EdPsych Modules PDF Cluster 2 Module 06

M O D U L E

Summary Key Concepts Case Studies: Re

ﬂect and Evaluate

The Relevance of Brain Research

Physiology of the Brain

Brain Structure and Function

Factors Affecting Brain Development

Brain Activity During Learning

The Brain and Development

Outline Learning Goals

Describe the major arguments for and against the relevance of brain research for educators.

Identify the major factors that can lead to individual differences in brain development.

Identify the contributions from neuroscience to our understanding of what it means to learn.

Applications for the Classroom

Current State of Research in Memory, Reading, Math, and Emotion

Evaluating Claims About Brain-based

Learning

Discuss those areas in which neuroscience

ﬁndings have led to implications for classroom practice.

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THE RELEVANCE OF BRAIN RESEARCH

In 1990, President George Bush ofﬁcially proclaimed the 1990s the
“Decade of the Brain.” From 1990 to the end of 1999, the Library of
Congress and the National Institute of Mental Health sponsored a
unique interagency initiative to advance neuroscience research, and
federal agencies were prompted to provide increased funding for
neuroscientiﬁc endeavors. In the wake of all the excitement generated
about the brain, teachers now face an astounding array of news
stories, books, teaching kits, and conference workshops promoting
“brain-based learning.” Unfortunately, many authors and journalists
have mischaracterized the ﬁndings, causing controversy and
confusion about the role of the brain in learning (Bruer, 1997; Byrnes
& Fox, 1998; Katzir & Pare-Blagoev, 2006). Our goals in this module
are:

to consider how brain research can inform educational practice and

to help teachers understand what claims can and cannot

justiﬁably be made about the direct connections between current
lab ﬁndings and classroom applications.
Critics have argued that neuroscience data are still too new and too

inconclusive to be of any real value to educators (Byrnes, 2001).
Some claim that the gap between the levels of analysis in
neuro-science (which examines learning and development at the
cellular level) and the types of questions most important to educators
is simply too large to bridge (Bruer, 1997; Pylyshyn, 1984).
Advocates, on the other hand, emphasize that new research methods
in neuroscience, such as those found in Table 6.1, can provide
tangible evidence to support ﬁndings in traditional educational and
psychological research (Kosslyn & Koening, 1992; Sejnowski &
Churchland, 1989).

As a middle ground in the debate, educational decision making can

be informed by the combined scientiﬁc data from the areas of
psychology, education, and neuroscience, drawing on multiple
research methods in different settings (Katzir & Pare-Blagoev, 2006;
Lyon et al., 2001; Stanovich, 2003). Brain science has contributed to
the general understanding of the physiology of the brain, but in order
to better understand and interpret the biology of learning, we need to
consider neuroscience data in light of psychological theory and
research. We can have more conﬁdence in research that is connected
to a theoretical framework and in educational theories that are
supported by interdisciplinary, multilevel research. Hence, the
soundest approach is to make inferences only when multiple
neuro-science methods support a claim and when this claim is also
supported by ﬁndings from traditional psychological research
(Byrnes, 2001; Kosslyn & Koening, 1992; Sejnowski & Churchland,
1989).

Given popular misconceptions, the immense volume of research

information available, and the rapid pace of neuroscientiﬁc
discoveries, teachers must be informed consumers of information,
keeping current with the latest ﬁndings from neuroscience and
evaluating the relevance of research ﬁndings to classroom application.
Consider these statements and decide whether each is true or false
based on what you think you know about the brain:

Humans stop growing brain cells shortly after birth.

Humans use only about 10% of their brains.

There are two kinds of people, left-brained people and right-brained people.

Here are the facts:

Belief: Humans stop growing brain cells shortly after birth.

FALSE in some cases. New research is beginning to show that the
brain can grow new cells and develop new connections, at least in
some regions, into adulthood (Bruel-Jungerman, Davis, Rampon,
& Laroche, 2006; Tashiro, Makino, & Gage, 2007; Thomas,
Hotsenpiller, & Peterson, 2006).

Belief: Humans use only about 10% of their brains. FALSE.

There is no evidence to support this popular belief (Blakemore &
Firth, 2005). Learning and thinking are widely distributed across
many parts of the brain (Ornstein, 1997; Thelen & Smith, 1998).
Even a single task such as recognizing a word as you read
activates multiple areas of the cortex (Rayner, Foorman, Perfetti,
Pesetsky, & Seidenberg, 2001).

Belief: There are two kinds of people, left-brained people and

right-brained people. FALSE. While it is true that each of the
brain hemispheres (the right and left symmetrical halves of the
brain) is specialized for certain functions, both sides of the brain
work together in almost all situations, tasks, and processes
(Black, 2003; Blakemore & Firth, 2005; Saffran & Schwartz,
2003).

