PSYCHOSOCIAL DEVELOPMENT 1Psychosocial D.docx

PSYCHOSOCIAL DEVELOPMENT 1
Psychosocial Development
Chanda Crews
PSY 104 Child and Adolescent Development
Instructor: Julian Achim
December 13, 2019
Psychosocial Development
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Age-appropriate refers to the particular age in which a child
goes through as a mode of
the development period. Different psychologists have given out
different views on the various
stages in which a child develops in consideration of specific
events, which take place (Cherry,
2018). The first stage outlined by Erikson in his development
theory is none other than the hope,

which takes place in every child under the age of two years. In
this stage, a child has room to
evaluate the environment as a way of developing either
trust or mistrust. As illustrated by
Erikson, the parents are a hope for the child according to
how the parents support the child.
Some parents do not care for their children through the failure
to raise basic needs for that child.
As a result, the environment becomes rough for the child a
situation that leads to mistrust to that
child.
Then again, if a parent supports a child, then the environment
becomes comfortable for
the child, a situation that develops trust to that child. Thus,
Erikson states it clear that hope is a
crucial stage for a child. Hence, all the caregivers should
be in a position to help the child
develop trust. Will is the other concept, which supports child
development as illustrated by the
Erikson’s psychosocial theory on child development. However,
in this particular stage, a child
starts exploring the surrounding a situation which helps
the child in understanding the
environment. Therefore, a parent or caregiver should be in a

position to provide security for the
child as the concept occurs between 2-4 years (Knight, 2017).
The motive behind this logic is
that in this age, a child cannot differentiate on the things,
which can bring harm. Therefore,
parents are advised to take control of their children as a way of
supporting child development
during this critical stage. Then again, in this particular stage, a
child starts to express interests in
different activities. Like for instance, a child will develop
feeding modes without the support of
the parent. On the other hand, a child will start playing
with different objects as a way of
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PSYCHOSOCIAL DEVELOPMENT 3
satisfying their needs. Thus, a parent should support the
child without distracting them from
understanding the environment.
Conversely, the purpose is the different concept as
illustrated by Erikson in his

psychosocial theory. In this case, a child starts doing things
with an intention after developing the
will concept. Like for instance, a child understands that round
objects roll and that objects can
fall. Therefore, a child will start dropping objects, and if they
fail to achieve the child’s intention,
the child develops emotions. The child will end up crying to get
the assist of the parent to help in
meeting the child’s purpose of dropping an object (Cherry,
2018). On the other hand, a child will
develop speaking habits from socializing with the
environment and learning that people talk.
Thus, all the parents have a big responsibility of supporting
their children during this particular
stage. As for instance, a parent is advised to play with the child
to help the child achieve their
purpose in a situation, which allows the child in development.
On the other hand, a parent is
advised to help the child in speaking through different
activities. One of the events is none-other
than buying toys, which produce sound to help the child in
speaking mode.
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References
Cherry, K. (2018). Erik Erikson's Stages of Psychosocial
Development. Retrieved Juny.
Knight, Z. G. (2017). A proposed model of psychodynamic
psychotherapy linked to Erik
Erikson's eight stages of psychosocial development.
Clinical psychology &
psychotherapy.
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This week's assigned readings from your textbook:
Edgar Allan Poe:
Biography, Vol. 1 pp. 731-735 and "The Cask of Amontillado,"
Vol. 1 pp. 785-790
Henry David Thoreau:
Biography, Vol. 1 pp. 900-902 and "Resistance to Civil
Government," Vol. 1 pp. 903-918 (essay)
Post 1: Look at Henry David Thoreau's "Resistance to Civil
Government." He claims that it is not just our right as
Americans, but it is also our duty to defy unjust laws. This is a
very American idea. Part of the American identity involves
intervening in the face of injustice. Do you agree with this
point? What boundaries should exist to those interventions?

Support your claims using "Resistance to Civil Government"
AND one of the other assigned readings from this week.
Criteria:
· 300 words minimum (excluding quotations and citations)
· Include two properly and integrated quotations (one from each
work) to support your claims. You may use either direct or
paraphrased quotes. See the Literary Analysis Tools Modules in
Weeks 1 and 2 for information about integrating and citation
quotes.
8Cognitive Development: Information Processing
Digital Vision/Photodisc/Thinkstock
Learning Objectives
After completing this module, you should be able to:
ሁ Identify various components of information-processing
theory and explain how they are used to
organize information.
ሁ Synthesize evidence to explain how we know that infants
develop memories.
ሁ Trace the expansion of memory development throughout
childhood, according to information-
processing theory.
ሁ Explain how verbatim memory trace and gist are integrated
into fuzzy trace theory.
ሁ Differentiate between selective attention and sustained
attention.
ሁ Appraise available information on attention-

deficit/hyperactivity disorder, including standards for
diagnosis, its causes, and treatment.
ሁ Understand how executive function is applied to cognitive
development.
ሁ Evaluate the application of cognitive theory to contemporary
education.
Section 8.1Information-Processing Approach
Prologue
What is your earliest memory? Although most people think they
have memories from when
they were 2 or 3 years old, psychologists have known for a long
time that we actually con-
struct early memories from a combination of photographs,
stories we have heard, and our
imaginations. We know that infants who escaped the Jewish
Holocaust in Germany or the
ethnic cleansing in Bosnia, or who suffered other kinds of
trauma, do not have any recollec-
tion of their early childhoods. Children born into privilege with
generally happy experiences
have a similar lack of early memory.
But we know that infants do indeed remember from moment to
moment. Otherwise, they
would not learn to search for objects, would not be able to
distinguish their primary caregiv-
ers from strangers, and would not have consistent preferences
for favorite foods and other
stimuli. The information-processing model of cognitive
development acknowledges that
memory, along with attention, is a key determinant of the way

that a child’s mind develops.
Unlike Piaget’s stage model, information-processing views
growth as a steady, progressive
process that is the result of exposure to and processing of
information. That is, it describes
incremental improvements in the amount of information that
developing children store
and use.
The information-processing approach is a more contemporary
theory; it is modeled after
the way in which information flows logically in computers.
Because it is theorized that
human information-processing involves the encoding, storage,
and retrieval of informa-
tion—just like a computer—the study of memory is an essential
part of the theory. As
such, it is a focus of this module. For humans, there is the
additional factor of attention.
Without attention, the input of stimuli is modified greatly—if it
occurs at all. This module
also explores the issues and potential controversies of a
commonly diagnosed attention
disorder. Finally, the module closes with a discussion of how
the information-processing
approach to cognitive development is sometimes applied within
the current educational
system in the United States.
8.1 Information-Processing Approach
According to the information-processing theory of cognitive
development, the mind is
analogous to a computer. Both are able to remember, categorize,
and process ways to retrieve
information. They take in, store, process, and manipulate
information like words and num-

bers. Like computers, though, humans have a limited capacity to
hold and manipulate infor-
mation. And, like a computer that gets a processor or software
upgrade, as we develop we
become more efficient thinkers. Therefore, one way to look at
cognitive change is to look at
the component parts, like memory and processing speed.
Contemporary information-processing models expand on the
traditional theories. Both
Piaget’s stage theory and information-processing models
acknowledge that cognitive capac-
ity is somewhat predetermined at birth and at times thereafter is
restricted to certain
limits. Remember that biological evidence supports this
assertion. For instance, both theo-
ries agree that a 2 year old would not be expected to understand
algebra. The difference
in the approaches is the way they describe a child’s capacity to
eventually understand the
complexities of math. Instead of the step-like (qualitative)
change described by Piaget, the
information-processing approach sees development as a
smoother, linear progression. There
are simply gradual changes in the way we take in, store, and
process information. The growth
is described as more quantitative, because the amount (quantity)
of information is key to
cognitive growth, not maturation of stages.
This approach epitomizes the continuous view of development.

Understanding mathematical
concepts, for instance, progresses from being able to count in
sequence, to performing simple
arithmetic, and eventually to engaging in more complex
operations. Knowledge of mathe-
matical concepts changes not only in the way information is
organized, but also in the sheer
volume of concepts. The same could be said for oral language;
music; understanding how
chemistry, physics, and biology function in the world; and so
on.
The information-processing approach also fits in with the view
that cognition has biologi-
cal controls. Cognitive development can be compared to
specific skill-based endeavors like
playing a musical instrument, running, or drawing. We can all
be trained to excel up to a cer-
tain degree, but there are individual limitations. Whether for a
physical skill or cognition,
maturation directs the gradual unfolding of potential. At its
most basic level, information-
processing theory says that thinking is an inherent mental
activity that involves import-
ing information into the brain and mind, and then processing it
so that it can be useful
(Mayer, 2012).
We all use information differently depending on our unique
experiences and how that
information is inputted into our brains. Ultimately, after
information is entered and stored,
we are interested in how responses become relevant. That is, we
want to follow the infor-
mation from when it is perceived to the discovery of how it
comes to be used. Therefore,

we focus on how information flows through the system,
especially with regard to memory.
Children become better processors of information (more
advanced cognitively) as they
gather more knowledge, encode it in memory, compare it with
other memories, and finally
make an appropriate response. There is constant interchange
between storage and pro-
cessing in order to efficiently take in and use information. This
feedback loop is illustrated
in Figure 8.1.
Like Vygotsky’s sociocultural theory, information processing is
continuous and depends at
least partly on context. Theorists who support the information-
processing model often point
to the learning of math and reading as representative of the
model. For example, the key to
reading better is using strategies for processing the symbols on
the page. Long-term knowl-
edge about sounds and meanings are used to decode words; a
cognitive feedback loop about
the reading passage is used to “update” comprehension and the
meaning of new vocabulary.
There is a constant interchange between storage and processing,
which allows retrieval pro-
cesses to utilize reserved memories.
Figure 8.1: The information-processing approach
ሁ The information-processing approach views cognitive
development as forming a feedback loop.

