My chapter from new book Mind, Brain, Education edited by David Sousa, Solution Tree
Current Impact of Neuroscience in Teaching and Learning
By Judy Willis, M.D., M.Ed
Introduction
The convergence of laboratory science and cognitive research has entered our
classrooms. Welcome and invited by many educators who seek ways to breath life into
increasingly compacted curriculum, evoking suspicion and anxiety in others who have
experienced the negative impacts of mandated change without sufficient support. In this
chapter I offer a perspective that may offer solace to the latter, and temper hastiness in
the former.
My background as an adult and child neurologist is the lens through which I
evaluate the quality and potential applications of the new science of learning. It is,
however, my own schooling when I returned to school in 1999 to earn my teaching
credential and Masters of Education and my past ten years of classroom teaching that
allow me the privilege of incorporating the theoretical wisdom of great educators who
preceded the scanners and computers with the data these tools now offer. The pairing of
what was believed before the laboratory research with current research interpretation
suggests neuro-logical teaching strategies that are applicable to today’s classrooms where
we are educating students for the 21st century.
Life Support: There can never be adequate control of all variables such that what
we see in a brain scan, brain wave, or genetic code can prove or predict exactly what a
strategy or intervention will mean for individual students. By using my neuroscience
background and classroom experience I offer interpretations of the research and
correlations to teaching strategies that appear to have the strongest ties. As I share the
stories of scientific validation of the wisdom of educational visionaries I hope to also
illuminate the pathways through the brain that we “see” in science such as neuroimaging.
This knowledge can guide us in planning instruction that coincides with the increased
understanding of how the brain processes sensory input into learning and learning into
wisdom.
The purest truth I suggest is the least open to statistical analysis and comes not
from my twenty years as a physician and a neuroscientist, but from my past ten years as a
classroom teacher. There is no more critical life support and satisfaction than the breath
of life and resuscitation of the joy of successful learning that passionate, informed
teachers provide their students.
The most surprising of all the connections I recognized between the science and
the practice of teaching was the astonishing accuracy of the theories of the best
educational and psychological visionaries coming from the accumulated scientific
research over the past twenty years. The ideas of William James, Lev Vygotsky, John
Dewey, followed by Steven Krashen, Howard Gardner, and others, are strikingly
consistent with what we are learning about the conditions most suitable for the brain to
select which sensory input gains access to its neural circuitry, where that information
goes, and how it influences our actions. This correlation also reminds me of the value of
scientists heeding the observations of classroom teachers and their colleagues.
Strategies can be deduced from correlations with research about the most suitable
emotional, cognitive, and social environments, and effective methods of providing
information through multisensory input, planning for individualization of achievable
challenge, opportunities for inquiry, fostering of pattern recognition, and mental
manipulation. When educators have opportunities to learn about the ways the brain
processes, recognizes, remembers, and transfers information at the level of neural
circuits, synapses, and neurotransmitters and share that knowledge with students, the
empowerment for both enriches motivation, resilience, memory, and the joys of learning.
Warning Label: Over the past two decades, the neuroscience of learning
has been in almost constant transition. The union of mind, brain, and learning with
laboratory and cognitive research is limited to suggesting strategies based on correlations
and what I call neuro-logical predictions. By neuro-logical, I refer to strategies suggested
by research that is consistent with my neuroscience background and my own, and others’,
classroom experiences.
For example, neuroimaging can only demonstrate that brain activity is correlated
with a cognitive task or influenced by variable presentations or emotional states.
However, measurements of metabolic, electrical, or chemical activity in a region of the
brain do not prove that the region or chemical is the direct cause of the behavioral
outcome. To do that conclusively would require a lesion that disrupts the neural input to
the brain region to which a cognitive activity is attributed. These lesion studies are being
done in animal models, with techniques such as inducing electrical activity in the part of
the brain with magnetic stimulation that disrupts localized regions of brain activity, but
we are not at the stage of safe lesion studies for human subjects (Poldrack & Wagner
2004).
Neuroimaging for education and learning research is still largely suggestive,
rather than completely empirical, in establishing a solid link between how the brain learns
and how it metabolizes oxygen or glucose. Teaching strategies derived from wellcontrolled neuroimaging are at best compatible with the research to date about how the
brain seems to preferentially respond to the presentation of sensory stimuli.
There are no formal guidelines to which researchers, curriculum publishers, or
private educational consultants must adhere that restrict what they can claim are brainbased strategies. The status of the “science of learning” is still speculative because there
are no infallible confirmations between neuroimaging, cognitive testing, strategies, and
completely objective measurements of results. Even the most scrupulous researchers and
clinicians cannot claim direct links from research to replicable results for individual
students.
It is up to professional educators possessing background knowledge about the
brain to use the deductions of scientific research to guide the strategies, curriculum, and
interventions they select for specific reasons and individual students. Knowing the
workings of the brain makes the strategies we already know more adaptable and
applicable. We can be guided to use strategies that appear most consistent with the
interpretations of the way the brain respond to stimuli during scientific studies and the
long-term outcomes of these interventions.
This evaluation of neuroscience data is achieved through the same process of
transfer we strive to develop in our students. Just as we help them develop foundational
knowledge from which to construct conceptual understanding, so can we build an
informed neuroscience background with which to evaluate and apply the information
offered by the scientists of learning.
Too Good to Be True is Sometimes True
An advertisement in a national Sunday newspaper supplement recently offered a
brain-energizing pill guaranteed to increase memory, mood, and motivation. As “proof”
there were neuroimaging brain scans side by side. There were clearly the same image, but
one had the contrast turned high to appear much brighter than the other. I would not
expect any educators to be fooled by that. But, what if I offered you a neurochemical
intervention to increase motivation, perseverance, creativity,….. and higher test scores in
your students. Not for $100, or for ten easy payments of $8.99 plus tax and shipping. The
price is telling a good joke and offering a choice of which test they take first.
