Middle Childhood Cognitive Development PDF
Document Details
Uploaded by ExaltingCesium1388
University of Bridgeport
Tags
Summary
This chapter explores middle childhood cognitive development, covering learning objectives, self-regulation, emotional intelligence, and language. It also touches on intelligence, academic performance, and common childhood disabilities.
Full Transcript
Chapter 9:Middle Childhood Cognitive Development Learning Objectives: Middle Childhood Cognitive Development 1. Describe self-regulation in middle childhood. 2. Discuss the construct of emotional intelligence. 3. Describe language development...
Chapter 9:Middle Childhood Cognitive Development Learning Objectives: Middle Childhood Cognitive Development 1. Describe self-regulation in middle childhood. 2. Discuss the construct of emotional intelligence. 3. Describe language development in middle childhood. 4. Differentiate concrete operational thought from preoperational thought. 5. Discuss language development and speech disorders in middle childhood. 6. Explain the construct of intelligence. 7. Explain how intelligence is measured. 8. Discuss the relationship between childhood intelligence and adult outcomes. 9. Discuss factors that contribute to academic performance in middle childhood. 10. Identify common disabilities in childhood and the legislation that protects disabled children and adults. Freud called middle childhood the latency period because during this time emotions and drives appear to be “latent” or hidden as the balance between emotion and cognition shifts to favor cognition. Balance shifts in favor of emotions again when physical changes associated with puberty occur at the end of middle childhood. Because sex steroids are low during middle childhood and emotional drives are less, the average child of this age has enough self-regulation ability to focus on the task of learning. This developmental period is “critical” because there is no other time in early life when a person is “less emotional.” Erickson called this period industry versus inferiority noting that children learn the technology (industry) of their culture at this age. They learn how to be productive and to accept evaluation of their efforts or they become discouraged and feel inferior. Competency is the most important need at this stage; and competencies developed are the basis of adolescent and adult identity. After puberty, drives and emotions do not decrease again until middle and older adulthood. In Chapter 1 we introduced the domains of development as physical, cognitive, and social-emotional. In adopting this organization, we do not imply that there is a strict separation between the domains. Cognitive development includes reasoning, learning and memory, all of which are impacted by emotions. Furthermore, self-regulation is part of cognition and includes emotion regulation. In this section we cover development of self-regulation, memory, and intellect in enough detail to provide a perspective for future educators and health care professionals. 221 Self-Regulation To review, self-regulation is the control of attentional, emotional, and behavioral impulses to achieve personally valued goals. Embedded in this definition is the idea that some goals are important; and people are more willing to work hard to get what they really want. Personal values are identified by the goals people work toward. The development of values is discussed In Chapter 10. Here we discuss control of attention, emotions, and behavior. Students of psychology quickly find out that very similar psychological constructs are studied by different researchers under different names. The reason for this is that psychologists tend to narrow their work to one subdiscipline, and they boost their careers when they name constructs (see EI Chapter 10). Self-Regulation skills improve steadily in both girls and boys between the ages of 5 and 9. After that time development slows but individual differences remain stable. Girls consistently show better self-regulation than boys at this age (Raffaelli et al., 2005). Self-regulation is the term used by developmental and educational psychologists for the set of abilities called “executive functions” by neuropsychologists. Clinicians are stuck in the middle and left wondering whether these are the same! Executive functions are defined as “higher level cognitive processes of planning, decision making, problem solving, action sequencing, task assignment and organization, effortful and persistent goal pursuit, inhibition of competing impulses, flexibility in goal selection, and goal- conflict resolution.” Tests of executive functions assess working memory, planning, inhibition of impulses, and cognitive flexibility (Best et al., 2011). Neurologists and neuropsychologists recognize that the opposite of cognitive flexibility is perseveration, or the inappropriate repetition of behavior linked to dysfunction in the frontal lobes of the brain. Working Memory Working memory is also called short-term memory and is measured as part of general intelligence (Table 9-5 on p. 228). “Working memory can be defined as the small amount of information that can be held in an especially accessible state and used in cognitive tasks” (Cowan, 2014, p. 198). In early childhood the executive functions― inhibitory control, cognitive flexibility, and working memory are so highly correlated they are a single ability. In middle childhood the correlation between these decreases and they become distinct abilities (Lensing & Elsner, 2018). At the start of middle childhood (ages 6-7) individual differences in working memory are not large and improvement is steady between 6 and 12 years. Individual differences in working memory are more pronounced by age 8 and different children progress at different rates (Lensing & Elsner, 2018). While growth steadily progresses in some children, growth spurts in working memory can occur for others (Brocki & Bohlin, 2004). Improvements in working memory parallel the development of the prefrontal cortex at this age (Romine & Reynolds, 2005). 222 Working memory is critical to reading comprehension because details of a reading passage must be kept in mind long enough to understand the message. Children with low working memory need to read well-organized passages with shorter sentences. Children also use working memory when they hold the directions in mind while doing schoolwork. Children with learning disabilities often display lower than average working memory. These children may be accused of not paying attention to the directions when in reality they have a hard time holding the directions in mind due to below average working memory (Cowan, 2014). Teachers can help students by simplifying instructions and presenting less information at one time. Students interested in learning more about working memory are encouraged to read Working Memory Underpins Cognitive Development, Learning, and Education available free through PubMed. “Cool” and “Hot” Inhibitory Control The HTKS test is used in early childhood to assess executive functions. In middle childhood, “cool” inhibitory control can be assessed with Stroop, flanker and go-nogo tasks (follow the links for demonstrations). These tasks require people to inhibit responses they are inclined to or have been trained to make. Children make steady improvements in their ability to inhibit responses between the ages of 8 and 12 years. Researchers have been able to perform fMRI scans on children (6-10 y/o) and young adults while performing a go-nogo task. In adults, the accuracy of performance was associated with activation in a circuit that included parts of the frontal lobes and left caudate nucleus. These same regions were active in children during the task, with areas of the frontal lobe being more active in children than adults. Results indicated that children’s brains work a lot harder to do the same tasks. “Hot” inhibitory control tasks require children to determine the best outcome in a task that has a balance between rewards and losses. The most common test of “hot” inhibitory control is the Iowa Gambling Task. Participants draw cards from one of 2 or 4 decks of cards. Half of the decks have cards that yield a high payoff along with cards that yield large losses. Participants who choose cards from these decks always lose but they are lured by the high payoff cards. When participants choose from the other decks, they always win in the long term, but the single card payoffs are low. Researchers have modified the task to include children’s themes. Similar to the other executive function abilities, middle childhood is a time when children become progressively better at delaying reward to get a higher payoff in the end (Lensing & Elsner, 2018). 