Psychology- a Complete Introduction

Home > Other > Psychology- a Complete Introduction > Page 12
Psychology- a Complete Introduction Page 12

by Sandi Mann


  THURSTONE’S PRIMARY MENTAL ABILITIES

  Louis Thurstone (1887–1955) was a US pioneer in the field of psychometrics. Thurstone’s work in factor analysis led him to formulate a model of intelligence centred around ‘Primary Mental Abilities’ (PMAs), which were independent factors of intelligence that different individuals possessed in varying degrees. Unlike Spearman, he opposed the notion of a singular general intelligence and instead focused on seven primary factors:

  1 Verbal comprehension

  2 Reasoning

  3 Perceptual speed

  4 Numerical ability

  5 Word fluency

  6 Associative memory

  7 Spatial visualization.

  Some intelligence tests, such as the Wechsler Adult Intelligence Scale (WAIS), which will be discussed later in this chapter, have sections that test for these seven factors, although they might have different names (e.g. perceptual speed is called processing speed on the WAIS).

  GARDNER’S THEORY OF MULTIPLE INTELLIGENCES

  Again, this is a theory that does not see intelligence as a single entity. In his 1983 book, Frames of Mind: The Theory of Multiple Intelligences, the US developmental psychologist Howard Gardner (born 1943) articulated seven criteria for a behaviour to be considered an intelligence. These were that the intelligences showed the following traits:

  1 Identification in the case of brain damage (i.e. damage to a specific area of the brain isolates that ability from others)

  2 An evolutionary purpose

  3 Presence of a clear operation or information-processing mechanism that manages specific kinds of input

  4 Ability to be encoded (i.e. they showed symbolic expression in outputs such as language, images and music)

  5 A distinct developmental progression

  6 The existence of giftedness, savants and prodigies in that area

  7 Support from various experimental psychology and psychometric findings.

  Gardner believed that each individual possesses a unique blend of all the intelligences and he claimed that eight abilities met these criteria:

  • Musical–rhythmic: this is an intelligence that centres around sounds, rhythms, tones and music. People with a high musical intelligence usually sing and play instruments to a high standard, may compose music and generally have a natural flair for all things musical. Many have good or even perfect pitch.

  • Visual–spatial: people with a high visual–spatial intelligence are good at making spatial judgements and at picturing and manipulating objects and scenes in their imagination. They are good at remembering faces and images and tend to notice fine details.

  • Verbal–linguistic: people with high verbal–linguistic intelligence are good with words and languages. They are typically good at reading, writing, telling stories, explaining things to others and so on.

  • Logical–mathematical: people high in this area are strong at logic, abstractions, reasoning, numbers, pattern detection and critical thinking. Logical reasoning is closely linked to fluid intelligence (see below) and to general intelligence (the g factor).

  • Bodily–kinaesthetic: people who have high bodily–kinaesthetic intelligence tend to be good at physical activities such as sports, dance, acting, fine motor skills and making things. They are often quite active people with strong motor skills and body awareness.

  • Interpersonal: individuals who have high interpersonal intelligence have great sensitivity to others’ moods, feelings, temperaments and motivations, and are good at working in a team. Because of these skills they are often quite popular and have many friends.

  • Intrapersonal: this area has to do with introspective and self-reflective capacities. People high in these skills have a clear understanding of themselves, their strengths and weaknesses. They tend to analyse themselves quite deeply, trying to work out their goals and motivations.

  • Naturalistic: people high in this area tend to be good at working with their sense of touch and they learn by holding, feeling and manipulating. They probably have a natural affinity for plants and the animal kingdom, an ability that was clearly of value in our evolutionary past as hunters, gatherers and farmers.

  Fluid vs crystallized intelligence

  This is another way to conceptualize intelligence that was originally identified in 1971 by Raymond Cattell (who is well known for his work on individual differences such as personality).

  Fluid intelligence (sometimes called ‘fluid reasoning’) is the ability to think logically and to solve problems in new situations without the need for previous or learned knowledge. Thus, people with good fluid intelligence are good at analysing novel problems by identifying the patterns and relationships that underpin these problems. Fluid reasoning includes inductive reasoning and deductive reasoning (as explained in Chapter 6).

  While fluid intelligence is independent of learning, crystallized intelligence is the ability to use learned skills, knowledge and experience. It is distinct from memory, though it does rely on accessing information from long-term memory. Crystallized intelligence uses what we have learned and thus involves vocabulary and general knowledge. This is why crystallized intelligence tends to improve with age, as the experiences we have throughout our lives tend to expand our knowledge. Crystallized intelligence is thus the product of both educational and cultural experience but it also interacts with fluid intelligence.

  The two intelligences are thus correlated with each other, and most IQ tests attempt to measure both varieties. For example, the Wechsler Adult Intelligence Scale (WAIS) measures fluid intelligence on the performance scale and crystallized intelligence on the verbal scale. The overall IQ score is based on a combination of these two scales.