This chapter will describe the evolution of several current neuroscience to
classroom topics in which the interpretations of the new sciences of learning correlate
strongly with past predictions based on observation without benefit of looking into the
brain. A look back and forward at the lab to classroom implications of attention, emotion,
and neuroplasticity theories and research reveals the potential valuable, practical
implications for instruction, curriculum (concepts), and assessment for today’s learners –
tomorrow’s 21st century citizens.
Neuroscience of Joyful Learning Emotion
History Foretold: Remember, “No smiles until after winter holidays.” Recall the
time when proper learning behavior was represented by students sitting quietly, doing
exactly what they were told without question or discussion, and reporting back rote
memorized facts on tests.
Where did those notions come from? Certainly not the visionary educational
theorists of the past. A few thousand years ago in 360 B.C., Plato advised against force
feeding of facts to students without providing opportunities for them to relate learning to
interest or evaluating their readiness.
“Calculation and geometry and all the other elements of instruction…should be
presented to the mind in childhood; not, however, under any notion of forcing our system
of education. Because a freeman ought not to be a slave in the acquisition of knowledge
of any kind. Bodily exercise, when compulsory, does no harm to the body; but knowledge
which is acquired under compulsion obtains no hold on the mind.” (Plato, 387 B.C.)
Jump ahead several thousand years and we have Lev Vygotsky’s zone of
proximal development theory that students learn best when guided the distance between
their level of independent problem solving and their level of potential development
through problem solving under adult guidance, or in collaboration with more capable
peers. (Vygotsky, L. (1978).
Similarly, Steven Krashen supported the need for individualizing and
differentiating instruction in the ZPD, which he called comprehensible input. Krashen
also described the negative impact of stress on learning (Krashen, 1981). "Language
acquisition, first or second, occurs when comprehension of real messages occurs, and
when the acquirer is not 'on the defensive'... Language acquisition does not
require…tedious drill. The best methods supply 'comprehensible input' (a bit beyond the
acquirer's current level) in low anxiety situations, containing messages that students
really want to hear. These methods do not force early production in the second language,
but allow students to produce when they are 'ready', recognizing that improvement comes
from supplying communicative and comprehensible input, and not from forcing and
correcting production." Krashen, S. (1981).
What We’ve Learned
The compelling nature of computer games is an excellent example of the success
of differentiating instruction to students’ ZPD or level of comprehensible input. In a
study of what makes computer games so captivating, variable player-ability-based
challenge was interpreted to be the key element. The most popular computer games took
players through increasingly challenging levels as they became more and more skillful.
As skill improved, the next challenge would stimulate new mastery to just the right extent
that the player could reach with practice and persistence (Malone 1981). This
incremental, achievable challenge in the classroom, at the appropriate level for students’
abilities is motivating and strategically builds mastery by lowering the barrier not the bar.
In the computer games, the level of challenge for each level of the game is such
that the player is neither bored nor overwhelmed and frustrated. Practice opportunities
allow the player to improve and experience the neurochemical response of pleasure when
they succeed at the short-term goals that are provided by multiple levels of incremental
challenge as they move to on the way to the longer-term goal of completing the game.
This is the power of achievable challenge with opportunities for students to see their
progressive improvement along the way to the ultimate goal, instead of only having the
feedback of a test or other endpoint assessment. The computer game doesn’t give prizes,
money, or even pats on the back, yet it remains compelling because of the powerful brain
response to intrinsic reward, as you’ll read regarding the dopamine effect in the next
section.
Before the research on the dopamine-reward system was done, it was Krashen’s
theory of an affective filter that started my search for physical structures or neural
networks that are influenced by stress. We have come to see how the brain literally filters
(selects) the information that enters our neural networks and which networks (reactive or
reflective) they enter, as well as the impact of stress and other emotions on these filters.
“Motivation, self-confidence, and anxiety all affect language acquisition, in effect
raising or lowering the ‘stickiness’ or ‘penetration’ of any comprehensible input that is
received…A low or weak affective filter is needed to allow the input 'in'"(Krashen, 1981)
We now have the tools of the sciences of learning to support the
recommendations to avoid forced instruction and incorporate appropriate environmental,
social, emotional, and cognitive considerations in our instruction. We’ve come a long
way in the nature versus nature controversy. Where it was once believed to be genetics’
heavy hand predominantly determining intelligence limits, we now increasingly
recognize the brain’s environmental responsiveness. Humans share all but 5-10% of the
genetic code with earthworms, which barely seems adequate to account for the physical
and cognitive differences. Where once it was assumed that genes all expressed
themselves, we now know that sections of many genes called alleles are turned on or off
by environmental and social interactions (Lo, et al., 2003).
Neuroimaging studies reflect the influence of stress and pleasure on the filtering
of sensory input that enters the brain (Reticular Activating System), and the next filter
(Amygdala – Krashen’s Affective Filter) determines whether the information goes to the
thinking brain (prefrontal cortex) or the lower, involuntary reactive brain. When stress
directs sensory input to the lower brain, the input does not become consolidated as stored
memory (Hippocampus and Prefrontal Cortex). The interpretation of scientific research
supports interventions for emotional support, stress reduction, and strategies such as
novelty, discovery, and conceptual learning that change the brain’s neurochemistry,
processing of information, and construction of neural networks that hold information in
memory.