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TA B L E 6 .1

New Tools for Studying the Brain

Technique What it measures

Electroencephalography (EEG)
Magnetoencephalography (MEG)

Brain waves

The electrical and magnetic activity occurring during mental processing (The spikes of activity are called
event-related potentials or ERP.)

The brain

’s use of oxygen during cognitive processes

Ability to locate active brain regions to within one centimeter

Positron emission tomography (PET scan)

“Fuel uptake” or activity level in various regions of the brain

Magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI)

Functional magnetic resonance spectroscopy (fMRS)

CAT scans (computerized axial tomography)

Conversion of MRI information into a three-dimensional picture

Levels of speci

ﬁc chemicals present during brain activity

Brain chemistry analysis Levels of neurotransmitters (hormones) produced in the brain, such as

cortisol and serotonin

Previous methods for studying the brains were limited to animal studies and autopsies of human brains. With today

’s amazing new

technologies, we can study the brains of living people in ways that are non-invasive.

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TA B L E 6 . 2

Old Thinking Versus New Thinking About the Brain

Old thinking New

thinking

How a brain develops depends on the genes you are born with.

A secure relationship with a primary caregiver creates a favorable context for early development and learning.
Brain development is linear. The brain

’s capacity to learn and change grows steadily as an infant progresses toward

adulthood.

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How a brain develops hinges on a complex interplay between the genes you

’re born with and the experiences you

have.
The experiences you have before age three have a limited impact on later development.

Early experiences have a signi

ﬁcant impact on the architecture of the brain and on the nature and extent of adult

capacities.
Early interactions do not merely create a context; they directly affect the way the brain is

“wired.”

Brain development is nonlinear. There are prime times for acquiring different kinds of knowledge and skills.
A toddler

’s brain is much less active than the brain of an adult.

By the time children reach age three, their brains are twice as active as those of adults. Activity levels drop during
adolescence.
Individuals are either left-brained or right-brained.

Both hemispheres of the brain work together closely in virtually all thinking and learning tasks.

The brain is fully developed by age

ﬁve or six.

Brain changes continue throughout the lifespan.

Sources: Blakemore & Firth, 2005; Shore, 1997.

Table 6.2 compares older views of the brain with new views based on the most recent advances in neuroscience.

What are your initial feelings about the relevance of brain research for teachers? See whether those feelings
change in any way as you continue reading this module.

PHYSIOLOGY OF THE BRAIN

Brain Structure and Function

To understand and better interpret future ﬁndings from brain research, we ﬁrst need a basic understanding of brain
anatomy and function. The cerebral cortex, among the larger anatomical structures of the brain, is the extensive
outer layer of gray matter of the two cerebral hemispheres, largely responsible for higher brain functions including
sensation, voluntary muscle movement, thought, reasoning, and memory. While many learning tasks involve
processing distributed across multiple areas of the brain, certain brain structures are specialized to handle particular
functions, such as vision (back portion of the brain) and control of physical movements (the motor cortex). These
functions may overlap or work together with other parts of the brain, as illustrated in Table 6.3.

The various parts of the brain work together through connections among brain cells. Neurons are brain cells that

send information to other cells through a synapse, a gap between two neurons that allows the transmission of
messages, as shown in Figure 6.1. Although neurons can vary in shape and size, they have certain features in
common (see Figure 6.2):

a cell body that contains a nucleus;

dendrites, branchlike structures that receive messages from other neurons; and

an axon, a long armlike structure that transmits information to other neurons. A single axon can branch out many

times, and these tiny branches end in terminal buttons containing chemicals called neurotransmitters.

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Parietal lobe

Frontal lobe

Parietal lobe

TA B L E 6 . 3

Brain Physiology and Functions

Occipital lobe

Temporal lobe
Pons

Medulla oblongata
Spinal cord Cerebellum

Structure Examples of Processes

Frontal lobes Arousal and inhibition
Aspects of memory and attention
Certain verbal and reading skills Emotional
processing

Reasoning skills

Stress Temporal lobes Aspects of memory

Auditory information

Emotional

reactions

Parietal lobes Aspects of memory and attention
Math skills
Occipital lobes Spatial working memory
Visual processing
Cerebellum Certain verbal and visual tasks
Motor coordination and balance

By the twentieth week of fetal life, over 200 billion neurons have

been created, yet over time, 50% of the original cells are eliminated.
The early overproduction of neurons and neural networks guarantees
that the young brain will be capable of adapting to virtually any
environment into which the child is born, whether San Francisco, São
Paulo, or Shanghai. Consider the case of language development. At
birth, every child has the innate capacity to master any of the 3,000
languages spoken on Earth. Instead of being preprogrammed to speak
any one particular language or every dialect possible, the cerebral
cortex will focus its developmental activities around just those sounds
that have regularity and meaning within its environment and will start
to weed out those neurons that seem unnecessary in a process called
neural pruning. Consider some additional examples of how the brain
changes over time.

