Have you ever wondered how you make sense of the world around you? Cognitive psychology is founded on a collection of theories that attempt to explain how the human brain processes information and makes sense of environmental events (Schunk, 2020). Information processing theories explore the intricate journey of information: from entering your senses, to being encoded, stored, and retrieved later from your mental library. In the past, cognitive theorists have likened this process of information processing to how a computer processes information.

In this chapter, we will build on the information we explored in the last chapter on the development of cognitive processes. The authors will take a more detailed approach to how information is processed and remembered by humans. Finally, this chapter will wrap up with a discussion on the ambiguous concept of human intelligence.

10.1 Information Processing

Our digital age has also brought new ways of thinking about how the human brain works. Although the computer was conceptualized via ideas about how the human brain functions, psychologists now use the functioning of a computer as a metaphor for understanding how we think.

From the 1960s onward, the metaphor of information processing has been a helpful way to think about cognition and cognitive development (Atkinson & Shiffrin, 1968). One key concept is that of information flowing into the brain, being processed or acted on, and then leaving the brain in the form of behavioral output, just like data in a computer. This concept also relies on a modular view of the brain: the idea that discrete structures within our brain specialize in various cognitive tasks, such as memory, sensory processing, language comprehension, and spatial reasoning. As information flows into the brain through various senses, it is routed to the appropriate brain region and acted on, and then behaviors emerge through actions and words. From a developmental perspective, cognitive development is fostered as the various parts of this information processing system mature and gain operational efficiency.

While the information processing model is useful, it has also become more simplistic as science has progressed. Our brain indeed has many functional modules that are connected and share information back and forth. The advent of brain imaging technology brought insight into further complexities of how the brain and its cognitive abilities are organized. Essential components to understanding the complexity of information processing in the brain and the Atkinson and Shiffrin’s model is to first learn about human memory.

10.2 Memory

Memory is the set of processes used to encode, store, and retrieve information over different periods. One of the most influential models of information processing theory is Atkinson-Shiffrin’s (1968) multi-store model of human memory. Based on studies of adults, people with amnesia, and neurological research on memory, researchers have proposed several “types” of memory.

Stage 1

Sensory memory (also called the sensory register) is the first stage of the memory system, and it stores sensory input in its raw form for a very brief duration; essentially long enough for the brain to register and start processing the information. Studies of auditory sensory memory have found that the sensory memory trace for the characteristics of a tone lasts about one second in 2-year-olds, two seconds in 3-year-olds, more than two seconds in 4-year-olds, and three to five seconds in 6-year-olds (Glass et al., 2008). Other researchers have found that young children hold sounds for a shorter duration than older children and adults and that this deficit is not due to attentional differences between these age groups but reflect differences in the performance of the sensory memory system (Gomes et al., 1999).

Attention

The next step in the model is attention and information that is not attended to is lost. Changes in attention have been described by many as the key to changes in human memory (Nelson & Fivush, 2004; Posner & Rothbart, 2007). However, attention is not a unified function; it is comprised of sub-processes. The ability to switch our focus between tasks or external stimuli is called divided attention or multitasking. This is separate from our ability to focus on a single task or stimulus, while ignoring distracting information, called selective attention. Different from these is sustained attention, or the ability to stay on task for long periods of time. Moreover, we also have attention processes that influence our behavior and enable us to inhibit a habitual or dominant response, and others that enable us to distract ourselves when upset or frustrated.

1) Divided Attention/Multitasking

Young children (age 3-4) have considerable difficulties in dividing their attention between two tasks, and often perform at levels equivalent to our closest relative, the chimpanzee, but by age five they have surpassed the chimp (Hermann et al., 2015; Hermann & Tomasello, 2015). Despite these improvements, 5-year-olds continue to perform below the level of school-age children, adolescents, and adults.

2) Selective Attention

Children’s ability with selective attention tasks improves as they age. However, this ability is also greatly influenced by the child’s temperament (Rothbart & Rueda, 2005), the complexity of the stimulus or task (Porporino et al., 2004), and along with whether the stimuli are visual or auditory (Guy et al., 2013). Guy et al. found that children’s ability to selectively attend to visual information outpaced that of auditory stimuli. This may explain why young children are not able to hear the

3) Sustained Attention

Most measures of sustained attention typically ask children to spend several minutes focusing on one task, while waiting for an infrequent event, while there are multiple distractors for several minutes. Berwid et al. (2005) asked children between the ages of 3 and 7 to push a button whenever a “target” image was displayed, but they had to refrain from pushing the button when a non-target image was shown. The younger the child, the more difficulty he or she had maintaining their attention.

