and Instruction, University of Wisconsin– Madison Abigail Larrison’s current research focuses on informing educational practice through the application of knowledge from the brain sciences. Having received her doctorate from Rutgers Center for Molecular and Behavioral Neuroscience in 2000, Abigail engaged in two post-doctoral positions and researched systems level neuroscience, behavioural neuropharmacology of attention systems, and drug reward circuits. She then moved to education. After teaching for three years on the South Side of Chicago she entered a second doctoral program in educational leadership.

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Laurillard

Diana

Leaske

Marilyn

LeDoux

Joseph

Lee

Meg

Lená Pierre J.

181

Diana Laurillard is Professor of Learning with Digital Technologies at the London Knowledge Lab at the University College of London, where she leads research projects on developing the Learning Designer suite of tools and online community for teachers and trainers, adaptive software interventions for learners with low numeracy and dyscalculia, and on the use of MOOCs for professional development. Marilyn Leask is Professor of Education at De Montfort University. Leask specialises in the knowledge required for teaching, knowledge management in education and in building the evidence and knowledge base for teacher education. Leask co-chairs the Mapping Educational Specialist Know How (MESH), and several translational research initiative in education. Joseph E. LeDoux is an American neuroscientist whose research is primarily focused on survival circuits, including their impacts on emotions such as fear and anxiety. LeDoux is Professor of Science at New York University, and director of the Emotional Brain Institute, a collaboration between NYU and New York State with research sites at NYU and the Nathan Kline Institute for Psychiatric Research in Orangeburg, New York. Meg Lee is a teacher from the Frederick Country Public Schools and considers herself an MBE practitioner. Pierre J. Lená, Pontifical Academy of Sciences, Observatoire de Paris, University of Paris and is an astrophysicist. His life work was aimed at translation of science for the public and is known for his promotion of hands-on learning.

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182

Levine

Felice

Levitt

Patrick

Liben

Lynn S.

Liebenberg

Jacobus

Linnenbrink Garcia

Lisa

Lipina

Sebastian

Felice Levine, former President of the American Educational Research Association and current Executive Director of the American Educational Research Association. She holds A.B., A.M., and Ph.D. degrees in sociology and psychology from the University of Chicago. Pat Levitt is a Senior Fellow at the Center for the Developing Child at Harvard University and serves as Scientific Director of the National Scientific Council on the Developing Child, a policy council that brings the best research from child development and neuroscience to assist state and federal policy makers and private sector business leaders in making decisions regarding child program investment. Lynn S. Liben, professor of Department of Psychology, Pennsylvania State University and she directs the Cognitive and Social Development Lab. She also holds faculty appointments in the College of Health and Human Development and in the College of Education. Jacobus Liebenberg considers himself an MBE practitioner and applies MBE principles in schools. Lisa Linnenbrink-Garcia, Department of Counseling, Educational Psychology and Special Education, Michigan State University. Linnenbrink-Garcia’s research focuses on the development of achievement motivation in school settings and the interplay among motivation, emotions and learning, especially in science and mathematics. Sebastián J. Lipina, is a Researcher on the Council of Science and Technology and Director of the Applied Neurobiology Lab Buenos Aires, Argentina. He is Adjunct Professor of "Social Vulnerability and

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Lloyd-Fox

Sarah

Lucariello

Joan

Luk

Gigi

Mackey

Allyson

183

Cognitive Development" in the School of Humanities at the Universidad Nacional de San Martin (UNSAM). Sarah Lloyd-Fox currently works at Birkbeck, University of London as a Research Fellow and the University of Cambridge as an Affiliated Lecturer. Her research focuses on the investigation of core early cognitive and neural mechanisms in infancy and how individual differences in neurodevelopmental trajectories associate with factors such as increased familial likelihood for developmental disorders and poverty associated challenges. Joan Lucariello is a Professor of Psychology and Education at the Graduate Center of the City University of New York. Her research focus is on learning, including how sociocultural context affects students, and on educational factors, such as instruction/teaching and curriculum. She is also focused on educational policy related to evidence-based practices to facilitate student achievement in higher education and issues of teacher preparation. Gigi Luk is Associate Professor of Education / Counselling Psychology at McGill University and researches the cognitive and neural consequences of bilingualism extends across the lifespan. She leads a research program that examines how diverse language experiences shapes development and learning using neuroimaging and behavioural methods. Allyson Mackey is an Assistant Professor at the University of Pennsylvania. She is interested in how changes in the brain give rise to changes in the mind, both as development unfolds, and in response to experience. Specifically, she is studying how maturational changes restrict plasticity,

Appendix C

184

Magsamen

Susan

Maldonado

Pedro

Malykh

Sergei

Manes

Facundo

Mareschal

Denis

and the mechanisms by which environmental factors tip this balance to shorten or shift windows of peak plasticity. Susan Magsamen is a Professor at the Brain Science Institute at Johns Hopkins University, where she is dedicated to a rigorous translation of basic science to guide practical applications in health, wellbeing and learning. Over the last 15 years, she has actively participated in the development of two emerging progressive fields: neuroaesthetics and the science of learning. These dynamic and evolving interdisciplinary disciplines offer the promise of rigorous research to practice and enhanced outcomes, across a range of societal issues. Pedro Maldonado is a Professor at the University of Chile, Faculty of Medicine where he researches in areas of cognitive neuroscience, neuropsychology using EEG, Eye Tracking Electroencephalography. He also works in teacher education programs. Sergei Malykh, Laboratory for Cognitive Investigations and Behavioral Genetics, Tomsk State University; Laboratory of Developmental Behavioral Genetics, Psychological Institute of Russian Academy of Education. Facundo Manes is a neurologist and neuroscientist at the Institute of Cognitive Neuroscience in Argentina and former Rector at the Universidad Favaloro. Denis Mareschal is a Professor of Psychology at the Centre for Educational Neuroscience, Birkbeck. His interests lie in all aspects of perceptual and cognitive development in infancy and childhood. His research involves a blend of (connectionist) computational modelling and empirical studies with infants and children and focusses on these properties in learning systems.