A toddler’s brain has twice as many connections among its neurons

as does the brain of a college student, as shown in Figure 6.3. The
toddler brain also appears to expend more energy than does an adult
brain, as toddlers encounter more sensory data that is completely new
to them (requiring more attention and energy to process) and are

trying to master skills that will become automatic and effortless by
adulthood (Shore, 1997). Between ages three and six, extensive
rewiring takes place within regions involved in organizing actions,
planning activities, and focusing attention (Thompson et al.,

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2000). This process primes the child to meet the demands of formal schooling encountered in kindergarten or ﬁrst
grade.

Although the overall size of the brain does not change much after age 6, striking growth spurts can be

seen from ages six to thirteen in those areas that connect brain regions specialized for language and understanding
spatial relations. Perfor mance on some tasks is dependent on the development of myelin, a fatty substance that
speeds the transmission of information from one neuron to another. Rates of myelination (and subsequent
processing speed) have been linked to stages of child development:

Myelination of brain cells related to hand-eye coordination is not complete until about 4 years of age.

Myelination in areas responsible for focusing attention is not complete until around age 10 (Posner &

Rothbart, 2007).

The most extensive myelination in the areas of brain responsible for thinking and reasoning does not take

place until adolescence (Nelson, Thomas, & deHaan, 2006).
Areas of the adolescent brain involved in reasoning, impulse control, and emotions have not fully reached
adult dimensions, and the connections between speciﬁc reasoning and emotion-related regions are still being
strengthened (Blakemore & Choudhury, 2006; Gogtay et al., 2004; Sowell et al., 2004). These ﬁndings
may indicate that cognitive control over high-risk behaviors is still maturing during adolescence, making teens
more likely than adults to engage in risky behaviors (Giedd et al., 1999; Sowell et al., 1999).

Axon

Receptor

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Synaptic vesicles

Dendrites

Neurotransmitter

Figure 6.1 : Communication Through Brain Chemistry. Scientists have learned a great deal about neurons by studying the
synapse

—the place where a signal passes from a neuron to another cell. The neurotransmitters cross the synapse and attach to

receptor sites on the dendrite of another neuron.

Synapse

Cell body

Dendrites

Synapse

Axon

Figure 6.2: The Neuron. A neuron is comprised of a cell body, an axon, and dendrites. The axon of most neurons is covered in a
sheath of myelin, which speeds the transmission of impulses down the axon. The synaptic terminals on the dendrites are contact
points with other neurons.

Factors Affecting Brain Development

The brain is dynamic, remodeling itself in response to environment and experience (Begley, 2007; Tashiro et al.,
2007). Before discussing the many factors that contribute to individual differences in brain structure and
development, we should acknowledge the chicken-and-egg phenomenon in development. When research shows that
individuals who differ in certain cognitive functions (e.g., reading, math, language) also have different patterns of
brain functioning, we must be cautious in our interpretation. Did the different patterns of brain functioning give rise
to diverse cognitive abilities, or do different experiences, as a result of diverse cognitive abilities (e.g., poor readers
receiving less reading practice), lead to altered brain functioning? Research in neuroscience cannot yet tease apart
the direction of this relationship. Credible research on both sides of the issue indicates that the relationship is
bidirectional, meaning that certain patterns of brain functioning have a genetic basis but patterns of brain functioning
can change as a result of experience.

Genetics. While some characteristics of brain development seem to have a hereditary component, research

suggests that genes alone do not determine brain structure. Researchers often have relied

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At birth 6 years old 14 years old

on studies of identical and fraternal twins to identify within-species
differences in the role of genetics in brain development. Among their
ﬁndings: Identical twins, who have exactly the same genetic
instructions, sometimes develop brains that are structurally different,
indicating that other factors besides genetics are at work (Edelman,
1992; Segal, 1989; Steinmetz, Herzog, Schlaug, Huang, & Lanke, 1995).

Environmental stimulation. In a classic study conducted by Mark Rosenweig (1969), rats and other animals were

randomly assigned different environmental conditions in which to live. Some animals were placed in an enriched
environment that had stimulating features such as wheels to rotate, steps to climb, levers to press, and toys to
manipulate, while other animals were placed in standard cages or in deprived and isolated conditions.
Compared to the brains of animals raised in the standard or deprived conditions, the brains of the animals living in
enriched conditions were heavier and had thicker layers, more neuronal connections, and higher levels of
neurochemical activity. Similarly, studies have shown that humans need a stimulating environment in order to
achieve optimal learning and development (Molfese, Molfese, Key, & Kelly, 2003). Features of a stimulating,
enriched environment include social interaction, sensory stimulation, positive emotional support, novel changes, and
challenging but achievable tasks (Diamond & Hopson, 1998).