Stage 2

The second stage of the memory system is called short-term (STM) or working memory. Working memory is the component of memory in which current conscious mental activity occurs. Short-term memory often requires conscious effort and adequate use of attention to function effectively. As you read earlier, children in this age group struggle with many aspects of attention, and this greatly diminishes their ability to consciously juggle several pieces of information in memory. The capacity of working memory, that is the amount of information someone can hold in consciousness, is smaller in young children than in older children and adults (Galotti, 2018). The typical adult and teenager can hold a 7-digit number active in their short-term memory. The typical 5-year-old can hold only a 4-digit number active. This means that the more complex a mental task is, the less efficient a younger child will be in paying attention to and actively processing, information to complete the task.

Children differ in their memory abilities, and these differences predict both their readiness for school and academic performance in school (PreBler et al., 2013). During middle and late childhood children make strides in several areas of cognitive function including the increased capacity of working memory, their ability to pay attention, and their use of memory strategies. Changes in myelination and synaptic pruning in the cortex are likely behind the increase in processing speed and ability to filter out irrelevant stimuli (Kail et al., 2013).

Changes in attention and the working memory system also involve changes in executive function. Executive function (EF) refers to self-regulatory processes, such as the ability to inhibit a behavior or cognitive flexibility, that enable adaptive responses to new situations or to reach a specific goal. Executive function skills gradually emerge during early childhood and continue to develop throughout childhood and adolescence. Like many cognitive changes, brain maturation, especially the prefrontal cortex, along with experience influence the development of executive function skills. Children show higher executive function skills when parents are warm and responsive, use scaffolding when the child is trying to solve a problem and provide cognitively stimulating environments (Fay-Stammbach et al., 2014). For instance, scaffolding was positively correlated with greater cognitive flexibility at age two and inhibitory control at age four (Bibok et al., 2009).

Older children and adults use mental strategies to aid their memory performance. For instance, simple rote rehearsal may be used to commit information to memory. Young children often do not rehearse unless reminded to do so, and when they do rehearse, they often fail to use clustering rehearsal. In clustering rehearsal, the person rehearses previous material while adding additional information. If a list of words is read out loud to you, you are likely to rehearse each word as you hear it along with any previous words you were given. Young children will repeat each word they hear but often fail to repeat the prior words in the list. In a longitudinal study of 102 kindergarten children by Schneider et al. (2009), the majority of children used no strategy to remember information, a finding that was consistent with previous research. As a result, their memory performance was poor when compared to their abilities as they aged and started to use more effective memory strategies.

Stage 3

The third component of memory is long-term memory (LTM), which is also known as permanent memory. A basic division of long-term memory is between declarative and nondeclarative memory. Declarative memories sometimes referred to as explicit memories, are memories of facts or events that we can consciously recollect. Nondeclarative memories, sometimes referred to as implicit memories, are typically automated skills that do not require conscious recollection. Remembering that you have an exam next week would be an example of a declarative memory. In contrast, knowing how to walk so you can get to the classroom or how to hold a pencil to write would be examples of non-declarative memories. Declarative memory is further divided into semantic and episodic memory. Semantic memories are memories of facts and knowledge that are not tied to a timeline, while episodic memories are tied to specific events in time.

10.3 Memory During Infancy and Childhood

Memory requires the capacity to mentally represent experience, so it should not be surprising that infant memory is rather fleeting and fragile. As a result, older children and adults experience infantile amnesia (sometimes called childhood amnesia), the inability to recall memories from the first few years of life. Several hypotheses have been proposed for this amnesia. From the biological perspective, it has been suggested that infantile amnesia is due to the immaturity of the infant’s brain, especially those areas that are crucial to the formation of autobiographical memory, such as the hippocampus. From the cognitive perspective, it has been suggested that the lack of linguistic skills of babies and toddlers limits their ability to mentally represent events; thereby, reducing their ability to encode memory. Moreover, even if infants do form such early memories, older children and adults may not be able to access them because they may be employing very different, more linguistically based, retrieval cues than infants used when forming largely photographic or visual memories. Finally, social theorists argue that episodic memories of personal experiences may hinge on an understanding of “self”, something that is clearly lacking in infants and young toddlers.

