MIND, BRAIN, AND EDUCATION

The Future of Educational

Neuroscience
Kurt W. Fischer, Usha Goswami, John Geake, and the Task Force on the Future of Educational
Neuroscience∗

ABSTRACT—The primary goal of the emerging field of mental models that pervade meaning making in human
educational neuroscience and the broader movement called cultures and (2) the learning pathways along which peo-
Mind, Brain, and Education is to join biology with cognitive ple develop those models and related skills. For these
science, development, and education so that education can tools to reach their potential, a stronger infrastructure
be grounded more solidly in research on learning and for educational research needs to be created, including
teaching. To avoid misdirection, the growing worldwide the development of (1) Research Schools, where practice
movement needs to avoid the many myths and distortions and science jointly shape research; (2) a new generation
in popular conceptions of brain and genetics. It should of ‘‘neuroeducators’’—interdisciplinary researchers and edu-
instead focus on integrating research with practice to create cational engineers with rigorous training in educational
useful evidence that illuminates the brain and genetic bases neuroscience and the construction of tools that connect
as well as social and cultural influences on learning and research with practice and policy; (3) shared data bases on
teaching. Scientists and educators need to collaborate to learning and development, including multisite studies that
build a strong research foundation for analyzing the ‘‘black use common measures across domains; and (4) frequent
box’’ of biological and cognitive processes that underpin use of research designs influenced by neuroscience and
learning. genetics.
Educational neuroscience is emerging as a new field that
brings together biology, cognitive science, developmental
science, and education to investigate brain and genetic bases
Understanding the diversity of abilities and disabilities will of learning and teaching. Research and practice combine
help educators and parents to facilitate individual stu- routinely in many industries and fields to create usable
dents’ learning and development. Promising tools for under- knowledge that has great practical value, but education has
standing learning and teaching include analysis of (1) the not been systematically grounded in such practical research.
Creating a strong research foundation for education requires a
collaborative approach, with a two-way dialogue in which
practitioners and researchers work together to formulate
research questions and methods so that they can be connected
Address correspondence to Kurt W. Fischer, Harvard Graduate School of
Education, Larsen 702, Appian Way, Cambridge, MA 02138-3752; e-mail: to practice and policy.
kurt fischer@harvard.edu. The traditional model will not work. It is not enough for
∗
Members of the Task Force: Daniel Bullock, James Byrnes, Kevin
researchers to collect data in schools and make those data and
Dunbar, Guineviere Eden, Julie Fiez, Kurt Fischer (co-chair), Daniel the resulting research papers available to educators. That is
J. Franklin, John Geake (co-chair), Usha Goswami (co-chair), Sharon not a way for research to create knowledge that is useful for
Griffin, Patricia Kuhl, Bruce McCandliss, Vinod Menon, Ennio Mingolla, shaping education. The traditional way leaves out teachers and
Nora Newcombe, Tomas Paus, Kevin Pelphrey, Russ Poldrack, L. Todd
Rose, Reed Stevens, Rosemary Tannock, Jennifer Thomson, and Lee
learners as vital contributors to formulating research methods
A. Thompson. and questions and neglects the importance of the ecology of
This article is based on a meeting at the National Science Foundation schools and other learning environments. Contributions from
facility, in which a Task Force of researchers and educators considered researchers, teachers, and learners together can create more
the future of educational neuroscience and ways to catalyze its fruitful
development. The views expressed in this article are those of the authors
useful research evidence that will feed back productively to
and do not necessarily represent the views of the National Science shape schools and other learning situations (Fischer, 2009;
Foundation or the United States. Geake, 2005; Goswami, 2008b).

© 2010 the Authors

68 Journal Compilation © 2010 International Mind, Brain, and Education Society and Blackwell Publishing, Inc. Volume 4—Number 2
 Kurt W. Fischer et al.