Environmental stimulation can have different effects on brain structure depending on when it occurs in

development. For example, in a famous study of visual deprivation in kittens, researchers found that kittens reared in
total darkness (with their eyelids surgically sewn shut) for two weeks right after birth would be permanently blind;
however, if the visual deprivation occurred somewhat

Figure 6.3: Synaptic Density in the Human Brain. The number of synaptic connections between neurons peaks during early childhood. Over time,

these connections are

“pruned” to allow for more directed and efﬁcient functioning of the brain. Image reprinted from R. Shore (1997). Rethinking the

brain: New insights into early development (p. 20). New York: Families and Work Institute.

Wired for Learning. The brain has undergone major restructuring by the time a child starts formal schooling.

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Stimulating experiences enhance brain development.

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later in the postnatal period, the kittens were able to develop normal
visual skills (Hubel & Weisel, 1962). Findings such as this led to the
notion of a critical period in human brain development, a window of
opportunity during which certain experiences are necessary for the
brain and corresponding cognitive skills to develop normally. The
assumption underlying critical periods is that the window of
opportunity will close after a certain period of time, making it nearly
impossible to develop normal levels of skill. However, there is
limited neuroscientiﬁc evidence in studies with human beings to
support this assumption (Blakemore & Firth, 2005; Breur, 1999).

Most neuroscientists now believe that development is

characterized by sensitive periods. During a sensitive period, the
brain is particularly sensitive to environmental inﬂuences (Knudsen,
1999). Although it is possible to develop certain capacities after the
sensitive period has passed, skills acquired after that time are subtly
different and may rely on different strategies and brain pathways
(Blakemore & Firth, 2005). For example, individuals who learn a
second language after puberty do not acquire the same level of
grammatical skill that is attained by younger children who learn a
second language (Johnson & Newport, 1989, 1991; White &
Genesee, 1996).

Plasticity. Studies of patients with brain damage indicate that the

brain can rewire itself in an attempt to compensate for loss of
function. The brain’s ability to reorganize itself by forming new
neural connections throughout life is called plasticity. Some brain
systems are more plastic than others, some are highly plastic during
limited periods, and some change more quickly in response to
targeted interventions (Begley, 2007). Plasticity may be considered as
experience-expectant or experience-dependent plasticity (Greenough,

Black, and Wallace, 1987). Experience-expectant plasticity is
available from conception and describes the brain’s ability to
ﬁne-tune its powers to adapt to environmental conditions. For
example, although the brain is equipped to interpret visual signals
from both eyes, it will restructure itself to compensate for a nonseeing
eye. Experience-expectant plasticity involves windows of opportunity
that may gradually close (or at least narrow) if the brain identiﬁes the
skills involved as unnecessary for the individual.
Experience-dependent plasticity refers to the emergence of skills
that are unique to particular cultures and social groups. For example, a
student who moves from rural Indiana to New York City will have to
activate or develop new neural connections that help her negotiate her
new and different living conditions. This form of plasticity involves
strengthening weak synapses and forming new ones and seems to be
viable throughout the lifespan (Bruer & Greenough, 2001; Merzenich,
2001).

Nutrition. Experimental studies with animals and correlational

studies with humans have shown that malnutrition can have different
effects on brain development, depending on the timing of the
malnutrition and how long it lasts (Winick, 1984). The brain of a
human fetus grows very rapidly from the tenth to the eighteenth week
of pregnancy, and good nutrition during this formative period is
believed to be particularly critical to healthy development (Chafetz,
1990; Dhopeshwarkar, 1983). Malnutrition during periods of rapid
brain growth can have devastating effects on the nervous system and
on myelin development (Byrnes, 2001). Malnutrition can impair the
ﬂow of neurotransmitters, the chemical messengers in the nervous
system that permit nerve cells to communicate, thereby placing an
individual at higher risk for neurological and mental disorders
(Coleman & Gillberg, 1996; Edelson, 1988).

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Figure 6.4: The Effects of Fetal Alcohol Syndrome on the Brain. The image on the left shows the brain of a healthy 6-week-old infant. The image

on the right shows the brain of an infant with fetal alcohol syndrome. Image retrieved from http://www.acbr.com/ fas/fasbrail.jpg.

