Which term describes intelligence that reflects the ability to solve and reason about novel problems?

Fluid intelligence (Gf) is defined as reasoning ability, and the ability to generate, transform, and manipulate different types of novel information in real time.

From: Aging and Decision Making, 2015

Assessment

Alan S. Kaufman, Elizabeth O. Lichtenberger, in Comprehensive Clinical Psychology, 1998

4.08.3.5 DTLA-3 Integration with Wechsler Scales

The DYLA-3 has several theoretical underpinnings, including models such as fluid and crystallized intelligence, simultaneous and successive processes, and verbal and performance abilities. DTLA-3 subtests may be used to augment the Wechsler scales in several instances. To further assess perceptual organization ability, fluid ability, and simultaneous processing, Design Reproduction or Symbolic Relations may be administered. For hypotheses regarding similar fluid abilities, but tapping sequential processing, examiners may administer Design Sequences. DTLA-3 Design Reproduction is also a good supplement Wechsler Performance subtests if there is a question regarding a person's ability being hampered by response speed tests. This test does require visual-motor coordination but places minimal demands on speeded performance. Like the K-ABC, the DTLA-3 offers some alternative modalities of receiving input and expression of response to supplement Wechsler subtests that mainly use the auditory-vocal and visual-motor channels of communication. The DTLA-3 offers two subtests which call for use of the visual and vocal modalities (Story Construction and Picture Fragments), and has one subtest that uses the auditory-motor channel (Reversed Letters).

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Neuropsychological Battery Patterns

Elbert W. Russell, in The Scientific Foundation of Neuropsychological Assessment, 2012

Fluid and Crystallized Effect

Another generalized effect of brain damage is that produced by fluidity or the difference between fluid and crystallized intelligence (Cattell, 1963; Russell 1986, pp. 63–64).This was thoroughly discussed previously and need not be discussed here. However, note that there has been a general and long-accepted concept that brain damage produces a tendency for the individual to shift from abstract to concrete thinking (Goldstein & Scheerer, 1941; Walsh, 1978). This effect may, in fact, represent a tendency for brain-damaged individuals to change from a more fluid form of thinking to a more crystallized form (Russell, 1986, p. 60). Because crystallized intelligence remains more intact, it is a more reliable means of dealing with problems when the brain’s functioning is impaired.

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Handbook of Sleep Research

van den BergN.H. , ... FogelS. , in Handbook of Behavioral Neuroscience, 2019

II Sleep Oscillations and Cognitive Abilities

A NREM Sleep

Among the most influential and longest-standing theoretical models of intelligence is Raymond B. Cattel's concept of fluid intelligence and crystallized intelligence (Carroll, 1993; Cattell, 1963; Cattell & Horn, 1978), which includes the common assumption that intelligence can be more accurately described as a subset of factors consisting of distinct cognitive domains and skills. Particularly, compelling neuropsychological support for this model of intelligence has relied on functional neuroimaging to delineate factors based on activation of distinct neural networks in response to increasing demands across a wide variety of tasks adapted from classic neuropsychological tests (Hampshire, Highfield, Parkin, & Owen, 2012). Interestingly, two of the main data-driven, activation-derived factors across 12 cognitive tasks in a large (N = 44,600) sample, synonymously termed “reasoning” and “verbal” abilities, map onto Cattel's concepts of fluid and crystallized intelligence, providing support that these trait-like cognitive abilities are supported by distinct neural substrates.

