Intelligence Research Paper

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Intelligence is defined as the capacity for learning, reasoning, understanding, and similar forms of mental activity. This definition implies that the concept of intelligence is both multifaceted (i.e., reflective of many aspects of mental ability) and implicative of differences among people (i.e., reflective of degrees of capacity, ability, or aptitude among individuals). Yet this definition does not necessarily relate directly to the definition of intelligence used by scientists. In fact there is no consensus on the definition of intelligence among professionals who study it (e.g., psychologists, educators, computer scientists).

Multiple Definitions

There have been multiple attempts to define intelligence. These definitions can be broadly classified into five large groups: (1) consensus definitions, (2) operational definitions, (3) task-based or psychometric definitions, (4) process-based definitions, and (5) domain definitions. “Consensus definitions” of intelligence are typically associated with attempts of researchers in the field to consolidate a variety of points of view and produce, collectively, a comprehensive common definition. In this regard two symposia that brought together researchers in the field are important. The first symposium, which took place in 1921 under the title “Intelligence and Its Measurement: A Symposium,” focused on the abilities to learn and adapt to the environment. However, the definitions of these abilities varied. For example, the American psychologist Lewis Terman emphasized abstract thinking, whereas another American psychologist, Edward Thorndike, stressed the importance of providing good responses to questions. The second symposium, which took place in 1986, brought together a new generation of intelligence researchers (e.g., Douglas Detterman, Ulric Neisser, Robert Sternberg). By then the field of intelligence had developed markedly, having produced hundreds of research articles and books. The resulting consensus definition kept the reference to learning and adaptive abilities but expanded to include many other abilities, including meta-cognitive abilities.

Although there is still no single consensus definition of intelligence, based on the discussions at these symposia, multiple other meetings, and in the press a broad definition of intelligence includes references to lower-level processes, such as perception and attention, and higherlevel processes, such as problem solving, reasoning, and decision making, with regard to learning and demonstrating adaptive behaviors in problem situations. These lowerand higher-level processes are typically referred to in two dimensions: quality and speed. Quality refers to efficacy or lack of errors, and speed refers to time while learning or solving a problem. Intelligence implies the presence of no or few errors and high speed in all processes.

“Operational definitions” of intelligence are closely linked to the concept of intelligence testing. Intelligence testing was conceived of and developed by the French psychologists Alfred Binet and Théodore Simon, who first used such a test to identify learning-impaired Parisian children in the early 1900s. The “invention” was welcomed by psychologists around the world, especially in the United States, and resulted in the development of innumerable tests of intelligence. To reflect the wealth of the research and the differential power of intelligence tests in describing individual differences, the American psychologist Edwin Boring noted in 1923 that intelligence was simply what intelligence tests test. Although obviously circular in nature, this definition of intelligence is still powerful. Researchers and practitioners often use the common metric of IQ (intelligence quotient), even though IQ typically reflects many different theoretical positions when generated by different tests of intelligence. For example, the first tests of intelligence by Binet were primarily based on sensory processes; David Wechsler’s tests (which exist in three versions spanning infancy, childhood, and adulthood) measure primary judgment skills. Then there are theory-based tests, such as the tests of Raymond Cattell, which are based on the theory of crystallized (i.e., acquired and learned over the total life span) and fluid (i.e., transformable to novel materials, situations, and tasks) intelligence, and such modern tests of intelligence as the Cognitive Assessment System (by Jack Naglieri and Jagannath Prasad Das) or K-ABC (by Alan and Nadeen Kaufman), which are both based on the theories of the Soviet neuropsychologist Alexander Luria. Yet as long as a test can generate an IQ, it is assumed to measure intelligence.

“Task-based or psychometric” definitions of intelligence are associated with ideas of defining intelligence through tasks that, by agreement among researchers, call for intelligence. One of the first proponents of task-based definitions of intelligence was the American psychologist Charles Spearman (1863–1945). In the early 1900s Spearman proposed that intelligence includes a so-called general (g-, or mental energy) factor and task-specific factors. The g-factor can explain the observation that indicators of performance on all intelligence tasks tend to correlate with each other (e.g., doing well on one task typically suggests strong performance on other tasks as well), whereas task-specific factors can explain why these correlations are not perfect (e.g., the performance indicators will differ on tasks that involve reading versus arithmetic). Spearman’s work had a tremendous impact on the field of intelligence: Students and followers include Cattell, Wechsler, Anne Anastasi, Detterman, Arthur Jensen, and many others. Spearman’s work also had opponents. For example, Thorndike argued for three forms of intelligence: abstract, mechanical, and social. Similarly Louis Thurstone argued that several primary mental abilities form intelligence (verbal comprehension, word fluency, number facility, spatial visualization, associative memory, perceptual speed, and reasoning). In an attempt to reconcile the theories of Spearman and Thurstone, Cattell proposed a hierarchical theory of intelligence in which lower-level abilities form two higher-order factors, fluid (reasoning with novel stimuli) and crystallized (reasoning with acquired knowledge) intelligence, which in turn contribute to the g–factor. Another opponent of Spearman’s was Joy Paul Guilford, who, developing Thurstone’s ideas, stated that intelligence can be represented by 150 abilities that result from different combinations of operations (e.g., cognition and memory), content (e.g., figural and symbolic), and products (e.g., unit and class).