However, in a series of clever studies Carolyn Rovee-Collier and her colleagues have demonstrated that infants can remember events from their life, even if these memories are short-lived. Three-month-old infants were taught that they could make a mobile hung over their crib shake by kicking their legs. The infants were placed in their cribs, on their backs. A ribbon was tied to one foot and the other end to a mobile. At first, infants made random movements, but then came to realize that by kicking they could make the mobile shake. After two 9-minute sessions with the mobile, the mobile was removed. One week later the mobile was reintroduced to one group of infants and most of the babies immediately started kicking their legs, indicating that they remembered their prior experience with the mobile. A second group of infants was shown the mobile two weeks later, and the babies made only random movements. The memory had faded (Rovee-Collier & Hayne, 1987; Giles & Rovee-Collier, 2011). Rovee-Collier and Hayne (1987) found that 3-month-olds could remember the mobile after two weeks if they were shown the mobile and watched it move, even though they were not tied to it. This reminder helped most infants to remember the connection between their kicking and the movement of the mobile. Like many researchers of infant memory, Rovee-Collier (1990) found infant memory to be very context-dependent. In other words, the sessions with the mobile and the later retrieval sessions had to be conducted under very similar circumstances or else the babies would not remember their prior experiences with the mobile. For instance, if the first mobile had had yellow blocks with blue letters, but at the later retrieval session the blocks were blue with yellow letters, the babies would not kick.

Infants older than 6 months of age can retain information for longer periods of time; they also need less reminding to retrieve information in memory. Studies of deferred imitation, that is, the imitation of actions after a time delay, can occur as early as six months of age (Campanella & Rovee-Collier, 2005), but only if infants are allowed to practice the behavior they were shown. By 12 months of age, infants no longer need to practice the behavior in order to retain the memory for four weeks (Klein & Meltzoff, 1999).

During middle childhood, children can learn and remember due to an improvement in the ways they attend to and store information. As children enter school and learn more about the world, they develop more categories for concepts and learn more efficient strategies for storing and retrieving information. One significant reason is that they continue to have more experiences on which to tie new information. New experiences are similar to old ones or remind the child of something else about which they know. This helps them file away new experiences more easily.

10.4 Memory and Aging

There are many stereotypes regarding older adults – as forgetful and confused, but what does the research on memory and cognition in late adulthood reveal? Memory comes in many types, such as working, episodic, semantic, implicit, and prospective. There are also many processes involved in memory. Thus, it should not be a surprise that there are declines in some types of memory and memory processes, while other areas of memory are maintained or even show some improvement with age.

Sensory Memory

Aging may create small decrements in the sensitivity of the sensory register. And, to the extent that a person has a more difficult time hearing or seeing, that information will not be stored in memory. This is an important point because many older people assume that if they cannot remember something, it is because their memory is poor. In fact, it may be that the information was never seen or heard.

Attention

Changes in sensory functioning and speed of processing information in late adulthood often translate into changes in attention (Jefferies et al., 2015). Research has shown that older adults are less able to selectively focus on information while ignoring distractors (Jefferies et al., 2015; Wascher et al., 2012), although Jefferies and her colleagues found that when given double time, older adults could perform at young adult levels. Other studies have also found that older adults have greater difficulty shifting their attention between objects or locations (Tales et al., 2002). Consider the implication of these attentional changes for older adults.

How do changes or maintenance of cognitive ability affect older adults’ everyday lives? Researchers have studied cognition in the context of several different everyday activities. One example is driving. Although older adults often have more years of driving experience, cognitive declines related to reaction time or attentional processes may pose limitations under certain circumstances (Park & Gutchess, 2000). In contrast, research on interpersonal problem-solving suggested that older adults use more effective strategies than younger adults to navigate through social and emotional problems (Blanchard-Fields, 2007). In the context of work, researchers rarely find that older individuals perform poorer on the job (Park & Gutchess, 2000). Similar to everyday problem solving, older workers may develop more efficient strategies and rely on expertise to compensate for cognitive decline.

The Working Memory

Older people have more difficulty using memory strategies to recall details (Berk, 2007). As we age, the working memory loses some of its capacity. This makes it more difficult to concentrate on more than one thing at a time or to remember details of an event. However, people compensate for this by writing down information and avoiding situations where there is too much going on at once to focus on a particular cognitive task.