Crossing Mind, Brain, and Education Boundaries

Marzano

Robert

Mason

Lucia

Masson

Steven

Masterson

Jackie

185

Robert J. Marzano is an educational researcher who studies standards -based assessment, cognition, high-yield teaching strategies, and school leadership, including the development of practical programs and tools for teachers and administrators in K-12 schools. Lucia Mason is a Professor of Educational Psychology at the University of Padua, Italy, and head of the doctoral program in Developmental Psychology and Socialization Processes. Her main research interest is conceptual change. She has carried out studies on analogical reasoning, argumentation in group discussions, and writing to learn as tools for knowledge revision. Her current research interest also regards students’ epistemic beliefs and their role in learning processes, in particular in conceptual change. Steve Masson is a professor in neuroeducation at Université du Québec à Montréal and director of the Laboratory for Research in Neuroeducation (LRN). He also is Editor-in-Chief of the journal of Neuroeducation. Jackie Masterson is professor of Education at the University College of London. Her main research interests are in the areas of literacy development and literacy difficulties. She has used models of skilled reading in order to provide a context for thinking about the set of cognitive processes that are required for competent reading and spelling. She has investigated potential sensory difficulties as underlying causes of literacy problems and have looked at relationships with verbal memory processes.

186

Mayer

McBride

McBride

McCandliss

Appendix C

Richard E. Mayer is an Educational Psychologist who has made significant Richard E. contributions to theories of cognition and learning, especially as they relate to problem solving and the design of educational multimedia. Mayer’s best known contribution to the field of educational psychology is multimedia learning theory, which posits that optimal learning occurs when visual and verbal materials are presented together simultaneously. Hazel McBride is a Professor at the Hazel University of Toronto. She was a certified teacher prior to obtaining her PhD in Cognitive Psychology and now teaches and researches the crossroads of neuroscience and education. Peter McBride is from Far Hills Country Day School in New Jersey and considers Peter himself to be an MBE practitioner. Over the last few years, his school has taken a deeper dive into the research around Mind, Brain, and Education. And partnered with the Center for Transformative Teaching and Learning to advance teacher knowledge about the brain and its functioning. Bruce McCandliss is Professor of Education at Stanford University. Formerly Bruce Assistant Professor of Psychology in Psychiatry at the Sackler Institute for Developmental Psychobiology, Weill Medical College of Cornell University. His research explores how different brain areas change during the acquisition of the foundational skills in reading words and numbers of children in their early school years, and how different aspects of the learning process can influence these changes.

Crossing Mind, Brain, and Education Boundaries

McGuire

Means

Medin

Mehrmohammadi

187

Saundra Yancy McGuire is the Director Emerita of the Center for Academic Success Saundra and retired Assistant Vice Chancellor and Yancy Professor of Chemistry at Louisiana State University. She is author of Teach Students How to Learn: Strategies You Can Incorporate into Any Course to Improve Student Metacognition, Study Skills, and Motivation, and was given the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring in 2007. Barbara M. Means works at Learning Sciences Research, Digital Promise. Means founded the Center for Technology in Barbara M. Learning research group and her research examines the effectiveness of innovative education approaches supported by digital technology. Her recent work includes evaluating the implementation and impacts of newly developed adaptive learning software. She is also studying the long-term effects that attending an inclusive STEMfocused high school has for students from underrepresented minorities. Donald L. Medin is a Professor in the Department of Psychology at Northwestern Douglas L. University. He is trying to understand the role of protected or moral values and decision making as well as the role of emotions in decision making. He is interested in how meaning making affects decision making. As always, the role of culture in cognition remains an important theme. Mahmoud Mehrmohammadi is Mahmoud educational scholar, curriculum theorist and Emeritus Professor of Tarbiat Modares University, Iran. He is former chancellor of a national teacher education university named Farhangian University and has published extensively in this field.

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Appendix C

Renata Meneces Rosat is a physicians and an Associate Professor in the Department of Meneces Rosat Renata Physiology at the Institute of Basic Health Sciences of the Federal University of Rio Grande do Sul. She teaches Physiology, with emphasis on Neuroscience and is dedicated to improved transdisciplinary exchanges, especially from the neuro-, psychological, and educational sciences. Michael M. Merzenich is a Professor Emeritus of Neuroscientist at the University Merzenich Michael of California, San Francisco. He is known for refining sensory cortex maps, improving cochlear implant technology and co founded Scientific Learning, a company that produced FastForWord, to improve children’s language skills. José Mestre is a Professor at the University of Illinois at Urbana-Champaign who is Mestre José interested in how people learn and solve problems in the STEM (science, technology, engineering and mathematics) disciplines. He works at the interface of science learning and cognitive science and studies how both experts and novices store, retrieve and apply knowledge. Andrew N. Meltzoff is a psychologist and an internationally recognized expert on infant and child development. His Metzoff Andrew N. discoveries about infant imitation greatly advanced the scientific understanding of early cognition, personality and brain development. Based on his work on imitation, Meltzoff has developed the "like me" hypothesis of infant development, which explains how infants begin to acquire an understanding of other minds and their mental states (desires, visual perception and basic emotions, for instance), leading to the Theory of Mind hypothesis.

Crossing Mind, Brain, and Education Boundaries

Mills

Debbie

Mora

Sergio

Morris

John

Mugle

Nancy

Murphy

Robert

Nathan

Linda

189

Debbie Mills is a Professor in the School of Psychology, Bangor University. Mills’ research bridges the areas of cognitive neuroscience and cognitive development. She is particularly interested in how learning two languages shapes the organization of the brain, and the interaction between social/emotional experience and language development. In another line of work, she studies links between genes, brain, cognition, and culture. Sergio Mora is a Chilean professor (ret) who developed the Neuroscience and annual Learning conferences in the University of Chile. John Morris is a post-doctoral research fellow at the University of Queensland Brain Institute. He is author of "Neuroscience and Education: Mind the Gap". Nancy Mugle is the Head of school at the Kent School and considers herself an MBE practitioner. Robert Shoichi Murphy is an Associate Professor at the University of Kitakyushu in the Center of Fundamental Education. Robert conducts research in Applied Linguistics, neuroELT, Science Teacher Education, and Microbiology. He is one of the co-founders of the FAB conferences, the JALT BRAIN SIG, and producer of the MindBrainEd Think Tanks, a magazine that connects brain science to language teaching. Linda Nathan, is an Adjunct Lecturer at the Harvard Graduate School of Education where she teaches a course called “Building Democratic Schools: Studio Design Workshop.” Nathan actively mentors teachers and principals and consults nationally and internationally on issues of educational reform, leadership, teaching