“Process-based” definitions of intelligence are linked to theories that are not test or task based but, rather, capture processes involved in intelligence across tasks, domains, and tests. For example, the so-called triarchic theory of Robert Sternberg postulates three fundamental processes underlying intelligence: (1) analytical processes, which reflect judgment of a quality of an argument; (2) practical processes, which indicate skills of adaptation to situations or environment; and (3) creative processes, which capture skills of generating new knowledge and practices. Each of these types of processes is “constructed” from three different components: (a) knowledge acquisition components, (b) performance components, and (c) metacognitive components. These componential processes can manifest themselves in any area of human functioning.

“Domain-based” definitions of intelligence are typically associated with domains of expertise. For example, Howard Gardner postulates eight dimensions of intelligence. These dimensions, to a various degree, are present in all people and are recruited when particular types of tasks are performed or in particular domains of expertise. Specifically these intelligences are (1) bodily-kinesthetic, in which sportsmen excel; (2) musical, demonstrated to a high degree by musicians; (3) interpersonal, characteristic of philosophers; (4) intrapersonal, common among politicians; (5) logical-mathematical, possessed by mathematicians; (6) naturalistic, demonstrated by scientists; (7) verbal-linguistic, characteristic of writers; and (8) visualspatial, necessary at high levels for engineers. Another example of domain-based definitions of intelligence is the theory of emotional intelligence (developed by Peter Salovey, John Mayer, and Daniel Goleman). This theory specifies intelligence in the domain of emotional functioning as the ability to perceive, appraise, express, access, generate, and regulate emotions and feelings.

Development of Intelligence

The concept of IQ was developed by psychologists and statisticians in such a way that the distribution of scores remains relatively constant over a life span. IQs are compared across people, not within an individual, and are characterized by a population mean of 100 and a standard deviation of 15. Yet intelligence changes developmentally, and these changes occur in a number of ways. It is obvious that the intelligence of a one-year-old cannot be compared with the intelligence of a fifty-year-old, although their IQs can be compared. There are many developmental theories, for example those of Jean Piaget (1896–1980), that demonstrate that children reason in ways distinctly different from adults. Thus if a person had an IQ score of 110 at age one and has an IQ score of 110 at age fifty, this person’s “texture” of intelligence has changed, but his or her relative position among peers has remained constant. A few relevant observations should be noted. First, early childhood intelligence is not a good predictor of level of intelligence later in life. Second, intelligence tends to vary across a person’s life span, with a gradual increase toward middle age adulthood and a graduate decline in older ages. Third, it has been reported that in the developed world, intelligence tended to increase during the twentieth century (often called the Flynn effect), but it has appeared to stabilize or even decrease in the twenty-first century.

Etiology of Intelligence

Individuals in the general population differ in their intelligence. Differences are captured by assessments of intelligence, which include both standardized tests (e.g., K-ABC) and experimental tasks (e.g., computerized tasks administered to register reaction time in response to particular stimuli). To identify the sources of these individual differences, researchers investigate the etiology (i.e., origin) of intelligence.

The etiology of intelligence is typically formulated in psychology as a question of nature and nurture: Does intelligence stem from genes (i.e., nature) or environments (i.e., nurture)? This question can be traced back to ancient times, where it was initially formulated as an “either/or” dilemma. In the early twenty-first century, however, there is a consensus that both hereditary and environmental factors play substantial and complementary roles in the development of intelligence. Two statistical coefficients are typically used to express the contributions of both genes and environments: “heritability,” which shows the amount of variation in intelligence among individuals attributable to genes, and “environmentality,” which captures the variation in intelligence attributable to environment. Both coefficients are relevant only at the level of population analyses and cannot be applied to individuals. Exciting tasks in early twenty-first century research pertain to the identification of specific genes and environments that underlie differences in intelligence. For example, it has been shown that variants in such genes as COMT (a gene responsible for the production of catechol-O-methyl transferase, an enzyme involved in the breakdown of major neurotransmitters) and BDNF (a gene responsible for the production of brain-derived neurotrophic factor, a protein involved in the biochemistry of neuronal survival, growth, and differentiation) are associated with individual differences in cognitive functioning and intelligence. It has also been shown that specific environments, such as impoverished or enriched with certain micronutrients (e.g., iodine), lead to individual differences in intellectual functioning. It is important to realize that neither genes nor environment have a deterministic impact on intelligence. The influence of both types of etiological factors, both additive and interactive, is probabilistic and takes place through the brain. Specifically there is a body of research that establishes evidence regarding which structures and pathways of the brain are associated with solving intellectual tasks and how patterns of brain activation vary among people and in different experimental conditions (e.g., sleep depleted versus deprived).