The Long-Term Memory

This type of memory involves the storage of information for long periods of time. Retrieving such information depends on how well it was learned in the first place rather than how long it has been stored. If information is stored effectively, an older person may remember facts, events, names, and other types of information stored in long-term memory throughout life. The memory of adults of all ages seems to be similar when they are asked to recall the names of teachers or classmates. And older adults remember more about their early adulthood and adolescence than about middle adulthood (Berk, 2007). Older adults retain semantic memory or the ability to remember vocabulary. Whereas, younger adults rely more on mental rehearsal strategies to store and retrieve information. Older adults’ focus relies more on external cues such as familiarity and context to recall information (Berk, 2007). And they are more likely to report the main idea of a story rather than all of the details (Jepson & Labouvie-Vief, in Berk, 2007).

A positive attitude about being able to learn and remember plays an important role in memory. When people are under stress (perhaps feeling stressed about memory loss), they have a more difficult time taking in information because they are preoccupied with anxieties.  Many of the laboratory memory tests require comparing the performance of older and younger adults on timed memory tests in which older adults do not perform as well. However, few real-life situations require speedy responses to memory tasks. Older adults rely on more meaningful cues to remember facts and events without any impairment to everyday living.

10.4 Intelligence

Psychologists have long debated how to best conceptualize and measure intelligence (Sternberg, 2003). These questions include: How many types of intelligence are there? What is the the role of nature versus nurture in developing human intelligence? How and where is intelligence represented in the brain? What are the differences in intelligence?

Measuring Intelligence

From 1904-1905 the French psychologist Alfred Binet (1857–1914) and his colleague Théodore Simon (1872–1961) began working on behalf of the French government to develop a measure that would identify children who would not be successful with regular school curriculum. The goal was to help teachers better educate these students (Aiken, 1994). Binet and Simon developed what most psychologists today regard as the first intelligence test, which consisted of a wide variety of questions that included the ability to name objects, define words, draw pictures, complete sentences, compare items, and construct sentences.

Binet and Simon (Binet, Simon, & Town, 1915; Siegler, 1992) believed that the questions they asked the children all assessed the basic abilities to understand, reason, and make judgments. It turned out that the correlations among these different types of measures were in fact all positive; that is, students who got one item correct were more likely to also get other items correct, even though the questions themselves were very different.

General(g) versus Specific(s) Intelligences

Based on these results, psychologist Charles Spearman (1863–1945) hypothesized that there must be a single underlying construct that all of these items measure. He called the construct that the different abilities and skills measured on intelligence tests have in common the General Intelligence Factor(g). Virtually all psychologists now believe that there is a generalized intelligence factor, “g”, that relates to abstract thinking and that includes the abilities to acquire knowledge, to reason abstractly, to adapt to novel situations, and to benefit from instruction and experience (Gottfredson, 1997; Sternberg, 2003). People with higher general intelligence learn faster.

Soon after Binet and Simon introduced their test, the American psychologist Lewis Terman at Stanford University (1877–1956) developed an American version of Binet’s test that became known as the Stanford-Binet Intelligence Test. The Stanford-Binet is a measure of general intelligence made up of a wide variety of tasks, including vocabulary, memory for pictures, naming of familiar objects, repeating sentences, and following commands.

Although there is general agreement among psychologists that “g” exists, there is also evidence for specific intelligence “s”, a measure of specific skills in narrow domains. One empirical result in support of the idea of “s” comes from intelligence tests themselves. Although the different types of questions do correlate with each other, some items correlate more highly with each other than do other items; they form clusters or clumps of intelligence.

One advocate of the idea of multiple intelligences is the psychologist, Robert Sternberg. Sternberg has proposed a triarchic (three-part) theory of intelligence that proposes that people may display more or less analytical intelligence, creative intelligence, and practical intelligence. Sternberg (1985, 2003) argued that traditional intelligence tests assess analytical intelligence, academic problem solving and performing calculations, but that they do not typically assess creative intelligence, the ability to adapt to new situations and create new ideas, and/or practical intelligence, the ability to demonstrate common sense and street-smarts. As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence (Furnham & Bachtiar, 2008) and exceptionally creative scientists, artists, mathematicians, and engineers do not score higher on intelligence than their less, creative peers (Simonton, 2000).