Teratogens. Teratogens are any foreign substances that can cause abnormalities in a developing fetus. For

example, maternal exposure to high levels of lead is associated with higher rates of spontaneous abortion (Bellinger
& Needleman, 1994). Maternal consumption of alcohol has consistently been linked to a range of cognitive and
motor deﬁcits (Barr, Streissguth, Darby, & Sampson, 1990; Streissguth et al., 1989; 1994). Infants born to mothers
who were heavy drinkers during pregnancy may have some form of mental retardation or behavioral problems.
Prenatal exposure to alcohol can occasionally lead to a disorder called fetal alcohol syndrome (FAS), which has an
incidence of 3 per 1,000 births. FAS is a permanent condition characterized by abnormal facial features, growth
deﬁciencies, and central nervous system problems. Children with FAS might have problems with learning, memory,
attention span, communication, vision, hearing, or a combination of these. These problems often lead to academic
difﬁculties as well as social problems (Centers for Disease Control and Prevention, 2007). Figure 6.4 shows the
dramatic differences between the brain of a healthy six-week-old infant and the brain of an infant with fetal alcohol
syndrome.

Think about other areas of physical development, such as your height, and how those aspects of physical

development are affected by genetics, environmental stimulation, plasticity, nutrition, and teratogens.

Brain Activity During Learning

What happens in the brain when a child is learning to read, play the piano, or ride a bike? During
learning, neurons reach out to one another to form new connections or strengthen old ones. The
adult brain contains about 100 billion neurons, but when we speak of “reading words,” “adding
numbers,” “writing sentences,” or “forming a hypothesis,” we are not referring to the work of
individual brain cells. Many cognitive tasks require millions of interconnected neurons (Blakemore
&

Firth, 2005). The very architecture of each human brain is altered as a result of all

newly acquired skills and competencies—in other words, learning. Figure 6.5
illustrates the dispersion of brain activity that takes place during reading.

Certain emerging skills and behaviors have a greater likelihood of developing

elaborate neural connections that become almost impervious to destruction.
These are skills and behaviors that:

New experiences spark new neural connections.

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Word identification

Figure 6.5: Areas of the Brain Involved in Reading. The reading process involves many distinct skills and activates multiple areas
of the brain.

Image retrieved from http://www

.brainconnection.com. Used with permission from PositScience.

Processing rate

Visual processing

Verbal short term memory

Word memory

Text comprehension

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Decoding

Phonological processing

Text

C A T

receive signiﬁcant amounts of time, attention, and practice; and

have key emotional, personal, and/or survival linkages.

As you use certain combinations of skills repeatedly, your brain begins to recognize the pattern and becomes faster
and more efﬁcient at performing the task (Begley, 2007; Hebb, 1949). Certain brain cells actually learn to ﬁre in
unison. Neuroscientists use the phrase “Cells that ﬁre together, wire together” to describe this pattern of
increasing efﬁciency in the brain. Well-entrenched behaviors that are practiced to automaticity (becoming fast and
error-free and needing few cognitive resources) become centered in the regions of the brain responsible for
automatic, unconscious processing. This frees up the conscious cerebral cortex for new learning, because
deep-rooted skills no longer demand a learner’s full attention for their execution. For example, as you read this
sentence, your having already developed automaticity of word identiﬁcation (identifying words and their meanings)
allows you to focus more cognitive resources on comprehension.

Practice strengthens neural connections, while infrequent use of certain skills may cause synaptic connections

to weaken or degenerate in a process called synaptic pruning. The brain is the quintessential example of the
“use-it-or-lose-it” principle. Synaptic pruning eliminates useless connections and makes it possible for the
remaining connections to operate more efﬁciently. Some loss of synapses is both inevitable and desirable. How
might this apply to the classroom? Teachers should clearly identify important skills and concepts and make sure they
are used and reviewed on a regular basis to ensure that they are retained or learned.

What skills have you practiced to a level of automaticity? What skills have you lost or become less ef

ﬁcient

in performing because you haven

’t used them often enough?

Automaticity: See page 197 and page 230.

APPLICATIONS FOR THE CLASSROOM

Recent advances in neuroscience, combined with studies in educational psychology, have validated some of the
educational practices that teachers have intuitively considered educationally sound. Let’s review some of the
ﬁndings and discuss their implications for teachers and students.

Current State of Research in Memory, Reading, Math, and Emotion

Memory. The psychological model of memory suggests that instruction is most likely to succeed if it involves
practice and helps students create detailed representations. This model is highly

Memory: See page 187.

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consistent with both psychological and neuroscientiﬁc evidence
(Byrnes, 2001). Speciﬁc ﬁndings regarding human memory include
these:
1. Attention. The problem of forgetting is not always a memory
problem. Often it is the neural consequence of attention-related
problems. The brain pays little attention to information it feels is
irrelevant. Psychological studies, supported by ﬁndings using
brain-imaging techniques, have shown that some aspects of attention
(such as ﬁltering out unimportant information) are particularly
difﬁcult for children in elementary school and other aspects (such as
orienting attention where directed) are relatively easy (Posner, 1995;
Posner & Raichle, 1994). Neuroscientists are also examining the
possible neural basis of attention-deﬁcit hyperactivity disorder and
are considering the effects that drugs such as Ritalin have on the
brain (Durston et al., 2004; Sowell et al., 2003).