Beginning with the brain’s filters, this chapter extends to the research and
classroom implications regarding strategies to influence the brain’s attentive focus,
conduction of information to the prefrontal cortex, using the brain’s own
neurotransmitters to facilitate learning, and concludes with interventions relevant to
motivation and neuroplasticity.
Intake Filters: The first such filter is the Reticular Activating System, a primitive
network of cells in the lower brainstem through which all sensory input must pass to
reach any higher regions of the brain. All learning enters the brain through the senses.
Much like other mammals, the human RAS favors intake of sights, sounds, smells, and
tactile sensations that are most critical to survival of the animal and species. Priority goes
to changes in an animal or human’s environment that are appraised as threatening. When
threat is perceived, the RAS automatically selects related sensory input and directs it to
the lower, reactive brain where the involuntary response is fight, flight, or freeze (Raz &
Buhle, 2006).
The RAS is a virtual editor that grants attention and admission to a small fraction
of all the available sights, sounds, and tactile sensations available at any moment. This
survival directed filter is critical for animals in the wild, but as it has not changed
significantly as man evolved, the implications for the classroom are significant. Reducing
students’ perception of threat (punishment or embarrassment in front of classmates for
not doing homework, fear that they will be picked last for a kickball game, or anxiety that
they will make an obvious error because they are not fluent in English) is not a touchyfeely option. Unless the perception of threat is reduced, the brain persists in doing its
primary job – protecting the student or animal from harm. The neural activity on scans
during fear, sadness, or anger is evident in the lower brain, and the reflective, cognitive
brain does not receive the sensory input not relative to survival even though that is the
content of the day’s lesson (Shim, 2005).
Neuroimaging has also given us information about which sensory input gets
through the RAS when threat is not perceived. The RAS is particularly receptive to
novelty and change that is associated with pleasure, color, and to sensory input about
something that has aroused curiosity. Novelty, change, and other curiosity evoking events
alert the RAS to pay attention (Wang, Wetmore, & Furlan, 2005).
Students are criticized for not paying attention; they may just not have their RAS alerted
to what their teachers think in important. Knowing about the RAS means we can promote
classroom communities where students feel safe, where they can count of the adults in
charge to enforce the rules that protect their bodies, property, and feelings from
classmates or others who threaten these.
Our increasing knowledge of what gains access through the RAS once threat is
reduced also offers clues to strategies that promote attentive focus to our lessons (Raz and
Buhle, 2006). Examples of building novelty into learning new information such as
changes in voice, appearance, marking key points in color, variation in font size, hats,
changes in seating arrangements, music, dance, photos, discrepant events, and radishes
keep the RAS focused to admit sensory input!
Advertising a coming unit with curiosity provoking posters or adding clues or
puzzle pieces each day so students are invested in predicting what lesson might be
coming gets the RAS primed to “select” the sensory input of that lesson when it is
revealed (Perry, Hogan, & Marlin, 2000).
Playing a song when students enter the room can also promote curiosity, hence
focus, if they know that there will be a link between some words in the song and
something in the lesson. If you behave in a novel manner, such as walking backwards, at
the start of a lesson, the RAS will be primed by curiosity to follow along when you unroll
a number line on the floor and begin a unit about negative numbers.
Other RAS alerting strategies include engaging curiosity such as having students
make predictions in discussions, KWL charts, and book previews. You can promote RAS
admission to a lesson on estimating by overfilling a water glass and when students react,
responding, “I didn’t estimate how much it would hold.” Even a suspenseful pause in
your speech before saying something particularly important builds anticipation as the
students wonder what you will say or do next.
If you think about the RAS as a gateway instead of just a filter, you can add your
own creativity to any lesson without taking time “away” from teaching. You’ll actually
be accelerating the learning by increasing focus when your students want to know what
you have to teach. There may be several minutes of curious excitement when your
students enter the classroom and find a radish on each of their desks, but this time will be
paid back – literally with interest.
Students’ RAS will be curious so their attention will promote sensory input
“clues” to the puzzle of a novel object on their desks. They will be engaged and
motivated to discover the reason the radishes are there. Younger students, learning the
names and characteristics of shapes, now have the opportunity to develop a concept of
roundness and evaluate what qualities make some radishes have greater “roundness” than
others.
The lesson for older students might address a curriculum standard such as analysis
of similarities and differences. The RAS will respond to the color, novelty, peer
interaction of evaluating these objects, that are usually disdained when found in their
salads, as they develop their skill of observation, comparison, contrast, and even
prediction as to why the radishes that seemed so similar at first, become unique as they
become detectives using magnifying glasses. Students’ stress levels remain low as they
use their individual learning strengths to sketch, verbally describe, or diagram on graphic
organizers (such as Venn diagrams) and discover what the radishes in their group have in
common and how they differ.
As the survival tool, the RAS seeks pleasure, as animals have adapted to their
environments and seek to repeat behaviors that are pleasurable and survival related, such
as eating tasty food or following the scent of a potential mate. Engaged and focused
brains are alert to sensory input that accompanies the pleasurable sensations. In animals
these associations makes them more likely to find the source of pleasure in the future. As
students enjoy the investigation with the radishes, the required lesson content can follow
the open gateway to reach the higher, cognitive brain.
The multisensory, novel experience has a greater chance of becoming long-term
memory as the students are likely to actually answer parents’ often ignored queries about,
“What did you learn in school today?” Students will summarize and mentally manipulate
the day’s learning as grateful parents give the positive feedback of attentive listening. The
impact of the radish as a novel object, and something they’d never expect to hear
described by their child, now alerts their own RAS, and the stage is set for family
discussion of the lesson beyond the doors of the classroom.