  Fluid intelligence typically peaks in young adulthood and then steadily declines. This decline may be due to local atrophy of the right cerebellum in the brain, though some researchers have suggested that a lack of practice, along with age-related changes in the brain, may contribute to the decline. Crystallized intelligence, on the other hand, typically increases gradually, stays relatively stable across most of adulthood, and then begins to decline after age 65.

  Spotlight: Inteligenz-quotient

  The abbreviation ‘IQ’ was coined by the psychologist William Stern for the German term Intelligenz-quotient, his term for a scoring method for intelligence tests he advocated in a book he published in 1912.

  Measuring intelligence

  The pioneer of intelligence testing was the French psychologist Alfred Binet (1857–1911). In the early 1900s the French government was reforming education for children and wanted to know which children would benefit the most and which would need extra help. Binet, with his colleague Théodore Simon (1872–1961), attempted to design a battery of questions aimed at separating out the children likely to do well at school from those who were less likely. He focused on those skills not dependent on taught material, such as problem-solving (fluid intelligence). The test they devised was known as the Binet–Simon Scale and it is generally recognized as the first effective intelligence test (and it still forms the basis of measures of intelligence today).

  Binet realized that some children were able to answer more advanced questions than older children were generally able to answer, while other children of the same age were only able to answer questions that younger children could typically answer. Based on this observation, Binet developed the concept of a mental age, or a measure of intelligence based on the average abilities of children of a certain age group. A child’s mental age could be higher or lower than their chronological age.

  The Binet–Simon Scale was brought to the United States where the psychologist Lewis Terman from Stanford University took Binet’s original test and standardized it using a sample of American participants. This version, first published in 1916, was called the Stanford–Binet Intelligence Scale and soon became the standard intelligence test used in the United States. It utilized a single measure of intelligence that was known as the intelligence quotient
(or IQ). This score was calculated by dividing the test taker’s mental age by their chronological age, and then multiplying this number by 100. For example, a child with a mental age of eight and a chronological age of ten would have an IQ of 80 (8/10 x 100). No matter what the child’s chronological age, if the mental age matched the chronological age, then the IQ would equal 100. An IQ of 100 thus indicates a child of average intellectual development.

  Spotlight: The deviation method

  The old ‘ratio method’ of computing IQ as described above is no longer used. The currently used method is called the deviation method, and is based on the fact that IQ scores tend to closely follow a normal distribution (sometimes known as the ‘bell curve’ – see below).

  To map the IQ scores on to the normal distribution, the test was given to a large sample and the median (average) and standard deviation (a measure of score variability) computed for the group. These statistics were then used in a conversion formula to convert the ‘raw’ scores from the test into standard IQ scores that have a predetermined mean and standard deviation. When current IQ tests were developed, the mean raw score of the norming sample was defined as IQ 100 (i.e. an average IQ is 100). Approximately 95 per cent of the population have scores within two standard deviations (SD) of the mean. If one SD is 15 points, as is common in almost all modern tests, then 95 per cent of the population are within a range of 70 to 130, and 98 per cent are below 131. Alternatively, two-thirds of the population have IQ scores within one SD of the mean – that is, within the range 85–115.

  Spotlight: The bell-shaped curve

  IQ, like many attributes, is distributed within the general population in a way that follows a bell, or inverted U shape, with a few scores appearing at the farthest points from the centre and a large bulge of scores at and around the centre. This means that most people will score in the middle bulge with fewer people at either end. The bell curve is sometimes referred to as a Gaussian distribution, after the German mathematician and physicist Karl Gauss, who brought the model to the scientific community by using it to show the distribution of astronomical data.

  In psychological terms, the bell-shaped curve is referred to as the ‘normal distribution’ and any attributes that follow this shape are said to have a normal distribution (height is another example of a normally distributed attribute in that most people of a certain age and gender will have an average height, with only a few particularly tall or short people at either ends of the scale).

  During the First World War, intelligence testing really took off as the army needed to screen and test thousands of recruits quickly. Special army IQ tests were developed called Army Alpha and Beta and used to screen 2 million recruits. This heralded the arrival of mass IQ testing.

  THE WECHSLER INTELLIGENCE SCALES

  The next significant development in the history of intelligence testing was the creation of a new measurement instrument by the American psychologist David Wechsler (1896–1981). Like Binet, Wechsler believed that intelligence involved a number of different mental abilities but he felt that the Stanford–Binet Scale suffered from too many limitations (such as a heavy reliance on verbal ability). He thus developed the Wechsler Adult Intelligence Scale (WAIS) in 1955 and this is still in wide use today (although it has been revised several times since that first version – the one currently in use is WAIS-IV). Wechsler also developed two different tests specifically for use with children: the Wechsler Intelligence Scale for Children (WISC) and the Wechsler Preschool and Primary Scale of Intelligence (WPPSI).

  Rather than score the test based on chronological age and mental age, as was the case with the original Stanford–Binet, the WAIS is scored by comparing the test taker’s score to the scores of others in the same age group. The average score is fixed at 100, with two-thirds of scores lying in the normal range between 85 and 115. This scoring method has become the standard technique in intelligence testing and is also used in the modern revision of the Stanford–Binet test.