The sleep spindle is the only known spontaneous neural oscillation that has been identified as an electrophysiological marker of cognitive abilities and aptitudes that are typically assessed by intelligence quotient (IQ) tests (for review, see Fogel & Smith, 2011). As one of the defining features of NREM2 sleep, spindles are traditionally defined as neural oscillations between 11 and 16 Hz (Iber, Ancoli-Israel, Chesson, & Quan, 2007) and lasting up to ~ 3 seconds in duration (Rechtschaffen & Kales, 1968). Spindles are remarkably stable from night to night but vary considerably from one individual to another and have even been suggested to be an “electrophysiological fingerprint” (De Gennaro, Ferrara, Vecchio, Curcio, & Bertini, 2005), due to the trait-like nature of spindles (Silverstein & Levy, 1976). Previous studies have revealed that interindividual differences in spindle characteristics are related to the capacity for reasoning, that is, the ability to identify complex patterns and relationships, the use of logic, existing knowledge, skills, and experience to solve novel problems (Fogel & Smith, 2006; Fogel, Smith, & Cote, 2007; Nader & Smith, 2001, 2003). Moreover, the relationship between spindles and cognitive abilities is predominantly specific to the capacity for reasoning and not verbal abilities or short-term memory (Fang, Ray, Owen, & Fogel, 2019; Fogel, Nader, Cote, & Smith, 2007), suggesting that spindles are heavily involved in fluid intelligence as reflected through the capacity to identify and solve novel, logical problems. Together, these studies have provided insight into the electrophysiological correlates of reasoning abilities, insofar as they suggest that efficient functioning of the neural substrates that support spindle generation (e.g., thalamocortical circuitry) may be related to the capacity for these cognitive skills. Interestingly, spindle generation is reduced with age (Carrier, Land, Buysse, Kupfer, & Monk, 2001; Fogel et al., 2014, 2017) and is abnormal in developmental disorders such as autism (Limoges, Mottron, Bolduc, Berthiaume, & Godbout, 2005), learning disabilities (Shibagaki, Kiyono, & Watanabe, 1982), and schizophrenia (Wamsley et al., 2012). Thus, a better understanding of the neural basis of the relationship between spindles and cognitive abilities may ultimately help to better understand the significance for a variety of normal and abnormal cognitive functioning in healthy individuals and in neurological conditions. This may eventually lead to novel interventions to precisely target cases where spindle production is abnormal or nonoptimal. However, it is necessary to first understand the physiological mechanisms of the relationship between spindles and reasoning abilities in healthy individuals.

The association between sleep spindles and individual differences in cognitive abilities has been well documented by a number of different research groups. For example, both the number of sleep spindles and sigma power (12–14 Hz) have been uniquely correlated with performance IQ scores, but not verbal IQ (Fogel, Nader, et al., 2007). Consistently, Bódizs et al. (2005) found that spindle density was correlated with reasoning abilities (i.e., “fluid intelligence”), measured by Raven's Progressive Matrices. Similar studies identified a positive correlation between right-parietal fast spindles and visuospatial abilities assessed by the Rey-Osterrieth complex figure test (Bódizs, Lázár, & Rigó, 2008) and a positive correlation between spindles and the intellectual abilities measured by the Cattell culture fair intelligence test, specifically in women, but not men (Ujma et al., 2014). However, a similar relationship in men was subsequently identified in daytime sleep by the same group (Ujma et al., 2015). Most recently, Fang and colleagues (Fang, Sergeeva, et al., 2017) used the Cambridge Brain Sciences (CBS) test battery (Hampshire et al., 2012) to explore if the relationship between sleep spindles and intellectual ability was a direct relationship or whether it could be partially (or fully) explained by other spindle-related factors such as sleep quality or circadian chronotype. Fang and colleagues found that the relationship between spindles and reasoning abilities was independent of sleep quality and circadian chronotype (Fang, Sergeeva, et al., 2017). Taken together, these studies support the notion that sleep spindles are an electrophysiological marker of cognitive abilities, specifically the ability to solve problems using logic and reasoning.

At the same time, the neuroanatomical and neurophysiological mechanisms that mediate the relationship between spindles and reasoning abilities are largely unknown. Only a small number of EEG-fMRI studies have explored the patterns of brain activation that are associated with spindle generation (Andrade et al., 2011; Caporro et al., 2011; Laufs, Walker, & Lund, 2007; Schabus et al., 2007; Tyvaert, Levan, Grova, Dubeau, & Gotman, 2008). Interestingly, some of the brain regions that were identified in this work are also known to support reasoning abilities. For example, in a preliminary report, we recently identified neural activation patterns that are time-locked with spindles and correlate with cognitive abilities (Fang, Sergeeva, et al., 2017). Using simultaneous EEG-fMRI sleep recordings, activations time-locked to spindles were observed in the thalamus, bilateral striatum, middle cingulate cortex, and cerebellum. Further, reasoning abilities were correlated with spindle-related activations in the thalamus, bilateral striatum, medial frontal gyrus, middle cingulate cortex, and precuneus. These results were specific to spindles and cannot be attributed to some epiphenomena during NREM sleep, given that these results were not observed when random onsets during NREM sleep were used instead of onsets time-locked to spindle events. Together, these results identified, for the first time, the neural correlates of the relationship between spindles and reasoning abilities. Thus, spindles may serve as an electrophysiological marker of brain activations in brain regions that support the ability to employ reasoning to solve problems and apply logic in novel situations.