Need for Infrastructure to Ground Learning and Teaching The lack of grounding of education in research is a key reason
in Research that governments in many parts of the world have initiated
Both business and government commonly support connecting the assessment of students’ learning through standardized
science and practice in order to create useful outcomes, testing in programs such as Program for International Student
leading to usable knowledge. Meteorology combines science Assessment (PISA) (OECD, 2007a) and No Child Left Behind.
and practice to analyze and predict weather patterns, led by These assessment tools provide useful data, but they also
organizations such as the National Center for Atmospheric have serious limitations. They do not assess learning as it
Research. Cosmetics companies spend billions doing research takes place in schools and other educational settings but
on skin care, cosmetics, and personal hygiene, producing examine only performance on group tests, and they mostly
thousands of products grounded strongly on research evidence. preclude input from teachers and learners into the assessment
Food processing, automobile manufacturing, agriculture, the process or the formulation of research questions and methods.
chemicals industry, construction . . . so many fields ground General Motors could not assess cars effectively by testing
themselves solidly in research that is shaped by practical them on a race track and ignoring what they do in everyday
questions about how products function and how they can be driving situations. Nor could Revlon create effective cosmetics
used effectively in real-world contexts. by testing their effects only on people gathered into large
The field of medicine provides a close analogy to education, meeting halls once a year. Education needs assessments in
combining scientific research with practice to improve actual learning situations that are shaped by researchers,
the long-term well-being of human beings. Scientists and teachers, and students working together to examine learning
practitioners work together in teaching hospitals and other and teaching where learning takes place—what Daniel and
locations of practice to apply research to issues of health Poole (2009) call ‘‘pedagogical ecology.’’
and illness. In medicine, which includes the closely related
field of public health, research and practice are thoroughly Obstacles to Moving Forward
intertwined, resulting in huge improvements in treatments and Neuroscience and genetics are booming, both scientifically and
interventions. For example, identifying predictive risk factors in the public imagination. This popularity creates problems
via medical epidemiology can lead to experimental work to for educational neuroscience by creating widespread beliefs
identify causal mechanisms for disease, and understanding that are incorrect, and legitimate scientific efforts to rein
those mechanisms in turn enables targeted treatments in expectations lead to problematic overgeneralization of
and interventions (e.g., Hemenway, 2001, 2009). The same concerns. Scientific findings have been oversimplified to
scientific approach needs to apply to education. form widely held neuromyths. Simultaneously, legitimate
Yet what happened to education? Research produces useful limitations of biological research have been overgeneralized
knowledge for most of the industries of the world, yet via ‘‘postpositivism’’ to create barriers to building research that
somehow it does not serve the same function for education effectively connects biology with education. Of course, there
(Fischer, 2009; Szücs & Goswami, 2007). Despite the obvious are real limitations to making inferences from neuroscientific
importance of schools and other learning institutions for the evidence, and one area in which caution is required is often
well-being of human beings, usable knowledge arising from called ‘‘mind reading,’’ using brain images to infer mental
research on education has been scant, without broad-based activity in individual people.
institutions created to connect science and practice in order to
provide means for grounding learning and teaching in research. Neuromyths, Ethics, and ‘‘Brain-Based Education’’
More than a century ago in 1896, John Dewey proposed the The many scientific advances in neuroscience and genetics
establishment of laboratory schools to provide this grounding have led to a popular obsession that has engendered common
by connecting research with practice. Unfortunately, his vision neuromyths as well as sometimes irresponsible efforts to
has never been realized. There is no infrastructure in education sell commercial projects with claims that they are ‘‘brain
that routinely supports scientific research on learning and based.’’ Expectations about how neuroscience and genetics can
teaching to assess effectiveness. If Avon and Toyota can spend shape educational practice and policy have grown far beyond
millions on research to create better products, how can schools what is merited by the state of educational neuroscience and
continue to use alleged ‘‘best practices’’ without collecting knowledge about how brains and genetics function (Goswami,
evidence about what really works? The emerging field of 2006; OECD, 2007b). Many neuromyths have entered popular
educational neuroscience provides an opportunity to build an discourse—beliefs about, for example, right and left brain
infrastructure to create research grounding for learning and thinking, male and female brains, how much of the brain
teaching, and government funding bodies and institutions as people do not use—that are widely accepted but blatant
well as other stake holders can help to facilitate the creation distortions of research. Most of what is put forward as ‘‘brain-
of this infrastructure. based education’’ builds on these scientifically inaccurate

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myths: The one small way that neuroscience relates to most who lack relevant background knowledge (Weisberg, Keil,
‘‘brain-based education’’ is that students and other learners Goodstein, Rawson, & Gray, 2008).
have brains. These myths typically relate to common mental In fact, drawing inferences about mental activity from brain
models that people learn from their language and culture and activity is a tricky enterprise, requiring much more careful
use unconsciously, such as a model of the brain as a library statistical analysis than is commonly assumed. Most behaviors
that stores information and a model of teaching and learning involve multiple brain regions, not just one or a few, and activity
as direct transmission of information from expert to novice in a brain region or two does not reliably indicate a particular
(Lakoff & Johnson, 1980). These implicit models lead to many kind of mental operation. For example, research evidence may
misconceptions in science, but they can also be harnessed to show that a brain region such as the rostrolateral prefrontal
facilitate education (Fischer, 2009). cortex is active during a particular cognitive process, such
The young field of educational neuroscience needs to move as speaking. Activity in this region does not reliably indicate
beyond these unfounded myths and claims and establish that the person is focusing on a language function, however,
a rigorous research foundation for learning and teaching because other kinds of processes can also evoke activity in
in educational settings. This foundation must start with that region. Poldrack (2006) has demonstrated the statistical
insistence on carefully grounded analysis of neural, genetic, difficulties of drawing this kind of inference. When inferences
cognitive, and emotional components of learning that is based connecting behavior with brain processes such as myelination
in collaboration of teachers and students with researchers. or synaptic pruning are involved, directly relevant data are
Most important, for educational neuroscience to reach its seldom available, and special caution is required in drawing
potential, infrastructure must be created to catalyze research inferences (Paus, Keshavan, & Giedd, 2008). At the same
on learning and teaching, creating scientific knowledge for time, useful inferences can sometimes be drawn from relating
education (Fischer, 2009; Geake, 2009; Goswami, 2006). Then brain activity patterns with behaviors, such as identification
research tools such as brain imaging, analysis of cognitive of common neural networks by their correlation with mental
processing and mental models, and genetics assessment states (Poldrack, Halchenko, & Hanson, 2009). But contrary to
can be used to illuminate the ‘‘black box’’ and uncover images in science fiction and claims in brain-based education,
underlying learning mechanisms and causal relations (Hinton these correlations seldom allow firm inferences about the
& Fischer, 2008). mental state of an individual person.
An important topic for debate as educational neuroscience
emerges is neuroethics, including both the ethics of application
of scientific findings to education and related enterprises such Constructive Bridging: Biological Grounding of Activity and Learning
as parenting and the neuroscience of ethics (how ethical Although care is required in drawing conclusions from brain
behavior is grounded in brain and biology) (Farah & Heberlein, imaging about cognitive and learning processes, biological
2007; Illes & Sahakian, 2009; Sheridan, Zinchenko, & Gardner, knowledge can be useful in analysis of behavior and learning.
2005). Many of the materials that are promoted as brain-based From early in the young history of educational neuroscience,
education raise ethical questions because of their inadequate skepticism has been expressed about the usefulness of linking
grounding in scientifically sound research, as well as other biology to education, especially brain science (Bruer, 1997).
factors, such as the role of individual agency in child-rearing The core argument has been that going from brain science
versus treating children as objects to be designed (Stein, della to education is ‘‘a bridge too far’’ because connecting brain
Chiesa, Hinton, & Fischer, in press; Stein, 2010). Education has knowledge directly to school-related learning is not possible
such powerful effects on children that ethical issues should be given the current state of the art. Importantly, cognitive
as central there as they are in medicine. Debate is needed that science can serve as an intermediary, with a bridge linking
includes not only the scientific community but also parents neuroscience to cognitive science, and then another bridge in
and the public. turn linking cognitive science to education. According to this
argument, education must be combined with neuroscience by
cognitive models and analyses. Yet if narrowly framed, the
Reading Minds from Brain Imaging argument can neglect the broad usefulness of a biological
Brain imaging has especially captured the popular imagination, framework for analyzing learning and teaching (Dunbar,
with images of brain anatomy or brain activity appearing Fugelsang, & Stein, 2007; Fischer, 2009). As a very simple
regularly in articles in newspapers and on the Internet, as example, learning will be impaired if basic biological needs
well as in scientific papers. Several studies have documented (for sleep or nutrition) have not been met (Golombek &
how influential these diagrams are. Readers find articles more Cardinali, 2008).
convincing when they contain brain images as opposed to Moving from neuroscientific knowledge such as images of
graphs or other illustrations (McCabe & Castel, 2008), and brain activity directly to educational application is indeed
neuroscience information is particularly influential in readers difficult in many cases. For example, knowledge of brain