190

Nelson

Nelson III

Newcombe

Norton

Novo-Olivas

Appendix C

with a commitment to racial justice and equity, and the critical role of arts and creativity in schools. Drew Nelson is a Visiting Strategy Analyst Allen Drew (Think Tank at German Aerospace Center (DLR). He is an MBE Harvard Graduate, Teaching Fellow for "Neuroscience of Learning course" and manages the MBHE Facebook page for former students of the MBE programs. Chuck Nelson is a Neuroscientist and Psychologist at the Harvard University Charles A. Medical School. His specific interests are concerned with the effects of early experience on brain and behavioural development, particularly as such experience influences the development of memory and the development of the ability to recognize faces. Nelson studies typically developing children, children at risk for neurodevelopmental disorders, and children experiencing profound early psychosocial deprivation. Nora S. Newcombe is a Professor of Psychology and the James H. Nora Glackin Distinguished Faculty Fellow at Temple University. She is a researcher in cognitive development, cognitive psychology and cognitive science, working on the development of spatial thinking and reasoning and on the development of episodic memory. She was the principal investigator of the Spatial Intelligence and Learning Center, one of six NSF-funded Science of Learning Centers. Anderson Anderson Norton is a professor at Virginia Tech University and studies the mathematical mind from a neo-Piagetian perspective. Carlos Novo is a Mexican neuroscientist Carlos who works frequently with universities and teacher programs to improve knowledge about human brain functioning.

Crossing Mind, Brain, and Education Boundaries

Osgood Campbell

Elisabeth

Pakulak

Eric

Paré-Blagoev

E. Juliana

Pasquinelli

Elena

191

Elisabeth Osgood-Campbell works at the Strategic Education Research Partnership at the Harvard Graduate Schools of Education. is an educator, dancer, expressive arts therapist, writer, and researcher, who cherishes the Body as an on-going, creative process. Eric Pakulak is the Acting Director of the Brain Development Lab at the University of Oregon and Associate Professor in the Department of Child and Youth Studies at Stockholm University. His areas of research concern the plasticity of neurobiological systems important for language, attention, and self-regulation, and the effects of early adversity and early training programs on these systems and related behaviours. E. Juliana Paré-Blagoev is Assistant Professor at the School of Education at Johns Hopkins University. She was formerly one of the founding members of the International Mind, Brain, and Education Society. Her current research takes a collaborative, partnership approach to understanding and addressing the needs of children returning to school after being successfully treated for cancer. Elena Pasquinelli is an Associate Member of Institute Jean Nicod is an interdisciplinary lab at the interface between cognitive, humans, and social sciences in Paris, where she is in charge of creating synergies between educators and researchers (cognitive science, neuroscience, and education). She develops pedagogical resources and contributes to the professional development for teachers and teachers’ trainers.

Appendix C

192

Patten

Kate

Payne Bryson

Tina

Peabody

Stephanie

Pellant

Daisy

Pellegrino

James W.

Peña

Marcela

Kate Patten is the Outreach Coordinator for the Educational Neuroscience Laboratory at Simon Fraser University. Patten’s current research interests lie in the neuroscience and neuropsychology of emotion and its implications for neuropedagogy, specifically within the research field of educational neuroscience. Tina Payne Bryson is co-author of The Whole-Brain Child and No -Drama Discipline, along with The Yes Brain, and The Power of Showing Up. Payne Bryson speaks internationally to parents, educators, camps, and clinicians. Stephanie Peabody is a Professor at the Harvard University Extension School and creator of the Mind, Brain, Health and Education course with Kurt Fischer. Daisy Pellant is a teacher at the Breck School and an MBE practitioner. James W. Pellegrino is a Professor at the Learning Sciences Research Institute, College of Education, University of Illinois at Chicago. Pellegrino’s research focuses on children’s and adult’s thinking and learning and the implications of cognitive research and theory for assessment and instructional practice through the analyses of complex learning and instructional environments, including those incorporating powerful information technology tools, with the goal of better understanding the nature of student learning and the conditions that enhance deep understanding. Marcela Peña is Full Professor at the Pontíficia Universidad Católica de Chile. Her research interest is focused to explore early cognitive development and early learning. Integrating behavioural and neuroimage techniques and methods, she and her team study how the infants and

Crossing Mind, Brain, and Education Boundaries

Perkins

Pete

Petersen

Petitto

193

young children learn their native language and develop their mathematical cognition and their symbolic mind. In her studies she includes healthy participants and patients. David Perkins is the Carl H. Pforzheimer, Jr., Professor of Teaching and Learning, David Emeritus, at the Harvard Graduate School of Education, recently retired from the Senior Faculty. He has conducted long-term programs of research and development in the areas of teaching and learning for understanding, creativity, problem-solving and reasoning in the arts, sciences, and everyday life. Brian Pete is president and cofounder of Robin Fogarty and Associates, an Brian international educational consulting firm. Pete works with adult learners and is author of Data! Dialogue! Decisions! And co-author of Twelve Brain Principles That Make the Difference, and A Look at Transfer, and The Right to Be Literate, which was named the 2017 Teachers’ Choice Award Winner for Professional Development. Steven E. Petersen is a Professor in the Department of Neurology and Neurological Steven E. Surgery at the School of Medicine at Washington University Medical School. His lab uses behavioural, functional neuroimaging (fMRI) and functional connectivity (fcMRI) to study the neural mechanisms underlying attention, language, learning and memory. Laura-Ann Petitto is a Cognitive Neuroscientist and a Developmental Cognitive Neuroscientist widely known for Laura Ann her discoveries about the biological foundations of language. She has uncovered key brain structures underlying early human language processing and, with brain imaging technology called functional Near-