B REM Sleep

As discussed above, there is a wealth of support suggesting that sleep spindles are electrophysiological markers of cognitive abilities, particularly of fluid intelligence. However, the investigation of these phenomena has been highly focused on spindles, and very few studies have looked more broadly at other stages of sleep or additional features of NREM sleep. Nevertheless, at least a handful of studies provide some provocative support for the notion that interindividual differences in REM sleep might relate to trait-like cognitive abilities as well. Smith, Nixon, and Nader (2004) found that postlearning performance on procedural tasks that tap into reasoning skills was correlated with REM density. Interestingly, this relationship was strongest in individuals with high IQ scores. In a separate study (Fogel, Nader, et al., 2007), in individuals with a high IQ (i.e., reasoning/performance IQ scores from 115 to 126, compared with medium 108–114 and low 77–107 IQ scores), rapid eye movements were correlated with crystallized intelligence, but not fluid intelligence. This suggests a double dissociation for the relationship between spindles in NREM sleep and eye movements in REM sleep for fluid intelligence and crystallized intelligence, respectively. One of the earliest studies establishing this link (De Koninck, Lorrain, Christ, Proulx, & Coulombe, 1989) found that, during a period of intensive second-language learning, individuals who progressed the fastest experienced incorporations into REM-based dreams earlier and experienced more verbal communication in their dreams compared with those who made little progress. Taken together, these studies are consistent with the notion that there is a relationship between cognitive abilities and specific features of REM sleep, particularly for verbal abilities. However, this intriguing distinction remains to be fully explored.

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Intelligence: Historical and Conceptual Perspectives

E. Hunt, in International Encyclopedia of the Social & Behavioral Sciences, 2001

4.1 The Individual Level

At the individual level, it becomes important to distinguish between physical and social causes of cognitive competence, and between fluid and crystallized intelligence (Gc and Gf). People who perform well on tests of fluid intelligence and reasoning are, to a very large extent, people who are adept at keeping track of several things at once, and who can manage fairly large amounts of information. This ability is known as an ability to manage ‘working memory’ for information relevant to the problem currently being worked on. It is contrasted with ‘long-term memory,’ which refers to memory for information about how the world works and information about biographic events that happened some time ago. Working memory, in turn, appears to be related to the functioning of the frontal and prefrontal areas of the brain. There is now a good deal of evidence suggesting (but not yet proving) that individual differences in the ability to activate information in these areas of the brain is related to scores on tests of fluid intelligence. Just what these relations are, and how they relate to individual differences in neural functioning in other parts of the brain, is an important topic in research on intelligence.

While individual differences in fluid intelligence are related to individual differences in brain functioning, it is important not to exaggerate the relationship. Statistical analyses suggest that individual differences in brain functioning can account for only a part of the wide individual differences in the ability to deal with ‘new and unusual problems,’ that is, fluid intelligence. By default, the remaining influences must be social (e.g., education, early training that might set a particular style for problem solving), but as of this article psychologists have been unable to determine what these environmental influences are.

