Building a Bridge from Science to the Classroom
Phi Delta Kappan - Feb 2008
Building a Bridge from Science to the Classroom
Knowledge of the underlying science, Ms. Willis argues,
will enable educators to make good use of all that
neuroscientists are learning about our brains, young and
old. It is also the best defense against misleading assertions
put forth by opportunists.
By Judy Willis, M.D. NEUROSCIENCE and cognitive science
relating to education are hot
topics. They receive extensive but
simplified coverage in the mass media,
and there is a booming business
in “brain-booster” books and products,
which claim to be based on the
research.
Eric Jensen advocates more collaboration among
scientists from the full variety of disciplines engaged
in brain research. This collaboration, with corresponding
evaluations using cognitive and classroom research,
can offer educators more coherent knowledge
that they can use in teaching. And educators want this
knowledge, as shown by a communication I received
from Lisa Nimz, a fifth-grade teacher in the Chicago
suburb of Skokie, in response to my May 2007 Kappan
article:
We know how important it is for relevant research from
the scientific community to be shared with and used in
the education community. We are anxious for neurological
research to become more a part of educators’ thinking
and wonder how to make it so. There seem to be only a
few people in the unique position of being able to understand
the research, figure out its implications for the classroom,
and use those implications to direct their teaching.
We are actively pondering how a sturdy and wide enough
bridge can be built between the scientific community and
the education community.
There are many obstacles to building such a construct.
Reading the primary sources of neurological research can
be challenging even for the brightest of us. And even if
someone can comprehend these primary sources, there are
many highly educated people who don’t seem to approach
scientific evidence with the caution and skepticism necessary
to make fair judgments about the implications of that
evidence. There are also many members of the scientific
community and academia who haven’t studied pedagogy.
We are thankful for books, articles, and presentations that
mitigate some of that disconnect.
Ms. Nimz’ quandary reflects educators’ increasing
concern about how to keep up with the exponential
growth of the body of information coming from the
varied scientific specialties about the structure and
function of the brain with regard to learning and
memory. Of equal concern is how to interpret the
multitude of claims, usually by nonscientists, that the
effectiveness of various “brain-based strategies” has
been “proven by brain research.”
The interdisciplinary collaboration of neuroscientists,
molecular geneticists, cellular biologists, cognitive
scientists, and education professionals can be the
“wide, sturdy bridge” Ms. Nimz seeks to connect scientific
knowledge of the human brain to applications
of that research in the classroom. But before that
bridge is completed, we need to allow some flexibility.
In order to help educators make sense of the massive
amounts of information, I propose a two-tiered
structure in which factual, collaborative brain research
is designated as such and educational strategies
strongly suggested by neuroscientific data are identified
as interpretations of that research. The resulting
structure will change with time because the interpretive
tier will become more concrete as initial interpretations
are supported or contradicted by subsequent
neuroscience.
The first step is to debunk the neuromyths. Even
some of the purest, most accurately reported neuroscience
research has been misinterpreted. People trying
to capitalize on research with their elixirs, books,
cure-all learning theories, and curriculum packages
have perpetrated much of the damage. Other folks
have unintentionally made errors of interpretation
when they have been unfairly asked for scientific evidence
to support the strategies they have been using
successfully for years.
But it is important to understand that some research
findings can be applied to education now. For
example, a review of neuroplasticity research shows
how collaboration across fields, with certain checks
and balances, can lead to classroom strategies that can
add to teaching success.
Brain research has not yet provided a direct connection
between classroom interventions and brain
function or structure, but that does not mean it is irrelevant.
Its use is akin to the “off-label” uses of medications
by doctors. While Food and Drug Administration
regulations require that the label information
and advertising of a medication indicate the drug’s
use only for specific, approved conditions, physicians,
based on their knowledge and available current information,
may prescribe a medication for a use not indicated
in the approved labeling. In the same way, educators
should use their understanding of brainlearning
research to evaluate, develop, and use strategies
that are neuro-logical, based on knowledge and
available current information.
NEUROMYTHS
We study history, in part, so that we can learn from
the mistakes of the past. Analyzing the errors in interpretation
that led to brain-learning myths helps us
evaluate the interpretive strengths and limitations of
neuroimaging and other current neuroscientific research
and avoid misinterpretation.
I go through the research in my fields of neuroscience
and education with the goal of finding scientific
studies that relate to learning and that adhere to
the medical model of limiting the variables and confining
interpretation to objective data. Then I seek
cognitive testing of the conclusions neuroscientists
make from their data. Do the study’s data about how
the brain responds to a specific input or stimulus correlate
with the cognitive test? When I find a valid fit
between the neuroscience and the cognitive testing, I
go in search of the holy grail: objective evaluation of
the effect of the intervention on statistically appropriate
numbers of students in their classrooms. To my
knowledge, there has not yet been a strategy or intervention
that has made it through all three of these filters.