223 Self-Regulation and Outcomes Childhood R2 Childhood MH R2 Later MH Outcome R2 Outcome Outcome Academic.14 Externalizing - Criminal Behavior -.04 Performance Problems.12 (14Y) Mathematics.18 Aggressive Behavior - Criminal Behavior -.02.07 (36Y) Literacy.12 Internalizing - Internalizing (35Y) -.09 Problems.08 Vocabulary.12 Depression - Depression (36Y) -.01.14 School Engagement.09 ETOH/SA (Adol. & -.02 Adult) Social Competence.07 Smoking (Adult) -.08 Peer Victimization -.11 Table 9-1. Relationship between self-regulation in middle childhood and outcomes during middle childhood and later. R2 = explained variance; MH= mental health; ETOH= alcohol abuse; SA=substance abuse; Adol.=adolescent Self-regulation is associated with many positive outcomes for children and adults. A recent quality meta-analysis linked self-regulation in middle childhood with academic and social outcomes during middle childhood (Table 9-1) (Robson et al., 2020). Self- regulation explains between 12-18% of the variability in academic outcomes and 7-14% of the variability in mental health outcomes and remains an important target for educational and clinical interventions. Concrete Operational Thought In Chapter 5 you learned that children in early childhood are in Piaget’s preoperational stage, and during this stage, they learn to think symbolically about the world. By middle childhood, children have reached the concrete operations stage where they learn to use logic in concrete ways. The word concrete refers to things that can be seen, touched, or experienced directly. The concrete operational child can make use of logical principles in solving problems involving the physical world. For example, children of this age can understand principles of cause and effect, size, and distance. They can use logic to solve problems and generalize based on experiences with cases (use induction). Lack of generalization in early childhood manifests in conservation and classification errors. Piaget’s experiments demonstrated concrete operational thought enables classification, identity, reversibility, conservation, decentration, and seriation (Table 9-2). These skills depend on executive functions and frontal lobe development. New cognitive skills increase children's understanding of the physical world, however at this age they still have trouble understanding abstract concepts. If an adult asks a child a question that requires abstract thought or more awareness than the child has, the child will most likely 224 answer, “I don’t know.” Adults may become frustrated when children say this, but they are just being honest. For example, children may not be able to describe people, “What is your friend Jimmy like?” or themselves, “Why did you make such a mess?” Watch video about concrete operational thought. Classification: As children's vocabularies and knowledge of the world increase, they build schemata and can organize objects in more than one way. They also understand classification hierarchies and can arrange objects into a variety of classes and subclasses. Identity: Objects have qualities that do not change even if the object is altered in some way. For instance, mass of an object does not change by rearranging it. A piece of chalk is still chalk even when the piece is broken in two. Reversibility: The child learns that some things that have been changed can be returned to their original state. Water can be frozen and then thawed to become liquid again, but eggs cannot be unscrambled. Arithmetic operations are reversible as well: 2 + 3 = 5 and 5 – 3 = 2. Many of these cognitive skills are incorporated into the school's curriculum through mathematical problems and in worksheets about which situations are reversible or irreversible. Conservation: Remember the example in Chapter of preoperational children thinking that a tall beaker filled with 8 ounces of water was "more" than a short, wide bowl filled with 8 ounces of water? Concrete operational children can understand the concept of conservation which means that changing one quality (in this example, height or water level) can be compensated for by changes in another quality (width). Consequently, there is the same amount of water in each container, although one is taller and narrower and the other is shorter and wider. Decentration: Concrete operational children no longer focus on only one dimension of any object (such as the height of the glass) and instead consider the changes in other dimensions too (such as the width of the glass). This allows for conservation to occur. Seriation: Arranging items along a quantitative dimension, such as length or weight, in a methodical way is now demonstrated by the concrete operational child. For example, they can methodically arrange a series of different-sized sticks in order by length, while younger children approach a similar task in a haphazard way. Table 9-2. Characteristics of concrete operational thought. 225 Development of Language Vocabulary Vocabulary development is very important for reading and overall academic success. Without intervention some children do not make enough progress. One study showed that vocabulary in first grade predicted 30% of individual differences in reading comprehension in 11th grade (Biemiller & Slonim, 2001). Vocabulary allows children to develop concept knowledge because concepts depend on the words and word definition. Children can understand more words than they can speak. Reading comprehension depends on knowing what words mean. Vocabulary growth happens mainly through learning root words (parts of words without prefixes or suffixes). Children know about 3,100 root words in grade 1 and 7,500 root words in grade 5. Children learn 1-3 root words a day and they learn them in a specific order (Biemiller & Slonim, 2001). Easier words are learned first. Vocabulary growth occurs most in second grade (Biemiller & Slonim, 2001). Teachers and parents can help children build vocabulary by teaching root words. Given that verbal ability helps emotional competence (Chapter 10), children who have emotional difficulties and low verbal ability need to have both problems addressed. Mental health clinicians should include the child’s educational functioning in their assessments and treatment plans. Developmental Language Disorders Between 7 and 10% of grade school children have a developmental language disorder (DLD) or a communication disorder that interferes with learning, understanding, and using language. These language difficulties are not explained by other conditions, such as hearing loss or autism, or by extenuating circumstances, such as lack of exposure to language. DLD can affect a child’s speaking, listening, reading, and writing. Routine screening of children under 5 for DLD is not recommended (Siu, 2015). As a result, grade school children with DLD may go without treatment (Ebert et al., 2020). DLD affects more than just communication. DLD is associated with social and academic consequences. Children with DLD may have lower quality friendships and experience more peer rejections. They often have co-occurring learning disorders and if their problems are not addressed these children may not attain their full potential. Longitudinal studies of children with DLD show that as a group, they have lower levels of education and select occupations with lower socioeconomic status than unaffected peers (Ebert et al., 2020). Speech disorders such as articulation disorders, phonological disorders, disfluency and voice disorders or resonance disorders are the most common DLDs (Table 4, (Speech Disorders - Children, n.d.)). Watch this video about speech disorders. 226 Disorder Symptoms Disfluency (stuttering) Repetition of sounds, words, or parts of words or phrases after age 4 (I want...I want my doll. I...I see you.) Putting in (interjecting) extra sounds or words (We went to the...uh...store.) Making words longer (I am Boooobbby Jones.) Pausing during a sentence or words, often with the lips together Tension in the voice or sounds Frustration with attempts to communicate Head jerking while talking Eye blinking while talking Embarrassment with speech Phonological The child is not able to produce speech sounds clearly, disorders such as saying "coo" instead of "school." Certain sounds (like "r", "l", or "s") may be consistently distorted or changed (such as making the 's' sound with a whistle). Errors may make it hard for people to understand the person (only family members may be able to understand a child). Disfluency The child does not use speech sounds to form words as expected for their age. The last or first sound of words (most often consonants) may be left out or changed. The child may have no problem pronouncing the same sound in other words (a child may say "boo" for "book" and "pi" for "pig", but may have no problem saying "key" or "go"). Voice disorders or Hoarseness or raspiness to the voice resonance disorders Voice may break in or out Pitch of the voice may change suddenly Voice may be too loud or too soft Person may run out of air during a sentence Speech may sound odd because too much air is escaping through the hose (hypernasality) or too little air is coming out through the nose (hyponasality) Table 9-3. Speech Disorders source. 