Where Heart Meets Mind
The portal to sensory input entering the brain is the RAS but, as we see on
neuroimaging, the amygdala and associated neural networks function very much as
Krashen described about the affective filter that reduces successful learning when
students are stressed. Until recent neuroimaging provided data about real-time influences
on the amygdala and surrounding components of the emotional networks in the limbic
system, were thought to respond to danger, fear, or anger. As we now see on
neuroimaging and measurement of neurotransmitter and cortisol levels, this system also
responds to positive emotional influences.
Experiments carried out while subjects were in the fMRI scanner involved a
“stressed” and “calm” group. Subjects were shown a series of photographs of people with
happy or grumpy expressions. These were not dramatic photos with laughing or furious
expressions, but rather looked as people might at random walking down a busy street
depending on their mood. After viewing the faces subjects were shown a list of words
and instructed that the words would then appear mixed into a longer series of words. If
they recognized a word from the initial list they were to respond with a clicker.
The results on replicated tests revealed better recall in subjects who viewed the
happy faces and their scans demonstrated a clear variation in metabolic activity. The
scans taken during their recall testing had higher activity in the prefrontal cortexes. It is in
the prefrontal cortex (PFC) that neural networks converge that dominate in the regulation
of our highest cognitive functions as well as executive functions (judgment, organization,
prioritizing, risk-analysis, goal-directed behavior, critical analysis, concept development,
conceptualization, knowledge transfer to creative problem solving), long-term memory
construction, and emotional behavioral self-monitoring/control.
Unlike the RAS, which is proportionately the same size in humans as other
mammals, the PFC comprises the greatest proportional volume in the human brain. For
voluntary learning to take place and memories stored the sensory input needs to pass
through the RAS and be directed through the amygdala to the PFC.
Subjects who viewed the grumpy faces showed metabolic activity high in the
amygdalas, but significantly lower than the control group in their PFC while trying to
recall the words they were instructed to remember. The significance of studies with
varying sources of stressful variables replicated these findings that when in a negative
emotional state, the metabolic brain activity is more prominent in the lower, reactive
brain (fight/flight/freeze) (Pawlak, Magarinos, Melchor, McEwen, & Strickland, 2003).
Just as Krashen predicted, there is an affective filter, but it is not just a block that
closes access to the higher, reflective brain. The amygdala also has connections that
expedite information flow to the reflective, voluntary, thinking prefrontal cortex. Seeing
in these scans the response to facial expressions that we might ourselves manifest during
the course of a school day, is a powerful illustration of the impact of emotion upon
cognition.
Before suggesting strategies that are neuro-logical regarding the research on the
amygdala, it is helpful to consider the chemical influences that are at work
simultaneously in response to stress and pleasure. The example of the neurotransmitter
dopamine is just one of dozens of neurochemicals and hormones that are coming to light
as not only influencing learning, but also being activated by teaching strategies and
environmental influences that activate or release these neuroactive substances.
Dopamine one of many neurotransmitters that carries information across synapses
between axons and dendrites of connecting neurons. Dopamine also has a more
generalized influence on the brain. Dopamine release is associated with pleasurable
experiences such that when dopamine is elevated we experience pleasure and when we
use strategies or students participate in activities or reflections that are correlated with
increasing dopamine release, the brain responds not only with pleasure, but also with
increased focus, memory, and motivation (Stirn & Tecott, 2005). This makes sense going
back to the survival benefits of pleasure and of animals remembering information that
can result in pleasure attainment in the future.
What Goes Up, Must Go Down – even in the brain
Just as dopamine levels rise in association with pleasure, a drop in dopamine can be
associated with negative emotions. Unconsciously the nucleus accumbens, a dopamine
storage organ located between each amygdala and the prefrontal cortex, releases more
dopamine when one’s prediction (answer) is correct and less dopamine when the brain
becomes aware of a mistake (which actually takes place even before the person is
conscious of having made the incorrect prediction). As a result of the lowering of
dopamine, pleasure drops after making an incorrect prediction. When a choice/answer is
correct, the increase release of dopamine increases positive feelings (Salamone & Correa,
2002).
Dopamine is a learning friendly neurotransmitter. It is associated with pleasurable
feelings, motivation, memory, and focus. The increased dopamine released from nucleus
accumbens (NAc), allows us to put positive value on actions or thoughts that resulted in
the dopamine release (Galvan, Hare, Parra, Penn, Voss, Glover, & Casey, 2006).
This is the dopamine-reward part of the system that relates to the compelling
aspects of achievable challenge computer games. When players make progress toward the
achievement of their goals and feel the pleasure the dopamine-reward they remain
intrinsically motivated to persevere through the next challenges of the game (Gee, 2003).
Similarly, when students experience the dopamine pleasure of a correct prediction in
class, they are intrinsically motivated to similarly persevere through the challenges of the
next level of learning O’Doherty, 2004).
The rise and fall of dopamine released from the NAc in response to the
satisfaction of a correct choice (answer) is a way of reinforcing the memory of the
information used to answer the question, make a correct prediction, or solve a problem.
The brain favors and repeats actions that release more dopamine and the neural memory
circuit becomes stronger and is used to make future successful choices.
However, if the prediction is wrong, a drop in dopamine release from the NAc
means there will be some degree of unpleasantness. The brain responds to this mistake
negativity by altering the memory circuit to avoid repeating the mistake (Thorsten, et al,
2008).
The value of the brain’s dopamine disappointment response to mistakes is
associated ht the brain changes through neuroplasticity. Changes in the neural circuits
develop so the brain is more likely to make correct response the next time and avoid the
mistake negativity (van Duijvenvoorde, et al, 2008).
The dopamine-pleasure modulating reward center in the nucleus accumbens
(NAc) increases in reactivity through the teen years then settles down into adult pattern of
less sudden, profound emotional shifts (Philpota, McQuona & Kirstein, 2001).