Misinterpreted neuroscientific data have led to beliefs
that some people cling to despite objective evidence
to the contrary. For example, it has taken more
than a decade to debunk the left brain/right brain
oversimplification of learning styles, even though
neuroimaging studies have, for more than a decade,
demonstrated that human cognition is far too complex
to be controlled by a single hemisphere. We now
know that although parts of the brain are particularly
active during certain memory or learning activities,
these regions do not work in isolation. There are networks
throughout both hemispheres of the brain that
constantly communicate, and even these neural networks
change in response to genetics and environment
throughout our lives.
In the December 1999 Kappan, John Bruer reviewed
several decades of biological and neuroimaging
research and revealed important unconnected
dots between laboratory findings and the theories that
hitchhiked on the research. For example, Bruer took
on the popular assumptions “correlating” synaptic-
density growth, high brain metabolism, critical braingrowth
periods, and their proposed long-range effects
on intelligence and found several weak foundations.
He pointed out the flaws in the assumption that critical
brain-growth periods of rapid synapse formation
are windows of opportunity for instruction geared to
those parts of the brain. He reported contradictory research,
such as findings that brains build knowledge
and store memories with no drop in efficiency long
after peak rates of synaptic, axonal, and dendritic
growth have leveled off in adolescence.
Bruer also questioned whether increased corticalglucose
metabolism, as measured by PET scans, is direct
evidence of rapid growth in synaptic density during
the so-called critical periods. This, in turn, called
into question the correlations between high metabolic
activity measured by neuroimaging and periods of
increased potential for learning that were the basis for
claims that brain research proved that increased environmental
stimulation of students during critical
brain-growth phases resulted in more learning.
NEUROPLASTICITY AND PRUNING
It is important for educators to remember that the
absence of a positive correlation between neuroimaging
data and environmental stimulation does not
mean that stimulating classrooms are not valuable for
learning. It is likely that environmental stimulation
does influence learning. However, that theory has not
yet been proved by brain research. I remain hopeful,
as does Bruer, that the indirect evidence from neuroimaging
and other neuroscience research has the
potential to suggest teaching strategies and environmental
stimuli that are valuable for learning. One
promising area of ongoing study is neuroplasticity
and pruning.
One longtime misconception held that brain
growth stops with birth and is followed by a lifetime
of brain-cell death. Now we know that, though most
of the neurons where information is stored are present
at birth, there is lifelong growth of the support
and connecting cells that enrich the communication
between neurons (axons, dendrites, synapses, glia)
and even some brain regions that continue to form
new neurons (neurogenesis) throughout life, such as
in the dentate nucleus of the hippocampus and the olfactory
cortex.1 Even after the last big spurt of brain
growth in early adolescence, neurotrophins (growthstimulating
proteins) appear elevated in the brain regions
and networks associated with new learning and
memory formation.2
Neuroplasticity is the genetically driven overproduction
of synapses and the environmentally driven
maintenance and pruning of synaptic connections.3
Once neural networks are formed, it is the brain’s
plasticity that allows it to reshape and reorganize these
networks, at least partly, in response to increased or
decreased use of these pathways.4 After repeated practice,
the connections grow stronger, that is, repeated
stimulation makes each neuron more likely to trigger
the next connected neuron.5 The most frequently
stimulated connections also become thicker with
more myelin coating, making them more efficient.6
While active cells require blood to bring nourishment
and clear away waste, cells that are inactive do
not send messages to the circulatory system to send
blood. This reduced blood flow means that calcium
ions accumulate around the cell and are not washed
away. This calcium ion build-up triggers the secretion
of the enzyme calpain, which causes cells to self-destruct,
in what is called the pruning process.7 When
unused memory circuits break down, the brain becomes
more efficient as it no longer metabolically sustains
the pruned cells.
As neurological research provides information
about various stages of brain maturation through
neuroplasticity and pruning, we come full circle to
Jean Piaget’s theories regarding the developmental
stages of the thought processes of children. If neuroplasticity
and pruning represent stages of brain maturation,
this may be indirect evidence in support of
Piaget’s theory that, until there is maturation of brain
neural networks, children do not have the circuitry to
learn specific things or perform certain tasks.8
These neuroplasticity findings allow us to consider
which strategies and classroom environments promote
increased stimulation of memory or strengthening
of cognitive neural networks. For example, appealing
to a variety of learning styles when we review
important instructional information could provide
repeated stimulation to multiple neural networks
containing this information. Each type of sensory
memory is stored in the lobe that receives the input
from that sensory system. Visual memory is stored in
the occipital lobes, auditory memory is stored in the
temporal lobes, and memories of tactile experiences
are stored in the parietal lobes. There could be greater
potential for activation, restimulation, and strengthening
of these networks with practice or review of the
information through multisensory learning, resulting
in increased network efficiency for memory storage
and retrieval.
OFF-LABEL PRESCRIBING
Jensen cautions, “Brain-based education suggests
that we not wait 20 years until each of these correlations
is proven beyond any possible doubt.” The toll
of one-size-fits-all education with its teaching to the
standardized tests is so high that it calls for a compromise
of the pure medical research model. We do
need to take some temporary leaps of faith across the
parts of the bridge that are not yet sturdy and try interventions
before the research is complete.
When a patient has exhausted all the regular treatments
for epilepsy or a brain tumor, neurologists try
investigative therapies or “off-label” uses of medications.