194

Petrill

Pinker

Plomin

Poldrack

Appendix C

infrared Spectroscopy (fNIRS), she has tracked the typical and atypical development of these brain structures across the human lifespan (infants through adults; Scientific Contributions) Stephen A. Petrill is a Professor in the Department of Human Development and Family Science at Ohio State University. He Stephen A. researches why some children struggle to learn to read, and/or have difficulty with language, or experience challenges solving math problems, whereas other children develop these skills almost effortlessly. His goal is to identify genetically and/or environmentally mediated biomarkers that help identify the varied pathways through which learning difficulties develop, with larger goal of developing biobehavioural models of prevention and remediation. Steven Arthur Pinker is a CanadianAmerican cognitive psychologist, linguist, Steven and popular science author. He is Johnstone Family Professor in the Department of Psychology at Harvard University and is known for his advocacy of evolutionary psychology and the computational theory of mind. Pinker’s academic specializations are visual cognition and psycholinguistics. Robert J. Plomin is a Psychologist and Robert J. Geneticist at King’s College in London. He is best known for his work in twin studies and behaviour genetics and his stance that intelligence is primarily inherited. Russell A. Poldrack is a professor of Computer Science and Psychology at Russell A. Stanford University, member of the Stanford Neuroscience Institute and director of the Stanford Center for Reproducible Neuroscience, and author of The New Mind Readers-What neuroimaging can and cannot reveal about our thoughts.

Crossing Mind, Brain, and Education Boundaries

Politano

Colleen

Pollack

Courtney

Posner

Michael

Purdy

Noel

Quartz

Steve

195

Colleen Politano is a consultant working for school districts and the Bureau of Education and Research in British Columbia. She presents workshops on a wide variety of topics, including literacy, brain-based learning, differentiated instruction, multi-age classrooms, and authentic assessment Courtney Pollack is a Research Affiliate at the Massachusetts Institute of Technology in the Gabrieli Laboratory. She works across education research, developmental psychology, and cognitive neuroscience to understand and reduce challenges to student learning. Michael I. Posner is currently an Emeritus Professor of Psychology at the University of Oregon in the Department of Psychology, Institute of Cognitive and Decision Sciences, and an Adjunct Professor at the Weill Medical College in New York (Sackler Institute). He is an eminent researcher in the field of attention and has been ranked by the Review of General Psychology survey as the 56th most cited psychologist of the 20th century Noel Purdy is a Professor at Strandmills University College, Belfast, Ireland. His research interest is in pastoral care in education, bullying in schools, educational underachievement, special needs and initial teacher education. Steven Quartz is the principal investigator of the National Science Foundation (NSF) Integrative Graduate Education and Research Traineeship grant-supported program Brain, Mind, and Society, which provides students with the analytic foundations and the experimental skills needed to pursue careers at the intersection of neuroscience and the social sciences.

Appendix C

196

Racine

Eric

Ramacciotti

Mirela

Rechtschaffen

Daniel

Reimann

Peter

Restak

Richard

Eric Racines is the Director of the Pragmatic Health Ethics Research Unit and Brainstorm Magazine, Pragmatic Health Ethics Research Unit, IRCM. Racine is a leading international researcher in bioethics. Inspired by philosophical pragmatism, his research aims to bring to the forefront the lived experience of ethically problematic situations by patients and stakeholders and then to resolve them collaboratively through deliberative and evidence-informed processes. Mirela Ramacciotti directs Neuroeducame in Brazil, an organization dedicated to scientific translation of neuroscientific research for teachers and the promotion of Mind, Brian, and Education in Sao Paolo. She is an MBE practitioner. Daniel Rechtschaffen is a marriage and family therapist. He is the author of The Way of Mindful Education and teaches mindfulness practices to both teachers and students. Peter Reimann is a researcher for the European Commission in the area of educational technology. His primary research areas are cognitive learning research with a focus on educational computing, multimedia-based and knowledge-based learning environments, elearning, and the development of evaluation and assessment methods for the effectiveness of computer-based technologies. Richard Restak is a Psychiatrist and Clinical Professor of Neurology at George Washington University School of Medicine and Health sciences. He is the author of more than 20 best-selling books on the brain and is a prominent scientific translator.

Crossing Mind, Brain, and Education Boundaries

Ribeiro

Sidarta

Rinne

Luke

Risko

Evan F.

Ritchhart

Ron

Robey

Alison

197

Sidarta Tollendal Gomes Ribeiro is Professor of Neuroscience and Director of the Brain Institute at Universidade Federal do Rio Grande do Norte (UFRN); Ribeiro is currently the Chair of the Regional Committee in Brazil of the Pew Latin American Fellows Program in the Biomedical Sciences. He is also member of the Steering Committee of the Latin American School for Educational, Cognitive and Neural Sciences Luke Rinne is a Research Scientist, Institute of Child Development, University of Minnesota. His research focuses on the development of mathematics abilities and related cognitive functions from early childhood through adolescence. Evan Risko is an Associate Professor of Cognitive Research heads the Department of Psychology at the University of Waterloo. His research is focused on embodied and embedded cognition. Ron Ritchhart is Principal Investigator for the “Cultures of Thinking Project,” and Senior Research Associate at Project Zero at Harvard University. He is the co-author of Making Thinking Visible. Alison Robey is a Professor at the University of Maryland, College Park in the Department of Psychology. Her main focus is on identifying and testing educational applications based on cognitive theory. Robey’s previous research was on why retrospective confidence judgments are better predictors of future recall. She is now focused on self-regulated learning which involves what students decide to study and how.