2. Building patterns and connections. The hippocampus, a
brain structure that plays an important role in memory formation,
may temporarily bind separate sites in the cerebral cortex associated
with a memory (e.g., what an object looks like, what it is called, and
so on) until connections that constitute a more permanent record are
established in the brain (Squire & Alvarez, 1998). Learning involves
the establishment of relatively permanent synaptic connections
among neurons (Byrnes, 2001). The popular press and
practitioner-oriented books have emphasized the importance of
teaching in ways that build synaptic connections and that encode
information in multiple ways, yet neuroscientiﬁc research has not
been able to demonstrate that one particular instructional technique
is any better than another for actually generating synapses in the
brain (Begley, 2007; Byrnes, 2001).
3. Novices vs. experts. An individual’s level of expertise shows
itself through major differences in neural representations of the same
information. When we compare brain images of “novices” and
“experts” performing the same task or playing the same game, the
differences are vividly apparent. Experts organize and interpret
information in their brains differently from nonexperts (National
Research Council, 2000). Teachers can support the development of

expertise by giving students plenty of time to practice essential
skills. Many psychological studies have conﬁrmed the importance of
practice and repetition, as well as the value of a variety of
metacognitive strategies to aid learning, memory, and transfer
(Anderson, 1995; Flavell, Green, & Flavell, 2000; Weinstein &
Mayer, 1986).

Reading. Reading is probably the area with the highest degree of

convergence between educational psychology and neuroscience.
Educational researchers had already developed sophisticated theories
of reading and dyslexia based on behavior, and these theories have
guided the interpretation of neuroscientiﬁc data (Willingham &
Lloyd, 2007). Here are some classroom implications suggested by
research in these two ﬁelds:

1. Based on studies of neural development and psychological
studies of cognitive development, reading instruction is likely to be
relatively ineffective before age three or four (Goswami, 2006;
Katzir & Pare-Blagoev, 2006).

2. Sophisticated brain-imaging technology reveals that individuals
with a reading disability show decreased functioning in certain brain
regions while performing reading tasks that require phono-logical
processing—a skill needed to consciously manipulate the letter
sounds in words (Begley, 2007; Shaywitz et al., 2002). However, it
is not yet clear to what extent differences in brain functioning are a
cause of phonological processing deﬁcits in reading disability or a
product of the phonological deﬁcits that individuals with a reading
disability experience when learning to read. The relationship seems
to be bidirectional. Neurological conﬁrmation of the role of
phonological processes in reading and reading disability has led to a
reevaluation of how reading disabilities are deﬁned and understood
(Perfetti & Bolger, 2004).

Practice Makes Perfect.
Students can develop expertise by practicing essential skills.

Reading disability:

See page 431.

Memory, metacognition, and transfer: See page 187, page 214,
and page 230.

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3. Brain scans reveal that intervention makes a difference in the
reading performance of dyslexic students. Individuals with reading
disabilities who participated in targeted instructional programs
improved their reading performance, and their brain activation
patterns began to more closely resemble those of typical readers
(Shaywitz et al., 2004; Simos et al., 2002). Currently, almost a
quarter million children are participating in the Fast ForWord
reading program derived from neuroscience research and
developed by the Scientiﬁc Learning Corporation (http://www.
sciencelearn.com/). Cognitive-behavioral and neurological ﬁndings
indicate that speciﬁc remediation programs such as this, which
provide intensive training to improve auditory processing deﬁcits,
can alter the functioning of the brain (Katzir & Pare-Blagoev,
2006; Temple et al., 2003).

Math. Few educational implications exist for math skills because at

present, the number of neuroscientiﬁc studies is limited. The available
research evidence, however, supports some tentative conclusions
(Byrnes, 2001; Geary, 1996):
1. Calculation skills seem to be largely conﬁned to the left hemisphere (though not always).

2. Individual math facts and procedures seem to be stored in their own separate areas of the cortex (one
area for multiplication facts, another for subtraction procedures, and so on).

3. Skills of comparing and ordering information seem to be
localized in the posterior regions of the right hemisphere (though
not always).

These ﬁndings tell us a little about activity in the brain during math
but contribute little to understanding how to teach math. Some of the
most useful ﬁndings about how to teach math have come from studies
in educational psychology that examine children’s conceptual
understanding, factual knowledge, and calculation processes
(Peterson, Fennema, Carpenter, & Loef, 1989; Resnick & Oman-son,
1987).