The situation is quite different for tests of crystallized intelligence, that is, the ability to recognize and apply previously acquired solutions to new situations. In part this ability appears to depend upon generalized pattern-recognition abilities in the brain. However, it is also extremely responsive to education and training. This is seen most clearly by studies of expertise, individual differences in solving problems within a particular domain. Study after study has shown that specialized problem-solving depends upon the acquisition of schematic forms of reasoning appropriate to the domain at hand. Furthermore, these schema are very largely acquired by extensive practice. This has been shown in domains as far apart as chess, physics, and economics. Fluid intelligence appears to be one determinant of how efficiently information can be acquired during the schema-acquisition period. (This may partially account for the correlation between measures of fluid and crystallized intelligence.) However, knowledge builds on knowledge, so soon the expert has an advantage over the novice in learning how to learn within a particular field. Whether or not there is a generalized ability to learn to learn, regardless of the field being studied, is an open question. If there is, this ability is probably quite closely related to fluid intelligence.

As would be expected, any influence that causes a deterioration of brain structure is likely to have a deleterious effect on intelligence. In modern industrialized society alcoholism is undoubtedly the biggest single effect; repeated studies have shown a negative correlation between excessive alcohol use and intelligence test performance. Once again, whether or not this is causal is hard to determine, as excessive alcohol use could either produce or be produced by low intelligence. However, the effect can be transgenerational. A major cause of mild mental retardation in children is excessive alcohol use by the mother during pregnancy. Other negative influences on intelligence include prolonged malnutrition (primarily in the developing nations) and exposure to atmospheric lead.

Aging has a paradoxical effect on intelligence. Fluid intelligence test scores drop. This is not surprising, as there is considerable evidence for an age-related drop in performance in tasks involving working memory. However there are very large individual differences in the extent of the drop. If we compare the fluid intelligence test scores of otherwise comparable individuals in their 20s and 60s we find that the top scores of the older group are only slightly below the top scores of the younger examinees, but the lowest scores in the older group are considerably below the lowest scores in the younger examinees.

Crystallized intelligence, in the sense of scores on such things as vocabulary and knowledge tests, may rise slightly during the adult working years, and declines only slowly until people reach their 70s or beyond. Because we live in a specialized society this may actually underestimate the abilities of older people. People become quite competent in those things that they practice, so during their working years people may become ‘cognitive specialists’ in the tasks that they encounter every day. Perhaps for this reason, general cognitive tests, such as the Department of Labor's General Aptitude Test Battery (GATB), seem to underestimate the out-of-laboratory performance of older workers. Of course, these statements apply only so long as the workplace and social environments remain the same.

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Aging and Education

S.L. Willis, J.A. Margrett, in International Encyclopedia of the Social & Behavioral Sciences, 2001

A well-established approach to the study of adult cognitive ability has been the examination of higher-order dimensions of psychometric mental abilities, particularly fluid and crystallized intelligence (Horn and Hofer 1992). Fluid intelligence refers to abilities needed for abstract reasoning and speeded performance whereas crystallized intelligence refers to knowledge acquired through one's culture including verbal ability and social knowledge (Schaie 1996).

Longitudinal research examining cognitive development has revealed that mental abilities vary in their developmental trajectories across adulthood (e.g., the Seattle Longitudinal Study: Schaie 1996, the Berlin Aging Study: Smith and Baltes 1999). A substantial body of research in the USA has demonstrated that fluid abilities, such as inductive reasoning, peak in early middle adulthood rather than in adolescence as previously thought. Fluid abilities remain stable in middle age and first show reliable decline in the mid-sixties. In contrast, crystallized abilities, such as vocabulary, do not peak until middle age and show reliable decline later in the mid-seventies (Schaie 1996). Similar developmental trajectories in abilities have been reported in Canadian and European longitudinal research (Backman 2001).

Decline in cognitive ability prior to age 60 is usually considered to be associated with ensuing pathological changes, and universal decline on all markers of intelligence in normal elderly is not evident even by the eighties (Schaie 1996). Findings from Swedish longitudinal study demonstrate that even the oldest-old (i.e., a sample of individuals aged 84 and older), who do not exhibit cognitive impairment at baseline assessment, demonstrate relative stability over a two-year period on several markers of cognitive ability (Johansson et al. 1992).