  The current version of the WAIS was released in 2008 and includes ten core subtests as well as five supplemental subtests. The test provides four major scores:

  • Verbal comprehension

  • Perceptual reasoning

  • Working memory

  • Processing speed.

  Additionally, WAIS-IV provides two overall summary scores:

  1 Full Scale IQ

  2 General Ability Index.

  RAVEN’S TEST OF INTELLIGENCE

  It is worth mentioning Raven’s Progressive Matrices as a test of intelligence since this is a non-verbal test and as such does not rely on verbal skill. This makes it suitable for young children or for people for whom language skill is an issue that could interfere with ordinary intelligence measures (e.g. where English is not their first language). The tests were originally developed by the English psychologist John Carlyle Raven (1902–71) in 1936, and in each test item the subject is asked to identify the missing element that completes a pattern. Many patterns are presented in the form of a 4 × 4, 3 × 3 or 2 × 2 matrix.

  The matrices are available in three different forms for participants of different ability:

  • Standard Progressive Matrices: these were the original form of the matrices, first published in 1938, with items within a set becoming increasingly difficult. All items are presented in black ink on a white background.

  • Coloured Progressive Matrices: these were designed for children aged five through eleven years of age, for the elderly, and for mentally and physically impaired individuals. Most items are presented on a coloured background to make the test visually stimulating for participants.

  • Advanced Progressive Matrices: the advanced form of the matrices contains 48 items and is appropriate for adults and adolescents of above-average intelligence.

  WHAT DO IQ TESTS REALLY MEASURE?

  Even the modern ‘IQ test’ is not a perfect measure of intelligence, with many researchers today claiming that all IQ tests really measure is your ability to do IQ tests. An intelligence quotient, or IQ, is a measure of ‘fluid and crystallized intelligence’. An IQ test thus measures reasoning and problem-solving abilities. There are different kinds of IQ tests, but most analyse visual, mathematical and language abilities as well as memory and information-processing speed. IQ is really a measure of how well you do in a test compared with other people of your age. However, IQ scores do not measure practical intelligence, creativity, common sense or emotional intelligence (see below) – all factors needed to perform and interact successfully with the world around us. IQs do not always stay stable either; they change slightly as we age and factors such as nutrition, stress and education can all affect them. Taking many IQ tests can also increase your score.

  Case study: The ‘Termites’

  In the early part of the twentieth century the American psychologist Lewis Terman (1877–1956) set up what was known as the Genetic Studies of Genius. Terman believed that IQ was all that was needed to predict future success and he set out to prove this by selecting an elite group of children using IQ tests. This group had an average IQ of 151 (which is very high).

  Terman then followed these children (who later called themselves ‘Termites’) through to adulthood and found that, 35 years later, his expectations appeared to have been proven. They were taller, healthier and more socially adept than average, and had an impressive array of accomplishments: nearly 2,000 scientific and technical papers and articles and some 60 books and monographs in the sciences, literature, arts, and humanities had been published by the Termites. Patents granted to them amounted to at least 230. Thirty-one of them appeared in Who’s Who in America.

  While the evidence certainly sounds impressive, the Termites study is not without its critics. For example, it is argued that the socio-economic status of the Termites was more of a predictor of their success than their IQ. There are also some who argue that even their impressive list of accomplishments is overshadowed by those of non-Termites of the same era: William Sho
ckley, for example, was rejected from the study as not being intelligent enough, yet went to Harvard, earned a doctorate and eventually a Nobel Prize in Physics, an award that not one of the Termites managed to earn.

  Over the years more than 100 scientific articles and almost a dozen books have been based on the Terman data.

  INTELLIGENCE AND CULTURE

  Researchers have long debated whether average differences in IQ scores – such as those between different ethnic groups – reflect differences in intelligence, social and economic factors, or both. The debate intensified in 1994 with the publication of The Bell Curve (the book’s title comes from the bell-shaped normal distribution of intelligence quotient scores in a population, described above) by Richard Herrnstein and Charles Murray, which suggested that the lower-than-average IQ scores of some ethnic groups, such as African-Americans and Hispanics, were due in large part to genetic differences between them and Caucasian groups.

  ‘It seems highly likely to us that both genes and the environment have something to do with racial differences [in IQ].’

  R. Herrnstein and C. Murray, The Bell Curve (New York: Free Press, 1994)

  That view has been challenged by many scientists. The Bell Curve prompted the publication of several multiple-author books responding with a variety of points of view. They include The Bell Curve Debate (1995), Inequality by Design: Cracking the Bell Curve Myth (1996) and a second edition of The Mismeasure of Man (1996) by Steven J. Gould. More recent examples of responses to the arguments in The Bell Curve include that of Richard Nisbett, a psychologist at the University of Michigan, in his 2009 book Intelligence and How to Get It, in which he argued that differences in IQ scores found were largely as a result of social and economic factors and that, by controlling for these, the differences between ethnic groups largely disappeared.

 

‹ Prev