227 Speech and Language Pathologists Speech-language pathologists (SLPs) are health professionals trained to evaluate and treat people who have voice, speech, language, or swallowing disorders (including hearing impairment) that affect their ability to communicate. SLPs work in research, education, and health care settings with varying roles, levels of responsibility, and client populations. To become a SLP individuals must complete graduate course work and a clinical practicum at a college or university whose program is accredited by the Council on Academic Accreditation in Audiology and Speech-Language Pathology (CAA). There is high demand for these professionals, and this may be a good career choice for psychology majors. Learn more about this career. Watch this video of SLPs working with children. 228 Development of Memory Figure 9-1. Long term memory systems. To review memory development so far, you learned that memory for conditioned preferences (Figure 9-1, emotional memories) begins before birth. Brain reward systems present at birth enable classical and operant conditioning and social bonding. A social bond is a special kind of memory for an important person (Leedom, 2014). In addition to social memories, infants immediately begin to acquire procedural memories as voluntary movements and actions replace reflexes. Infants also have semantic and perceptual memory in the first year of life, but specific memories may not last. Infants do not yet reason in symbols or generalize and so their memories are more tied to the sensory details of the situations where learning occurred. To test infant memory, researchers must exactly repeat the original learning conditions. Figure 9-1 diagrams the three long-term memory systems that relate to different kinds of learning that happen in distinct brain circuits present beginning at the end of early childhood (Squire, 2004). Perceptual memory functions to identify objects and words, allowing quick recognition of previously encountered stimuli. Perceptual memories are thought to be stored in brain circuits that include the sensory cortex (Henson & Gagnepain, 2010). Perceptual memory interacts with semantic memory which holds knowledge about the world. After early childhood, semantic memory is connected to noetic consciousness― the feeling, “I know that.” Perceptual and semantic memory interact with episodic memory or the conscious recollection of personal experiences that contain information about what has happened and where and when it happened. All three forms of explicit memory are influenced by emotions and emotional memory (Phelps & LeDoux, 2005). Episodic memory is especially important to mental health clinicians and this memory system begins to develop at the end of early childhood, with steady gains through adolescence (Picard et al., 2009; Renoult & Rugg, 2020). 229 Autobiographical memory is about the self and includes both semantic and episodic memories. Whereas semantic memories are for facts that are not part of events in time; episodic memories are tied to individuals’ sense of self as a person who exists in space and time (Tulving & Markowitsch, 1998). The experience of an episodic memory is different from that of other memories because this kind of remembering feels like reliving. People remembering with episodic memory know they are remembering something they went through. Think about the difference between knowing what a fried egg is (semantic memory) and remembering you ate fried eggs for breakfast this morning (episodic memory). At the age of 5 a new kind of consciousness emerges that psychologists call autonoetic consciousness― a sense of self in time (Picard et al., 2009). From this point on, the individuals’ life story begins to be experienced and children can talk about episodes of their lives. Episodic memory and autonoetic conscious arise from activity in a brain network that includes the hippocampus and frontal cortex (Tulving & Markowitsch, 1998). Semantic Memory Organization and Memory Strategies Semantic memory enables meaning making, understanding, and knowledge of conceptual facts about the world. Meaning includes word meaning and so semantic memory depends on language function (Antonucci & Reilly, 2008). Learning in middle childhood involves building semantic memory which is conceptually organized and tied to vocabulary (Denervaud et al., 2021). Children in WEIRD nations must learn a lot of information, and what they learn determines much about their future lives. It is also true that children who know more, learn more, and learn faster. In all age groups knowledge begets knowledge and better memory (Bjorklund et al., 2008). It makes sense that educators and parents would want to know how best to help primary grade children learn information. Memory strategies are executive function tasks that are deliberately used to learn information. Memory strategies require mental effort and may not work for children under age 8 if they are not developmentally ready to use them (Bjorklund et al., 2008). Examples of memory strategies include rehearsing information, visualizing, and organizing information, creating rhymes, such “i” before “e” except after “c”, or inventing acronyms, such as “roygbiv” (the colors of the rainbow). Such strategies are often not practiced by younger children but strategy use increases in frequency in the elementary school years. Table 9-4 shows the percentage of children ages 6-10 not using strategies. The point is to understand why some children have more trouble than others retaining the information they are taught. Children may experience three problems with their use of memory strategies. A mediation deficiency occurs when a child does not understand the strategy being taught, and thus, does not benefit from its use. If they do not understand why using an acronym might be helpful, or how to create an acronym, the strategy is not likely to help. In a production deficiency the child does not spontaneously use a memory strategy 230 and must be prompted to do so. In this case, children know the strategy and are more than capable of using it, but they fail to “produce” the strategy on their own. A utilization deficiency refers to children using a strategy that fails to aid their performance. Utilization deficiency is common in the early stages of learning a new memory strategy (Bjorklund et al., 2008). Age Percentage Children can be taught to use strategies but until the use of 6 55 the strategy becomes well practiced it may slow down the 7 44 learning process. Once they have practiced the strategy 8 25 enough, children’s memory performance will improve. Some 9 17 children under 8 can use rehearsal and organizing strategies. Older children often use rehearsal, grouping, 10 13 self-testing and elaboration. Longitudinal studies show that Table 9-4 Percentage of students for 10-20% of children, support for strategy use is not using any memory strategies necessary because they do not practice strategies on their own (Schneider et al., 2009). Child Neuropsychology and Neuropsychological Evaluations Professionals who evaluate children’s learning and memory problems are called clinical neuropsychologists. They have a PhD or PsyD and are licensed as psychologists and have special training in how the brain develops. According to the American Academy of Clinical Neuropsychology, clinical neuropsychologists use their training to evaluate and help children with brain disorders. These professionals are qualified to administer IQ and other neuropsychological tests (discussed below). They are also in short supply. Pediatric neuropsychologists help parents, teachers, and other clinicians to: 1. Understand how problems with the brain may relate to problems seen at school, home, or with peers 2. Understand how a child learns best 3. Understand why a child may have behavior problems 4. Help a child deal with thinking or behavior problems 5. Identify neurological or psychiatric problems 6. Help match expectations to a child’s specific strengths and weaknesses 7. Work with other clinicians and teachers to develop the best treatment and school plan for a child 231 Individual Differences in Intellectual Development and Achievement Middle childhood is the time in life that individuals devote the largest share of their energy to the development of skills. (Before middle childhood individuals are not mature enough to perform skills; and after middle childhood individuals must balance the emotional demands of sexuality and the peer group with skill development.) During middle childhood individual differences in skills emerge and these individual differences become the basis for aspects of identity. Erikson named the task of middle childhood “industry versus inferiority” and said that individuals who successfully navigate middle childhood develop competency. The skills developed during middle childhood often determine adult jobs and therefore economic success. Parents have an interest in their children’s later economic success and therefore beliefs