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regions that play a central role in using mathematics does cognitive psychology, can provide a unique means of linking
not obviously facilitate helping students to learn mathemat- structure and function and thereby understanding the nature
ics. But the bridge-too-far analysis omits the usefulness of of developmental change and the effects of environmental and
biological concepts for thinking about educational situations, affective inputs.
especially those involving learning differences, including vari- Although modern genetics has shown the importance of
ations in organic capacities. Understanding the biological inherited biological predispositions in shaping individual dif-
(organic) foundations of vision or hearing or use of the hands ferences, the environment plays the critical role in determining
makes important practical contributions to facilitating stu- how these predispositions play out in terms of developmental
dents’ effective use of their eyes, ears, or hands and thus and learning pathways (Goswami, 2008b; Plomin, Kovas, &
facilitates educational objectives. At the same time, a biological Haworth, 2007). Furthermore, the new field of epigenetics
framework illuminates causal mechanisms regarding how our shows that children create their own learning environments
sensory and motor systems help to build our cognitive systems to some extent. Teachers may react to a child’s genetically
(Goswami, 2008a). Learning differences permeate education, influenced physical characteristics and thus affect the child’s
and biological knowledge often illuminates processes involved behavior, and simple behavioral measures will not capture this
in those learning differences. The relevance of biology is obvi- connection. Likewise, socioeconomic status (SES) appears
ous when a teacher is dealing with a child who is visually hand- to have varied effects depending on genetics (Raizada &
icapped or has brain damage, and it is often also illuminating Kishiyama, 2010). For example, for high SES groups, genet-
in analysis of other kinds of learning differences, ranging from ics shows a stronger link to intelligence test scores than for
plasticity to limitations such as dyslexia (Goswami, 2008b; low SES because of the comparatively uniform environmental
Immordino-Yang, 2007; Schneps, Rose, & Fischer, 2007). experiences of the group. Conversely, for low SES groups,
having a genotype that predisposes a student to a learning
difficulty along with a suboptimal environment can act as a
Diverse Pathways: Many Kinds of Learning, and Many ‘‘double whammy’’ in terms of learning outcomes. Providing the
Kinds of Learners optimal educational environments therefore requires a better
Learning takes many different forms, varying across brain understanding of the interactions of biology (including brain
systems and behaviors within a person and also varying across and genetics) with mind and education. This quest to better
people and social groups. When schools take on the goal understand the biology of learning systems can be informed
of educating everyone, these differences become vital: Every by neuroscientific accounts of identified learning problems
student has a right to learn effectively, whether they learn such as dyslexia, dyscalculia, and Asperger’s syndrome (Fis-
easily with traditional instruction or require a different kind cher, Bernstein, & Immordino-Yang, 2007; Pennington, 2009;
of instructional support. One of the most promising topics Schneps et al., 2007).
for educational neuroscience research is the brain systems Two broad research goals that are feasible to pursue given
necessary for learning and their development. the current state of the field are: (1) understanding how
In order to improve the identification of the particular the brain and genetics contribute to building structured
learning strengths and weaknesses of individual children, an representations and (2) understanding how complexity of
understanding of developmental mechanisms is required (Coch structures of input, action, and neural systems vary and
& Ansari, 2008; Fischer, 1980; Goswami, 2008b). Neuro- develop, and how they can be represented mathematically.
science can help provide better understanding of the entire
range of commonalities and individual differences, from dis-
ability to typical ability to exceptional ability. Neuroscientific Understanding the Development of Structured Representations
and genetic studies support the view that most individual dif- This goal of understanding how structured representations
ferences in learning follow a normal distribution. For example, develop can be addressed by programs of research that focus
most learning difficulties represent the tail end of a normal on either a particular educational skill (such as literacy, numer-
distribution rather than representing qualitatively different acy, reflective judgment, or artistic design) or development of
developmental profiles (Kovas, Haworth, Dale, & Plomin, the representations and processes that mediate people’s educa-
2007). Any understanding of individual differences must also tional interactions (such as language, mathematical symbols,
encompass understanding how environmental factors work to attention, motivation, social interaction, or mental models).
amplify or modify learning strengths and weaknesses shown For example, research in the neuroscience of reading and
by particular children. For example, identical twins can have literacy has highlighted the importance of the efficient func-
markedly different brains, because of epigenetic and environ- tioning of various language-related structures (e.g., Goswami,
mental factors. Integrating data from cognitive neuroscience 2008b; Niogi & McCandliss, 2006), in particular those linked
with data from anatomical, physiological, and social neu- to phonology (sound structure). Work with atypical read-
roscience and genetics, within behavioral frameworks from ers (deaf readers, children with developmental dyslexia) has