198

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Rogoff

Rose

Rose

Rose

Appendix C

Vanessa Rodriguez is an Assistant Professor in the Department of Population Vanessa Health in the Center for Early Childhood Health and Development at New York University School of Medicine. She is a graduate of the Harvard University Mind, Brain, and Education program, runs The Teaching Brain Project, and is a former NYC middle school teacher. Barbara Rogoff is the University of California at Santa Cruz’s Distinguished Barbara M. Professor of Psychology. She investigates cultural aspects of children’s learning and how communities arrange for learning, finding especially sophisticated collaboration and attention among children from Indigenous communities of the Americas. David Rose is a Developmental Neuropsychologist and Educator whose David primary focus is on the development of new technologies for learning. As a researcher, Rose has been the Principal Investigator on many US Department of Education and National Science Foundation grants, most of them related to advancing the ideas and practices of Universal Design for Learning (UDL). Steven Peter Russell Rose is Emeritus Steven P.R. Professor of Biology and Neurobiology at the Open University and Gresham College, London. He is also an author, and social commentator. L. Todd Rose is the co-founder and president of the Center for Individual Todd L. Opportunity and a faculty member at the Harvard Graduate School of Education. He is a scientist in Developmental Psychology known for his work applying dynamical systems principles to the study of development, intelligence, and learning, and

Crossing Mind, Brain, and Education Boundaries

Rothbart

Mary K.

Rowe

Meredith

Rueda

Rosario

199

for his contributions to the field of Mind, Brain, and Education (Educational Neuroscience). He is the author of Square Peg and The End of Average. Mary K. Rothbart is Distinguished Professor Emerita of Psychology at the University of Oregon. Her research has focused on temperament, attention, emotion, and social development, and she has developed several widely used measures of temperament, including parent and selfreport questionnaires, home observations, and laboratory observations. Rothbart’s work with Michael Posner has explored the cognitive skills, attention networks, and attention genes that support effortful control in children. Meredith Rowe is a Professor at the Harvard Graduate School of Education (HGSE). She leads a research program on understanding the role of parent and family factors in children’s early language and literacy development. She is particularly interested in uncovering how variations in children’s early communicative environments contribute to language development and in applying this knowledge to the development of intervention strategies for low-income families. Rosario Rueda is a Professor in the Department of Psychology, University of Oregon and Associate Professor of Cognitive Neuroscience in the Department of Experimental Psychology at the University of Granada, in Spain. Rueda runs the Developmental CogNeuro Lab at the Center for Research on Mind, Brain and Behavior (CIMCYC) at the UGR in Spain. She is primarily interested in studying the development of attention and self-regulation

Appendix C

200

Sah

Pankaj

Sahlberg

Pasi

Sapolsky

Robert

during childhood, as well as factors that influence such development, including environmental (e.g., parenting and socioeconomic status), educational (e.g., cognitive training) and constitutional (e.g., temperament and genes) variables. Pankaj Sah is Director of the Queensland Brain Institute (QBI) at The University of Queensland (UQ). He is renowned for his work in understanding the neural circuitry of the amygdala, an area of the brain that plays a central role in learning and memory formation. His laboratory uses a combination of molecular tools, electrophysiology, anatomical reconstruction, calcium imaging and behavioural studies to examine the electrophysiological signatures of different brain regions and their impact on disease. He is the Editor-in-Chief of the Nature Partner Journal npj Science of Learning. Pasi Sahlberg is a Professor of Education Policy at the Gonski Institute for Education, University of New South Wales in Sydney, Australia and visiting Professor at Harvard University. Sahlberg is a Finnish educator and author who has worked as schoolteacher, teacher educator, researcher, and policy maker and is a former senior education specialist at the World Bank, a lead education expert at the European Training Foundation, and a director general at the Finland’s Ministry of Education. Robert Morris Sapolsky is a Neuroendocrinologist and author. He is currently a Professor of Biology and Neurology and Neurological sciences and, by courtesy, Neurosurgery, at Stanford University. He is best known for his work on emotions, specifically stress, and their impact on behaviour.

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Schumacher

Schwartz

Schwartz

Schwartz

Schweingruber

201

Ralph Schumacher, Professor, ETH Zurich, Research Scientist, heading the MINT Learning Center together with Andreas Vaterlaus. Specializes in research on teaching and learning and Mind, Brain and Education. Daniel L. Schwartz is the Dean of the Graduate School of Education at Stanford Daniel University. Dr. Schwartz studies student understanding and representation and the ways that technology can facilitate learning. He works at the intersection of cognitive science, computer science, and education, examining cognition and instruction in individual, cross -cultural, and technological settings. Jeffrey Schwartz is a Psychiatrist and Jeffrey M. research in the field of neuroplasticity and the author of The Mind and the Brain: Neuroplasticity and the Power of Mental Force. He is a proponent of mind-body dualism and researches obsessive compulsive disorder. Marc Schwartz is the former Director of the Southwest Center for Mind, Brain and Marc Education at University of Texas at Austin. Schwartz is a charter member and served as the president of the International Mind, Brain and Education Society (IMBES). Marc Schwartz’s expertise focuses on translating cognitive and neuroscience for educational contexts. Heidi Schweingruber is Director of the Board on Science Education at the National Heidi Academies of Sciences, Engineering and Medicine. In that role, she oversees a portfolio of work that includes K-12 science education, informal science education and higher education. Schweingruber work resulted in the report "A Framework for K12 Science Education" (2011) which served as the blueprint for the Next Generation Ralph

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Science Standards. Catherine L. Sebastian is co-author of “Social Development” in Mareschal, Sebastian Catherine Butterworth and Tolmie’s Educational L. Neuroscience. Her research looks at how young people learn to regulate or control their emotions, and how this relates to socioemotional wellbeing and mental health. Núria Sebastián Gallés is Professor of Psychology at Pompeu Fabra University Sebastián Galles Nuria where she heads the Speech Acquisition and Perception (SAP) Research Group. She is a cognitive scientist known for her work on bilingual language development and the impact of bilingualism on cognition. Zewelanji N. Serpell is an Associate Professor in the Department of Psychology Serpell Zewelanji at Virginia Commonwealth University. Her N. work considers school a context for cognitive development and, examines sociocultural processes that promote or inhibit learning, specifically for African American students. She is specifically interested in harnessing advances in cognitive science to develop and test schoolbased programs that support executive functioning. Sebastian (Hyeonjun) Seung is a multidisciplinary scientist whose research efforts Seung Sebastian have spanned the fields of neuroscience, physics, computer science, bioinformatics, machine learning, deep learning, and artificial intelligence. He has helped pioneer the new field of Connectomics, "developing new computational technologies for mapping the connections between neurons," as the cartographer of the brain. Shaules Joseph Joseph Shaules is a teacher and MBE practitioner in Japan. He has written books on social contagion, language acquisition and MBE.