Furthermore, the brain areas that are associated with convergent thinking, thinking that is directed toward finding the correct answer to a given problem, are different from those associated with divergent thinking, the ability to generate many different ideas or solutions to a single problem (Tarasova et al., 2010). On the other hand, being creative often takes some of the basic abilities measured by “g”, including the abilities to learn from experience, to remember information, and to think abstractly (Bink & Marsh, 2000). Ericsson (1998), Weisberg (2006), Hennessey and Amabile (2010), and Simonton (1992) studied creative people and identified at least five components that are likely to be important for creativity as listed in the table below (Adapted from Lally & Valentine-French, 2019).

Important Components of Creativity

Adapted from Lally & Valentine-French, 2019

The last aspect of the triarchic model, practical intelligence, refers primarily to intelligence that cannot be gained from books or formal learning. Practical intelligence represents a type of “street smarts” or “common sense” that is learned from life experiences. Although a number of tests have been devised to measure practical intelligence (Sternberg et al., 1993; Wagner & Sternberg, 1985), research has not found much evidence that practical intelligence is distinct from “g” or that it is predictive of success at any particular tasks (Gottfredson, 2003). Practical intelligence may include, at least in part, certain abilities that help people perform well at specific jobs, and these abilities may not always be highly correlated with general intelligence (Sternberg et al., 1993).

Gardner’s Theory of Multiple Intelligences

Another champion of the idea of specific types of intelligences rather than one overall intelligence is the psychologist Howard Gardner (1983, 1999). Gardner argued that it would be evolutionarily functional for different people to have different talents and skills and proposed that eight intelligences can be differentiated from each other. A potential ninth intelligence; that is, existential still needs empirical support. Gardner investigated intelligence by focusing on children who were talented in one or more areas and adults who suffered from strokes that compromised some capacities, but not others. Gardner also noted that some evidence for multiple intelligences comes from the abilities of autistic savants, people who score low on intelligence tests overall, but who nevertheless may have exceptional skills in a given domain, such as math, music, art, or in being able to recite statistics in a given sport (Treffert & Wallace, 2004). In addition to brain damage and the existence of savants, Gardner identified these 8 intelligences based on other criteria including a set developmental history and psychometric findings. See the table below for a list of Gardner’s eight specific intelligences.

Howard Gardner's Eight Specific Intelligences

Adapted from information found in Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century. Basic Books.

The idea of multiple intelligences has been influential in the field of education, and teachers have used these ideas to try to teach differently to different students. For instance, to teach math problems to students who have particularly good kinesthetic intelligence, a teacher might encourage the students to move their bodies or hands according to the numbers. On the other hand, some have argued that these “intelligences” sometimes seem more like “abilities” or “talents” rather than real intelligence. There is no clear conclusion about how many intelligences there are. Are a sense of humor, artistic skills, dramatic skills, and so forth also separate intelligences? Furthermore, and again demonstrating the underlying power of a single intelligence, the many different intelligences are, in fact, correlated and thus represent, in part, “g” (Brody, 2003).

Measuring Intelligence: Standardization and the Intelligence Quotient (IQ)

The goal of most intelligence tests is to measure “g”, the general intelligence factor. Good intelligence tests are reliable, meaning that they are consistent over time, and also demonstrate validity, meaning that they measure intelligence rather than something else. Because intelligence is such an important individual difference dimension, psychologists have invested substantial effort in creating and improving measures of intelligence, and these tests are now considered the most accurate of all psychological tests. The ability to accurately assess intelligence is one of the most important contributions of psychology to everyday public life.

Intelligence changes with age. A 3-year-old who could accurately multiply 183 by 39 would certainly be intelligent, but a 25-year-old who could not do so would be seen as unintelligent. Thus, understanding intelligence requires that we know the norms or standards in a given population of people at a given age. The standardization of a test involves giving it to a large number of people at different ages and computing the average score on the test at each age level.

Intelligence tests must be standardized regularly because the overall level of intelligence in a population may change over time. The Flynn effect refers to the observation that scores on intelligence tests worldwide have increased substantially over the past decades (Flynn, 1999). Although the increase varies somewhat from country to country, the average increase is about 3 IQ points every 10 years. There are many explanations for the Flynn effect, including better nutrition, increased access to information, and more familiarity with multiple-choice tests (Neisser, 1998). Whether people are getting smarter, however, is debatable (Neisser, 1997). Most of the increase in IQ occurred during the second half of the 20th century. Recent research has found a reversal of the Flynn effect in several nations around the world, although some nations still show an increase in IQ scores (Dutton et al., 2016).