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suggested a compensatory role for structures involved in how these models function in human communication and
speech articulation (e.g., those mediated partly by the left infe-
learning (Lakoff & Johnson, 1980). For instance, the conduit
rior frontal gyrus) when the neural networks that typically model of teaching and learning shapes and limits educational
support phonological development are inefficient. Hence to practice in many schools and other settings: Teaching is
foster in all children the optimal development of the structured
treated as simply the transmission of information from teacher
phonological representations that underpin literacy acquisi- to learner, with items of knowledge being treated as objects
tion, more focus on oral language and articulatory processes that are directly exchanged: A teacher gives the student items
may be required. Having developed basic understanding of of knowledge, and then the student has them (supposedly).
language and articulatory processes, research can focus on the Yet students do not learn knowledge merely because it has
roles of other sources of individual differences (such as social
been ‘‘covered’’ in class.
factors, differences in SES, and different teaching environ- In contrast, educators can also make constructive use of
ments), in order to understand their relative contributions at mental models by teaching to them explicitly. For example, the
different points in development. This kind of basic research onbroad model of cognition most widely used takes knowledge
mechanisms of individual differences as they relate to learning and
as an active process, like building, in contrast to direct
education is complementary to categorical disease-based (in transmission. Young children working to understand number
the style of the National Institutes of Health [NIH]) research build a number line, starting with the number 1 and adding one
approaches, and is necessary in order to account for the large digit at a time up to 4 or so, when they generalize to the mental
variation that exists across the whole population of learners. model of a number line, which numerical operations move
As an example of basic research on the structured repre- along. This mental model is used implicitly in many languages
sentations that mediate learning (such as those underpinning and cultures, but it can also be taught explicitly, which creates
language or attention), one attainable research goal is to under-
rapid improvement in arithmetic performance for many young
stand the developmental links between precursor skills and students (Carey, 2009; Griffin, 2005; Griffin & Case, 1997; Le
how the brain builds expertise. For language, such research Corre, Van de Walle, Brannon, and Carey, 2006).
aims to investigate learning and development from the very Although all people use mental models, scientists use
beginning, starting with how infants build linguistic knowl- explicit models to characterize their theories rigorously and
edge prior to the emergence of competent language skills. precisely. Understanding the development of structured rep-
This research requires addressing multiple related questions: resentations including both actions and symbolic systems
for example, understanding the role of basic visual and audi- requires explicit modeling of complex systems. Mathematical
tory processing in language development, understanding how and connectionist models, such as those derived from engi-
small early biases and differences may develop into larger neering, machine learning, and growth modeling, are needed
skill differences, mapping the effects of age on learning (doesto connect research on cognitive and neural constructs with
early learning have a special role?), and considering how thesethe effects of learning, individual differences in, and the nature
research questions apply to educationally critical issues and of developmental change. These models not only capture
contexts (such as becoming bilingual). existing data and help to explain it in principled ways but
Within this broad set of goals, such research programs need they can also be important in generating new insights and
to include developmental and learning studies that capture research questions, such as interpreting different learning sys-
interactive specialization— investigations of how changes in one
tems in interaction with diverse learning environments. To
system impact another system. One example is the connections capture many of the characteristics of education, such models
between written and spoken language: We know that the will have to be dynamic and nonlinear in structure, explic-
impact of learning to recognize visual words has important itly incorporating feedback as a necessary feature of earning
effects on the later development of language systems, but (Bullock, 2004; Fischer & Bidell, 2006; Spencer, Thomas, &
such effects have rarely been mapped with respect to which McClelland, 2009; van Geert, 1998).
languages people are learning and when (Kovelman, Baker, Model testing will require multivariate analytic methods
& Petitto, 2008; Petitto, 2009; Ziegler & Goswami, 2005). to deal with the multitude of important factors influencing
People may also show important differences when they learn learning and performance (Singer & Willett, 2003). For
the phonology of two similar languages such as German and example, when relationships among variables are known,
Dutch, in contrast to two dissimilar languages, such as German Bayesian probability models can be valuable in understanding
and Mandarin. neural systems at all levels of neuroscience (molecular, cellular,
and neural networks). One surprise has been that Bayesian
Understanding Complexity Through Models models show that noisy networks improve learning, at both
People naturally build and use mental models, and analysis and cellular and whole-network levels (Ma, Beck, Latham, &
manipulation of those models have come to play an essential Pouget, 2006). Another surprise has been that hierarchical
role in scientific research. Cognitive linguists have analyzed growth models produce very different growth patterns with