Crossing Mind, Brain, and Education Boundaries

Sheese

Brad

Sheridan

Kimberly M.

Shonkoff

Jack P.

Siegel

Daniel

203

Brad Sheese is a Professor in the Departments of Neuroscience and Psychology. He researches development of self-regulation, attention, and executive functions in infancy and early childhood and the teratogenic influences on early development. Kimberly Sheridan is an Associate Professor of Educational Psychology at George Mason University. She is also affiliated with the Learning Technologies and Research Methods programs and holds a joint appointment in the College of Visual and Performing Arts. Her research interests include informal/non-formal education, creativity, design thinking, STEM/STEAM education, arts learning, museum education, and sociocultural perspectives. Jack P. Shonkoff, M.D., is the Julius B. Richmond FAMRI Professor of Child Health and Development at the Harvard T.H. Chan School of Public Health and Harvard Graduate School of Education; Professor of Paediatrics at Harvard Medical School and Boston Children’s Hospital; Research Staff at Massachusetts General Hospital; and Director of the universitywide Center on the Developing Child at Harvard University. He currently chairs the National Scientific Council on the Developing Child. Daniel Siegel is a Clinical Professor of Psychiatry at the University of California at Los Angeles School of Medicine and the founding co -director of the Mindful Awareness Research Center. Siegel is also the executive director of the Mindsight Institute, an educational organization, which offers online learning and in-person seminars that focus on how the development of mindsight in individuals, families and

Appendix C

204

Sigman

Mariano

Simmers

Kristin

SinclaireHarding

Lysandra

Small

Dana M.

Smilkstein

Rita

communities can be enhanced by examining the interface of human relationships and basic biological processes. Mariano Sigman is the Director of the Integrative Neuroscience Laboratory in the University of Buenos Aires in Argentina. He is a physicist by training, is a leading figure in the cognitive neuroscience of learning and decision making. Sigman is the author of The Secret Life of the Mind. Kristin Simmers is a 14-year veteran teacher and MBE practitioner who is now conducting doctoral work in neuroscience and education at the University of Connecticut. Lysandra Sinclaire-Harding is a Faculty Member of Education in the University of Cambridge. She is co-author of the “Neuroscience and Early Childhood Education” chapter book published in International Handbook of Early Childhood Education. Her research and practice is dedicated to children displaying complex emotions and behaviours in class and who may be struggling to learn. Dana M. Small is a Professor of Psychology in the Department of Psychiatry at the Yale Medical School and the Director of the Modern Diet and Physiology Research Center. Her research focuses on understanding how sensory, metabolic and neural signals are integrated to determine food choices and on how the dysregulation of these systems contribute to the development of obesity, diabetes and cognitive impairment. Rita Smilkstein is co-author of Igniting Student Potential: Teaching with the Brain’s Natural Learning Process and was a leader in brain-based education for teachers at its onset.

Crossing Mind, Brain, and Education Boundaries

Smith

Marshall Mike

Sodian

Beate

Sousa

David A.

Stanovich

Keith

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Marshall Mike Smith is a Senior Fellow at the Carnegie Foundation for the Advancement of Teaching at Stanford University. Previously, he served for two years in the Obama administration as the senior counsellor to the secretary of education and director of international affairs. From 2001-2009 he directed the Education Program at the William and FloraHewlett Foundation. Prior to that, he was the undersecretary of education for seven years. Beate Sodian is a Full Professor in Developmental Psychology at the University of Munch, Center For Neuroscience, Brain and Mind where she studies Theory of Mind and scientific thought. David A. Sousa is a former Adjunct Professor at Seton Hall University, an international consultant in educational neuroscience, and author of a dozen books that translate brain research into strategies for improving learning. He has presented to more than 100,000 educators across the United States, Canada, Europe, Australia, New Zealand, and Asia. He has taught high school chemistry, and served in administrative positions, including superintendent of schools. Keith E. Stanovich is Emeritus Professor of Applied Psychology and Human Development, University of Toronto and former Canada Research Chair of Applied Cognitive Science. His research areas are the psychology of reasoning and the psychology of reading. His research in the field of reading was fundamental to the emergence of today’s scientific consensus about what reading is, how it works and what it does for the mind.

206

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Stern

Sternberg

Strauman

Strauss

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Henderien Steenbeek works as Associate Professor at the Department of Henderien Developmental Psychology and Professor in the Teachers College at the University of Groningen, the Netherlands. She works in the research program Curious Minds, which aims to unravel the dynamics of teacher -student interaction in a range of domains, including science education within naturalistic circumstances. Elsbeth Stern has been Professor of Empirical Learning and Instruction Research Elsbeth and head of the Institute of Behavioral Sciences in the Department of Humanities, Social and Political Sciences at the ETH Zurich since autumn 2006. She is responsible for the pedagogical aspect of the ETH teacher training program. For the past 20 years, her work as a cognitive psychologist has focused on learning in science and mathematics. Robert J. Sternberg is a Psychologist and Robert Psychometrician. He is Professor of Human Development at Cornell University. He was the past President for the American Psychological Association. Among his major contributions to psychology are the triarchic theory of intelligence. Timothy J. Strauman is a Professor in the Department of Psychology and Neuroscience Timothy J. at Duke University. Strauman’s research focuses on the psychological and neurobiological processes that enable selfregulation, conceptualized in terms of a cognitive/motivational perspective, as well as the relation between self-regulation and affect. Sidney Strauss is Emeritus Professor at the Sidney School of Education in Tel Aviv University. He studies analogical reasoning in children; child development; and teaching as a natural condition.