Although the majority of experts agree on the importance of both genes and environment in the etiology of intelligence, there are still leftovers of the raucous debate of the early 1990s related to the arguments put forth in The Bell Curve. Written by the psychologist Richard

Herrnstein and the geneticist Charles Murray, The Bell Curve claimed IQ is hereditary and, as such, the single determinant of a person’s life outcomes. That and similar debates indicate that the concept of intelligence remains a point of disagreement with the capacity to raise charged social issues.

The concept of intelligence is viewed by some as a social construct developed to capture individual differences in cognitive functioning and as such has no “permanent” definition or understanding; both vary with the change of societal context. Thus yet another disagreement in the literature on intelligence pertains to the debate of a “social” versus “real” phenomenon. Those who argue that the concept of intelligence is a social construct suggest it was invented by the privileged classes to maintain their privilege. Those who argue that the concept of intelligence is based on the latent ability truly differentiating people maintain it is a helpful differentiating and predictive concept that has value in decisions pertaining to education and job placement.

Group Differences in Intelligence

Four types of differences are typically discussed in the study of intelligence: sex differences, ethnic and racial differences, cultural differences, and differences in conditions (i.e., intelligence in deaf and hard of hearing versus in hearing people). Males and females tend to demonstrate equivalent or comparable average scores on tests of intelligence. Yet although there are no differences in performance when performance indices are averaged across tasks, there are differences on specific tasks as well as differences in variability and range. Specifically males tend to score higher on spatial and visual tasks, among others, requiring memory, motor tasks involving aiming, and certain tasks requiring mathematical skills. Females tend to score higher on tasks requiring phonological and semantic processing, verbal production and comprehension, and fine motor skills. Broadly speaking, males demonstrate advantages in spatial reasoning, and females demonstrate advantages in verbal reasoning, but this generalized statement can be challenged by the presence and absence of sex differences on other tasks. As of the early twenty-first century there is no consensus on the profile, stability, and nature of sex differences in intelligence.

Another source of group differences in intelligence is variation in performance among different ethnic and racial groups. Group differences are typically seen on standardized tests of intelligence, especially those that rely heavily on g-theories. The differences among ethnic and racial groups demonstrate the underperformance of Hispanic Americans, Native Americans, and African Americans as compared with Asian and white Americans (of a variety of ethnic backgrounds). The differences are asystematic, meaning that the profiles of differences vary for different tasks. In other words, there is no systematic differentiation of profiles of abilities among the ethnic or racial groups. It is of special interest that the ethnic gap appears to be smaller or closed when testing is conducted using tasks from process- or domain-based theories of intelligences.

Similarly people in different cultural groups around the world demonstrate varied performances on intelligence tasks. Moreover definitions of intelligence vary across cultures as well. Thus what is considered to be “intelligent” behavior among the Luo people of Kenya is different from that of Yup’ik people of Alaska. A number of researchers have studied so-called implicit theories of intelligence—ideas about intelligence conceived by laypeople. It turns out that definitions of intelligence in the East and the West, for example, are quite different, with Eastern cultures emphasizing more social-emotional components of intelligence and Western cultures emphasizing information-processing aspects of intelligence.

Another source of group differences is the difference among people with special needs. For example, deaf people tend to score lower on tests of intelligence that call for verbal skills, but their performance on tests of spatial reasoning is similar to hearing individuals. Blind people score lower on spatial tasks (when administered in Braille), but their scores are average on verbal tasks. Thus characteristics of biological development (i.e., hormonal differences), acculturation, education, and various other peculiarities of development can all be related to group differences in intelligence. At this point there is no definitive answer to why these group differences exist.

Bibliography:

  1. Cianciolo, Anna T., and Robert J. Sternberg. 2004. Intelligence: A Brief History. Malden, MA: Blackwell.
  2. Deary, Ian J. 2000. Looking down on Human Intelligence: From Psychometrics to the Brain. Oxford: Oxford University Press.
  3. Mackintosh, N. J. 1998. IQ and Human Intelligence. Oxford: Oxford University Press.
  4. Sternberg, Robert J., ed. 2000. Handbook of Intelligence. New York: Cambridge University Press.
  5. Sternberg, Robert J., ed. 2004. International Handbook of Intelligence. New York: Cambridge University Press.

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