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different environmental inputs: Sometimes they demonstrate of research arises from educational concerns and the potential
attractors for different skill domains (moving toward the applications of the research are field-tested in educational
same pattern) while at other times they show dispersion settings (e.g., Kuriloff, Richert, Stoudt, & Ravitch, 2009).
or repulsion between domains (different tasks or domains Creating this strong connection between research and practice
moving apart with development) (Fischer & Kennedy, 1997; in educational neuroscience requires building new kinds of
van Geert, 1998). infrastructure to nurture and sustain the field.
Insights like these may be critical to advancing a new field Four essential components of a stronger infrastructure are
like educational neuroscience, where educators are continually (1) creation of Research Schools where researchers and prac-
faced with ‘‘noisy systems’’ (viz. children!). However, many titioners work together, (2) training of a new generation of
critical relationships among variables will need to be interdisciplinary researchers expert in both educational and
discovered, and data-mining techniques will be invaluable in scientific research methods, who can grow the new field, as
helping to structure models based on the way learning systems well as a new category of educational engineers who specialize
actually work (Boudett, City, & Murnane, 2005; Singer & in translating between research and practice such as engineer-
Willett, 2003; van Geert & van Dijk, 2002). Such investigations ing educational materials and activities, (3) establishment
in educational neuroscience will need to incorporate measures of useful data bases on learning and development, crafted
of learning, in order to study the learning mechanisms carefully for improvement of knowledge about educational
themselves, including whether they are intact or impaired. neuroscience, and (4) encouraging the use of research designs
A core requirement for a systematic understanding of influenced by neuroscience and genetics.
complexity in development is characterization of learning
pathways for important educational domains (literacy, history,
mathematics, art, science, etc.), including detection of Research Schools
differences in pathways for different kinds of learners. Rather Educational neuroscience requires institutions that support
than age-normed assessments as with intelligence testing, sustainable collaboration between researchers and teachers
what is required is assessments that are normed by complexity so as to build better research and training on teaching and
level as well as relations to brain development, including learning. One important vehicle is the creation of Research
markers of cognitive variability and diverse learning sequences Schools to improve educational neuroscience research by
in populations of children (Fischer & Bidell, 2006; Rose & building institutions that connect researchers with practi-
Dalton, 2009; Stein, Dawson, & Fischer, in press). tioners in order to shape research questions and methods
(Coch, Michlovitz, Ansari, & Baird, 2009; Hinton & Fis-
cher, 2008). One of the strongest institutions in medicine
Creating Infrastructure to Facilitate the Development of for promoting medically usable knowledge is the teaching
Educational Neuroscience hospital. There researchers and practitioners work together
Educational neuroscience research can both advance scientific to both shape research and train future medical researchers
knowledge about the brain and learning and also provide a and practitioners. The result is not only refining procedures
useful base of knowledge for educational practice and policy. and medications but also generating hypotheses and methods
Although powerful tools are available to build this base, the that shape research so that it can more directly affect practice
infrastructure for educational neuroscience is weak (Fischer, and policy. Similarly in agriculture (and many other fields,
2009). Improving the research foundations of educational such as cosmetics and meteorology), researchers and farmers
practice and policy requires creating a stronger infrastructure collaborate in field tests to evaluate and improve agricul-
to support educational research. That research needs to be tural products, equipment, and farming methods. Education
scientifically sound, but for it to be useful for education it lacks this kind of infrastructure for creation of a scientific
also must be connected with the ways teaching and learning groundwork for learning and teaching (Fischer, 2009).
happen in real educational settings, such as homes, schools, Fortunately, education shares with medicine a paradigm
playing fields, the Internet, computer games, and television that captures the essence of experimental research—interven-
(Bell, Lewenstein, Shouse, & Feder, 2009). tion followed by assessment. In an experiment some condition
Importantly, the benefits of educational neuroscience for is created or some manipulation is performed, and it is followed
practice and policy can only be realized if educational by assessment of the result. For medicine, the intervention is a
practitioners (particularly educational researchers and school medication, inoculation, therapy, surgery, or other treatment,
teachers but also curriculum designers and educational policy which is followed by an appraisal or assessment of function or
makers) incorporate educational neuroscientific implications health. Similarly in schools, teachers intervene by attempting
and applications into their professional practices and policies. to teach something, and they then assess students’ skill or
To this end, educational neuroscience needs to include an understanding, either by observing the students’ activity or
action research framework in which the genesis and rationale directly administering a test.

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 Future of Educational Neuroscience

Despite this common paradigm, education and medicine questions in brain-based learning. Schools can then work with
differ greatly in how they treat research in their practice and local universities to apply these model protocols to questions
in the philosophical assumptions underpinning their choice of of interest to them, such as: Will a specific curriculum work in
research methods. Every strong medical school has a teaching my school setting? The role of the templates is to model study
hospital, at which researchers and practitioners jointly work design (e.g., the importance of including appropriate control
to improve research and practice. The usefulness of approaches groups, the benefits of randomized-controlled-trial designs,
that are standard in the natural sciences, utilizing quantitative etc.). These supports help individual teacher–researchers to
methods and the experimental manipulation of variables, do effective research and not to have to ‘‘reinvent the wheel’’
is taken for granted. In contrast, high-quality education each time.
schools have not had Research Schools that bring together The International Mind, Brain, and Education Society
research and practice to advance teaching and learning. Many (IMBES) is working to create a network of Research
such institutions also eschew experimental paradigms drawn Schools around the world by supporting collaborations
from the natural sciences, in the belief that quantitative between scientists and teachers. The Research Schools
experimental approaches have nothing to offer in terms of will help promote changes in school culture, establishing
understanding classroom performance or children’s behavior. the expectation, for example, that empirical research on
We propose that educators need Research Schools—an educational principles and products is an intrinsic part of their
institution comparable to the teaching hospital with the mission. When schools get involved in research, we expect it
express goal of connecting the work of researchers and to have a transformative impact on their delivery of education
practitioners in order to craft research methods and questions and on the research questions addressed in universities. A
that address important issues in education. We argue that few model Research Schools already exist in the United
universities and schools should join together to create States, Europe, Israel, and elsewhere, and they can provide the
Research Schools—real-life schools (public and private) relevant expertise and experience for creating paradigms for
affiliated with universities where educators and researchers Research Schools (Chen, 2010; Cuch et al., 2009; della Chiesa,
work together to create research that relates to educational Christoph, & Hinton, 2009; Kubesch et al., 2009; Kuriloff et al.,
practice and policy and to train future practitioners and 2009; Hinton & Fischer, 2008; Schwartz & Gerlach, in press).
researchers (Hinton & Fischer, 2008). We also propose that Related points of leverage in the system are initial teacher
these Research Schools endorse and promote the application training and continuing professional development. Schools
of both quantitative and qualitative research methods in of Education need to teach trainee teachers and practicing
education. professionals the application of evidence-based standards,
Over a century ago in 1896, John Dewey proposed what starting with research design and statistics (see Boudett et al.,
came to be called ‘‘laboratory schools,’’ which he proposed 2005; Cooper, Field, Goswami, Jenkins, & Sahakian, 2009).
would serve this function. He began the Laboratory School Including educational neuroscience would allow teachers to
at the University of Chicago to test practices in vivo see that neural data are not privileged, but are subject to the
based on hypotheses from psychology and cognitive science. same biases and difficulties of interpretation as data yielded by
Unfortunately, today almost all so-called laboratory schools any experimental method. In this way, teachers can understand
have no involvement in research, but instead function as how to evaluate the claims made by the ‘‘brain-based learning’’
elite schools to provide excellent education for children of industry, which is crucial given the privileged role of the
faculty and students at universities. Despite the name, they teacher as an agent of educational change (Fischer, 2009;
do not serve the function that Dewey proposed. Educational Geake, 2009; OECD, 2007b).
neuroscience faces the problem that Dewey described—little
or no connection between educational practice and research
on learning and teaching. The establishment of Research Creating a New Generation of Interdisciplinary Researchers
Schools can help to solve this problem by creating institutions and Educational Engineers
whose purpose is to produce a strong research foundation for Educational neuroscience requires innovation in training
educational practice and policy. regarding research methods, assessments of teaching and
A central challenge to educational neuroscience is how to learning, analysis of courses, curriculum, and informal learn-
bring educational insights into brain development and brain ing environments, and continuing professional development.
mechanisms into classrooms. The ultimate agent of change in Bringing together the disciplines required (education, psy-
the educational system is the teacher, and so the development chology, neuroscience, genetics, human development, and
of infrastructures that bring teachers and researchers together others) means dealing with different philosophies underpin-
is an important goal. As Research Schools and school–re- ning research (such as the quantitative methods of the natural
searcher partnerships emerge, they can provide templates or sciences versus the qualitative methods of the humanities) and
‘‘model protocols’’ of research methods that enable the study of providing rigorous training in research methods. The different