about power and who should have it influence beliefs about how skills are acquired. These beliefs tend to support the prevailing power structure. Gendered and racist beliefs contaminate interpretation of research regarding skills and abilities (Nisbett et al., 2012). In discussing this topic, we hope to provide you with information that will empower and inspire you to pursue your own skill development and to help others with theirs. Whether it is fair or not a great deal rides on how individuals choose to invest in themselves between the ages of 6 and 12. Given the importance of skill development during middle childhood, an important question is, how do we provide children and parents with feedback about their mastery of skills? Feedback about progress toward goals enables individuals to adjust and assess their effort, but feedback and beliefs about ability can also reduce effort (Dweck, 2006). It is in this context that we discuss the construct of intelligence and its measurement. This discussion will give you a perspective on the balance between effort, opportunity and inborn abilities that determine skill development. You know intuitively that inborn ability is relatively meaningless in the absence of practice. A person with artistic or musical “talent” will not learn to paint or play if they lack access to a paintbrush or a musical instrument. People with natural “talents” are also more motivated to use them and so they practice more (Gottfried & Gottfried, 2004). Intelligence and Intelligence Testing Individual differences in cognitive development are measured and studied as individual differences in intelligence or “the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.” (Gottfredson, 1997, p. 13). In reading this definition note that intelligence is a construct and not something concrete like height or weight that can be directly measured. Psychologists devise methods for measuring constructs and then work to prove the methods are valid and reliable. Validity here means tests measure the construct “intelligence” and not something else. It also means that test results predict outcomes that the construct is 232 supposed to predict such as achievement and academic skills. Reliability means that repeated testing yields the same results and that test items correlate with each other. Health sciences students are used to diagnostic tests in medicine that are sensitive and specific. Sensitivity means how accurately the test identifies those with the diagnosis. Specificity means that the test only identifies those with the diagnosis. Sensitivity and specificity determine the usefulness of a diagnostic test and therefore the test’s reliability and validity. On a recent trip to the drug store, one of us (LJL) observed an angry customer demanding their money back for a COVID-19 test because the “worthless” and “fraudulent” test was negative when their child had coronavirus and needed to go to the emergency room. Although every medical test has false negatives and false positives people assume tests will always be accurate. Similarly, if you do not understand the limitations of psychological tests, you will place too much confidence in them. The reliability and validity of medical tests is far greater than that of psychological tests. Consumers of any test should have a clear idea of why they are using it. They should then judge the test’s value for their specific use. Like medical testing psychological assessment is big business. The US market for psychological assessment including intelligence testing was $724 million in 2021 and is expected to increase 28.7% to $3.28 billion in 2027 (US Cognitive Assessment Market Size, Rising Trends, Analysis and Demands 2022-2027, n.d.). Profit motives impact assessment and assessment research in psychology just as they impact psychopharmacology research in psychiatry. Consumers of this research should be aware of sources of potential bias when they evaluate claims made. The authors of the opensource text that this etext is based on wrote, “(1) Because intelligence is such an important individual difference dimension, (2) psychologists have invested substantial effort in creating and improving measures of intelligence, and (3) these tests are now considered the most accurate of all psychological tests. (4) In fact, the ability to accurately assess intelligence is one of the most important contributions of psychology to everyday public life” (Lally & Valentine-French, 2019, p. 183, numbers added). We agree with statements 2 and 3 and disagree with statements 1 and 4. Psychologists have invested a great deal of effort into measuring intelligence and intelligence tests are relatively accurate. On the other hand, intelligence testing has been helpful for some people and decidedly harmful to others. We note that the authors neglect to mention that intelligence testing was promoted 100 years ago by members of the eugenics movement (Lowe, 2006). The Eugenics Archives of the government of Canada states, “Historically, psychology’s notion of intelligence is entangled with that of eugenics. The idea that intelligence is a unitary graded psychological trait that can be quantified goes back to Galton, and the development and use of intelligence testing was popularized as a tool to implement eugenic measures” (emphasis added). In sum, testing was promoted by eugenicists and test results were used to dehumanize and involuntarily sterilize people. “The United States was the first country to undertake sterilization for eugenic purposes. In the early 233 1900s, American Eugenicists argued that forced sterilization of people with intellectual disability was the best way to protect society. A Supreme Court judgement by Oliver Wendell Holmes in Buck v Bell in 1927 unleashed a wave of forced sterilization. By 1963, over 60,000 people were sterilized without consent” (Roy et al., 2012, p. 385). Victims of this practice are still alive today. Listen to a Radiolab Podcast, G:Unfit about involuntary sterilization and hear one woman tell her story. The historical entanglement between eugenics and the intelligence construct may have caused many people to think of intelligence in a dysfunctional way. The items on intelligence tests were developed specifically to predict performance in school. Some items on the tests assess general knowledge so it is not surprising test scores predict school performance. Predictive value may come from the fact that the best predictor of future behavior is past behavior. Next, we examine common beliefs about intelligence and discuss legitimate uses of intelligence tests. Belief #1. Intelligence is a single trait The idea that intelligence is a single trait was proposed by Galton then Spearman (both eugenicists) and so the factor is called Spearman’s g or simply g, for general factor (Flanagan et al., 2013). Intelligence tests have subtests that assess different abilities (Table 9-5). Individuals do not score at the same level on all subtests. Scores on the subtests have variability in common and they also have unique variability. The common variability produces g which reflects correlations between the subtests. The sum of the subtest scores is used to calculate IQ; and IQ is about 82-84% g and 16-18% the subtests (Reynolds et al., 2013). Intelligence testing has changed a great deal in the last 30 years as we will discuss. For now, let’s assume that the intelligence test total score measures a person’s IQ and that a large part of IQ reflects some general quality of the nervous system which we call g. First what could the biological basis of g be? Currently the best guess is that g reflects the efficiency of information processing in the nervous system (Nisbett et al., 2012). Between birth and age 30 the nervous system becomes more efficient (Durston et al., 2002), this process may happen faster with practice. Children who practice more due to high motivation may develop faster. Psychologists are moving away from the practice of using the total IQ score to predict how children will perform because they find the subtest scores to be more helpful (Flanagan et al., 2013). Subtest scores have predictive value and can be used for educational planning for individual students who are having problems (Flanagan et al., 2013). The move away from using the total score began in the 1940s with Raymond Cattell, a student of Spearman. Cattell’s research indicated that g was a composite of two abilities he called fluid (Gf) and crystalized (Gc) intelligence. Fluid intelligence (Gf) is a measure of problem-solving ability, while crystalized intelligence (Gc) is a measure of knowledge and a person’s ability to use their knowledge. 