We attend to information, and then it is processed in a way that
it can be stored. Information is then
compared with other memories and processed for output. There
is constant interchange between
storage and processing so that memory storage and retrieval are
efficient.
Input Output
Processing
Storage
Memory Systems
One of the overriding features of information-processing theory
is the idea that a number
of processes underlie what might look like a single response.
We know that there must be
some physical memory trace in the brain that coincides with the
ability to walk, compute,
and socialize, for instance. Usually we think only of the output
of memory retrieval, but we
want to know where those memories actually live. One way to
conceptualize how information
processing takes place is the stage model of memory (Atkinson
& Shiffrin, 1968). According
to this model, memory can be broken down into three kinds of
storage components: sensory
memory, short-term memory, and long-term memory. The three
components contain differ-
ent types of storage systems where information is encoded.
Sensory Memory
Input into the cognitive system begins with stimuli that are
received through the senses.
Before the brain can remember something, it first needs to

perceive the stimulus. That is, a
stimulus must first be noticed in order for it to be prepared for
encoding. This information
is stored very briefly—perhaps for less than a second. The short
impressions of informa-
tion that are gathered through the senses make up part of
sensory memory. Unless sensory
information is attended to and interpreted, it will be lost.
Short-Term Memory
If information is attended to and interpreted, it is stored in
short-term memory. The short-
term system consciously holds between five and nine of these
memories (sometimes referred
to as 7 ± 2) for up to 30 seconds. To store them permanently,
we work with these bits of infor-
mation by performing certain cognitive operations. Like a
computer system, we find ways to
both store and process the incoming bits. However, rather than
being a temporary storage
system, as the name implies, short-term memory is a more
complex working system. Recog-
nizing that active effort takes place in this “short-term” process,
this store of memory is now
more commonly referred to as working memory (Baddeley,
1986, 2007).
Working memory includes an overall “supervisory” or executive
system that oversees various
pieces of knowledge, including auditory, visual-spatial, and
semantic (relating to word mean-
ings) information. The working memory sometimes retrieves

information from long-term
storage (the “hard drive”), allowing us to store (remember) the
information more efficiently
so that we can work with it. For instance, we may consciously
store an image of an animal; we
can also recall categories of similar animal images from our
“permanent” storage of memo-
ries. If information about the new animal is not rehearsed or
otherwise stored, it is lost.
Long-Term Memory
If we are successful at encoding information for later retrieval,
it will become stored in long-
term memory. Unlike the small capacity of short-term memory,
long-term memory is virtu-
ally limitless (Schwartz, 2010). For information to be
transferred to long-term memory, it
must be organized. That organization is necessary for retrieval.
For instance, a 12 year old
may remember that an opposing soccer player kicks only with
the right foot. That informa-
tion is retrieved and then transferred to working memory when
deciding how to play defense.
The information is organized into a mental framework or
concept of, perhaps, soccer defense.
Information-processing theory calls this conceptual formulation
a schema. (The term schema
is used differently here than it is in Piaget’s theory.)
A C T I V I T Y
For a moment, pay attention to any noises in your environment.
If you are listening to
a music player, pay attention to all the sounds that are
produced. There are likely some
sounds that you were not aware of before you paid attention to
them. All of these sounds

were part of your sensory memory because they stimulated your
hearing—even if you did
not “know” it. For the moment, you have now stored the sounds
in your short-term memory
because you are attending to them. If you remember this little
exercise at a later time, you
will have successfully encoded the information into long-term
memory.
Critical Thinking
Provide an example of how working memory
might include traces of auditory, visual-spatial,
and semantic information. How might the
incoming information be associated with long-
term storage?
Memory Strategies
We must employ several strategies to construct various schemas
efficiently. Younger children
usually simply repeat information over and over in order to
keep it in short-term memory,
a process called rehearsal. By contrast, older children use
rehearsal in combination with
more sophisticated strategies, like organization (Bjorklund &
Douglas, 1997). Imagine, for
instance, that you need to remember these items: mayor,
congress, senator, governor, repre-
sentative, borough, district, president, senate, vice president,
lieutenant governor, city council,
ward, and legislative assembly. Whereas younger children do
not easily appreciate how the

terms can be organized, older children recognize that the terms
can be grouped by city, state,
and national government so that they can be retained more
easily.
Children can be taught to use other deliberate strategies, as
well. To improve memory, chil-
dren can be prompted to make information more meaningful, in
an activity called elabora-
tion. It involves more extensive processing of information,
results in more connections to
long-term storage, and therefore makes information easier to
remember (Schneider, 2011).
For instance, you could memorize by rote that plants take in
carbon dioxide and give off oxy-
gen as a waste product. However, it is easier to forget whether
plants take in oxygen or emit it
when the two facts remain independent of other information. By
contrast, we can elaborate:
most people can remember that humans (and other animals) take
in oxygen and give off car-
bon dioxide. If you think that nature must maintain a balance of
oxygen and carbon dioxide, it
makes sense that plants and animals would have opposing
processes. Elaboration therefore
makes the information easier to recall. Elaborative strategies
may include visual images or
wordplay, as well. For example, if you remember the symbol for
atomic element 79 by think-
ing that AUstralia won the gold, you have used elaboration to
encode information (the symbol
for gold is AU). Although children elaborate more efficiently
with age, even preschoolers can
learn these strategies (Pressley & Hilden, 2006).
Processing Speed

Nevertheless, only a small set of basic processes underlie
cognitive development (Galotti,
2011). That is, mental processes like reading, contemplating
what to say to a teacher, search-
ing for art supplies, and putting together a puzzle are systemic
and spring from mechanisms
that underlie cognitive development in general. Part of the
overall gain we see in cognition
stems from increased speed in the processing of information.
Kail and his colleagues illustrated this general mechanism in a
series of experiments that
evaluated changes in processing speed and working memory
(Kail, 1986, 1988; Kail & Bisanz,
1992). Children of various ages performed cognitive activities
such as name retrieval, mem-
ory search, visual rotation of objects, and mental math. Between
early childhood and late
adolescence, processing speed increased across every task. In
addition, as Figure 8.2 shows,
processing speed across each task showed the same pattern of
improvement and reached
adult levels in all areas by late adolescence. Therefore, it was
concluded that some general
mechanism must underlie all of cognitive development.
Figure 8.2: Processing speed across childhood
ሁ An increase in processing speed and a more efficient
working memory account for the consistent,
steady decline in response time across a number of tasks.

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Source: Kail, R. (1991). Developmental Change in Speed of
Processing During Childhood and Adolescence. Psychological
Bulletin. Vol 109 No 490–501. Published by the American
Psychological Association. Reprinted with permission of the
American
Psychological Association.
For most tasks, speed of processing increases rapidly during
early childhood, slows down
during early adolescence, and improves only a little after the
age of 16 (Demetrioua, 2013;
Kail, 1991). Processing tasks involving language show a

slightly different pattern. When com-
pared to nonlanguage tasks, processing speed of language tasks
is faster at age 9, and then
levels off by age 14 (Kail & Miller, 2006). This finding makes
intuitive sense since the develop-
ment of language occurs relatively quickly compared to tasks
involving other developmental
areas like motor behavior.
F O C U S O N B E H A V I O R : F a c i l i t a t i n g C o g n
i t i o n
Problem solving in math needs to be explored like other types
of cognitive activities. For
example, at The Children’s Corner, when the children created
art they were free to think
about producing anything they wanted. These activities
“stretched” their conceptualiza-
tion about art and provided experiences necessary to move on to
the next cognitive stage
of creative development. That is, exploration increased their
creative abilities. If children
are directed in art activities, that there is a “correct” way to do
it, those who are not ready
to perform a particular skill will lose interest. Likewise,
children are more likely to lose
interest in thinking about math solutions if they are presented
with tasks that are too
tightly restricted.
Educators often teach math as if there is only one correct way to
do it, even if you can
obtain the answer another way. Follow the steps and you get
credit for each step, even
if the answer is wrong. Like children who become less creative
when they are directed
toward one “right” way in art, Piaget would say cognition and

math ability are compro-
mised when knowing specific steps is more important than
thinking about how to get the
right answer. If children can find the correct solution
independent of one directed process,
they are showing mastery and cognitive advancement, even if
all the steps are not written
down. In math, especially, students cannot consistently get
correct answers unless they
understand the underlying concept one way or another. When
teachers insist on exact,
step-by-step mathematical operations, there is little cognitive
advancement. Piaget would
say that thought promotes learning; limiting the way children
think about math limits cog-
nitive development.
As an educational therapist, I could often be thought of as a
glorified tutor. A former
eighth-grade client used a math textbook that often asked her to
explain answers, as do
many contemporary textbooks. At one point when she had
computed a correct answer, the
text prompt asked her: “How did you arrive at that result?”
She replied, “It just popped into my brain.”
If you were her teacher, explain how you would grade her
response.
Processing speed can also be promoted through education. One
study used a commercially
available computer application and randomly assigned 634
elementary school children to
either an experimental or a control group. The experimental

group participated in “brain
training” for 20 minutes a day over 9 weeks as part of their
normal school activities. Children
used a commercially available computer game that required
them to compute numbers men-
tally. On average, the experimental group gained 50% more in
processing speed compared
to the control group. Accuracy improved by 50%, as well
(Miller & Robertson, 2011). Other
Section 8.2Fuzzy Trace Theory
studies have demonstrated similar results among intellectually
diverse students (Duan, Shi,
& Zhou, 2010).
S E C T I O N R E V I E W
Outline the various components of the information-processing
approach to cognition.
According to this theory, how does cognitive development
occur?
8.2 Fuzzy Trace Theory
Charles Brainerd and Valerie Reyna argue that acquiring more
knowledge, employing more
strategies, and increasing processing speed is not all that is
responsible for memory improve-
ment during early and middle childhood. Their fuzzy trace
theory proposes that memory
is represented in two different ways: verbatim memory trace and
gist. Brainerd and Reyna
discovered that being able to recall exact content is not
necessary for reasoning—getting the
gist of the information is sufficient. In fact, they report that