The difference can be observed particularly in the prefrontal cortex areas of
cognitive control. In children through age eight or nine, the reward center reacts strongly
to positive feedback and minimally to negative feedback (Crone, et al, 2006).
This is neuro-logical because young children (and baby animals) need to keep
exploring to make sense of their worlds. In upper elementary school things begin to
change and the prefrontal cortex is more negatively reactive to the drop in dopamine
release by the NAc that occurs with mistake recognition. Thus students from about 6th
grade through high school are impacted more by negative feedback and less by positive
feedback.
Reduce Fear of Mistakes
Students’ greatest fear is making a mistake in front of the whole class, but
learning increases with mistakes. In addition, “Solving the problems of tomorrow will
require critical analysis, willingness to collaborate/tolerate, take prediction risks but
analyze your options, and learn from mistakes. (McTighe, 2009) To construct and
strengthen memory patterns (networks) of accurate responses and revise neural networks
that hold incomplete or inaccurate information students need to participate – predict
correct or incorrect responses. The goal is to keep all students participating and engaged
because only the person who THINKS, Learns.
Only the students who risk making mistakes benefit from the nucleus accumbens
and dopamine pleasure fluctuations. It is in response to the dopamine response to correct
or incorrect predictions (answers) that increase brain receptivity to learning the correct
response. This requires that immediate corrective feedback follow the students’
predictions. The brain motivation is to retain and reinforce the response that results in the
pleasure or alter the incorrect information in the neural patterning network that resulted in
the incorrect prediction and thus avoid the mistake negativity dopamine drop in the
future. As will be discussed in the next section, this neural network strengthening or
correcting are part of the processes of neuroplasticity
Fear of risking mistakes reduces the active participation and construction of
knowledge because the sensory input (instruction) cannot pass through the RAS and
amygdala to the PFC. To keep stress low and information flowing to the reflective PFC,
instead of the reactive, autonomic neural centers, students need to feel safe. We know
from evaluation of effective teaching strategies, that frequent formative assessment and
corrective feedback are powerful tools to promote long-term memory and develop the
executive functions of reasoning and analysis. The frequency of assessment is critical so
students don’t become frustrated by confusion and drop into the fight/flight/freeze mode
where learning cannot take place.
For the process of assessment and expedient feedback to work, students must
participate. The interventions are twofold. Keep the amygdala open to the PFC and
reduce the fear of participation. When students are in this low stress state, they will
participate and learn from feedback provided in a nontreatening manner. They will
remain engaged in the lesson (Yaniv, Vouimba, Diamond & Richler-Levin, 2003).
For the first goal, frequent individualized assessment throughout the class period
can be done with anonymity. Ask frequent whole class questions with single word or
multiple choice (by letter) answers and have students respond by writing on individual
whiteboards. Students need only hold up their whiteboards long enough for you to see
their responses and nod to signify you’ve seen them.
Corrective feedback can follow after you tell the class the correct answer. These
feedback interventions can be planned to coincide with syn-naps, my term for brain
breaks. These syn-naps are needed to replenish neurotransmitters in the synapses that
have been active in the neural networks engaged in the lesson activity. In this “burnout”
state focus can’t be maintained and the amygdala can begin to divert input to the lower,
reactive brain instead of to the hippocampus and prefrontal cortex where new memories
are created.
During the syn-naps a change of pace, such as a dopamine boosting activity can
continue the active learning, but does so using a different neural processing network.
This is also a time when you can respond to the whiteboard assessments with appropriate
individualized corrective feedback for appropriate students, while others move up into
their higher achievable challenge level, such as discussing a challenge question with a
partner, creating a graphic organizer comparing the new material to prior knowledge, or
predicting how what they learned can be transferred to other uses related to their
interests.
When the frequent whiteboard assessment/feedback process is a regular part of
your class, the amygdala stressing frustration of confusion is reduced, because students
know within a few minutes have help to acquire the understanding needed to proceed
with their classmates. With the decrease in stress comes the lower likelihood of the brain
diverting processing to the reactive networks. The classroom behavior problems of fight
(acting out, disturbing others), flight (self stimulation and ADHD-like behaviors), or
freeze (zoning out, losing focus) are reduced, as the filters are open to the reflective PFC
instead of the reactive lower brain.
Positivity
Common stressors in the classroom include fear of being wrong, embarrassed
about reading aloud, test-taking anxiety, physical differences, language limitations,
negative peer relationships, cliques, frustration with difficult material, and boredom from
lack of interest. You can set a positive emotional climate by being the solid force that
keeps students feeling safe and the classroom community strong, thus lowering the stress
that can block the flow of information into the thinking parts of the brain.
When classroom learning environments are supportive and lessons tare engaging,
personally meaningful, developmentally appropriate, and suitably differentiated to offer
achievable challenge, students’ anxieties and participation reluctance can be replaced by
confidence and their filters open to directing the information you teach to their prefrontal
cortex.
Strategies to promote input through the amygdala to the prefrontal cortex overlap
with those associated with increased brain levels of dopamine. Examples of these
amygdala-friendly and dopamine boasting interventions include movement, being read
to, intrinsic satisfaction such as achievement of meaningful goals, humor, optimism,
positive peer interactions, and choice.
Examples of incorporating these positivity influences in the classroom include
pantomime or drawing sketches of vocabulary words, ball-toss to review high points of a
lesson, well-planned collaborative group work, choice of practice or assessment options,
and even sharing a humorous story.