Emotion. There is still much to learn about the ways emotion

relates to learning and how brain research on emotions might be
applicable to classroom practice. However, let’s consider two
interesting avenues of research:

1. Psychologists have hypothesized that human brains may reﬂect
an inherent sociability and need for afﬁliation (Lefebvre, 2006;
Pinker, 1997). This “social brain” hypothesis could explain why
children perform better in school when they view their teachers as
caring (Wentzel, 1997) and also could have implications for the
use of independent versus collaborative approaches in the
classroom. Additional research with human subjects needs to
investigate further the connection between social and emotional
centers in the human brain and related learning outcomes.

The

“Social Brain.”

Children perform better in school when they believe their teachers care about
them.

Emotions and learning: See page 63.

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114

cluster two

the developing learner

2. Chronic stress and fear can lead to the physical destruction of
neurons in the hippocampus, an area buried deep in the forebrain
that helps regulate emotion and memory (McEwen, 1995). Anxiety
increases in the presence of pressures to perform, of severe
consequences for failure, and of competitive comparisons among
students (Wigﬁeld & Eccles, 1989). High anxiety can interfere with
learning by distracting a student’s attention from the material to be
learned (Cassady & Johnson, 2002).

Evaluating Claims about Brain-based Learning

The No Child Left Behind Act of 2001 and the Individuals with
Disabilities Education Improvement Act of 2004 have required
schools to provide students with academic instruction that uses
scientiﬁc, research-based methods. Unfortunately, many claims about
brain-based education are not well supported by credible research.
Also, “brain-based learning” recommendations often are based on
ﬁndings from educational psychology studies rather than on
neuroscientiﬁc evidence. Other studies have been conducted with
animals and the results generalized to humans, with no real
understanding of between-species differences.

The rapid explosion of brain research has sparked the interest of

educators who have drawn premature conclusions about educational
implications. Consider, for example, these claims:

Suggestions by Geoffrey and Renata Caine (1997) and Howard

Gardner (2000) that brain research justiﬁ es a shift toward more
thematic, integrated activities. There currently is no neuroscientiﬁc
evidence to support such a sweeping conclusion.

The assertion by Gardner (2000) that brain research supports

active learning. This assertion is based on behavioral studies, not
neuroscientiﬁc ﬁndings.

Brain Gym, a popular commercial program marketed in more

than 80 countries, is claimed to lead to neurological repatterning
and greater whole-brain learning (Ofﬁ cial Brain Gym Web site,
2005). The brain is dynamic and is constantly repatterning itself, so
this outcome is not unique to Brain Gym.

While these and other prescriptions for brain-based learning may

turn out to be valid, at the present time data to support these claims is
insufﬁcient. The evidence most frequently cited comes from
traditional psychological studies, not from neuroscience (Bruer, 1999;
Coles, 2004; Hyatt, 2007; Stanovich, 1998). When sorting through
claims made about brain-based learning, we must proceed with
caution and analyze the data with a critical eye.

You hear from a friend that listening to classical music boosts

infants

’ brain power. How can you judge whether this claim is

valid?

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key concepts

115

Summary

Describe the major arguments for and against the relevance of brain research for
educators. Critics have argued that neuroscience data are still too new, too inconclusive, and too
different from educational frameworks to be of any real value to educators. Advocates, on the other hand,
emphasize that new research methods in neuroscience can provide tangible evidence to support what
has been found in traditional educational and psychological research. They suggest that
educational decision making can be best informed by combining scienti

ﬁc data from psychology,

education, and neuroscience, using multiple research methods in different settings.
Identify the major factors that can lead to individual differences in brain development. Several
factors produce individual differences in brain structure and development: (1) genetics; (2) environmental
stimulation;

(3) plasticity, which allows the neurons (nerve cells) in the brain to compensate for injury and disease and
to adjust their activities in response to new situations or changes in their environment; (4) nutrition; and
(5) teratogens, or foreign substances that can cause abnormalities in a developing fetus.
Identify the contributions from neuroscience to our understanding of what it means to
learn. During learning, neurons respond by reaching out to one another in an elaborate branching
process that connects previously unaligned brain cells, creating complex neural circuits.
Neurons are constantly rearranging their connections in response to new information and
experiences. Learning can involve strengthening existing synapses or forming new ones. In some
cases, cognitive development can require the elimination of synapses through synaptic pruning. Teachers
should clearly identify important skills and concepts and make sure they are used and reviewed
on a regular basis

—otherwise students’ ability to remember and use these skills is likely to weaken or

disappear altogether. Practice strengthens neural connections and allows more ef

ﬁcient retrieval of

information.
Discuss those areas in which neuroscience

ﬁndings have led to implications for classroom

practice. Research now suggests that brain development is not determined solely by genetics.