accurate (verbatim) reconstruc-
tion of information remains independent of accuracy in
reasoning (Reyna & Brainerd, 1995).
Read this list of words. We will refer back
to it later: rest, tired, blanket, dream,
slumber, snore, yawn, bed, nap, wake.
Research indicates that preschoolers use relatively more
verbatim memory, but they begin to
rely more on gist as they enter elementary school. Preschoolers’
reliance on details interferes
with reasoning processes. But as children age, they rely more on
fuzzy traces, which improves
recall because it is more efficient. In the “fuzzy” gist version,
essential meaning is recorded
without getting distracted by details. In this way, gist does not
negatively affect the higher
mental processes involved in problem solving. For example, a
high school student browsing
through books for a summer reading assignment would likely
use gist representations. The
student would get the central theme of each book, including
characteristics like genre, setting,
or length. It is not initially necessary to store specific
information like names of characters.
When it is time to provide details for a book report, verbatim
information is used to prepare
for the reconstruction of details. Therefore, according to fuzzy
trace, verbatim and gist memo-
ries exist for different purposes (Brainerd & Reyna, 1993, 2001,
2004).
Research on false memories not only supports the existence of
dual memory processes, but
also helps explain why we maintain memories about events that

never happened. To dem-
onstrate, of the words you read in the list, do you recall the
word desk? Potato? Sleep? If you
are like most adolescents and adults, you will recall that desk
and potato were not on the list,
but sleep was. When younger children unknowingly give false
reports, they are more inclined
to report random, unrelated (verbatim) information, since they
do not record as much gist.
As children age, they are able to recall more items on a list, but
they are also able to find
more gist information like sleep. The development of gist
processes as children age, therefore,
Section 8.3Memory Development Through Childhood
contributes to improved recall but also leads to a greater
number of gist inaccuracies, like
thinking that the word sleep appeared in the list when, in fact, it
did not (Brainerd, Forrest,
Karibian, & Reyna, 2006; Brainerd, Holliday, & Reyna, 2004).
Explain how fuzzy trace theory expands on the information-
processing approach to cogni-
tive development.
8.3 Memory Development Through Childhood
As you have learned, the information-processing model views
memory as the ability to
encode, store, and retrieve information from the world. Infants
demonstrate that they have
this ability when they discriminate between familiar people and
other stimuli. Studies on

habituation of touch and vision and the auditory recognition of
books and music that are
introduced in utero further demonstrate the strength of infant
memories and their capacity
to learn. Infants may, as philosopher-psychologist William
James said, initially experience the
world as a “great blooming, buzzing confusion,” but they begin
to make sense of it right away.
Infant Memory and Learning
Infants who are only hours old can learn new behaviors. In one
study, newborns between 2
and 48 hours old were taught to associate sucking with pleasant
stroking of the head. Using
classical conditioning principles (see Module 1), Blass,
Ganchrow, and Steiner (1984) admin-
istered a sugar solution to infants immediately after stroking
their heads. The sugar solu-
tion was an unconditioned (naturally occurring) stimulus that
evoked puckering (the uncon-
ditioned response). When babies were stroked on the head
(conditioned stimulus) right
before delivery of the solution, they were able to associate the
stroking with the sugar. After
a number of pairings, the babies puckered when they were
stroked, even if no solution was
delivered. Stroking became a conditioned (learned) stimulus and
puckering a conditioned
(learned) response.
Infants quickly learn through operant conditioning, as well. In
an experimental condition,
infants will learn to suck faster on a nipple in order to hear
specific auditory stimuli (Tre-
hub & Chang, 1977). Sucking responses also show that neonates
have a remarkable ability

to control the production of novel sights, sounds, and human
voices (Floccia, Christophe, &
Bertoncini, 1997). Furthermore, in a classic demonstration of
operant learning, 2-month-old
infants were quite successful in learning how their body
movements could bring about a con-
sequence. Rovee-Collier (1999) placed mobiles over the cribs of
infants and attached a ribbon
that connected the mobile to their feet. It took only a few
minutes for most infants to learn
that by vigorously kicking they could make the mobile move,
demonstrating a memory for
learning that had previously been thought to be restricted to
older infants.
Rovee-Collier (1999) was also able to demonstrate that the 2-
month-old infants could in
some ways remember the tasks they had learned. Her research
partly dispelled previous
notions of infantile amnesia, or the absence of lasting memories
from infancy (recall the
prologue to this module). It had been thought that children
could not remember in the same
way that adults do until language acquisition allowed them to
encode and rehearse informa-
tion (Nelson, 1990). From a Piagetian model, infantile amnesia
would end when preopera-
tional thought begins, as children become capable of symbolic
representation. Although, for
the most part, adults and older children indeed do not remember
events that occurred earlier

than 3 years of age, infants do have memories. The infants in
the Rovee-Collier study were
able to remember events that occurred before they were able to
talk, but those “body” memo-
ries are still far removed from symbolic or language-based
recall that develops later.
Even though infants and young children remember prior
experiences, early memories begin
to fade with age and become increasingly unreliable (e.g., Bauer
& Larkina, 2014; Peter-
son, 2013). For instance, one study asked children aged 4 to 13
to recall three of their “first
memories.” At 2-year follow-ups, younger children were unable
to recall their previous first
memories. Even after cues were given from the initial interview,
the memories were still not
recalled. First memories had essentially changed. It was not
until the children were 10 years
old that they began to consistently recall the same “earliest”
memories (Peterson, Warren, &
Short, 2011). So although research suggests that infants do
remember, it is not clear whether
memories are part of an infant’s (or young child’s) permanent
memory trace. In addition, even
adults do not always remember events from 2, 4, or 6 years
earlier if they are not reviewed.
It may not be an age-related phenomenon at all, but instead may
be a reflection of how a par-
ticular experience has been remembered over time.
Imitation
An infant’s ability to imitate behavior is another early
indication of memory. Even neonates
are able to remember and copy a person’s features. In a series of
experiments, Andrew Melt-

zoff and Keith Moore famously demonstrated that neonates
could imitate facial expressions of
adults. In their first study, when the babies
were 12–21 days old, Meltzoff imitated vari-
ous facial expressions and found that the
neonates did indeed mimic his expressions
(Meltzoff & Moore, 1977). For some time
though, others were unable to replicate the
findings (e.g., McKenzie & Over, 1983). It was
suggested that the babies were so “old” that
they were not imitating behavior so much
as they had already learned the behavior
through typical mother-infant interaction.
In response to the criticism, Meltzoff and
Moore (1983) then tested infants who were
just 0–72 hours old, and used only two ges-
tures so that independent observers could
evaluate responses more exactly. Results again indicated that
infants were able to imitate
behaviors right from birth. More recently, Nagy (2006)
confirmed the findings of Meltzoff
and Moore and suggested that imitation is how infants first
begin to use language. There is a
“natural, interactive purpose” to imitation rather than its simply
being a response to stimu-
lation; imitation provides evidence that specific built-in
neuronal activity is responsible for
language (p. 228). Further studies by Nagy and her colleagues
later concluded that there are
Vaphotog/iStock/Thinkstock
ሁ Imitative behaviors may be an infant’s first
attempt at linguistic communication.

discrete imitative behaviors like tongue thrusting. They argue
that inconsistent findings by
other investigators are the result of poor research methodology
rather than an absence of
imitative behavior (Nagy, Pilling, Orvos, & Molnar, 2013).
F O C U S O N B E H A V I O R : M o d e l i n g
When psychologists and others address the importance of role
models, they are referring
to behavior that can be imitated. As children mature, it is
natural for them to imitate what
they hear and see. The combination of a developing brain,
enhanced cognition, and various
psychosocial factors lead children to be especially ripe to
imitate the behaviors of others—
both good and bad.
A client once asked me what type of consequences there should
be for her 6-year-old son
whom she found spanking his younger sister. When the boy’s
mother reprimanded him, the
boy responded, “But you do it!” Consistent with social learning
principles, the mother had
done an excellent job modeling behavior and her child was
simply imitating her.
This imitative behavior, including the beginnings of language,
continues the progression that
begins with the genetic foundations for physical growth.
Whereas genes transmit information
to direct lifelong development, imitation typifies how

environmental stimuli build upon those
biological foundations; it therefore epitomizes the interaction of
nature and nurture.
Provide evidence of learning and memory during infancy.
Memory Development in Early Childhood and Adolescence
Information-processing theorists generally agree that there are
developmental limitations
with memory capacity and sophistication. With algebra, for
instance, information-processing
theory would say that some children are not ready to tackle
more sophisticated math because
the “software” that is necessary to interpret the data is not yet
installed. To continue the anal-
ogy, sometimes a computer has a slow processor or cannot
handle all of the data that are
being inputted. People do not “crash” like a computer would,
but they will take a longer time
performing tasks and eventually give up when tasks are too
difficult. As children mature, their
capacity to process information grows—there are automatic
upgrades to larger hard drives
and more advanced processors.
Young children use schemas and only simple memory strategies.
For instance, 3 year olds
develop knowledge that hugs make Mommy feel better. But they
do not use specific strategies
that would help them remember more, even if they have been
taught how to do so (Miller
& Seier, 1994). Working memory is also less developed. This
limitation is reflected in the
measurement of children’s short-term memory for random
digits, which increases from two

digits at 2.5 years old to five digits at 7 years old, to an
adultlike seven digits by the age of 15
(Dempster, 1981).
During middle childhood, memory becomes more sophisticated
and is demonstrated by an
increased use of rehearsal strategies and organization
(Bjorklund & Douglas, 1997). For
example, teenagers understand the nuances of different
situations that may call for a hug.
They recognize the use for different study strategies like using
flash cards or organizing notes.
Although memory structures do not improve dramatically after
about age 15, adolescence
is a time when more elaborate encoding strategies are utilized
(Schwartz, 2010). Speed of
thinking increases steadily throughout early and middle
childhood, and schemas become
increasingly complex (Demetriou, Christou, Spanoudis, &
Platsidou, 2002; Kail, 2000, 2003).
Teenagers call upon these more sophisticated, abstract thinking
abilities when they plan and
assess consequences of multiple decisions. Therefore,
information-processing theory says
that greater sophistication is explained by maturational factors,
leading to more efficient pro-
cessing and sorting of incoming information (Atkins, Bunting,
Bolger, & Dougherty, 2012).
As you learned in Module 5, the delay in development of the
prefrontal cortex throughout