Achievable challenge and feedback that builds intrinsic motivation has a similar
effect on the dopamine-reward circuit as the feeling of “I get it” that accompanies the
understanding of a subtle humor, such as a Gary Larson cartoon. This feeling of self
recognition and the associated increase in dopamine pleasure can lead to a more positive
attitude toward challenging academics. Using discovery and inquiry-based learning can
also result in these positive brain responses that build the foundations of long-term goal
development and self-directed learners.
Mind Controls Matter as Intelligence Can be Changed
The greatest positivity building tool comes from students learning about their
brains’ ability to change itself through its interaction with the environment. The ultimate
benefit of mistake negativity and dopamine reward are manifested by the altering of the
brain’s neural networks. It is within these networks of connecting neurons that
information is stored, transported, and organized. Neuroplasticity is the ability of these
networks to transform based on the acquisition of new information, recognition of
associations between new and prior knowledge, and the reorganization, extension,
correction, and strengthening that takes place.
When students understand that their brains have the capacity to develop stronger,
more efficient, accessible, and durable neural networks through their actions, they have
the positivity, resilience, and motivation to do their part to develop the skills, knowledge,
and intelligence to achieve their goals.
Scientists are certainly on to something regarding neuroplasticity and I enjoy
reading current day claims to both the terminology and the concept of neuroplasticity. I’d
split my vote between these discriptions of our ability to change our brains and change
our intelligence.
“Organic matter, especially nervous tissue, seems endowed with a very
extraordinary degree of plasticity...A path once traversed by a nerve-current might be
expected to follow the law of most of the paths we know, and to be scooped out and
made more permeable than before… with each new passage of the current.” The scientist
goes on to describe this response of brain tissue to repeated stimulation as forming a path
that becomes more embedded with repeated use (James, 1890).
Regarding our brain’s ability to develop intelligence through effort and active
mental manipulation, studying has been described as mental exercise comparable to
gymnastic practice “If he holds no conversation with the Muses, does not even that
intelligence which there may be in him, having no taste of any sort of learning or inquiry
…his mind never waking up or receiving nourishment…We must watch them from their
youth upwards …sustaining reason with noble words and lessons…so they toll at
learning …to reach the highest knowledge.” (Plato, 387 B.C.).
Neuroplasticity describes the phenomenon the development and strengthening of
neural networks (more synapses, dendrites, greater genetic production of protein in the
neuron, and layers of insulating myelin around axons). This construction of stronger,
more efficient (faster retrievable, greater transfer) networks of long-term memory is
stimulated by repeated activation of the circuit such that practice makes permanent
(Rivera, Reiss, Eckert & Manon 2005).
An example of the neuroplasticity phenomenon comes from an experiment
studying the visual cortex. When we see, the information reaches the cortex of the
occipital lobes. When we feel something that sensation is recognized and interpreted by
the parietal lobes. However, when subjects were blindfolded for a week and received
intense Braille practice, which is tactile-sensory, their occipital cortex, which before the
experiment did not respond to tactile stimuli, demonstrated new neural circuit plasticity
and fMRI activity. Their response as similar to the visual cortex in people blind from
birth (Theoret, Merabet, & Pascual-Leone, 2008).
Pattern Development for More Successful Prediction (Correct Answers)
The extension and modification of neural network connections follows the patterning
theories described by Piaget (Ginsberg & Opper, 1988).
When students’ knowledge increases through pattern recognition and matching
new information to existing stored related memories, the neural networks become more
extensive and knowledge grows. Further modification, correction, and strengthening of
the networks is stimulated by dopamine level feedback through the nucleus accumbens
reward/negativity response.
Mental manipulation or exercising the neural networks holding the related
information takes place each time students participate in the mental or physical endeavor
such that the specific pathway of neurons is activated and their connections strengthened.
Through neuroplastisity, the brain is changed by experience, environment and effort
(Dragansk & Gaser, 2004).
Patterning and Memory: To survive successfully animals need to understand
their environments and make meaning of what they see, hear, smell, and touch all around
them. The brain is designed to perceive and generate patterns and uses these patterns to
predict the correct response/decision/behavior/answer to new information.
Patterning refers to the meaningful organization and categorization of
information. Sensory data that passes through the brain's filters needs to be successfully
encoded into patterns that can be connected to existing neuronal pathways. Patterning is
the brain process of structuring information received through the senses (sensory data
input) into the format or coding by which it travels from brain cell to brain cell. In
response to sensory input, our brains build new connections and stimulate existing neural
networks by detecting patterns and evaluating new stimuli for clues that help us connect
incoming information with stored patterns, existing categories of data, or past
experiences and thereby extend existing patterns of stored information with the new
input.
When sensory input first reaches the hippocampus, just beyond the amygdala, it is
available only to working memory (short-term memory). The hippocampus takes sensory
inputs and integrates them with relational or associational patterns. This binds the new
information with already stored and patterned information and builds long-term relational
memories. This is the memory of what you think you need now and fades in less than
minute.
Working memory has limited capacity, usually about 5-9 items such as a
telephone number, so as new input comes in, others drop out. The brain responds to new
working memory by scanning memory stores for patterns of prior memories that might be
related to the new input. When new input connects with a previously stored memory the
dendrites connect in new pattern sequences and the new relational memory is integrated
into neuronal memory networks with previously stored memories. When either fact is
later recalled or prompted, the patterned integration or association that was created
activates the related memory (Davachi & Wagner, 2002; Eldridge, Engel, Zeineh, &
Knowlton, 2005).
Connect With Prior Knowledge: Help students relate the new information with
data they have already acquired through personal experience or real world associations.
Relational memory consolidation can be promoted by activities that help students see the
patterns and connections between what they know and what they are learning. Graphic
organizers, analogies, recognition of similarities and differences promote this patterning
and extended growth of the interneural connections.