234 Test Abilities Measured (Subtests) Raven's Progressive Matrices Gf Wechsler Intelligence Scale for Gf (Matrix Reasoning, Picture Concepts, Arithmetic Children–Fourth Edition (WISC-IV) Gc (Vocabulary, Information, Similarities, Comprehension, Word Reasoning Gv (Block Design, Picture Completion Gsm (Digit Span, Letter-Number, Sequencing) Gs (Symbol Search, Coding, Cancellation Wechsler Preschool and Primary Gf (Matrix Reasoning) Scale of Intelligence Fourth Edition Gc (Picture Concepts, Vocabulary, Information, (WPPSI-IV) Similarities, Comprehension, Receptive Vocabulary Picture Naming, Word Reasoning) Gv (Block Design, Object Assembly, Picture Completion) Gs (Coding, Symbol Search) Differential Ability Scales–Second Gf (Matrices, Picture Similarities, Sequential & Quantitative Edition (DAS-II) Reasoning Gc (Early Number Concepts, Naming Vocabulary, Word Definitions, Verbal Comprehension, Verbal Similarities) Gv (Pattern Construction, Recall of Designs, Recognition of Pictures, Copying, Matching Letter-Like Forms) Gsm (Recall of Digits-Forward, Recall of Digits-Backward, Recall of Sequential Order) Glr (Rapid Naming, Recall of Objects-Immediate, Recall of Objects-Delayed) Ga (Phonological Processing) Gs (Speed of Information Processing) Stanford-Binet 5 (SB5) Gf (Nonverbal Fluid Reasoning, Verbal Fluid Reasoning, Nonverbal Quantitative Reasoning, Verbal Quantitative Reasoning) Gc (Nonverbal Knowledge, Verbal Knowledge) Gv (Nonverbal Visual-Spatial Processing, Verbal Visual-Spatial Processing) Gsm (Nonverbal Working Memory, Verbal Working Memory) Table 9-5. Gf = Fluid Intelligence; Gc = Crystallized Intelligence; Gv = Visual Processing; Gsm = Short-Term Memory; Glr = Long-Term Storage and Retrieval; Ga = Auditory Processing; Gs = Processing Speed; Links with test neames are to publisher’s websites. Executive Functions Unite Gf and Gc! In childhood, Gf and Gc are highly correlated (about.75). Remember that working memory is an executive function and is used to calculate g. In young adults, about half of the individual differences in both Gf and Gc are due to individual differences in working memory. When these correlations are considered, shared variation between Gf and Gc is only 3 percent (Friedman et al., 2006). Put another way, working memory unites Gf and Gc. Why is this finding important to clinicians? 1. Exposure to poverty and deprivation impact the development of executive functions including working memory (Hackman et al., 2015; Johnson et al., 2021; Lawson et al., 2018). The more severe the poverty and the longer it persists the more executive functions are affected (Hackman et al., 2015). 235 2. Exposure to trauma impacts executive function development (Johnson et al., 2021). 3. Executive function impairment is associated with externalizing disorders (Huang- Pollock et al., 2017). This impairment may contribute to the cause of externalizing disorders (Huang-Pollock et al., 2017; Yang et al., 2022). 4. Executive function impairment also increases risk for internalizing disorders (Yang et al., 2022). Neuroimaging studies show that Gf and Gc depend on different brain areas (Nisbett et al., 2012). For many IQ tests, the total score reflects Gc more than Gf. Table 9-5 shows common intelligence tests and subtests that measure Gf and Gc. The Raven’s Progressive Matrices Test measures only fluid intelligence (Gf). Individual components of IQ become more differentiated and important after middle childhood and they continue to differentiate through middle adulthood (Li et al., 2004). Current best practices. Psychologists now recognize the Cattell-Horn-Carroll (CHC) model of cognitive abilities (McGrew, 2009) and have used this model to improve intelligence tests (Flanagan et al., 2013). In addition to Gf and Gc, there are other important components to intelligence that reflect various brain functions. The domains assessed by intelligence tests include short (Gsm) and long-term memory (Glr); sensory functioning (visual (Gv), auditory (Ga), and tactile (Gh)); motor functioning (psychomotor (Gp), kinesthetic (Gk)); and Speed (Gs) (Table 9-5). These domains provide important information about brain function and learning differences above and beyond a single IQ score. Psychologists working in schools can administer batteries of tests targeted to understand a specific child’s need. Testing is now appropriately used to help children who may have special needs. Specific training improves deficient abilities more than g (Reynolds et al., 2013). We note that Alfred Binet and Théodore Simon (1904) developed the first intelligence test to help teachers better educate students with disabilities. They were not eugenicists. Belief #2 Success is determined by childhood intelligence How well does this quality (g) as measured by the total IQ score predict academic performance? A recent meta-analysis that included results from 105,185 students of all ages, found that IQ and grades correlated.54 (Roth et al., 2015); hence IQ explains 29% of the individual differences in grades. If we look just at how IQ measured during childhood predicts educational achievement in adulthood, the correlation drops to.37 and predictive value is cut in half. Intelligence during childhood also correlates with occupation (.37) and adult income (.19) (Strenze, 2007). These correlations indicate a small to medium effect but also say other things are important. 236 Belief #3. Genes explain intelligence There is no doubt that genes influence brain function, and that IQ and other intellectual abilities reflect brain function. Individual differences in intelligence among upper middle class, college educated White people living in the United States may be largely due to genetics because the environment allows this group to develop closer to full genetic potential (Nisbett et al., 2012). Studies of different groups of people show that heritability of intelligence is lower in disadvantaged groups than it is in advantaged groups. Furthermore, adoption studies show that disadvantaged children adopted into better circumstances have higher IQs (Nisbett et al., 2012). Some of the environmental factors responsible for socioeconomic differences in IQ may be breastfeeding or diet (Protzko et al., 2013), differential exposure to complex spoken language, differential education, and differential exposure to traumatic stress (Nisbett et al., 2012). The Flynn Effect in the United States 120 115 SB Average IQ 110 WISC 105 100 WAIS-R 95 90 1932 1972 Year Figure 9-2. Change in average IQ in the US for three different IQ tests (Stanford-Binet (SB); Wechsler Intelligence Scale for Children (WISC); Wechsler Adult Intelligence Scale-Revised (WAIS-R). Additional evidence for environmental contributions to intelligence comes from the Flynn effect (Flynn, 1987) (Figure 9-2). Intelligence has been measured for just over 100 years now and the average scores have been rising at a rate of.30 IQ points per year in the US. Generational gains in average IQ scores are observed for all WEIRD nations. Changes in IQ from one generation to the next reflect increases in problem solving ability because Gf increases more than Gc. A recent meta-analysis showed that worldwide average Gf increased 33 points, Gc increased 19 points, and IQ increased 26 points between 1910 and 2010 (Bratsberg & Rogeberg, 2018). Intelligence gains begin with industrialization and economic development and are found in all nations studied irrespective of culture, race, and ethnicity. While gains in WEIRD nations are starting to level off, populations in the developing world are continuing to get smarter. The Raven’s Progressive Matrices test which has the least cultural bias shows the largest gains (Nisbett et al., 2012). 237 Belief #4. Intelligence is an unchanging attribute of a person The Flynn effect shows that intelligence has increased in groups of people over the last 100 years. What about individuals, can IQ change? Experiments of nature and randomized trials indicate that individual IQs can decrease or increase depending on the environment. For example, one study (Breslau et al., 2001) examined WISC-R IQ change between ages 6 and 11 in 717 children whose birth weight was normal (306) or low (411). Roughly half of each group were born and raised in urban environments and half in the suburbs. While IQs of children raised in the suburbs remained relatively stable, urban children of both groups experienced a 5-point decline. Because the IQs of low birthweight children were lower to begin with, the 5-point decline was more functionally significant for them. Higher maternal education reduced but did not eliminate IQ decline, indicating that community factors are important (see Chapter 11). Other studies show that disadvantaged children lose IQ points over the summer, while advantaged children gain points (Nisbett et al., 2012). Summer IQ gains in advantaged children are likely due to the enrichment activities they participate in. High quality teachers in kindergarten and first grade also can boost IQ (Nisbett et al., 2012). Intervention programs increase disadvantaged students’ IQs by 4-7 points depending on the quality of the intervention (Protzko et al., 2013). Imaging studies indicate that IQ changes correlate with typical changes in the cerebral cortex (Schnack et al., 2015). Prediction of Academic Performance In middle