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research methods of the natural sciences and humanities are with avoidance of overblown claims, such as those that are
complementary rather than mutually exclusive, yet they are common in advertisements for ‘‘brain-based education.’’
often put in juxtaposition within Education faculties.
What is needed is to build a new community of
researchers and practitioners who are expert in the multiple Improving Data Bases on Learning and Development
contributing disciplines and who investigate learning and A fundamental infrastructure to provide a strong scientific
teaching systematically in education settings. This new groundwork for learning and teaching is the creation of
community could be called ‘‘neuroeducators’’ (Gardner, large data bases about learning and development, including
2008) or educational engineers. A genuinely interdisciplinary longitudinal brain, genetic, and behavioral data for large,
training environment is required. Creating this new group typically developing populations. Such data bases have
of researchers and practitioners presents a major challenge great potential usefulness for both research and practice.
for Education departments and schools, requiring substantial For example, the U.S. database for traffic safety, the
changes to their traditional ways of teaching research methods Fatality Analysis Reporting System, shows how useful a
and their connections to practice (Cremin, 1976; Lagemann, comprehensive data base can be (Hemenway, 2001, 2009).
2000, 2008). Such interdisciplinary training would begin Established in 1966, this system collects systematic data on
with bringing together different research communities, and traffic accidents, especially those involving fatalities, with the
this interdisciplinarity should ideally be led by faculties result that data are available to determine the safety of many
of Education. Sustained partnerships with organizations aspects of car design, highway design, and so on. The effects
specializing in the design, development, and delivery of of this data base on traffic safety have been far-reaching and
instructional materials (such as publishers, curriculum deep, contributing substantially to an enormous reduction in
designers, media companies, and software companies) would traffic fatalities and injuries over the last 40 years. Data bases
be advantageous. for educational neuroscience, including evidence about how
One part of the new interdisciplinary community—perhaps educational practices function in real-life settings, can have
called educational engineers—needs to specialize in making similar far-reaching influence.
useful connections between practice and research. They One axiom of education is that children develop at
will have expertise at translating or applying findings different rates and along different pathways, and that better
from cognitive science and neuroscience to learning in understanding of how these differences occur will facilitate
classrooms and other educational settings, including curricula, delivery of the individualized instructional programs that
educational software, children’s television, and design of are likely to have the largest pay-off. Because variability in
playgrounds and sports products and fields. In older sciences, rates and patterns of development is determined by both
such as physics, chemistry, and biology, the role of engineer biological and environmental factors, the field of education
or translator has been established and respected for a long would benefit immensely from a large database of information
time. The models and knowledge from these sciences do not about the typically developing brain in its typical environments
automatically translate to practical questions, such as building with respect to population variability. This information will
a bridge, creating a new kind of skin cream, or preventing also facilitate conceptualizing educational inputs in terms
invasive species from destroying native species in inland lakes. of response to instruction by a student (and brain) at a
Businesses and governments depend on engineers in physics, certain developmental level (rather than assuming some lack
biology, and many fields to connect scientific knowledge with of inherent ability in a child of a given age).
issues of practice. Fortunately, a few data bases already exist that are relevant
An obvious place to train these neuroeducators is Research for educational neuroscience, including the PISA assessment of
Schools. Fortunately, institutions already exist where some the OECD, the National Assessment of Educational Progress,
professionals work to build connections between research and the Child Language Data Exchange System (which assesses
practice in education. Sesame Street Workshop is renowned language development), the NICHD Early Child Care Research
for its use of formative evaluation and practical assessment Network, the NIH MRI Study of Normal Brain Development,
to shape its many educational programs on television and in the ALSPAC database in the UK (Avon Longitudinal Study
other media (Lesser, 1974). Some education companies and of Parents and Children), and the U.S. state data bases
nonprofits also train educators with these kinds of practical that have resulted from No Child Left Behind. As useful
skills. For example, the Center for Applied Special Technology as these data bases are, however, most have major gaps,
(www.cast.org) creates educational software to facilitate which need to be remedied. They mostly include either
and support learning and teaching, focusing especially on behavioral or biological assessments, not both. Many of them
supports for diverse learning pathways (Rose & Dalton, 2009). focus only on performance in high-stakes tests, and they
An essential part of training for neuroeducators is rigorous omit assessments of learning and teaching in classrooms,
evaluation of ways to connect education with practice along with computers, or in other education settings. Educational