adolescence parallels this course.
Additional neuropsychological evidence supports the idea that
the brain becomes increas-
ingly sophisticated in a way that supports information-
processing theory. For instance, it
appears that increasing age leads to more efficient signal
conduction from neuron to neuron
(Mabbot, Noseworthy, Bouffet, Laughlin, & Rockel, 2006).
There is evidence that improved
speed of processing and overall cognitive development is
therefore a maturational process, as
specific axon connections lead to age-related gains in
performance. There is some question,
though, on direction of causality. Does increased brain growth
during early childhood and
adolescence lead to improved information processing, or does
experience with information
processing lead to increased neural connections?
Age by itself, however, is not always the prevailing factor in
memory performance. In one nota-
ble study, when chess pieces were placed in a meaningful
arrangement, 10- and 11-year-old
chess players had a much better memory for where pieces were
placed than did non-chess-
playing college students who had otherwise effective memories.
In contrast, when pieces
were arranged randomly, there was no difference in recall.
Experience with the structure of
chess (in chess, pieces are never assigned randomly) had a
profound effect on recall of chess
pieces, but not on other tests of memory (Chi, 1978; Schneider,
Gruber, Gold, & Opwis, 1993).
This finding points to the idea that experience facilitates
memory—if you have played chess,

you will remember something that may be meaningless to those
who have not. In addition to
providing well-developed schemas for how each piece moves,
chess skills can be thought of as
a series of interactive schemas: one for opening moves, one for
certain aggressive positions,
another for particular defensive positions, and so on.
Outline how memory changes throughout childhood. List
evidence that supports your
conclusions.
Section 8.4Attention
8.4 Attention
Mental representations like those employed while playing chess
also influence attention,
since players more easily notice stimuli that fit into existing
knowledge. For instance, you are
much more likely to pay attention to background noise in a
restaurant if you recognize a
familiar song. In this regard, attention refers to a state of
sustained concentration, where
awareness is focused. In chess, novice players might attend to
only a handful of board pieces
when an opponent employs a new strategy. By contrast,
experienced players pay attention to
a wider array of potential moves. Remember that for
environmental (sensory) information to
have a chance at being stored, it must first be attended to.
Therefore, attention is integral to
the information-processing system.

Identical environmental stimuli are sometimes taken in
differently depending on the person.
Sometimes differences are deliberate, but often it is a passive
activity. When we purposely
concentrate on specific stimuli while filtering out the rest, we
are engaging in selective atten-
tion. Youth athletes for instance will frequently report that they
do not “hear” parents yelling
encouragement (or otherwise!) from the sidelines. More
practically, when children hunt for
a solution to a problem, “distractors” (items that do not
contribute to the solution) will often
impede thought. A distractor might consist of irrelevant
information or an illogical solution.
A number of studies have demonstrated that the capacity to
selectively attend increases sig-
nificantly during the early elementary years. Children pay
increasing attention to relevant
information, but until the end of elementary school (age 11 or
so) they also pay more atten-
tion to irrelevant information. Attention performance
continues to improve throughout the high school years,
along with a tendency for decreased distractibility and
increased perceptual speed (Blumberg, Torenberg, &
Randall, 2005; Richards & Anderson, 2004; Trautmann
& Zepf, 2012; Wassenberg et al., 2008).
Children also get better at sustained attention, or maintained
focus over time (Fan et al.,
2009). This kind of attention is demonstrated when children
remain focused during an art
project, as they carefully copy letters and numbers, or while
listening to one stimulus (such
as a teacher) without simultaneously engaging in competing
tasks. It is likely that the capacity

for sustained attention is partly physiological and partly
learned. For instance, research has
found that parents who experience more stress and provide less
stimulation to their children
are more likely to have children who are more impulsive and
demonstrate less sustained
attention (Dilworth-Bart, Khurshid, & Vandell, 2007; Posner,
Rothbart, & Sheese, 2007; Razza,
Martin, & Brooks-Gunn, 2010). Furthermore, impairments in
sustained attention are often
associated with neuropsychiatric disorders such as
schizophrenia and with developmen-
tal disorders such as autism (see Module 10) and attention-
deficit/hyperactivity disorder
(Christakou et al., 2013; Corvin, Donohoe, Hargreaves,
Gallagher, & Gill, 2012).
Attention-Deficit/Hyperactivity Disorder (ADHD)
The issue of attention becomes particularly prominent in the
study of attention-deficit/
hyperactivity disorder (ADHD). (Some people still refer to
ADHD by its former diagnostic
name, attention deficit disorder or ADD. They are the same
condition.) Children diagnosed
Critical Thinking
Compare and contrast how a child might learn
to cook, from an information-processing view
and from Vygotsky’s perspective.
with ADHD have chronic, sustained problems with (1)
impulsivity (acting prematurely, or

without appropriate reflection), (2) inattention, or (3) excessive
motor activity (hyperactiv-
ity). But like many psychological disorders, an objective
medical diagnosis for ADHD does
not exist. Testing is entirely clinical (case study investigation)
and includes a fair amount of
interviews and surveys with parents, teachers, and the child.
Children with ADHD have dif-
ficulty staying focused on any one task and hence suffer
academically and sometimes socially
as well. One issue that remains controversial is whether or not
children with ADHD need to
show consistency in their behaviors. For example, if children
exhibit appropriate behaviors
and sustained attention at home, or while playing video games,
but not in school, is a diagno-
sis of ADHD appropriate (Van Cleave & Leslie, 2008)?
Cognitive deficits among those with ADHD are often reflected
in measures of attention, plan-
ning, and organization. Without proper planning and
organization, successful problem solv-
ing and goal-directed behavior is inefficient. These issues
become especially noticeable when
school assignments are consistently planned poorly or left
incomplete, even though there are
no deficits in ability. Therefore, some clinicians classify ADHD
within the realm of learning
disabilities, whereas others view it strictly as a behavioral
issue. The medical community is
similarly divided on whether ADHD is a neurological issue or a
mental disorder (Plichta &
Scheres, 2014).
Prevalence of ADHD
The proportion of U.S. children aged 4–17 who were diagnosed

with ADHD has increased by
an average of 5% each year over the recent decade, from 7.8%
in 2003, to 9.5% in 2007, to
11.0% in 2011 (Visser et al., 2014). In the United States, it is
diagnosed more than twice as
often in boys as in girls. However, teachers report a greater
number of problem behaviors
overall among boys, and boys are more likely to be identified as
having ADHD even when
they behave the same as girls. This bias may account
for at least part of the high male-female ratio of ADHD.
Because of the lack of standard diagnostic procedures,
there are legitimate controversies regarding its preva-
lence (Derks, Hudziak, & Boomsma, 2007; Plichta &
Scheres, 2014; Polanczyk et al., 2007).
To better understand the changes in prevalence, we can look at
cross-cultural differences and
historic trends. One meta-analysis of over 300 studies
encompassing 170,000 participants
found a worldwide prevalence for ADHD of 5.3% when the rate
in the United States was esti-
mated at 7.8%; six years later, the worldwide rate had increased
to 6.8%, but the increase was
less than half the rate of increase in the United States over the
same time period (see Figures
8.3a and 8.3b). Prevalence varies wildly between and within
different countries, from a low
of 1% to a high of 20%. It is unclear whether these differences
are a result of geographic and
cultural differences or of diagnostic practices. For example,
when subjective ratings are used,
children in Hong Kong have a higher rate of ADHD than do
children in England; when more
objective measures are used, they have a lower rate. These
differences are likely due to the

cultural emphases that each of the countries attaches to specific
behaviors (Polanczyk et al.,
2007; Wolraich et al., 2012).
Critical Thinking
What types of cultural variables might impact
the diagnosis of ADHD?
Figure 8.3a: Percentage of youth aged 4–17 ever diagnosed with
ADHD: National Survey of Children’s Health, 2003
≤5.0%
9.1–11.0%
5.1–7.0%
≥11.1%
7.1–9.0%
8.0
7.9
5.9
4.2
6.0
6.0

9.0
6.2
8.2
5.8
5.6
9.1
6.7
8.9
7.4
8.1
9.7
11.5
8.4
7.2
10.4
11.2
11.6
9.3
9.9
9.1

7.7
9.4 10.1
10.1
9.6
11.1
7.6
5.5
11.7
8.9
14.6
13.3
10.9 10.6 9.3
11.7
11.6
11.1
14.8
13.0
8.5
9.5
9.9
7.2

DC: 7.9
Source: Reprinted from Visser, S. N., Danielson, M. L., Bitsko,
R. H., Holbrook, J. R., Kogan, M. D., Ghandour, R. M., Perou
R. &
Blumberg, S. J. (2014). Trends in the parent-report of health
care provider-diagnosis and medication treatment for ADHD
disorder:
United States, 2003–2011. Journal of the American Academy of
Child and Adolescent Psychiatry, 53, 34–46, V. 53(1) page 5.
Used
by permission of Elsevier.
Figure 8.3b: Percentage of youth aged 4–17 ever diagnosed with
ADHD: National Survey of Children’s Health, 2011
ሁ Demographic shifts in diagnoses of ADHD include overall
increases in most states. What could
account for the changes?
14−15.9%
8.0–9.5%
11–13.9%
5.6–7.9%
9.6–10.9%
Source: Reprinted from Visser, S. N., Danielson, M. L., Bitsko,
R. H., Holbrook, J. R., Kogan, M. D., Ghandour, R. M., Perou
R. &
Blumberg, S. J. (2014). Trends in the parent-report of health
care provider-diagnosis and medication treatment for ADHD
disorder:

United States, 2003–2011. Journal of the American Academy of
Child and Adolescent Psychiatry, 53, 34–46, V. 53(1) Page 6.
Used
by permission of Elsevier.
It is important to remember that human traits are generally
assumed to follow a normal dis-
tribution. For that reason, about 5% of the population would be
expected to have ADHD, just
as 5% would be expected to have superior (i.e., gifted) attention
skills (see normal curve in
Figure 8.4). That averages out to about 1 student in a classroom
of 20. The question then
arises of whether attention that is less extreme than 1 out of 20
(perhaps 3 out of 20) repre-
sents simple “neurodiversity” along the normal curve or instead
denotes impairment (Bruch-
müller, Margraf, & Schneider, 2012; Plichta, & Scheres, 2014;
Smalley, 2008).
There is no doubt that ADHD is a problem for significant
numbers of children and adoles-
cents. But at what point along the (normal) continuum do we
say a child has ADHD and treat-
ment becomes indicated? As Figure 8.3a shows, the prevalence
of diagnosed ADHD has been
increasing. Like other developmental disorders (e.g., autism,
learning disabilities), it remains
to be seen if we are getting better at filtering children
who have ADHD or if we are casting a wider net. Cli-
nicians may simply be identifying greater proportions
of individuals at the lower end of the normal curve for

attention. The relatively large cultural and secular (over
time) changes in diagnoses confound researchers who
attempt to find consistent measures.
Figure 8.4: Extreme or normal?
ሁ By definition, most children have average attention skills.
Perhaps the maladaptive behaviors
marked by the low end of the normal curve (left side) are
creeping toward the middle, and children
who were previously considered to be exhibiting normal
behaviors are being identified as ADHD.
-3 -2 -1 0 +1 +2 +3
Standard deviations
Average
Previous ADHD diagnoses
restricted to most extreme
5% of behaviors
Represents the population of
children that are extremely
good at paying attention
Because there are no de�nitive criteria, perhaps
increased prevalence is due to less extreme
behavior being identi�ed as ADHD
Another possible confounding factor in ADHD diagnoses is a
child’s age relative to his or her
grade peers. This was a finding from a study of nearly one
million Canadian children that com-
pared the youngest and oldest students in kindergarten through

grade six. The data in Figures
8.5a and 8.5b clearly indicate that children who are younger
compared to their same-grade
peers are more likely to be diagnosed with ADHD and to
receive treatment (Morrow et al.,
2012). This evidence strongly suggests that some children are
treated for ADHD because they
are relatively less mature compared to their older but same-
grade peers. Perhaps teachers
sometimes base behavioral expectations on grade level rather
than on age and development.
Critical Thinking
What are some possible explanations for the
variation among differing regions in the United
States, as shown in Figures 8.3a and 8.3b?
Indeed, other research suggests that even licensed therapists
often opt for biased, personal
measures even when measures that are less subjective are
available (Bruchmüller et al., 2012).
Figure 8.5: Percentages of children aged 6–12 years receiving
diagnosis of, and pharmacologic treatment for, ADHD, by
month
of birth
ሁ For the Canadian schoolchildren in this study, the cutoff date
for entry into each grade is
December 31. Therefore, children born in January are the oldest
in their respective grades and
children born in December are the youngest. Figure 8.5a

indicates that age (as indicated by the month
of birth) is a strong predictor of ADHD diagnosis.
Consequently, those children who are relatively
young for their grades are more likely to receive medication to
control their behavior.
f08.05a_PSY104.ai
Month of birth
0
2.0
1.0
3.0
4.0
5.0
6.0
7.0
C
h
il
d
re
n
r

e
ce
iv
in
g
d
ia
g
n
o
si
s
fo
r
A
D
H
D
(
%
)
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
All children
Boys

Girls
f08.05b_PSY104.ai
Month of birth
0
2.0
1.0
3.0
4.0
5.0
6.0
7.0
8.0
C
h
il
d
re
n
r
e
ce

iv
in
g
t
re
a
tm
e
n
t
fo
r
A
D
H
D
(
%
)
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
Boys
Girls
Source: Morrow et al. (2012).

Causes of ADHD
Some researchers have concluded that ADHD has a biological
component since the concordance
rate is higher for monozygotic twins than for dizygotic twins.
And first-order relatives (parents
and siblings) of children diagnosed with ADHD have a two to
eight times higher risk of ADHD
(Akutagava-Martins, Salatino-Oliveira, Kieling, Rhode, & Hutz,
2013; Rasmussen et al., 2004).
Furthermore, distinctions in brain anatomy between those with
and without ADHD have often
been observed (e.g., Castellanos et al., 2002; Hart, Radua,
Nakao, Mataix-Cols, & Rubia, 2013).
There are also competing theories on whether ADHD is an
evolutionary adaptation or a
learned behavior. Remaining an active hunter-gatherer may have
had an evolutionary advan-
tage over sitting for 6 hours, as schoolchildren are expected to
do now. But critics of this
theory point to the substantial minority of cases—if ADHD is an
evolutionary adaptation,
why wouldn’t more children display it? Again, though, by
definition of the normal curve, only
a small percentage would ever be expected to display “extreme”
behavior.
Though no definitive causal factors have been identified, other
theories involve environmen-
tal factors like differences in parenting styles and societal
expectations (Banerjee, Middle-
ton, & Faraone, 2007; Hinshaw & Scheffler, 2014; Parens &

Johnston, 2009). One perspective
suggests that ADHD is partly learned due to demands of
everyday circumstances. As society
changes, children learn not to pay attention particularly well. If
televisions, phones, tablets,
computers, and other media are constant sources of stimuli,
children in a way may be trained
to divide their attention. If a television or computer is a
constant source of background enter-
tainment, as it is in many households, then individuals will
naturally attend only partially to
any one stimulus at a time (Christakis, Zimmerman,
DiGiuseppe, & McCarty, 2004; Landhuis,
Poulton, Welch, & Hancox, 2007; Williams & Taylor, 2006).
Finally, though contrary to popular media reports and parental
anecdotes, food additives
were ruled out long ago as a contributing factor to ADHD
(Kavale, & Forness, 1983).
ADHD Treatment
Regardless of whether ADHD is viewed as
normal variation or as a neurobiological dis-
order, it affects cultural norms of behavior.
The biological theory of ADHD is supported
by the successful, albeit paradoxical, use of
psychostimulant medications (e.g., Ritalin,
Dexedrine, Adderall). It could be that some
forms of hyperactivity are just a reaction to
inattention—a behavior that is indicative of
many people when they become impatient.
If a person is not attentive, then behavior
appears to be off-task and flighty. On the
other hand, if stimulants increase alertness,
then behavior will be more on-task. There-
fore, the effect of stimulants is not very dif-

ferent from when adults use coffee and high
school and college students take illicit sub-
stances to help them concentrate.
Chris Gallagher/Science Source/Getty Images
ሁ Prescriptions for psychostimulant medications
like Adderall (shown) have risen steadily,
alongside the increasingly common diagnosis
of ADHD.
Section 8.5Executive Function
Interestingly, although stimulant medication increases attention,
substantial evidence indi-
cates that a corresponding increase in cognitive performance
does not occur (e.g., Advokat
& Vinci, 2012; Bidwell, McClernon, & Kollins, 2011; Smith &
Farah, 2011). Nevertheless, use
of medication has followed the same pattern of growth as
ADHD diagnoses. If increased aca-
demic performance among children with ADHD is the goal of
treatment, then stimulant medi-
cation may not be an appropriate response.
Either as an alternative to or in conjunction with medication,
behavior therapy is usually
indicated for children with ADHD. Behavior therapy focuses on
changing specific, undesirable
behaviors such as being inattentive or distracted. Children are
systematically rewarded for on-
task behavior. For instance, children may earn checkmarks for
working through 10 minutes of
homework, completing a nighttime routine, or remaining seated

in a classroom. Checkmarks
can be exchanged for privileges or material rewards. By
identifying specific behaviors, it is
hoped that children will eventually gain conscious control over
unwanted behaviors. This
kind of self-control is one of the processes of executive
function, a focus of the next section.
Define selective attention and sustained attention. Discuss
contemporary issues in the
diagnosis and treatment of ADHD.
8.5 Executive Function
As memory expands and attention strategies improve during
childhood, the processing of
information becomes more efficient. In addition, we begin to
self-monitor the effectiveness
of our thinking skills. That is, we assess how and when certain
strategies might be used and
control which responses might be best for attaining a goal.
Executive function is this inten-
tional part of thinking. It oversees and directs the flow of
information by guiding attention
and organizing memory.
Evidence indicates both biological and learned factors are
involved in the development of
executive functions. Frontal brain activity during infancy and
positive maternal emotions pre-
dict higher-order executive skills beginning in preschool
(Kraybill & Bell, 2012). Other stud-
ies show that growth in the prefrontal cortex of the brain
beginning at around age 3 coincides
with increased executive function. Development is especially
noticeable during early child-

hood, but there are substantial changes in adolescence and
beyond, as well (Best, Miller, &
Jones, 2009; Moriguchi & Hiraki, 2013).
One study demonstrated developmental differences in executive
processes when participants
of different ages were given cash incentives to remember words.
Some words were worth
1-cent and others 10-cents if they were recalled successfully.
Fifth-grade children rehearsed
and recalled equal numbers of 1-cent and 10-cent words;
adolescents and college students
rehearsed more 10-cent words, and subsequently recalled more
as well. The older students
understood the consequences of directed, concentrated effort
better than the fifth graders
(Cuvo, 1974).
Section 8.5Executive Function
In general, executive processes allow children to contemplate
choices, learn self-regulation
(control over emotions and behavior), and perform more
sophisticated memory tasks, includ-
ing formulating solutions to problems before they are
implemented. An advanced part of self-
regulation is response inhibition, which is often referred to as
impulse control (Zheng, Oka,
Bokura, & Yamaguchi, 2008). As children become more
thoughtful, their responses become
more informed, including the potential for reinforcement or
punishment. In school, for
instance, response inhibition occurs when students reflect on a
question posed during a