childhood, self-regulation explains 8% of individual differences in intelligence broadly defined (Robson et al., 2020). Specifically, executive functions explain half of individual differences in Gf and Gc (Friedman et al., 2006). Beyond, executive functions, emotion regulation in middle childhood predicts 11% of the variance in academic achievement (Billings et al., 2014). General intelligence predicts about 29% of the variance in grades, but as we have said, measures of general intelligence include working memory which is part of executive function. A recent quality meta-analysis (Spiegel et al., 2021) found that executive function predicts 10% of the variance in grades, 10% of the variance in reading achievement, and 13% of the variance in math achievement. Over the course of middle childhood, the separate components of executive function become individually important. Although working memory shows the strongest association with reading and math skills, inhibition and cognitive flexibility are also important. Working memory predicts 18% of the variance in math word problem solving. These values align with the meta-analysis showing that self-regulation skills improve academic performance (Table 9-1). The picture that emerges from all these numbers is that intelligence, executive functions, and emotion regulation skills are correlated abilities that together explain less than half of the individual differences in academic performance. Of these three, intelligence is most predictive, but executive function and emotion regulation make significant contributions to 238 academic achievement over and above the contribution of intelligence (Figure 9-3) (Billings et al., 2014; Ferrando et al., 2011; MacCann et al., 2019; Robson et al., 2020). Figure 9-3. Individual characteristics that predict academic performance. Childhood Personality Traits and Academic Achievement What other person-factors predict cognitive development and academic performance during middle childhood? Personality traits (Chapter 1) start to unfold in middle childhood and also predict academic performance over and above intelligence and executive function skills (Neuenschwander et al., 2013; Poropat, 2009). Throughout this book we will discuss the Five Factor Model of personality that psychologists developed when they analyzed the way people describe themselves. A meta-analysis that included 8 studies and 3,196 children in grades 1-8 found that each of the five factors of personality predict academic performance. Agreeableness, Conscientiousness and Openness are the largest predictors of academic performance after intelligence (Poropat, 2009). As children get older Agreeableness and Openness have less predictive value and Conscientiousness has more predictive value. Agreeableness may impact grades in younger children by improving relationships with teachers and peers. Openness. The tendency to involve oneself in intellectual activities and to enjoy experiencing new ideas is measured by the trait of Openness. This trait may describe the ideal student who is highly motivated to learn (Poropat, 2014). It is not surprising then that adult ratings of child Openness corelate almost as strongly with academic performance as measures of intelligence (r=.43) (Poropat, 2014). Together executive functions and Openness explain 75% of the variance in achievement test performance and 35% of the variance in grades (Neuenschwander et al., 2013) (Figure 9-3). Personality traits of the Five Factor model reflect individuals 239 motivations over the long term. Different traits are affected by different motivations. Openness is influenced by an individual’s curiosity (Silvia & Christensen, 2020; Von Stumm et al., 2011). In earlier chapters and you learned that curiosity is important for cognitive development in infancy and early childhood. Curiosity is still important in middle childhood, but it becomes less predictive relative to other factors as children get older. Studies in children, adolescents and adults show that curiosity and interest make it easier to remember information (Fandakova & Gruber, 2021). Conscientiousness. Conscientiousness is the personality trait that arises from self- regulation (Eisenberg et al., 2012). Conscientious children are responsible, follow rules, and use self-control. They have high academic motivation that manifests as industriousness (Eisenberg et al., 2012). Adult rated child conscientiousness is highly correlated with academic achievement (.43) (Poropat, 2014). Academic motivation is influenced by self-regulation skills as well as openness (Eisenberg et al., 2012). Among the many external factors that impact children’s academic motivation are parent expectations (Pinquart & Ebeling, 2020), teacher behavior, school environment, and peers (Eisenberg et al., 2012). Grade Retention There are individual differences in cognitive development and these differences may not always mean children will be extreme in adulthood. Grade retention is one way to help children who are developing at a slower rate. Among WEIRD nations, the United States ranks low in grade retention with only 10% of students under 15 ever retained (Goos et al., 2021). In the US ability grouping is more common than retention and in Scandinavian countries grade retention is not practiced at all. In the US there appears to be a small positive effect of retention on academic achievement because retained children are also provided remediation (Goos et al., 2021). Retention has positive effects on self-efficacy because it is better for children not to feel inferior to others. The question of what to do with children who have late birthdays is related to the grade retention question. The cutoff birthdate for starting kindergarten varies around the country with some districts having a Fall cutoff and others a January cutoff. For young children who are rapidly developing and for early adolescents who are changing, the one-year age difference between students in a single grade might be significant. The children who are older relative to peers in grades 1-5 do better academically (Crosser, 1991). 240 Neurodevelopmental Disorders Neurodevelopmental Definition Prevalence Disorders Intellectual Disability Limitations in intellectual functioning and adaptive 1 to 3%. (Read more) behavior. 85% are mild. Intellectual Functioning: A score of 70 or below 1.5 times more on intelligence tests. males than Adaptive Behavior: These disabilities express as females. lacking competence in social, conceptual, and practical skills. Social skills include interpersonal skills, social responsibility, self-esteem, gullibility, naivety, resolution of social problems, and the ability to follow the rules of society and obey the laws. Conceptual skills include the ability to understand time, finance, and language. Communication Disorders Disorders of verbal and nonverbal communication 7-10% (Read More) caused by receptive or expressive language disorders, hearing disorders, cognitive dysfunction, or other neurological or psychiatric conditions. Autism Spectrum Disorder Persistent impairment in reciprocal social 1-2% (3-4 times (Read More) communication and social interaction (Criterion A), more males) and restricted, repetitive patterns of behavior, interests, or activities (Criterion B). These symptoms are present from early childhood and limit or impair everyday functioning (Criteria C and D). Attention-Deficit/ Three symptom groups that interferes with 7.2% (2 times Hyperactivity Disorder functioning or development: more males) (Read More) 1) Inattention― wandering off task, failing to follow through on instructions or finishing work or chores, having difficulty sustaining focus, and being disorganized and is not attributable to defiance or lack of comprehension. 2) Hyperactivity― excessive motor activity (such as a child running about) when it is not appropriate, or excessive fidgeting, tapping, or talkativeness. 3) Impulsivity― hasty actions that occur in the moment without forethought, which may have potential for harm to the individual (e.g., darting into the street without looking). 241 Neurodevelopmental Definition Prevalence Disorders Specific Learning Disorder Persistent difficulties learning and using academic 5%–15% (2-3 (Read More) skills: times more males) With impairment in reading: Word reading accuracy Reading rate or fluency Reading comprehension With impairment in written expression: Spelling accuracy Grammar and punctuation accuracy Clarity or organization of written expression With impairment in mathematics: Number sense Memorization of arithmetic facts Accurate or fluent calculation Accurate math reasoning Developmental Persistent problems with coordinated motor skills 5-8% (2-7 times Coordination Disorder including: more males) (Read More) clumsiness (e.g., dropping or bumping into objects) slowness and inaccuracy (e.g., catching an object, using scissors or cutlery, handwriting, riding a bike, or participating in sports). Stereotypic Movement Persistent repetitive, purposeless movements. 