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neuroscience needs rigorously designed assessments in real Research of this kind on learning pathways and the roles of
learning environments of what and how students learn and mental models in education will provide useful knowledge
teachers teach. Fortunately, relevant methodologies for such about learning patterns and differences.
assessments in genuine learning situations are already available To provide useful large data bases, researchers will need to
based on a century of research on cognitive development and coordinate across sites and use common measures. Multisite
learning (Bransford & Donovan, 2005; National Research studies are important because (1) research needs to sample
Council, 2001; Stein, Dawson, & Fischer, in press). diverse learners to represent the full range of learning pathways
For educational neuroscience, a key need is for data bases and environments and (2) longitudinal studies of typically
that combine biological markers relevant to learning with developing populations require large numbers, usually beyond
evidence of learning and teaching in real-life settings, not the capacity of any single research center. Carrying out
just performances on standardized tests in environments that multisite studies requires shared protocols and measures to
are not dedicated to learning. Although neuroscientific and be used. These studies should also track environmental inputs
genetic information are only part of the answer, educational in standard ways, including measures of developing behavior,
population studies (making use of, e.g., student electroen- SES (not just income, but correlated factors such as nutrition,
cephalograms [EEGs]) are likely to produce evidence about breast feeding experience, etc.), emotional development, and
relations between learning pathways and neural development, availability of educational resources.
as well as evidence relevant to formal and incidental learning. Interpretation of results will be greatly facilitated if com-
Combined with traditional standardized assessments, such mon measures are used in multiple sites. An important way to
data bases can move the field beyond ideology and opinion improve the quality of databases is to ask researchers within
to evidence-based practice and policy. An important direction the educational neuroscience community to include a few
for data collection with the goal of creating models of common core neural and behavioral measures in their investigations,
learning pathways and variations is to test the assumptions for example, assessments of basic sensory processing and
made by the current educational system regarding how devel- attention, even if the measures do not form part of the dom-
opment occurs and what should be taught, when, and to inant hypotheses in their particular area of inquiry. Choosing
whom. For example, in the area of numeracy, research on such measures will require recommendations from a panel of
the basic ‘‘number sense’’ has demonstrated a grounding in researchers and educators representing a wide range of areas
the parietal lobe shared by humans and animals and used for of expertise. This strategy will help in gathering information
estimating approximate number at a glance. These findings about learning and developmental pathways and likely causal
raised questions about assumptions concerning the optimal patterns.
arithmetic curriculum and the neural basis of understanding Large databases concerning developmental pathways are
number. Neuroscientists showed the existence of specialized needed to tackle research questions concerning how core
cells in the brain that respond to specific numbers (e.g., skills and structures develop similarly and differently across a
neurons that are most responsive to ‘‘3’’) and demonstrated range of real-life conditions. These large databases will require
that even infants have a degree of numerical competence for commitment to longitudinal studies, which will enable a
small specific numbers and for general judgments of quantity deeper understanding of important issues such as comorbid-
(Dehaene, 1997). These findings indicate that small numbers ity: Why do some learning strengths or difficulties co-occur
and relative size can be perceived directly at an early age. systematically, such as the comorbidity between attention
Further research on early development of numbers indicates deficit hyperactivity disorder, dyslexia, and other learning dis-
that starting with these elementary perceptual capacities, orders or the correlation between dyslexia and visual skills at
children who work with numbers in preschools or at home integrating information across wide areas (Parens & Johnson,
build the digits (1, 2, 3, and 4) into a representation (mental 2009; Schneps et al., 2007). The use of shared measures across
model) of the number line, gradually constructing it one domains of learning and disorder will provide a much broader
number at a time during the preschool years (Carey, 2009; foundation for tackling questions of comorbidity, difference,
Le Corre et al., 2006). Common language includes an implicit and complexity.
mental model of the number line, but children learn most
effectively if they are expressly taught the model, especially
through games that use the number line (Griffin, 2005; Griffin Research Designs Informed by Neuroscience and Genetics
& Case, 1997). Their construction of the mental model of Addressing these larger research questions about complexity
the elementary number line sets the stage for using the of inputs, actions, and biological structures requires
number line more broadly and deeply when they begin to learn recognition that learning states and characteristics (including
arithmetic. Educational intervention focusing on this mental those in the brain) can be treated as outcome measures that
model created a large improvement in students’ arithmetic can be analyzed at a population level. One of the common
skills, especially for educationally disadvantaged children. neuromyths is that specific functions such as language and