How a brain develops hinges on a complex interplay between the genes you

’re born with and the

experiences you have. Studies of memory and attention have shown that experts organize and interpret
information in their brains differently from nonexperts. Teachers can support the development of expertise
by giving students plenty of time to practice essential skills. Classroom interventions, such as the
Fast ForWord program used with students who experience reading dif

ﬁculties, can help students make

cognitive adaptations that cause the brain to rewire itself in more ef

ﬁcient and interconnected ways.

Unfortunately, the rapid explosion of brain research has sparked the interest of educators who have
drawn some premature conclusions about the educational implications. Neuroscienti

ﬁc research does not

support the speci

ﬁc claims of many “brain-based learning” programs that promise to boost brain power.

Key Concepts

experience-expectant plasticity fetal alcohol syndrome (FAS) myelin neurons neurotransmitters plasticity

brain hemispheres

“cells that ﬁre together, wire together” principle cerebral cortex critical period

experience-dependent plasticity

sensitive periods synapse synaptic pruning teratogens

“use-it-or-lose-it” principle

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116

case studies: re

ﬂect and evaluate

Case Studies:

Refl ect and Evaluate

Early Childhood:

“Fire Safety”

These questions refer to the case study on page 94.

1. De

ﬁne sensitive period and explain why the preschool years may

be a sensitive period for language development.
2. Explain the relationship between a stimulating environment and a
child

’s brain development. What types of activities, toys, and

interactions would characterize a stimulating preschool environment?
Based on this, evaluate whether Rolling Hills Preschool is a
stimulating preschool environment.

3. Suppose there was a child at Rolling Hills Preschool with fetal

alcohol syndrome. How might this child

’s learning, memory, and

communication skills compare to those of the other children in the

case? 4. Angela encouraged the children to practice their safety

information so they would know it by heart.

Explain what happens in the brain as individuals practice skills until they become
automatic.
5. Preschoolers often are said to have limited attention spans.
Evaluate the validity of this claim with respect to the evidence on
age-related patterns in the brain.
6. Angela introduced several different ways to practice and
remember phone numbers. How would you describe what happens in
the brain as each new method is introduced and used?

Elementary School:

“Project Night”

These questions refer to the case study on page 96.

1. Evaluate Carlos

’s assumptions about right-brained and

left-brained students. Based on your reading of the research in the
module, what would you say to him?
2. Explain why practicing research techniques such as using the
Internet and an encyclopedia is so important in developing
automaticity, and explain what happens in the brain as this occurs.
3. According to brain research on attention, why would you expect
the

ﬁfth graders to have difﬁculty distinguishing important information

from less important information in their project resources?
4. Based on the discussion of age-related patterns of brain
development, why might the exchange and evaluation of information
in the

“research teams” be challenging for ﬁfth-grade students?

5. Mr. Morales

’s project unit helps students build elaborate and

meaningful representations of their social studies knowledge. Explain
what happens in the brain as this occurs.

Middle School:

“Frogs”

These questions refer to the case study on page 98.

1. Tyler has fetal alcohol syndrome (FAS). Describe the problems
associated with FAS, and provide suggestions for modi

ﬁcations

Morgan might need to make in biology lab for Tyler.
2. Morgan assumes that because Tyler is 13, there is not much she
can do to help him improve his language skills because the critical
period for language development has passed. Explain why Morgan

’s

reasoning is

ﬂawed.

3. A student in Morgan

’s class who has struggled academically

throughout upper elementary school has just been diagnosed as
having a speci

ﬁc reading disability. He asks Morgan to help him

understand why he processes written text differently than his peers.
Based on brain research presented in this module, what might
Morgan say to this student?
4. If Morgan

’s students never have an opportunity to do another

dissection, what is most likely to happen to their dissection skills?
Give your answer in terms of what is known about the way the brain
functions.
5. How might the saying

“Cells that ﬁre together, wire together”

explain why students would be expected to become more ef

ﬁcient at

doing the steps involved in dissection if they repeated them multiple
times?

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case studies: re

ﬂect and evaluate

117

High School:

“The Substitute”

These questions refer to the case study on page 100.

1. Dylan appears to have begun engaging in some risk-taking
behavior. Explain the brain changes taking place during
adolescence that might contribute to decisions about risk-taking.
2. The students Mr. Matthews encounters on his

ﬁrst day are not

used to being actively engaged in class. Explain how the teaching
methods Mr. Matthews introduces might shape the way knowledge
of British literature is processed in the brain.
3. A teacher meets Mr. Matthews in the hall and says,

“You’ve had

quite an impact on your British literature students. So, I hear you

’re

using brain-based teaching.

” Explain why the teacher’s comment

about brain-based teaching is inaccurate. How should teachers use
brain research to support and inform their teaching?
4. If a student in Mr. Matthews

’s class had a reading disability,

would it be possible to change the way that student

’s brain

processes information during reading? Explain based on the
evidence from neuro-science research.

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