Crossing Mind, Brain, and Education Boundaries

Sullivan Palincsar

Swartz

Takeuchi Talkhabi

Tan

Tinling

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Annemarie Sullivan Palincsar is a Annemarie Professor at the School of Education at the University of Michigan. Palincsar’s primary research interest is in supporting students to learn how to engage in knowledge building with informational text, especially in the context of project-based scientific inquiry. Robert J. Swartz is Director of the National Center for Teaching Thinking, USA, and an Robert J. Emeritus Faculty member at the University of Massachusetts at Boston. He is co-author of Thinking-Based Learning and has worked extensively over the past twenty five years with teachers, schools, school districts, and colleges internationally in staff-development projects on restructuring curriculum and instruction by infusing critical and creative thinking into content teaching. Osamu Osamu Takeuchi is an MBE practitioner in Japan Mahmoud Talkhabi is the Director of the Mahmoud Mind, Brain and Education Program at the Iranian Institute for Cognitive Sciences Studies. He has published national works at the intersection of philosophical perspectives to education with students’ learning. Yuen Sze Michelle Tan is an Associate Yuen Sze Professor at the Graduate Schools of the Michelle University of British Columbia who researches professional learning communities, learning study, action research, lesson study, teacher inquiry, reflective practice and teacher research. David Tinling is a mind-body physician David who graduated from the University of Washington School of Medicine and was on the faculty of the University of Rochester Medical School. He lives in Vermont, where he writes fiction and poetry and makes conceptual art.

Appendix C

208

Tang

Yi-Yuan

Tardif

Eric

Thomas

Michael S.C.

Tolmie

Andrew

Tang Yi-Yuan is a Neuroscientist and Psychologist at Texas Tech University. He uses behavioural and physiological measures, neuroimaging, genetic analysis, and prevention/interventions in his basic and translational work. He is studying how the brain processes information, makes decision and drives behaviour in a large-scale network; how experiences (learning or training) affect brain processing and reshape brain networks that support attention control, and cognitive function (working memory, creativity, implicit learning). Eric Tardif, Professor University of Teacher Education at Vaud, Switzerland. His interests are in cognitive neuroscience, cognition and education sciences. He is also interested in adolescent development and risk taking. Special attention is also given to school-based prevention and the promotion of students’ psychosocial health. Michael S. C. Thomas is a Professor of Cognitive Neuroscience at Birkbeck, University of London, and the Director of the Centre for Educational Neuroscience. His primary interests are in cognitive and language development, both in terms of developmental processes in children and in the final cognitive structures they produce in the adult. He currently leads the Developmental Neurocognition lab. Andrew Tolmie is Professor of Developmental Psychology and currently the Deputy Director of the Centre for Educational Neuroscience at Birkbeck University. His research focuses primarily on the growth of children’s explicit knowledge, particularly in the pre-school and primary age range, on the role of dialogue with parents, tutors, teachers and peers in promoting this development, and on

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Torresi

Tzur

van Atteveldt

van Damme

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quantitative modelling of the impact of a range of influences on representational and behavioural change. Carol Ann Tomlinson is a Professor at the Carol Ann University of Virginia and a leader in differentiated education. She teaches courses for Leadership, Foundations, and Policy and for Curriculum and Instruction as well as serving as Co-Director of Curry’s Institute on Academic Diversity. Sandra Sandra Torresi is an Argentinian teacher educator who specializes in Dyscalculia and who considers herself an MBE practitioner. Ron Tzur is a Professor at the University Ron Colorado in the School of Education, and Human Development He is the current of Chair of the American Educational Research Association’s Special Interest Group on Neuroscience, Brain and Education. Nienke van Atteveldt is an Associate Professor at the University of Amsterdam, Nienke Faculty of Behavioural and Movement Sciences, Clinical Developmental Psychology; Associate Professor, LEARN! Brain, learning and development. Her research looks at why some adolescents avoid challenges, while others thrive at challenging school tasks? Why are some students more resilient to setbacks at school than others? Dirk Van Damme is currently Head of the Innovation and Measuring Progress Dirk Division (IMEP), which covers both the Centre for Educational Research and Innovation (CERI) and the Indicators of Educational Systems (INES) programme, in the OECD Directorate for Education and Skills

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210

van Geert

Varma

Vidal

Vuillier

Wanchisen

Paul L.C. van Geert is Emeritus and Honorary Professor of Complex Dynamic Systems in Development, Education, and Teaching at the University of Groningen. His research focuses on fundamental developmental theory, and on the application of the theory of complex dynamic systems in education, teaching, and clinical practice. Sashank Varma is Associate Professor at Sashank the University of Minnesota and heads The Cognitive Architecture Lab takes a multidisciplinary approach to the fundamental cognitive mechanisms that support high-level cognition. Fernando Vidal is a Research Professor of the Catalan Institution for Research and Fernando Advanced Studies (ICREA), Professor at the Center for the History of Science of the Autonomous University of Barcelona, and Associate Member of the Centre Alexandre Koyré, Paris. His book, Being Brains" (2019), critically explores the ‘cerebral subject’ in history and contemporary culture. Laura Vuillier is a Lecturer at Bournmouth University teaching Educational Psychology Laura and Eating and Behavioural Disorders. In her doctoral work, she investigated the relationship between self-regulation abilities and executive functions, and more particularly the relationship between emotion regulation and inhibitory control in children using EEG and behavioural assessments. Barbara A. Wanchisen has been the Barbara M. Executive Director of the Federation of Behavioral, Psychological, and Cognitive Sciences since 2001 and of the Foundation for the Advancement of Behavioral and Brain Sciences, which she was instrumental Paul L.C.

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Wandell Brian A.