3%–4% Disorder (Read More) (e.g., hand waving, body rocking, or head 4-16% in banging). The movements interfere with normal intellectual activity or may cause bodily harm. developmental disorder Note: simple stereotypic movements (e.g., rocking) are seen in 5%-19% of typically developing young children. Tic Disorders A tic is a sudden, rapid, recurrent, nonrhythmic.3-.9% (2-4 times (Read More) motor movement or vocalization. more males. Table 9-6. DSM 5 Neurodevelopmental disorders DSM 5 Neurodevelopmental disorders (Table 9-6) are biologically based conditions that begin in childhood and cause impairment in personal, social, academic, or occupational functioning. An interaction between genetic and environmental factors (including toxin exposure (lead), birth trauma, and infectious diseases) causes these disorders. Children may be diagnosed early but many are not identified until they begin school. These disorders often co-occur and are of varying severity. Because academic achievement is an important part of life-success, untreated children face considerable hardship and are at risk for poverty, externalizing, and internalizing disorders (American Psychiatric Association, 2013). Special Education and Children with Disabilities Children with physical and psychological disabilities are entitled to receive educational services that meet their needs (Table 9-7). Clinicians treating children should include the child’s education in the treatment plan! Read about Special Education in Connecticut. 242 Law (Year) Summary Rehabilitation Act, Required that individuals with disabilities be accommodated in any program or Section 504 activity that receives Federal funding (PL 93-112, 1973). Although this law was (1973) not intended specifically for education, in practice it has protected students' rights in some extra-curricular activities (for older students) and in some child care or after-school care programs (for younger students). If those programs receive Federal funding of any kind, the programs are not allowed to exclude children or youths with disabilities, and they have to find reasonable ways to accommodate the individuals' disabilities. Americans with Prohibited discrimination on the basis of disability, just as Section 504 of the Disabilities Act Rehabilitation Act (PL 101-336, 1990). Although the ADA applies to all people (ADA) 1990 (not just to students), its provisions are more specific and stronger than those of Section 504. The ADA extends to all employment and jobs, not just those receiving Federal funding. It also specifically requires accommodations to be made in public facilities such as with buses, restrooms, and telephones to allow those with disabilities access. Individuals with The law guarantees rights related to education for anyone with a disability from Disabilities birth to age 21. The first two influence schooling in general, but the last three Education Act affect the work of classroom teachers rather directly: (IDEA) (1975, 1. Free, appropriate education; and the educational program should be 2004) truly educational, i.e., not merely care-taking or babysitting. Every Student 2. Due process; in case of disagreements between an individual with a Succeeds Act disability and the schools or other professionals, there must be procedures (2017) for resolving the disagreements that are fair and accessible to all parties, including the person or the person's representative. 3. Fair evaluation of performance despite disability; tests or other evaluations should not assume test taking skills that a person with a disability cannot reasonably be expected to have, such as holding a pencil, hearing or seeing questions, working quickly, or understanding and speaking orally. Evaluation procedures should be modified to allow for these differences. This provision of the law applies to evaluations made by teachers and to school-wide or high-stakes testing programs. 4. Education in the least restrictive environment; education for someone with a disability should provide as many opportunities and options for the person as possible, both in the short term and in the long term. In practice this requirement has meant including students in regular classrooms and school activities as much as possible. 5. An individualized educational program (IEP); given that every disability is unique, instructional planning for a person with a disability should be unique or individualized as well. In practice this provision has led to classroom teachers planning individualized programs jointly with other professionals (like reading specialists, psychologists, or medical personnel) as part of a team. Table 9-7. Summary of laws protecting children and adults with disabilities. 243 References American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). Antonucci, S. M., & Reilly, J. (2008). Semantic memory and language processing: A primer. 29(01), 005–017. Best, J. R., Miller, P. H., & Naglieri, J. A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample. Learning and Individual Differences, 21(4), 327–336. https://doi.org/10.1016/j.lindif.2011.01.007 Biemiller, A., & Slonim, N. (2001). Estimating root word vocabulary growth in normative and advantaged populations: Evidence for a common sequence of vocabulary acquisition. Journal of Educational Psychology, 93, 498–520. https://doi.org/10.1037/0022-0663.93.3.498 Billings, C. E. W., Downey, L. A., Lomas, J. E., Lloyd, J., & Stough, C. (2014). Emotional Intelligence and scholastic achievement in pre-adolescent children. Personality and Individual Differences, 65, 14–18. https://doi.org/10.1016/j.paid.2014.01.017 Binet, A., & Simon, T. (1904). Méthodes nouvelles pour le diagnostic du niveau intellectuel des anormaux. L’année Psychologique, 11(1), 191–244. Bjorklund, D. F., Dukes, C., & Brown, R. D. (2008). The development of memory strategies. In The development of memory in infancy and childhood (pp. 157–188). Psychology Press. Bratsberg, B., & Rogeberg, O. (2018). Flynn effect and its reversal are both environmentally caused. Proceedings of the National Academy of Sciences, 115(26), 6674–6678. https://doi.org/10.1073/pnas.1718793115 Breslau, N., Chilcoat, H. D., Susser, E. S., Matte, T., Liang, K.-Y., & Peterson, E. L. (2001). Stability and Change in Children’s Intelligence Quotient Scores: A Comparison of Two Socioeconomically Disparate Communities. American Journal of Epidemiology, 154(8), 711–717. https://doi.org/10.1093/aje/154.8.711 Brocki, K. C., & Bohlin, G. (2004). Executive Functions in Children Aged 6 to 13: A Dimensional and Developmental Study. Developmental Neuropsychology, 26(2), 571– 593. https://doi.org/10.1207/s15326942dn2602_3 244 Cowan, N. (2014). Working Memory Underpins Cognitive Development, Learning, and Education. Educational Psychology Review, 26(2), 197–223. https://doi.org/10.1007/s10648-013-9246-y Crosser, S. L. (1991). Summer Birth Date Children Kindergarten Entrance Age and Academic Achievement. The Journal of Educational Research, 84(3), 140–146. https://doi.org/10.1080/00220671.1991.10886007 Denervaud, S., Christensen, A. P., Kenett, Y. N., & Beaty, R. E. (2021). Education shapes the structure of semantic memory and impacts creative thinking. Npj Science of Learning, 6(1), Article 1. https://doi.org/10.1038/s41539-021-00113-8 Durston, S., Thomas, K. M., Yang, Y., Uluğ, A. M., Zimmerman, R. D., & Casey, B. j. (2002). A neural basis for the development of inhibitory control. Developmental Science, 5(4), F9–F16. https://doi.org/10.1111/1467-7687.00235 Dweck, C. S. (2006). Mindset: The new psychology of success. Random House. Ebert, K. D., Ochoa-Lubinoff, C., & Holmes, M. P. (2020). Screening school-age children for developmental language disorder in primary care. International Journal of Speech-Language Pathology, 22(2), 152–162. https://doi.org/10.1080/17549507.2019.1632931 Eisenberg, N., Duckworth, A. L., Spinrad, T. L., & Valiente, C. (2012). Conscientiousness: Origins in childhood? Developmental Psychology, 50(5), 1331. https://doi.org/10.1037/a0030977 Fandakova, Y., & Gruber, M. J. (2021). States of curiosity and interest enhance memory differently in adolescents and in children. Developmental Science, 24(1), e13005. https://doi.org/10.1111/desc.13005 Ferrando, M., Prieto, M. D., Almeida, L. S., Ferrándiz, C., Bermejo, R., López-Pina, J. A., Hernández, D., Sáinz, M., & Fernández, M.-C. (2011). Trait emotional intelligence and academic performance: Controlling for the effects of IQ, personality, and self- concept. Journal of Psychoeducational Assessment, 29(2), 150–159. Flanagan, D. P., Alfonso, V. C., Ortiz, S. O., & Dynda, A. M. (2013). Cognitive assessment: Progress in psychometric theories of intelligence, the structure of cognitive ability tests, and interpretive approaches to cognitive test performance. In The Oxford handbook of child psychological assessment (pp. 239–285). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199796304.001.0001 Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101(2), 171. 