teacher’s instruction instead of responding immediately. The
increased conscious effort
inhibits automatic responses overall and leads to more strategic
planning (Luna, Garver,
Urban, Lazar, & Sweeney, 2004; Parault & Schwanenflugel,
2000).
Another core factor in executive process is cognitive flexibility.
It is the ability to shift focus
between multiple ideas or tasks, and it allows children to
analyze how to distribute a limited
amount of time to complete a task. Cognitive flexibility
is commonly measured using tests that require children
to sort by multiple classifications. For instance, they
might be asked to sort cards by both color and type of
object. Younger children have difficulty switching focus
between multiple concepts. Throughout childhood,
they gradually adjust their thinking to better accommo-
date these kinds of complex cognitive mental processes
(Best et al., 2009).
Metacognition
Executive control is also observed by the growth of
metacognition. Metacognition can be
described as “thinking about thinking,” or having awareness
about one’s own cognitive pro-
cesses (Flavell, 1976). It includes knowledge about storing
information, strategizing, planning, and problem solving.
Hypothesizing about different outcomes builds metacogni-
tion as thinking begets more sophisticated thinking. Many
educational practices today try to promote metacognition.
Examples include the many reflective questions that are
often asked in math and writing exercises (e.g., “How did
you come to that conclusion?”). Although metacognition is
evident earlier, there is a strong surge in its development
during adolescence. It becomes displayed when students

are able to more successfully plan and navigate the imple-
mentation of multiple activities, including homework, social
activities, and work (Weil et al., 2013).
When children are immersed in practices that engage meta-
cognition, they will get better at it. For instance, when a 3
year old asks constantly, “Why?”, the savvy adult can say,
“Why do you think?” In this way children are involved in
their own thinking. Children of all ages can be asked to
find their own solutions to conflicts with other children;
they can be asked to make their own questions regarding
schoolwork. When adolescents edit and re-edit essays, they
have to think about their knowledge process; sometimes
Critical Thinking
Describe how students use executive function to
complete homework that is assigned for multiple
subjects. How do you think the process differs
between elementary school students and high
school students?
Hybrid Images/Cultura/Getty Images
ሁ Engaging children in activities
that encourage them to “think
about thinking” will promote
metacognition.
Section 8.6Cognitive Development in the Classroom
students will work a math problem backwards (beginning with
the answer) in order to figure
out the process. The constant planning and evaluating represent
the metacognitive process.

Define self-regulation, response inhibition, cognitive f
lexibility, and metacognition. Explain
how they are related to the umbrella concept of executive
function.
8.6 Cognitive Development in the Classroom
Of the three cognitive theories presented, Piaget’s has perhaps
had the most profound impact
on schooling in the United States, especially early childhood
education. Skilled preschool edu-
cators acknowledge the special nature of young learners and
adjust activities accordingly. The
focus on the developmental stages of young children is an
important change from past gen-
erations, when children were often thought of as little adults.
Piagetian theory also states that
developmental stages are mostly fixed and dependent on a
natural course of maturation,
which varies somewhat for each child. Yet, the recently adopted
common core standards do
not particularly embrace individual exploration, nor do they
always take into account indi-
vidual differences.
Instead of depending on maturational changes,
information-processing proponents theorize that past
successes will gradually lead to more challenging activi-
ties. Give children enough time and instruction, and we
can expect the vast majority of them to perform. Matu-
ration is less of an issue than is incremental prepara-
tion. Information-processing and sociocultural theorists
acknowledge the significance of maturation but disagree
with Piaget about the predetermined qualitative change
that differentiates one stage from another.

While a Piagetian perspective has remained prominent
throughout education, the
information-processing and sociocultural perspectives have
become more highly integrated
within contemporary elementary and secondary school
classrooms. Children regularly
engage in social and contextual activities that include working
in small groups, cooperative
learning, peer tutoring, and plenty of scaffolding.
A meta-analysis of 36 relevant studies found broad benefits for
both learners and “experts”
when peer scaffolding is used (Ginsburg-Block, Rohrbeck, &
Fantuzzo, 2006). Cooperative
learning activities provide advantages in academics, behavior,
and self-concept. Interestingly,
although causal relationships cannot be established with the
limited research available so
far, more positive learning outcomes exist when boys and girls
are grouped separately. These
potential differences certainly warrant further study, especially
since it does not appear that
peer tutoring sacrifices the academic needs of more advanced
students. An important finding
Critical Thinking
If scientific evidence were conclusive that
Vygotsky was right about the social context of
learning, what changes should be made to cur-
rent educational structures? Conversely, what
if evidence were found that conclusively sup-
ported Piagetian principles? What if evidence
supported information processing?

Summary and Resources
is that gains extend beyond academics and include positive
psychosocial outcomes as well,
especially for lower-income students (Ginsburg-Block et al.,
2006; Hattie, 2008).
A concern of collaborative methods is the potential increase in
academic dishonesty and
imbalanced workloads if workgroups become a classroom norm
(Sutherland-Smith, 2013).
As most college students are aware, when students work
together there is a tendency for
some group members to do less than their share of work and for
others to make up for the
shortcomings. Learning outcomes may not be as robust when
workload distribution is the
responsibility of the group instead of individuals. Even so, the
process of working together—
both when it is equitable and when it is not—prepares students
for future interactions in
social encounters and work.
Summarize how cognitive theory is applied to contemporary
education.
Wrapping Up and Moving On
According to information-processing views, cognitive
development occurs within a feedback
loop. We attend to information, and then it is processed in a
way that it can be stored. Infor-
mation is then compared with other memories and processed for
output. Therefore, rather
than the stage-like changes described by Piaget, information

processing is clearly concerned
with incremental changes in thinking ability. Advancements in
memory for language and
numbers are examples of these small changes. Greater success
in cognitive tasks, like formal
schooling, is reflected in the gradual sophistication of
perception, memory, and processing of
stored information, overseen by an executive function. Next, we
explore how language fits in
to the various theories of cognitive development.
• The information-processing approach is a third major
perspective in the study of
cognitive development. Children take in, store, and process
information for output in
much the same way that a computer does.
• In information-processing theory, there are three stores of
memory: sensory,
short term, and long term. The three types of stores create a
system that explains
how children process, pay attention to, and remember
information from the
environment.
• Working memory is a newer term that acknowledges the
multifaceted nature of
short-term memory. Working memory includes information from
a number of
senses that work within a feedback loop with long-term
memory.
• Part of the development in cognition is related to
increased speed of processing.

There are steady increases in processing speed throughout
childhood.
• Fuzzy trace theory proposes that preschoolers use
relatively more verbatim memory
but begin to rely on more gist as they enter elementary school.
As children age they
rely more on fuzzy traces, which improves recall but also
contributes to the phenom-
enon of false memories.
• Contrary to what was once thought, it has been
demonstrated that infants do indeed
have memories. In the long term, it is unclear what happens to
information that was
once encoded during infancy, but even very young babies
clearly remember what
they have learned. Even during the first postpartum days,
infants can remember
facial expressions.
• The study of attention is an important component of
information-processing theory.
We need to understand how and when children attend to
stimulation in order to
understand initial cognitive processes. Psychologists usually
differentiate between
selective attention and sustained attention.
• Among developmentalists, medical doctors,
neuropsychologists, and others who

study children and attention, there is no clear consensus about
what defines
attention-deficit/hyperactivity disorder (ADHD). In recent
years, the rate of ADHD
diagnoses has shown marked increase, both in the United States
and throughout the
world.
• Biology likely accounts for at least part of the reason that
some children show inat-
tentive behaviors. Research also suggests that learning may play
a role.
• Psychostimulant medication promotes positive behavior,
but it may not affect aca-
demic performance.
• More sophisticated cognition includes executive function.
These self-conscious pro-
cesses include self-regulation, response inhibition, and
cognitive flexibility. Meta-
cognition is the process of “thinking about thinking,” using
thoughtful strategies for
planning and strategizing.
• The theories of cognitive development are often applied in
contemporary education.
We have seen changes in the way children are regarded in the
learning process, the
roles of teachers and classroom peers, and the emergence of
collaborative learning
processes.
Key Terms
ADHD See attention-deficit hyperactivity
disorder.

attention-deficit/hyperactivity disorder
(ADHD) A developmental disorder char-
acterized by impulsivity, inattention, or
hyperactivity.
behavior therapy Psychotherapeutic
intervention that focuses on systematically
changing specific behaviors.
cognitive flexibility The ability to shift
focus between multiple ideas or tasks.
elaboration The process of enriching
information and making it more meaningful,
resulting in stronger connections to long-
term stores.
executive function The conscious part of
the mind that oversees and directs the flow
of information.
fuzzy trace theory A theory of cognition
that accounts for changes in reasoning by
considering that memories are encoded in
one of two ways: verbatim or gist.
infantile amnesia The absence of lasting
memories from infancy.
information-processing theory A theory
that compares human cognitive develop-
ment to a computer in the way both take in,
store, and use information.

long-term memory Relatively permanent
storage of memory. Contrast with short-term,
or temporary, memory.
metacognition The awareness of one’s own
thinking process.
organization Constructing a pattern of
information to be remembered.
psychostimulant medications Central
nervous system stimulants that are often
prescribed for those diagnosed with
attention-deficit/hyperactivity disorder.
rehearsal The act of repeating information
in order to remember it.
response inhibition The self-regulatory
function of impulse control.
selective attention The process of concen-
trating on specific stimuli while filtering out
the rest.
self-regulation Regulation of emotions
and behaviors that is guided by metacogni-
tive processes; evaluating outcomes before
acting.
sensory memory Brief impressions that
include information gathered through the
senses.

short-term memory Temporary memory
that holds five to nine pieces of information
(sometimes referred to as 7 ± 2) for up to 30
seconds.
sustained attention Maintained atten-
tional focus over time.
stage model of memory The traditional
model of memory that includes sensory
memory, short-term memory, and long-term
memory.
working memory The part of memory that
actively stores and processes information.
Web Resources
See links below for additional information on topics discussed
in the chapter.
Adderall
http://www.ncbi.nlm.nih.gov/pubmedhealth/PMHT0008973/
Behavior Therapy
http://www.wisegeek.com/what-is-behavior-therapy.htm
Common Core
http://www.corestandards.org/
Dexedrine

Ritalin
William James
http://plato.stanford.edu/entries/james/
http://www.wisegeek.com/what-is-behavior-therapy.htm
http://www.corestandards.org/
http://plato.stanford.edu/entries/james/
5Physical Development
Novastock/Photolibrary/Getty Images
Learning Objectives
After completing this module, you should be able to:
ሁ Describe changes in body and brain structure from birth
through adolescence.
ሁ Detail the process of nerve function and how neurons
transmit signals.
ሁ Provide behavioral examples that demonstrate how the brain
is organized.
ሁ Outline major milestones in motor development.