While off-label medications have not completed
FDA testing for the condition in question, the
physician believes, through experience and knowledge
of the pharmacology, that the risk is worth taking
in order to treat the patient’s disease. For students
at risk in our schools, we should use a similar strategy,
that is, trying new methods even though they are
not yet proven.
However, educators need to use these methods
prudently. We need to discuss our successes and acknowledge
what doesn’t work. Our successful strategic
interventions may not yet be proven by brain research,
but that doesn’t mean they are not valuable.
Nevertheless, educators need to beware of opportunists
who claim that their strategies are proven by
brain research.
UNTIL THERE IS HARD EVIDENCE
The brain-research evidence for certain instructional
strategies continues to increase, but there still
is no sturdy bridge between neuroscience and what
educators do in the classroom. But educators’ knowledge
and experience will enable them to use the
knowledge gained from brain research in their classrooms.
For example, choice, interest-driven investigation,
collaboration, intrinsic motivation, and creative
problem solving are associated with increased
levels of such neurotransmitters as dopamine, as well
as the pleasurable state dopamine promotes.9 Novelty,
surprise, and teaching that connects with students’
past experiences and personal interests and that is low
in threat and high in challenge are instructional
strategies that appear to be correlated with increased
information passage through the brain’s information
filters, such as the amygdala and reticular activating
system. Lessons in which students are engaged and invested
in goals they helped to create have the potential
to stimulate and restimulate networks of new
memories as students actively process information in
the construction of knowledge.10 These instructional
strategies date back to theories developed decades before
neuroimaging. But they are consistent with the
increasing pool of neuroimaging, behavioral, and developmental
psychology.
We can look forward to a time when human brain
mapping, correlated with the other areas of neuroscience,
will reveal additional brain mechanisms involved
in memory and learning to help us define the
most successful teaching strategies for the variety of
learners we teach. We are likely to have neuroimaging
tools to identify presymptomatic students at risk and
genetic testing that will isolate the precise genes that
predispose children to such conditions as ADHD or
the various dyslexias. With these powerful diagnostic
tools, cognitive and education professionals will be
able to design strategies to provide at-risk children
with the interventions needed to strengthen areas of
weakness before they enter school and to develop differentiated
instruction allowing all learners to achieve
to their highest potentials.
University psychology and education departments
are already obtaining neuroimaging scanners. This
will increase educators’ influence on what is studied.
Teachers will communicate with researchers about the
strategies they find successful, so researchers can investigate
what is happening in students’ brains when
those strategies are used. Researchers will need to
make their data accessible to teachers who can develop
new strategies that bring the fruits of the research
to the students in their classrooms.
With time, collaboration, and greater integration
of the neuroscience of learning in schools of education
and in professional development, educators who
stay on top of the science will play leading roles in designing
and implementing curriculum and classroom
strategies that are effective and consistent with the
discoveries of how the brain learns best.
For now, the most powerful asset we educators have
to influence the direction of education policy is our
up-to-date knowledge and understanding of the most
accurate, collaborative, neuroscientific research. With
that knowledge, we can remain vigilant in our scrutiny
of any premature or misleading assertions about
interventions claimed to be proven by brain research.
And we will be ready to create, evaluate, and implement
the best, truly brain-based instruction in our
classrooms. These will be important challenges to
meet, but the next decade will reward us with extraordinary
opportunities. It may not seem like it
now, but we are on the brink of the most exciting time
in history to be an educator.
1. P_?_ Eriksson, E_?_ Perfilieva, and T_?_ Bjšrk-Eriksson, [[FULL
FIRST NAMES FOR THESE AUTHORS?]] “Neurogenesis in the
Adult Human Hippocampus,” Nature Medicine, vol. 4, 1998, pp.
1313–17.
2. Kang, 1997.
3. D_?_ Cicchetti and W_?_ Curtis,
“The Developing Brain and Neural Plasticity:
Implications for Normality, Psychopathology, and Resilience,” in D.
Cicchetti and D.J. Cohen, eds., Developmental Psychopathology: Developmental
Neuroscience, 2nd ed. (New York: Wiley, 2006), p. 11.
4. J_?_ Giedd et al., “Brain Development
During Childhood and Adolescence: A Longitudinal MRI Study,” Nature
Neuroscience, vol. 2, 1999, pp. 861-63.
5. Harry Chugani, “Biological Basis of Emotions: Brain Systems and
Brain Development,” Pediatrics, vol. 102, 1998, pp. 1225-29.
6. Guild, 2004
7. P_?_ Seeman, “Images in Neuroscience:
Brain Development, X: Pruning During Development,” American
Journal of Psychiatry, vol. 156, 1999, p. 168.
8. Jean Piaget, “Intellectual Evolution from Adolescence to Adulthood,”
Vita Humana, vol. 15, 1972, pp. 1-12.
9. P_?_ Thanos et al., “The Selective
Dopamine Antagonist,” Pharmacology, Biochemistry and Behavior, vol.
81, 2005, pp. 190-97.
10. Alfie Kohn, “The Cult of Rigor and the Loss of Joy,” Education
Week, 15 September 2004, available at www.alfiekohn.org/articles_subject.
htm. K
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