6

M O D U L E

Summary Key Concepts Case Studies: Reflect and Evaluate

The Relevance of Brain Research

Physiology of the Brain

ⁿ Brain Structure and Function

ⁿ Factors Affecting Brain Development

ⁿ Brain Activity During Learning

The Brain and Development

Outline Learning Goals

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

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

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

Applications for the Classroom

ⁿ Current State of Research in Memory, Reading, Math, and Emotion ⁿ Evaluating Claims About Brain-based Learning

4. 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:

n to consider how brain research can inform educational practice and

n 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:

n Humans stop growing brain cells shortly after birth.

n Humans use only about 10% of their brains.

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

Here are the facts:

n 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).

n 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).

n 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 specific 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 significant 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):

n a cell body that contains a nucleus;

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

n 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:

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

n Myelination in areas responsible for focusing attention is not complete until around age 10 (Posner & Rothbart, 2007).

n 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

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

n 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 efficient in performing because you haven’t used them often enough?

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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

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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.

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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.

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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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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:

n 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.

n The assertion by Gardner (2000) that brain research supports active learning. This assertion is based on behavioral studies, not neuroscientific findings.

n 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 scientific 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 efficient 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 difficulties, can help students make cognitive adaptations that cause the brain to rewire itself in more efficient 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. Neuroscientific research does not support the specific 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: reflect and evaluate

Case Studies: Refl ect and Evaluate

Early Childhood: “Fire Safety”

These questions refer to the case study on page 94.

1. Define 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 modifications 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 specific 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 efficient at doing the steps involved in dissection if they repeated them multiple times?

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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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