ሁ Clarify important issues related to toilet training.
ሁ Identify warning signs of various physical disabilities that
may first appear in early childhood.
ሁ Describe physical changes that take place during puberty,
including historical and cultural trends,
and the differential impact on males and females.
Section 5.1General Patterns of Growth
Prologue
Among infants and young children, tremendous changes occur
in every domain of develop-
ment. However, none are more apparent than the physical
changes. When new parents talk
about their baby’s growth, the first thing that usually comes to
mind is height, weight, and
motor activity. Imaging devices now allow us to track
coinciding changes in brain tissue. We
can conclusively differentiate between a male brain and a
female brain—even at birth. Though
we are far from making predictions about physical development
based on brain scans, we can
predict some effects of deprivation. For instance, malnutrition
can have far-reaching conse-
quences, extending into physical, cognitive, and even
psychosocial domains.
Quite unlike other animal species, human infants are virtually
helpless at birth. Babies can
eat only if a nipple is provided; they cannot move objects out of
the way or closer; and for the
most part they cannot manipulate the physical structure of the
environment. Initially they

do not even have the muscle strength needed to hold up their
heads. It is only with adult
assistance that infants can survive and eventually optimize
growth. Technology and scien-
tific advancement have allowed us to better understand how we
transition from completely
dependent beings into adolescents who are perfectly capable of
walking away from their par-
ents. This module focuses on those physical developments.
5.1 General Patterns of Growth
Though parents do not often notice, the heads of infants are
disproportionately large com-
pared to the rest of their bodies. On their way to adult
proportions, the torso and limbs grow
faster than the head. This pattern of growth is an example of
directionality, one of the gen-
eral principles of human growth. In this case, the direction is
cephalocaudal, literally meaning “head to tail.” At birth not
only is the head more developed physically than the rest of
the body, but also vision and hearing precede growth of the
limbs. That is, babies begin to focus their eyes on what they
hear well before they begin walking or perform coordinated
hand movements.
Physical growth also occurs in a proximodistal pattern—
from the inside out. In the prenatal environment, this prin-
ciple is displayed as the spinal cord develops before fingers
and toes. The pattern continues after birth, as infants learn
to move their torsos before their extremities. Babies learn
to use their arms to maintain balance before they use their
hands and fingers to reach for an object.
Another general principle of physical growth is indepen-
dence of systems. This principle suggests that different

body systems grow and mature independently. As seen in
Figure 5.1, the nervous system matures quite rapidly begin-
ning in childhood, whereas the pattern of growth of overall
stature (body size) is a bit more even. And neither the tim-
ing nor the rate of sexual maturation mirrors that of either
the nervous system or stature.
David De Lossy/Photodisc/Thinkstock
ሁ Physical development
depends on maturation but still
involves interchange with the
environment.
Section 5.2Neuropsychology and Brain Development
Figure 5.1: Independence of systems
ሁ This graph illustrates that different body systems grow and
mature independently.
S
iz
e
in
t
er
m
s
o
f

p
er
ce
n
ta
g
e
o
f
to
ta
l g
ro
w
th
Age in years
0
20
Birth 2 4 6 8 10 12 14 16 18 20
40
60

80
100
120
140
160
180
200
Lymph tissue Brain and head
General growth curveGenitals
Source: Tanner, J. M. (1962) Growth At Adolescence, 2nd ed.,
Oxford: Blackwell Scientific Publications.
Provide examples that demonstrate the three general patterns of
growth.
5.2 Neuropsychology and Brain Development
As the cephalocaudal principle implies, the brain is closer to its
adult size than is any other
physical structure in the newborn human. Embryonic cells have
been transformed into a
sophisticated machine with all kinds of specialized processes.
The brain integrates informa-
tion from the environment and from the body’s multiple
systems. Children learn to walk, run,
and hop, leading to more complex physical feats like executing
studied gymnastics moves,

diving into a pool, or high jumping. These changes necessarily
begin with the brain and ner-
vous system. In this section, we explore these developments as
they relate to early physical
growth. We look first at the brain from a cellular level, and then
explore how the different
parts of the brain communicate with each other and the rest of
the body.
Neurons and Synaptic Development
There are at least 100 billion neurons, or nerve cells, in the
human brain. The neuron is the
basic element of the nervous system, as displayed in Figure 5.2.
Unlike other cells, neurons
communicate with each other in an elaborate relay system.
Information is first transmitted by
dendrites, structures that receive incoming signals. The message
then travels to the soma
(cell body). If the signal is to be continued, it travels via the
axon. The transmission may be
sped up by a myelin sheath, which eventually covers most of the
long, threadlike axons.
The neuron transmits the impulse to the
next neuron (or gland or muscle fiber) at
bulblike structures called terminal but-
tons. This transmission is achieved with-
out the neurons actually touching each
other. Instead, they form a synapse, or gap
between the sending and receiving neurons.
Every terminal button contains vesicles that

release chemicals called neurotransmit-
ters into the synapse. Depending on a num-
ber of factors, especially the concentration
of the specific neurotransmitter, the receiv-
ing neuron will either carry the message
forward or not. That is why sometimes peo-
ple can perceive a faint sound or a distant
light while at other times they cannot. The
chemical messengers have either reached a particular threshold
to transmit the sensory mes-
sage or not.
Figure 5.2: The neuron
ሁ The neuron is the basic element of the nervous system.
Information is first received by the
dendrites. The message travels to the cell body (soma). If the
message is to be continued, it travels
to the axon, where transmission may be sped up by the myelin
sheath, which covers many axons. At
the terminals, neurotransmitters are released into the synapse
between the sending and receiving
neurons.
Dendrite
Nucleus
Myelin
sheath
Terminals
Axon

Courtesy of Ron Mossler
ሁ Every potential visual, auditory, and tactile
stimulus sparks production of synaptic growth.
It was previously thought that we do not manufacture neurons
after we are born. How-
ever, recent research has confirmed that some sensory neurons
continue to regenerate
throughout the lifespan, and there are even indications of the
growth of some neurons
related to cognition. For instance, evidence indicates that neural
growth can be promoted
in the hippocampus, possibly slowing or reversing the effects of
memory loss associated
with dementia (Frielingsdorf, Simpson, Thala, & Pizzo, 2007;
Ho, Hooker, Sahay, Holt, &
Roffman, 2013).
Timing
Although the infant brain is proportionately closer to adult size
than are other body parts, it
weighs only about 13 ounces (370 grams), whereas an adult
brain weighs a bit more than 3
pounds (1,400 grams). The brain grows faster by weight than
any other body part. By the time
children are 2 years old, the brain is about 75% of the size and
weight of an adult brain. Put
another way, it is quite apparent that evolution has provided the
brain a “head start,” relative
to the rest of the body, in order to direct development.

Though the quantity of neurons remains relatively constant after
birth, the number of postna-
tal synaptic connections multiplies tremendously. Therefore, the
rapid increase in mass is due
to the axons and dendrites that grow to form new synapses in
response to stimuli. As a new
object is seen, a new sound is heard, or a new movement is
made, neurons branch and extend
their reach to other neurons and form new synapses. By the time
a child is 2 years old, some
cells may have up to 10,000 connections (Sadava, Hills, Heller,
& Berenbaum, 2009). In total,
those 100 billion neurons establish trillions of synapses forming
a complex yet integrated
communication network. When brain development peaks, as
many as 250,000 synapses are
created every minute.
For every potential stimulus in a person’s environment, there is
massive overproduction of
synapses during infancy. As new synapses grow, continued
stimulation of those connections
is key to their survival, maintaining a principle of “use it or
lose it.” This physical develop-
ment serves as a biological foundation for learning. But as
discussed earlier, with regard to
sensitive periods and independence of systems, all development
does not happen at the same
time or at the same rate. The same is true for brain
development, as shown in Figure 5.3.
Synapses in the visual cortex that are responsible for sight reach
peak production between
the 4th and 8th postnatal months; synapses in the more
sophisticated reasoning centers of
the prefrontal cortex do not peak until the 15th month. Notice
also that growth in language

areas peaks just before infants begin to speak. Therefore, the
rate and timing of synapse and
dendrite formation are important to understanding development
(Tierney & Nelson, 2009;
Twardosz, 2012).
Figure 5.3: Timing of synapse and dendrite formation
ሁ The rate and timing of synapse and dendrite formation vary
by age and are important to
understanding development. Notice, for example, that growth in
language areas peaks just before
infants begin to speak.
Age in yearsAge in months
0 1 2 3-3 -2 -1 4 5 6 7 8 9 10 11 122 3 4 5 6 7 8 9 10 15 1613
1411 12 1
Visual/auditory cortex (seeing and hearing)
Prefrontal cortex (higher cognitive functions)
Angular gyrus/Broca’s area (language areas/speech production)
R
el
at
iv
e
g

ro
w
th
Source: From R. A. Thompson and C. A. Nelson,
“Developmental science and the media: Early brain
development,” American
Psychologist, 56(1): 5–15. Copyright © 2001. Reprinted by
permission of the American Psychological Association.
The timing of brain development is important to understanding
its processes. When peak
development for a particular process occurs at a later age, the
brain remains plastic (more
adaptable) for a longer time. That is, if a part of the brain is
damaged before it has begun
its major synaptic growth, other cells can take the place of those
that are damaged. This
ability to adapt due to experience (whether due to damage or
ordinary behavior) is called
neuroplasticity.
Pruning
To facilitate neuroplasticity, the brain goes through a process of
overproduction of synapses
(as shown in Figure 5.4) before engaging in a process of
reduction. Although synaptic devel-
opment unfolds by genetic programming (maturation),
experience dictates which synapses
receive the most stimulation and are likely to remain.
Conversely, synapses that are not stimu-
lated to a particular threshold will go through a natural
reduction process called synaptic
pruning. Neurons that are less used—and therefore less

necessary—are eliminated. This
favoritism allows neurons that receive the most stimulation—
and thus are interpreted as the
most important—to be given space to grow more elaborate
connections.
Figure 5.4: Neuron growth and pruning
ሁ According to scientists, the brain overproduces synapses
during early childhood and then goes
through a pruning process later. Neurons that receive the most
stimulation are favored over those
that receive less stimulation.
Source: From Reynolds and Fletcher-Janzen, Eds, Handbook of
Clinical Child Neuropsychology, Figure 4, p. 25. Copyright ©
2009.
Reprinted with kind permission from Springer Science+Business
Media B.V.
Though paradoxical, in this way development of the nervous
system actually profits most
effectively from the purging of cells. In a manner that is similar
to synapse production, timing
of pruning also varies by different brain areas. In some
instances, pruning of specific areas
of the brain is not complete until adolescence or beyond
(Selemon, 2013). This process of
overproduction and pruning continues while the mind remains
adaptive to unique individual
experiences.