Once the standardization has been accomplished, we have a picture of the average abilities of people at different ages and can calculate a person’s mental age, which is the age at which a person is performing intellectually. If we compare the mental age of a person to the person’s chronological age, the result is the Intelligence Quotient (IQ), a measure of intelligence that is adjusted for age.

Thus, a 10-year-old child who does as well as the average 10-year-old child has an IQ of 100 (10÷ 10 × 100), whereas an 8-year-old child who does as well as the average 10-year-old child would have an IQ of 125 (10 ÷ 8 × 100). Most modern intelligence tests are based on the relative position of a person’s score among people of the same age, rather than based on this formula, but the idea of an intelligence “ratio” or “quotient” provides a good description of the score’s meaning.

Concern for Bias

Intelligence tests and psychological definitions of intelligence have been heavily criticized since the 1970s for being biased in favor of Anglo-American, middle-class respondents and for being inadequate tools for measuring non-academic types of intelligence or talent. Intelligence changes with experience and intelligence quotients or scores do not reflect that ability to change. What is considered smart varies culturally as well, and most intelligence tests do not take this variation into account. For example, in the West, being smart is associated with being quick. A person who answers a question the fastest is seen as the smartest, but in some cultures being smart is associated with considering an idea thoroughly before answering. A well-thought-out, contemplative answer is the best answer.

Intelligence and Wisdom

When looking at scores on traditional intelligence tests, tasks measuring verbal skills show minimal or no age-related declines, while scores on performance tests, which measure solving problems quickly, decline with age (Botwinick, 1984). This profile mirrors crystallized and fluid intelligence. Baltes (1993) introduced two additional types of intelligence to reflect cognitive changes in aging.

Pragmatics of intelligence is cultural exposure to facts and procedures that are maintained as one ages and are similar to crystallized intelligence. Mechanics of intelligence are dependent on brain functioning and decline with age, similar to fluid intelligence. Baltes indicated that pragmatics of intelligence show a little decline and typically increase with age whereas mechanics decline steadily, starting at a relatively young age. Additionally, the pragmatics of intelligence may compensate for the declines that occur with the mechanics of intelligence. In summary, global cognitive declines are not typical as one ages, and individuals typically compensate for some cognitive declines, especially processing speed.

Wisdom has been defined as “expert knowledge in the fundamental pragmatics of life that permits exceptional insight, judgment and advice about complex and uncertain matters” (Smith & Baltes, 1990). A wise person is insightful and has knowledge that can be used to overcome obstacles in living. Does aging bring wisdom? While living longer brings experience, it does not always bring wisdom. Paul Baltes and his colleagues (Baltes & Kunzmann, 2004; Baltes & Staudinger, 2000) suggest that wisdom is rare. In addition, the emergence of wisdom can be seen in late adolescence and young adulthood, with there being few gains in wisdom throughout adulthood (Staudinger & Gluck, 2011). This would suggest that factors other than age are stronger determinants of wisdom. Occupations and experiences that emphasize others rather than the self, along with personality characteristics, such as openness to experience and generativity, are more likely to provide the building blocks of wisdom (Baltes & Kunzmann, 2004). Age combined with a certain type of experience and/or personality brings wisdom.

Children with Learning Disabilities

A Learning Disability (or LD) is a specific impairment of academic learning that interferes with a specific aspect of schoolwork and that reduces a student’s academic performance significantly. An LD shows itself as a major discrepancy between a student’s ability and some features of achievement: The student may be delayed in reading, writing, listening, speaking, or doing mathematics, but not in all of these at once. A learning problem is not considered a learning disability if it stems from physical, sensory, or motor handicaps, or from generalized intellectual impairment. It is also not an LD if the learning problem really reflects the challenges of learning English as a second language. Genuine LDs are the learning problems left over after these other possibilities are accounted for or excluded. Typically, a student with an LD has not been helped by teachers’ ordinary efforts to assist the student when he or she falls behind academically, though what counts as an “ordinary effort”, of course, differs among teachers, schools, and students. Most importantly, though, an LD relates to a fairly specific area of academic learning. A student may be able to read and compute well enough, for example, but not be able to write. LDs are by far the most common form of special educational need, accounting for half of all students with special needs in the United States and approximately 20% of all students, depending on how the numbers are estimated (National Center for Learning Disabilities, 2017). Students with LDs are so common, in fact, that most teachers regularly encounter at least one per class in any given school year, regardless of the grade level they teach.