Whenever new material is presented in such a way that students see relationships,
they generate greater brain cell activity (forming new neural connections) and achieve
more successful long-term memory storage and retrieval. Activating prior knowledge can
also be promoted with KWL brainstoming, preunit assessment, videos, class discussion
using current events of high interest to the students, and relating the unit to prior
knowledge with ball toss or discussions about what they learned about the topic from the
perspective of another class (especially if there is cross curricular planning).
Patterns connect new to prior experience, and prior experience provides reference
points for constructing new understanding and predicting the correct response to new
information. Patterns are paths for memories to follow. Education is about increasing the
patterns that students can use, recognize, and communicate. As the ability to see and
work with patterns expands, their ability to take in more associated information and make
better predictions is reflected in their long-term memory, concept formation, retrieval of
stored information, and transfer of learning from its original context to other uses.
executive functions are enhanced.
Younger students benefit from activities that build their pattern recognition skills.
Students can guess the pattern you are using as you call up students with a similar
characteristic such as blue shirts. You can give examples and non-examples of a concept
(such as past tense and present tense) and students make silent independent predictions as
to what category or concept the items share.
Graphic Organizers to Pattern: Graphic organizers with visual, diagrammatic,
pictorial, or graphical ways to organize information and ideas for understanding,
remembering, or before writing a paper. For the most part, the information on a graphic
organizer could be written as a list or outline, but graphic organizers give students
another way to see and mentally, as well as visually and kinesthetically, manipulate the
information.
Graphic organizers allow students to create visual pictures of information in
which their brains discover patterns and relationships. When the brain can find and
interpret information as a pattern, such as in a graphic organizer, it receives the
information as meaningful input for memory storage.
Multisensory Learning for Pattern Extension: Greater brain region stimulation
promotes the growth more connections between synapses and dendrites and more
myelination. In multisensory learning there is repeated stimulation of more areas of the
brain as information is presented through multiple senses. Presenting information in a
variety of ways makes the input more likely to resonate with prior knowledge stored in
existing categories and patterns of memories in multiple sensory cortex regions. In this
way, multiple brain regions are connected to the activity or lesson because each of the
senses has a separate storage area in the brain. (Wagner, Schacter, Rotte, Koutstaal,
Maril, Dale, Rosen, Buckner, 1998).
Multisensory learning increases the efficiency of memory retrieval as activation
of one area of the memory storage, such as the visual cortex, simultaneously activates
other cortical regions where the memory was stored (such as when it is also learned
through auditory input (temporal lobe) physical movement (cerebellum and basal
ganglion) (Rivera, Reiss, Eckert, & Menon, 2005).
Duplicated storage areas also result in faster, more accurate recall because stored
memories can be retrieved by a variety of cues. Activities that allow students to use a
variety of their senses can make the difference between engagement and frustration.
Further exercise and neuroplastic extension of these networks is consistent with
the recommendations of another pioneer of educational theory, Benjamin Bloom. His
recommendations included extending thinking beyond isolated facts into integrated
concepts using analysis, synthesis, and evaluation to build intelligence (Bloom, 1956).
When learning goes beyond rote memorization of isolated facts and students have
opportunities to construct knowledge through experiences of prediction, evaluation, and
discovery, the dopamine-reward/negativity circuit provides feedback that revises,
extends, and strengthens the neural networks into concepts. As new information is
recognized as related to prior knowledge already existing within the patterned categories
of neural networks, learning extends beyond the domain in which it took place and is
available for transfer creative new predictions and solutions to problems in other areas
beyond the classroom or test. In other words, intelligence grows.
Yes You Can Change Your Intelligence
Through mental scanning, activation of multiple memory storage areas in
previously constructed neural circuits (pattern) provides as templates upon which to
encode and attach the new sensory input. As students grow and learn, they continue to
expand their experiential database. The more experiences they have, the more likely their
brains are to find a fit when they compare new experiences with previous ones.
Intelligence can be considered a measure of students’ ability to make accurate
connections of new input with existing patterns in their neural networks of stored
information. These connections allow them to acquire and apply the new knowledge to
solve problems such that more successful, extensive patterning leads to more accurate
predictions (answers).
Children, as well as many adults, mistakenly think that intelligence is determined
at or before birth by their genes and that effort will not significantly change their
potential for academic success. Especially when students believe they are “not smart” and
nothing they do can change that, the realization that they can literally change their brains
through study and review strategies is empowering. This is also true of my neurology
patients who lose function due to brain disease or trauma and through practice beginning
with visualizing of moving the paralyzed limb or imagining themselves speaking,
neuroplasticity constructs new neural networks as undamaged parts of their brains take
over the job of the brain damaged regions.
Students and patients are motivated to take action when they learn about
neuroplasticity, see brain scan evidence of brain changes, and see the results of their own
actions when, with more and more practice, neurons that fire together, wire together,
stimulating their neural circuits and making them stronger.
As described in the Brain Owner’s Manual I created for educators, I explain to my
students, “Your own mental efforts in all types of executive function (higher thinking)
such as delaying immediate gratification, working to achieve goals, and evaluating the
strategies you used when you were most successful actually build your brain into a more
efficient and successful tool that you control.
You become the sculptor of your brain’s PFC nerve circuits that focus your
attention, retain information in long-term memory, and retrieve the stored knowledge you
need to solve new problems in your academic and emotional life. There is strong overlap
in the PFC networks of emotional control and intelligent thinking. As you exercise
(stimulate) these networks you’ll find that when you stop to evaluate your emotional
feelings the way you analyze problems in math or skills in soccer, your stronger PFC
nerve circuits will better enable you to manage frustration, confusion, or boredom instead
of these feelings controlling you.”