Myelination
In addition to the growth of synapses, the axons of neurons get
coated with myelin (refer
back to Figure 5.2), which represents the last stage of
sophistication of brain development.
Myelination, or the process of coating neurons with myelin, is
responsible for speeding up the
transmission of impulses. This is an important activity, as faster
neural processing is neces-
sary to move faster physically and to think in more complex
ways. Like other aspects of brain
development, myelination occurs in a manner predetermined by
maturational processes and
follows the same patterns described previously with regard to
synaptic growth and pruning
(Staudt et al., 1993; Tierney & Nelson, 2009).
The myelination of sensory and motor neurons that is essential
to early physical development
is mostly complete by 40 months, whereas the neurons that are
responsible for higher brain
functions like reasoning and complex decision making are not
myelinated until early adult-
hood. Compared to infants with richer experiences, those raised
in more limited environ-
ments indicative of low socioeconomic status show overall brain
differences in both structure
and weight (Lawson, Duda, Avants, Wu, & Farah, 2013). That
is, when experiences are limited,
it makes sense that brain growth is similarly restricted. Not
surprisingly, poor nutrition leads
to less myelin development as well as a general reduction in
brain size, though early treat-
ment can often reverse these negative effects (Atalabi, Lagunju,
Tongo, & Akinyinka, 2010;
El-Sherif, Babrs, & Ismail, 2012; Hazin, Alves, & Rodrigues

Falbo, 2007).
Section 5.3Increased Complexity in Neural Organization
Diagram the transmission of a signal from one neuron to
another.
5.3 Increased Complexity in Neural Organization
Although maturation processes dictate the course of peak brain
development, neurons con-
tinue to migrate and form new synapses when children learn
how to throw a ball, experience
what it is like to get one’s feelings hurt, and acquire the skill
needed to graph a geometric
equation. Developing brain processes become more apparent
when we see the effects of lat-
eralization and sex and gender differences. We explore these
processes in this section.
Brain Development in Later Childhood
The sophistication of brain growth throughout childhood is
evident in the growth patterns
illustrated in Figure 5.5. These images show extensive mapping
of cortical development
among individuals between 5 and 20 years of age. Brain scans
were obtained every 2 years,
and a dynamic map of development was constructed (Gogtay et
al., 2004).
Figure 5.5: Brain development through childhood and
adolescence
ሁ In an extensive project to map brain development, scientists
found that axons (white matter)

continued to replace cell bodies (gray matter) well into
adolescence.
Source: Image courtesy of Paul Thompson (USC) and the
NIMH.
As you can see from Figure 5.5, well into adolescence axons
continue to grow and expand
connections, supplanting cell bodies in the process. Basic
sensory and motor functions
mature first, coinciding with the basic learning outcomes of
infancy. Speech and language
areas come next; areas in the frontal lobe (one of four major
brain divisions) that are related
to judgment and the inhibition of impulses are last to develop.
Because these centers are
not mature until after adolescence, some researchers have
speculated that immature fron-
tal lobe development is linked to the risky behaviors that are
indicative of adolescence. This
possibility also raises questions about public policy and whether
adolescents should be
considered more like children or more like adults with regard to
forensic examinations,
driving, and other adultlike responsibilities. (See especially
Bonnie & Scott, 2013, Stein-
berg, 2013, and Steinberg & Scott, 2003). For instance, if
judgment among teens is develop-
mentally compromised, then there are implications for holding
them completely account-
able for crimes.

Adolescence also marks a second wave of overproduction of
synapses and neural pruning
(Hedman, van Haren, Schnack, Kahn, & Hulshoff Pol, 2012).
The architecture of the prefron-
tal cortex begins to change rapidly during this time and may
give rise to specific behaviors
that are associated with adolescence (Blakemore &
Choudhury, 2006). These behavioral changes include
improved cognitive control over activities like plan-
ning, attention, and other goal-directed behavior. On
the other hand, teenagers perform relatively poorly
on tests of emotional control. They are more reactive
rather than reflective. This behavior is consistent with
their brains performing more functions in the primitive
parts of the brain. It is during later adolescence that
emotional processing shifts to the frontal lobes, con-
tributing to improved reasoning, judgment, and control
over hypothesized outcomes (Zimmer, 2011).
Lateralization
The brain shows further sophistication in its contralateral
(“other side”) organization pat-
tern. That is, input from the right side of the body is transmitted
to the left half, or hemi-
sphere, of the brain; input from the left side of the body is
received in the right hemisphere, as
depicted in Figure 5.6. For nearly everyone, each hemisphere
specializes in specific functions.
For example, most people have language centers located in the
left half of the brain. The left
hemisphere processes tasks like thinking, reading, and speaking.
Right hemisphere special-
izations usually include emotional expression, music, and
visual-spatial relationships used in
geometry, art, and finding directions. This specialization is

called lateralization.
Critical Thinking
Should the knowledge that the reasoning cen-
ters of adolescents are not fully mature have
an impact on how they are treated when they
commit crimes? For further information and dis-
cussion, see Aronson (2007), Beckman (2004),
Bonnie and Scott (2013), Steinberg (2013),
and the case against Christopher Simmons
(International Justice Project, 2005).
Figure 5.6: Brain lateralization
ሁ Even though humans process a great deal of sensory
information in a contralateral fashion, other
functions, like language and emotion, are lateralized.
Left hand Right hand
Left hemisphere Right hemisphere
Lateralization
(language and emotion)
Contralateral control
(sensory information)
Lateralization is also demonstrated when we show a preference
for using either the right
or the left hand, called handedness. Across cultures and
continents, the proportion of right-

handedness remains at about 90% (Vuoksimaa, Koskenvuo,
Rose, & Kaprio, 2009). Though
some children exhibit handedness as soon as 12 months old,
except for the 3% of children
who are ambidextrous (showing equal preference for use of
either hand), dominance usu-
ally becomes well established by kindergarten (Hinojosa, Sheu,
& Michel, 2003).
Ninety-five percent of right-handed people show typical
lateralization patterns; they have
language centers located in the left hemisphere of the brain.
Among left-handers, though,
only about 75% are dominant for language in the left
hemisphere. It has been suggested that
differences in typical patterns of lateralization may lead to
greater engagement of both brain
hemispheres and result in cognitive flexibility (Beratis,
Rabavilas, Kyprianou, Papadimitriou,
& Papageorgiou, 2013; Szaflarski et al., 2002). Left-handedness
is often found to be more
common among those who have jobs related to visual-spatial
(right hemisphere) processing,
and other evidence indicates that more left-handed children
have language-based (left hemi-
sphere) learning problems. As yet, evidence for any consistent
overall patterns in intelligence
or academics as they relate to handedness appears to be lacking.
The process of lateralization is apparent even at birth. Verbal
stimuli are usually more respon-
sive in the left hemisphere, whereas emotion is associated with
more right-brain activity
(Dubois et al., 2009; Montirosso, Cozzi, Tronick, & Borgatti,
2012). Even so, both hemispheres
of the brain are usually engaged. They work in tandem to

understand experiences and to
respond. Consequently, there is no such thing as a “right-brain”
or “left-brain” person. The
interpretation of emotions that occurs in the left hemisphere
needs language areas in the
right hemisphere to understand the subtleties of how to act;
verbal conversations include
a fair amount of imagery and other right-brain functions.
Therefore, the hemispheres of the
brain should be thought of as interdependent.
Neuroplasticity remains important in lateralization as well.
When young children suffer dam-
age to one hemisphere of the brain, depending on the age at
which the trauma occurs, the
other side is often able to compensate. Among others, we can
reorganize large areas of the
brain related to language development, memory, emotions, and
vision (Cramer et al., 2011).
Sex and Gender Differences in Brain Development
A controversial topic involves findings that there are distinct
patterns and organization of
growth in the brains of males and females. In addition, girls
consistently perform better at
left-brain-dominated language tasks and boys consistently score
better on tests of right-
brain-dominated spatial perception and mathematical reasoning
(Guiso, Monte, Sapienza, &
Zingales, 2008). In their controversial book Brain Sex, Moir
and Jessel (1992) make a strong

case that measureable differences in the brains of males and
females are already apparent
soon after birth, before the environment has a major impact.
Other researchers have also
concluded that sex differences in brain organization and
cognition have their origins before
birth (e.g., Achiron, Lipitz, Hering-Hanit, & Achiron, 2001).
Studies show that newborn male
and female infant brains are quite different physically.
Specific structures like the corpus callosum (the bundle
of nerves that connects the two brain hemispheres)
and, at the cellular level, the length and function of cer-
tain chromosomes are indeed distinct (Hammer, Men-
dez, Cox, Woerner, & Wall, 2008). Relative size differ-
ences also exist in structures related to memory, vision,
and language processing (e.g., see Cahill, 2005).
In a widely publicized new brain study,
researchers found striking physical evidence
of differences in how male and female brains
are organized (Ingalhalikar et al., 2014). This
information appears to confirm behavioral
differences (such as verbal and math ability)
that are often only observed. Brain imaging of
521 females and 428 males aged 8 to 22 years
showed that male neural networks formed
superior connections from front to back in each
of the brain hemispheres (see Figure 5.7).
According to the researchers, there is some
indication that males have greater poten-
tial to connect perception with coordinated
action, like learning the single task of riding a
bicycle. In contrast, female brains have more
neural communication between the two hemi-
spheres, coinciding with a stronger connection

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