Watson

Andrew

Whitebread

David

Whitman

Glenn

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in founding, since 2004. She has been instrumental in furthering the mission to advocate for the brain, behavioural, psychological, and cognitive sciences. Brian A. Wandell is a Professor in the Department of Psychology at Stanford University. He is Director of Stanford’s Center for Cognitive and Neurobiological Imaging and Deputy Director of the Wu Tsai Neuroscience Institute. Wandell’s research centres on vision science, spanning topics from visual disorders, reading development in children, to digital imaging devices and algorithms for both magnetic resonance imaging and digital imaging. Andrew Watson is from Translate the Brain and self-described MBE practitioner. David Whitebread is a Professor at the University of Cambridge in the Faculty of Education and is a Developmental Cognitive Psychologist and specialist. His research interests are concerned with children’s psychological development and implications for early years and primary education. A particular focus has been the development of young children’s metacognition and selfregulation in relation to a member of areas of development. Glenn Whitman is the co-author of Neuroteach: Brain Science and the Future of Education and directs the Center for Transformative Teaching and Learning at St. Andrew’s Episcopal School. Glenn is a former Martin Institute for Teaching Excellence Fellow and author of Dialogue with the Past: Engaging Students and Meeting Standards through Oral History as well as co-editor of Think Differently and Deeply, the international publication of the CTTL. Glenn is also a blogger for Edutopia.

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Wiliam

Dylan

Williams

Diane L.

Williams

Jason

Willingham

Daniel T.

Willis

Judy

Dylan Ap Rhys Wiliam is a British educationalist and Emeritus Professor of Educational Assessment at the University College of London’s Institute of Education. His research focus is the professional development of teachers. He is co-author of Inside the Black Box, about formative assessment and author of Embedded Formative Assessment. Diane L. Williams is author of ‘The Speaking Brain’ in Sousa’s Mind, Brain, and Education: Neuroscience implications for the classroom. Her primary area of interest is in language processing, reciprocal communication, social cognition, memory, and learning in autism spectrum disorders using behavioural measures and functional magnetic resonance imaging. Her transdisciplinary work covers disorders, neurology, psychology, and cognitive science. Jason Williams is an MBR practitioner from Principal, Northeast High School. Daniel T. Willingham is a psychologist at the University of Virginia, where he is a Professor in the Department of Psychology. Willingham’s research focuses on the application of findings from cognitive psychology and neuroscience to K-12 education. In 2009, he published Why Don’t Students Like School. Judy Willis is an Adjunct Professor at the University of California in Santa Barbara. She is a board-certified Neurologist and has combined her 15 years as in this field with her years of classroom experience. She is now a full-time teacher educator. She travels nationally and internationally giving presentations, workshops, and consulting while continuing to write books for parents and educators. She is an authority in the

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Wilson

Wolf

Wolfe

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field of learning-centred brain research and classroom strategies derived from this research Donna Wilson is an Adjunct Faculty and lead developer of the EdD minor in BrainDonna Based Leadership, Educational Specialist degree in Teacher Leadership, and Master’s degree programs in Brain-Based Teaching with the Abraham S. Fischler School of Education at Nova Southeastern University. With a background in Education and Psychology, she has been a pioneer in bridging brain science and psychology to educational practice. Suzanne Suzanne Wilson is a Neag Endowed Professor of Teacher Education at the University of Connecticut where she currently serves as Professor in the Department of Curriculum and Instruction. She is the author of How Teachers Teach: Mapping the Terrain of Practice. Maryanne Wolf is a scholar, a teacher, and an advocate for children and literacy around Maryanne the world. She is the Director of the Center for Dyslexia, Diverse Learners, and Social Justice at the University of California at Los Angeles’ Graduate School of Education and Information Studies. She is best known for her work on reading and the brain and her books Proust and the Squid: The Story and Science of the Reading Brain and Reader, Come Home: The Reading Brain in a Digital World. Jeremy M. Wolfe, is Professor of Jeremy M. Ophthalmology at the Harvard Medical School and Director of the Visual Attention Lab at Brigham and Women’s Hospital where he researches visual perception and attention as they relate to cognition.

Appendix C

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Wolfe

Patricia

Xie

Yu

Zakrajsek

Todd L.

Zull

James E.

Patricia Wolfe is an award-winning author and presenter and author of Brain Matters. She has presented to Congress on the importance of neuroscience knowledge for classroom teachers. Yu Xie, professor in the Department of Sociology at the University of Michigan. And has a faculty appointment at the Princeton Institute of International and Regional Studies. He is also a Visiting Chair Professor of the Center for Social Research, Peking University. His main areas of interest are social stratification, demography, statistical methods, and sociology of science. Todd Zakrajsek is an Associate Research Professor at the University of North Carolina at Chapel Hill where he is charged with developing faculty resources pertaining to teaching, leadership and scholarly endeavours. He is co-author of The New Science of Learning. James E. Zull is a Professor of Biology and Biochemistry at Case Western Reserve University. He is also the Director of the Human Learning and Teaching Institute and author of From Brain to Mind. His research is focused on how brain research can inform teaching.

APPENDIX D QR CODES AND LINKS FOR TIMELINE ILLUSTRATION AND ANNEXES

Summary Timeline Illustration Poster The summary timeline of our findings is illustrated in a poster that can be accessed by: A. Clicking on this hyperlink; B. Copying and pasting or typing this hyperlink https://drive.google.com/file/d/1NGD5QDcEkPFMZpXeiCK4SjyO b0w2lyPw/view?usp=sharing in your preferred browser; or C. Scanning the following QR code with your device (e.g., phone, tablet or computer).

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Appendix D

Annexe A The evidence supporting the principles supplied by the 2017 Delphi panel and updated by the authors in 2020 can be accessed by: A. Clicking on this hyperlink; B. Copying and pasting or typing this hyperlink https://docs.google.com/document/d/110d8CuFJWOafJrP1UG2zjk n_9EKrOhKY/edit?usp=sharing&ouid=108256499104575728155 &rtpof=true&sd=true in your preferred browser; or C. Scanning the following QR code with your device (e.g., phone, tablet or computer).

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Annexe B The evidence supporting the tenets supplied by the 2017 Delphi panel and updated by the authors in 2020 can be accessed by: A. Clicking on this hyperlink; B. Copying and pasting or typing this hyperlink https://docs.google.com/document/d/13vDmh-SDvOtnnmypxYCMEylQVVP5bRd/edit?usp=sharing&ouid=10825 6499104575728155&rtpof=true&sd=true in your preferred browser; or C. Scanning the following QR code with your device (e.g., phone, tablet or computer).

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