245 Friedman, N. P., Miyake, A., Corley, R. P., Young, S. E., DeFries, J. C., & Hewitt, J. K. (2006). Not all executive functions are related to intelligence. Psychological Science, 17(2), 172–179. Goos, M., Pipa, J., & Peixoto, F. (2021). Effectiveness of grade retention: A systematic review and meta-analysis. Educational Research Review, 34, 100401. https://doi.org/10.1016/j.edurev.2021.100401 Gottfredson, L. S. (1997). Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Intelligence, 24(1), 13–23. Gottfried, A. E., & Gottfried, A. W. (2004). Toward the Development of a Conceptualization of Gifted Motivation. Gifted Child Quarterly, 48(2), 121–132. https://doi.org/10.1177/001698620404800205 Hackman, D. A., Gallop, R., Evans, G. W., & Farah, M. J. (2015). Socioeconomic status and executive function: Developmental trajectories and mediation. Developmental Science, 18(5), 686–702. https://doi.org/10.1111/desc.12246 Henson, R. N., & Gagnepain, P. (2010). Predictive, interactive multiple memory systems. Hippocampus, 20(11), 1315–1326. https://doi.org/10.1002/hipo.20857 Huang-Pollock, C., Shapiro, Z., Galloway-Long, H., & Weigard, A. (2017). Is Poor Working Memory a Transdiagnostic Risk Factor for Psychopathology? Journal of Abnormal Child Psychology, 45(8), 1477–1490. https://doi.org/10.1007/s10802-016- 0219-8 Johnson, D., Policelli, J., Li, M., Dharamsi, A., Hu, Q., Sheridan, M. A., McLaughlin, K. A., & Wade, M. (2021). Associations of Early-Life Threat and Deprivation With Executive Functioning in Childhood and Adolescence: A Systematic Review and Meta- analysis. JAMA Pediatrics, 175(11), e212511. https://doi.org/10.1001/jamapediatrics.2021.2511 Lally, M., & Valentine-French, S. (2019). Lifespan Development: A Psychological Perspective. Second Edition. https://dept.clcillinois.edu/psy/LifespanDevelopment.pdf Lawson, G. M., Hook, C. J., & Farah, M. J. (2018). A meta-analysis of the relationship between socioeconomic status and executive function performance among children. Developmental Science, 21(2), e12529. https://doi.org/10.1111/desc.12529 Leedom, L. J. (2014). Human Social Behavioral Systems: Ethological framework for a unified theory. Human Ethology Bulletin, 29. Lensing, N., & Elsner, B. (2018). Development of hot and cool executive functions in middle childhood: Three-year growth curves of decision making and working memory 246 updating. Journal of Experimental Child Psychology, 173, 187–204. https://doi.org/10.1016/j.jecp.2018.04.002 Li, S.-C., Lindenberger, U., Hommel, B., Aschersleben, G., Prinz, W., & Baltes, P. B. (2004). Transformations in the Couplings Among Intellectual Abilities and Constituent Cognitive Processes Across the Life Span. Psychological Science, 15(3), 155–163. https://doi.org/10.1111/j.0956-7976.2004.01503003.x Lowe, R. (2006). Eugenics and Education: A note on the origins of the intelligence testing movement in England. Educational Studies. https://doi.org/10.1080/0305569800060101 MacCann, C., Jiang, Y., Brown, L. E. R., Double, K. S., Bucich, M., & Minbashian, A. (2019). Emotional intelligence predicts academic performance: A meta-analysis. Psychological Bulletin, 146(2), 150. https://doi.org/10.1037/bul0000219 McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37(1), 1–10. Neuenschwander, R., Cimeli, P., Röthlisberger, M., & Roebers, C. M. (2013). Personality factors in elementary school children: Contributions to academic performance over and above executive functions? Learning and Individual Differences, 25, 118–125. https://doi.org/10.1016/j.lindif.2012.12.006 Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012). Intelligence: New findings and theoretical developments. The American Psychologist, 67(2), 130–159. https://doi.org/10.1037/a0026699 Phelps, E. A., & LeDoux, J. E. (2005). Contributions of the Amygdala to Emotion Processing: From Animal Models to Human Behavior. Neuron, 48(2), 175–187. https://doi.org/10.1016/j.neuron.2005.09.025 Picard, L., Reffuveille, I., Eustache, F., & Piolino, P. (2009). Development of autonoetic autobiographical memory in school-age children: Genuine age effect or development of basic cognitive abilities? Consciousness and Cognition, 18(4), 864–876. https://doi.org/10.1016/j.concog.2009.07.008 Pinquart, M., & Ebeling, M. (2020). Parental Educational Expectations and Academic Achievement in Children and Adolescents—A Meta-analysis. Educational Psychology Review, 32(2), 463–480. https://doi.org/10.1007/s10648-019-09506-z Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135(2), 322. 247 Poropat, A. E. (2014). A meta-analysis of adult-rated child personality and academic performance in primary education. British Journal of Educational Psychology, 84(2), 239–252. https://doi.org/10.1111/bjep.12019 Protzko, J., Aronson, J., & Blair, C. (2013). How to Make a Young Child Smarter: Evidence From the Database of Raising Intelligence. Perspectives on Psychological Science, 8(1), 25–40. https://doi.org/10.1177/1745691612462585 Raffaelli, M., Crockett, L. J., & Shen, Y.-L. (2005). Developmental Stability and Change in Self-Regulation From Childhood to Adolescence. The Journal of Genetic Psychology, 166(1), 54–76. https://doi.org/10.3200/GNTP.166.1.54-76 Renoult, L., & Rugg, M. D. (2020). An historical perspective on Endel Tulving’s episodic- semantic distinction. Neuropsychologia, 139, 107366. https://doi.org/10.1016/j.neuropsychologia.2020.107366 Reynolds, M. R., Floyd, R. G., & Niileksela, C. R. (2013). How well is psychometric g indexed by global composites? Evidence from three popular intelligence tests. Psychological Assessment, 25(4), 1314. https://doi.org/10.1037/a0034102 Robson, D. A., Allen, M. S., & Howard, S. J. (2020). Self-regulation in childhood as a predictor of future outcomes: A meta-analytic review. Psychological Bulletin, 146(4), 324. https://doi.org/10.1037/bul0000227 Romine, C. B., & Reynolds, C. R. (2005). A model of the development of frontal lobe functioning: Findings from a meta-analysis. Applied Neuropsychology, 12(4), 190–201. Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118–137. https://doi.org/10.1016/j.intell.2015.09.002 Roy, A., Roy, A., & Roy, M. (2012). The human rights of women with intellectual disability. Journal of the Royal Society of Medicine, 105(9), 384–389. https://doi.org/10.1258/jrsm.2012.110303 Schnack, H. G., van Haren, N. E. M., Brouwer, R. M., Evans, A., Durston, S., Boomsma, D. I., Kahn, R. S., & Hulshoff Pol, H. E. (2015). Changes in Thickness and Surface Area of the Human Cortex and Their Relationship with Intelligence. Cerebral Cortex, 25(6), 1608–1617. https://doi.org/10.1093/cercor/bht357 Schneider, W., Kron-Sperl, V., & Hünnerkopf, M. (2009). The development of young children’s memory strategies: Evidence from the Würzburg Longitudinal Memory Study. European Journal of Developmental Psychology, 6(1), 70–99. https://doi.org/10.1080/17405620701336802 248 Silvia, P. J., & Christensen, A. P. (2020). Looking up at the curious personality: Individual differences in curiosity and openness to experience. Current Opinion in Behavioral Sciences, 35, 1–6. https://doi.org/10.1016/j.cobeha.2020.05.013 Siu, A. L. (2015). Screening for speech and language delay and disorders in children aged 5 years or younger: US Preventive Services Task Force recommendation statement. Pediatrics, 136(2), e474–e481. Speech disorders - children: MedlinePlus Medical Encyclopedia. (n.d.). Retrieved December 30, 2022, from https://medlineplus.gov/ency/article/001430.htm Spiegel, J. A., Goodrich, J. M., Morris, B. M., Osborne, C. M., & Lonigan, C. J. (2021). Relations between executive functions and academic outcomes in elementary school children: A meta-analysis. Psychological Bulletin, 147(4), 329. https://doi.org/10.1037/bul0000322 Squire, L. R. (2004). Memory systems of the brain: A brief history and current perspective. Neurobiology of Learning and Memory, 82(3), 171–177. https://doi.org/10.1016/j.nlm.2004.06.005 Strenze, T. (2007). Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence, 35(5), 401–426. https://doi.org/10.1016/j.intell.2006.09.004 Tulving, E., & Markowitsch, H. J. (1998). Episodic and declarative memory: Role of the hippocampus. Hippocampus, 8(3), 198–204. https://doi.org/10.1002/(SICI)1098- 1063(1998)8:33.0.CO;2-G US Cognitive Assessment Market Size, Rising Trends, Analysis and Demands 2022- 2027. (n.d.). MarketWatch. Retrieved December 24, 2022, from https://www.marketwatch.com/press-release/us-cognitive-assessment-market-size- rising-trends-analysis-and-demands-2022-2027-2022-12-23 Von Stumm, S., Hell, B., & Chamorro-Premuzic, T. (2011). The hungry mind: Intellectual curiosity is the third pillar of academic performance. Perspectives on Psychological Science, 6(6), 574–588. Yang, Y., Shields, G. S., Zhang, Y., Wu, H., Chen, H., & Romer, A. L. (2022). Child executive function and future externalizing and internalizing problems: A meta-analysis of prospective longitudinal studies. Clinical Psychology Review, 97, 102194. https://doi.org/10.1016/j.cpr.2022.102194 249