These difficulties are identified in school because this is when children’s academic abilities are being tested, compared, and measured. Consequently, once academic testing is no longer essential in that person’s life (as when they are working rather than going to school) these disabilities may no longer be noticed or relevant, depending on the person’s job and the extent of the disability.

Dyslexia is one of the most commonly diagnosed disabilities and involves having difficulty in the area of reading. This diagnosis is used for a number of reading difficulties. Common characteristics are difficulty with phonological processing, which includes the manipulation of sounds, spelling, and rapid visual/verbal processing. Additionally, the child may reverse letters, have difficulty reading from left to right, or may have problems associating letters with sounds. It appears to be rooted in neurological problems involving the parts of the brain active in recognizing letters, verbally responding, or being able to manipulate sounds. Recent studies have identified a number of genes that are linked to developing dyslexia (National Institute of Neurological Disorders and Stroke, 2016). Treatment typically involves altering teaching methods to accommodate the person’s particular problematic area.

Dysgraphia refers to a writing disability that is often associated with dyslexia (Carlson, 2013). There are different types of dysgraphia, including phonological dysgraphia when the person cannot sound out words and write them phonetically. Orthographic dysgraphia is demonstrated by those individuals who can spell regularly spelled words, but not irregularly spelled ones. Some individuals with dysgraphia experience difficulties in motor control and experience trouble forming letters when using a pen or pencil.

Dyscalculia refers to problems in math. Cowan and Powell (2014) identified several terms used when describing difficulties in mathematics including dyscalculia, mathematical learning disability, and mathematics disorder. All three terms refer to students with average intelligence who exhibit poor academic performance in mathematics. When evaluating a group of third graders, Cowan and Powell (2014) found that children with dyscalculia demonstrated problems with working memory, reasoning, processing speed and oral language, all of which are referred to as domain-general factors. Additionally, problems with multi-digit skills, including number system knowledge, were also exhibited.

A child with attention-deficit/hyperactivity disorder (ADHD) shows a constant pattern of inattention and/or hyperactive and impulsive behavior that interferes with normal functioning (Whitbourne, 2025). Some of the signs of inattention include great difficulty with, and avoidance of, tasks that require sustained attention (such as conversations or reading), failure to follow instructions (often resulting in failure to complete school work and other duties), disorganization (difficulty keeping things in order, poor time management, sloppy and messy work), lack of attention to detail, becoming easily distracted, and forgetfulness. Hyperactivity is characterized by excessive movement, and includes fidgeting or squirming, leaving one’s seat in situations when remaining seated is expected, having trouble sitting still (e.g., in a restaurant), running about and climbing on things, blurting out responses before another person’s question or statement has been completed, difficulty waiting one’s turn for something, and interrupting and intruding on others. Frequently, the hyperactive child comes across as noisy and boisterous. The child’s behavior is hasty, impulsive, and seems to occur without much forethought; these characteristics may explain why adolescents and young adults diagnosed with ADHD receive more traffic tickets and have more automobile accidents than do others their age (Thompson et al., 2007).

A 2022 survey of parents found an estimated 7 million (11.4%) U.S. children aged 3–17 years have ever been diagnosed with ADHD (Danielson, et al., 2022). The same survey found that on average boys are almost twice as likely to have ADHD than are girls; however, such findings might reflect the greater propensity of boys to engage in aggressive and antisocial behavior and thus incur a greater likelihood of being referred to psychological clinics (Danielson, et al., 2022). Children with ADHD face severe academic and social challenges. Compared to their non-ADHD counterparts, children with ADHD have lower grades and standardized test scores and higher rates of expulsion, grade retention, and dropping out (Loe & Feldman, 2007). They also are less well-liked and more often rejected by their peers (Hoza et al., 2005).

ADHD can persist into adolescence and adulthood (Barkley et al., 2002). A recent study found that 29.3% of adults who had been diagnosed with ADHD decades earlier still showed symptoms (Barbaresi et al., 2013). Somewhat troubling, this study also reported that nearly 81% of those whose ADHD persist into adulthood had experienced at least one other comorbid disorder, compared to 47% of those whose ADHD did not persist. Additional concerns when an adult has ADHD include: Worse educational attainment, lower socioeconomic status, less likely to be employed, more likely to be divorced, and more likely to have non-alcohol-related substance abuse problems (Klein et al., 2012).