I have been teaching my upper elementary and middle school students about the
brain filters that determine what information reaches their higher, thinking brains
(prefrontal cortex) and how they can consciously influence those filters. They learn about
changes in their brains that take place through neuroplasticity. I show them brain scans,
and we draw diagrams and clay models of connections between neurons that grow when
new information is learned. I call their summaries of lessons “Dend-Writes” and we
discuss how more dendrites grow when information is reviewed and they have adequate
sleep. I even send home electron microscope photos of growing dendrites and synapses
and assign students to explain that neuroanatomy to family members and report their
responses.
Their results are wonderful. One ten-year-old boy said, “I didn’t know that I could
grow my brain. Now I know about growing dendrites when I study and get a good night
sleep. Now when I think about playing video games or reviewing my notes I tell myself
that I have the power to grow brain cells if I review. I’d still rather play the games, but I
do the review because I want my brain to grow smarter. It is already working and feels
really good.”
I use sports, dance, and musical instrument analogies about building greater skill
the more students practice a basketball shot and ask them to recall how their guitar or
ballet performances improved the more they rehearsed. Then we make connections to
explain that their brains respond the same way when they practice their multiplication
facts or reread confusing parts of a book, because through neuroplasticity - practice
makes permanent.
The Future
The most rewarding jobs of the 21st century will be those that cannot be done by
computers. The students best prepared for these opportunities, as well as the
responsibilities of solving problems that haven’t even been recognized yet, will need a
skill set far beyond the current subject matter and procedures evaluated on standardized
tests. The qualifications for success in the world today’s students will enter will demand
the abilities to think critically, communicate clearly, utilize continually changing
technology, be culturally aware and adaptive with the judgment and open-mindedness to
make decisions based on foundational and conceptual knowledge using their high order
executive functions for accurate analysis of information. They will need these skills to
succeed as creative, collaborative problem solvers in the world they inherit. The keys to
the success of today’s students are coming through the collaboration of the laboratory
scientist and the classroom teacher.
The Science: Neuroscience is showing us more of the brain’s potential to change
intelligence through neuroplasticity. With increasing developments in genetic analysis
and fMRI scanning, we will continue to add to understanding of how different people
learn and the role of environment and experience. We will have more predictive
information earlier to individualize learning for each student. As our knowledge of the
brain improves with better understanding of its information processing functions,
neurotransmitters, and localization of what parts do what, we’ll know more about the
strategies best suited for different types of instruction.
Technology will surely play an increasing part in the classrooms of tomorrow.
Just as more on-line classes and computerized instruction, especially for foundational
knowledge at all grade levels, are already in use, the possibilities for the future are almost
infinite. Models are developing to use neuroimaging, EEG, and cognitive evaluations to
predict the best instructional modes for individual students.
As we have gained greater understanding of brain dysfunction and early
intervention for problems from dyslexia to autism, there are even suggestions for “social
robots”. For example, mirror neuron research suggests that the same regions of the brain
that are active when an action is carried out are also activated earlier during the learning
process (Rizzolati & Craghero, 2004).
A theory is that when a young child sees an adult moving the mouth in
vocalization or displaying facial expressions related to emotions, the mirror neurons in
the child activated in response are starting construction of the neural networks that will
subsequently direct those same actions (Bastiaansen, Thious, & Keysers, 2009).
Further investigation of teaching application of mirror neurons and the role of
imitation is already funded by the NSF to evaluate the use of “social robots” to promote
social interaction skills in children. The research team foresees a place for these social
robots to personalized, individualized environment for each student (Littlewort, 2004).
Collaboration: An equally exciting trend is the development of learning
communities within schools or districts where classroom teachers, resource specialists,
and administrators use books, videos, and sharing of professional development
workshops attended to evaluate possible interventions appropriate to their students’
needs. These educators who teach and observe classrooms discuss successful strategies
and use the knowledge the acquire about the science of learning to further improve the
interventions and transfer their observations and assessments to other lessons or age
groups.
The interface of science and learning can continue to guide educators in the
development of the strategies, interventions, and assessments to prepare today’s students
for the world of tomorrow. A “so what” of educators learning about brain function and
structure starts with knowing why a strategy works. The more educators know about the
research-supported basis for a strategy or procedure, the more they feel invested in it and
the more comfortable they are using and modifying the strategy. This empowers and
encourages teachers to extend lessons beyond rote memory into conceptual
understanding, transferable knowledge, and help students become life-long learners
because they are embraced by neuroscience of joyful learning. With the collaboration of
neuroscientists, cognitive psychologists, educators, and other specialists, teachers will
have opportunities to reconnect with the resourcefulness, compassion, and creativity that
motivated the choice of a career in education.
Collaboration is what will propel the next educational advancements of the 21st
century. The one-way street of scientists telling teachers what to do, without spending
time in classrooms, has been modernized to a bridge between classroom and laboratory.
The future developments with the most extensive and useful classroom applications will
likely arise from input from educators to scientists.
The increased access from educator to research planning opens the way for
investigation of success so what goes right can be evaluated by the researchers to gain
understanding into the neurological and cognitive brain processing involved in the
successful strategies. This exchange is even now taking place through organizations such
as International Mind, Brain, and Education Society (IMBES) and Harvard's Mind, Brain,
and Education (MBE) program. Program director, Dr. Kurt Fischer sees movement
toward increasing integration of neuroscience and cognitive science with education to
further the interdisciplinary progress of improving successful learning for all students.
Through collaboration between educators and scientists, the seeds planted in a
single classroom by a creative, resourceful teacher could be analyzed, replicated,
expanded, and disseminated to benefit students worldwide.
After all, isn’t sharing what we teachers do so well.
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