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mathematics are located in one spot in the brain, when patterns and enable early detection of learning difficulties
in fact they involve orchestration of activity across many or strengths?
regions. The brain operates with complex networks not single 4. How can educators use educational environments to
locations. There is no ‘‘language center’’ or ‘‘reasoning center.’’ optimize trade-offs between learning and teaching
Recent research has shifted toward a focus on identifying strategies for individual children, such as the mix of rote
networks in the brain and their functions in action, thought, versus concept-focused learning?
and emotion (Buckner & Carroll, 2007; Immordino-Yang, 5. How are interventions more or less effective when they
2008; Immordino-Yang, McColl, Damasio, & Damasio, 2009; focus on weaknesses, strengths, or both, and how does their
Poldrack et al., 2009; Raichle et al., 2001). The development of effectiveness vary across areas of education and cognition?
such networks needs to be studied in real developmental time,
utilizing longitudinal research designs. These several recommendations for strengthening the
Indeed one of the best candidates for neural foundations of infrastructure of educational neuroscience will not only
learning and development is the coordination of brain activity improve the research foundations of this emerging field but
as measured by coherence in the electroencephalogram or also provide a sound basis for connecting research to practice
by axonal transmission (white matter) across brain regions. and policy. The potential is enormous, but hope and potential
For example, infants who are learning to crawl show a surge alone will not make it happen. We must create institutions
in coherence between prefrontal and occipital/parietal sites that will generate usable knowledge which connects research
within each hemisphere (Bell & Fox, 1996). Research in with practice and policy in educational neuroscience, and
educational neuroscience can usefully examine activity across we must train professionals to create a new world in which
the whole brain, including connection among regions (often research on mind and brain relates directly to practice and
measured by EEG coherence) as well as activity in targeted policy in education.
regions (such as the parietal lobes for studies involving
number or the motor cortex for crawling). Illuminating the Conclusion: Grounding Educational Practice and Policy
development and diversity of learning requires information With Research in Educational Neuroscience
about how critical neural areas develop links to other areas. The Mind, Brain, and Education movement aims to create
Studies of connectivity are likely to have special relevance for a strong scientific foundation for educational practice
educational questions (Hanlon, Thatcher, & Cline, 1999). and policy by connecting cognitive science, biology, and
Similarly, genetic markers provide powerful opportunities human development with education and by creating new
for uncovering biological roots of development and learning infrastructural institutions to relate research with practice and
(Plomin et al., 2007). For example, data from epigenetics policy. Effective educational research requires that educators
(the impact of environments on gene expression and gene play a central role along with researchers in formulating
interaction) indicate that genetically informed designs can questions and methods. Biology is central to this emerging
improve understanding of environmental effects on learning, field, informing educational practice in many ways through
such as showing how environmental conditions have effects providing basic knowledge about body and brain as they relate
for people with some genetic patterns but not others. The to learning and teaching.
field of genetics has gone beyond simple genetic determinism, All of us learn cultural/linguistic models implicitly from an
which should be reflected in educational research designs. early age, and those implicit models can interfere with the
Longitudinal and intervention studies are most likely to application of scientific knowledge to education, creating, for
illuminate underlying causation if they focus around questions example, neuromyths about how people learn or how the brain
such as the following: works. At the same time, analysis of those models (metaphors)
can create opportunities for substantial improvements in edu-
1. How do the brain’s multiple learning systems, each of cation, as has been demonstrated with mathematics teaching
which operate via different rules, contribute to learning based on the mental model/metaphor of the number line.
successes and difficulties in education? What kinds of Cognitive-science tools provide powerful means for assess-
models of processes and pathways can usefully represent ing learning pathways with a common scale (ruler), based
these learning systems and their patterns of change over on analysis of patterns of growth in both long-term develop-
time? ment and short-term learning. To build and sustain a strong
2. What are the best methods and models to characterize scientific foundation for education requires creation of var-
developmental and learning pathways in order to guide ious new forms of infrastructure: (1) Research Schools in
teaching and learning and clarify the relation of learning which researchers and practitioners work together to craft
difficulties and strengths? research questions and methods to shape practice and pol-
3. How can researchers and educators identify early neural icy, (2) Neuroeducators, a new kind of researcher/practitioner
and biomarkers that indicate variations in learning who has the interdisciplinary skills required to grow the

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new field of educational neuroscience and who specializes Cooper, C., Field, J., Goswami, U., Jenkins, R., & Sahakian, B. (2009).
in connecting practical questions with research findings and Mental capital and wellbeing. Oxford, UK: Wiley-Blackwell.
concepts, (3) Large shared data bases on learning and devel- Cremin, L. (1976). Public education. New York: Basic Books.
Daniel, D. B., & Poole, D. A. (2009). Learning for life: An ecological
opment, including biological markers, and (4) Educational
approach to pedagogical research. Perspectives on Psychological
research designs informed by neuroscience and genetics. In
Science, 4, 91–96.
addition, an informed debate on neuroethics with respect to Dehaene, S. (1997). The number sense: How the mind creates mathematics.
mind, brain, and education is essential. New York: Oxford University Press.
A strong base in research grounded in collaboration Della Chiesa, B., Christoph, V., & Hinton, C. (2009). How many
of researchers and practitioners will lead to many major brains does it take to build a new light? Knowledge manage-
improvements in education. Evidence will lead to better ment challenges of a transdisciplinary project. Mind, Brain, and
choices of ways to teach and to facilitate learning, including Education, 3, 16–25.
Dewey, J. (1896). The university school. University Record (University
specification of different learning pathways for different
of Chicago), 1, 417–419.
learners. Simultaneously, it will avoid misleading claims
Dunbar, K., Fugelsang, J., & Stein, C. (2007). Do naive theories ever
of ‘‘brain-based education’’ deriving from myths that are go away? Using brain and behavior to understand changes
scientifically specious. It will reduce the effects of misleading in concepts. In M. Lovett & P. Shah (Eds.), Thinking with data
models of learning and teaching that are implicit in language (pp. 193–206). Mahwah, NJ: Erlbaum.
and culture but not scientifically accurate, while creating ways Farah, M. J., & Heberlein, A. S. (2007). Personhood and neuroscience:
to teach models more effectively and take advantage of ways Naturalizing or nihilating? The American Journal of Bioethics, 7,
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and construction of hierarchies of skills. Psychological Review, 87,
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477–531.
learning in important domains. Educational neuroscience and Fischer, K. W. (2009). Mind, Brain, and Education: Building a
more broadly mind, brain, and education have an important scientific groundwork for learning and teaching. Mind, Brain,
role to play in improving education in the 21st century. and Education, 3, 2–15.
Fischer, K. W., Bernstein, J. H., & Immordino-Yang, M.H. (Eds.).
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