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Geriatric Neuropsychological Assessment

John L. Woodard, in Handbook of Assessment in Clinical Gerontology (Second Edition), 2010

Kaufman Adolescent and Adult Intelligence Test (KAIT; Kaufman & Kaufman, 1993, 1997)

The KAIT was developed as an individually administered intelligence test for persons between the ages of 11 and 85 years and older. It was based on an integration of the fluid and crystallized intelligence model (Horn & Cattell, 1966, 1967; Horn, 1985, 1989), as well as aspects of Piaget's theory of formal operations (Piaget, 1972) and Luria's neuropsychological concepts of planning ability (Luria, 1980). The integration of multiple theories of intelligence and cognitive processing lends considerable appeal to this measure.

The KAIT yields Fluid, Crystallized, and Composite IQs with a mean of 100 and standard deviation of 15. A 60-minute Core Battery may be administered, or additional data (including delayed recall) may be obtained by administering a 90-minute Expanded Battery. The Expanded Battery is typically recommended for use with older adults, given the presence of the additional neuropsychological components in the battery. The normative sample consisted of 2000 adolescents and adults between the ages of 11 and 94 years. The upper age group includes 100 persons between the ages of 75 and 94 years (65 females and 35 males), a group that spans nearly two decades. The lack of more age-specific normative data in the upper end of the age spectrum is potentially problematic. Nevertheless, age-related differences in fluid and crystallized intelligence across the lifespan are observed in the normative data for the KAIT (Kaufman & Kaufman, 1997). Crystallized intelligence abilities increased or remained the same through 50 years of age and did not begin to decline until ages 75 and older. Fluid intelligence abilities reached a peak around 20 years of age followed by a plateau between 20 and 50 years of age, and ending with a drop in ability after 55 years of age.

The subtests of the KAIT are generally quite novel and are unlike many cognitive measures routinely used in clinical practice. The Crystallized IQ scale is made up of four subtests: Definitions; Auditory Comprehension; Double Meanings; and Famous Faces. The Definitions subtest assesses knowledge of word meanings. It presents several letters of the target word, along with blanks indicating several other missing letters. In addition, a clue about the word's meaning is presented, and the examinee must use the configuration of the word along with the clue to identify the target word. Auditory Comprehension requires listening to a recording of a news story and then answering questions about the story. Double Meanings presents two sets of word clues, and the examinee must find a word that is closely related to both word clues. Famous Faces, an alternate subtest, involves identifying the names of famous individuals based on a photograph and a verbal clue.

The Fluid Scale includes four subtests. Rebus Learning requires the examinee to associate a word or concept with various rebus drawings. “Sentences” of rebuses are then presented, and the examinee must interpret the sentence using only the rebuses. Logical Steps involves logical reasoning skills based on visual and auditory premises. Based on the premises given, the examinee must respond to a series of questions by applying logical reasoning skills. Mystery Codes requires the examinee to identify specific codes associated with a picture and then deduce a code for a novel picture based on the preceding codes and pictures. This task involves a timed component. Memory for Block Designs is an alternate subtest for the Fluid Scale. An abstract design is briefly presented to the examinee and subsequently removed. The examinee must recall the design and reproduce it using six cubes. This measure is also timed.

Additional subtests include Rebus Delay Recall and Auditory Delayed Recall. These measures assess the ability to recall the previously learned rebuses after 45 minutes and the ability to recall the previously presented news story after 25 minutes, respectively.

Despite its excellent initial normative data, there do not appear to be revised normative data available to reflect changing census demographics. The measure consists of a number of novel, theoretically based tests, but unfortunately, relatively few research studies have employed the KAIT. The integration between assessment of both intellectual and neuropsychological abilities is highly appealing, particularly for older adults. Updated normative data and/or a revised version of the KAIT may enhance its utility in the future. Nevertheless, consideration should be given to the KAIT in research settings where assessment of fluid and crystallized intellectual skills are of interest.

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Measures of the Trait of Confidence

Lazar Stankov, ... Simon A. Jackson, in Measures of Personality and Social Psychological Constructs, 2015

Results and Comments

Much of the work employing confidence ratings to assess online judgments of accuracy has been carried out with cognitive tests. In our empirical work, we have employed virtually all types of cognitive tests used in studies of fluid (Gf) and crystallized (Gc) intelligence (see Carroll, 1993). These included measures of higher mental processes, such as memory, creative and critical thinking, and perceptual tests from visual, auditory, tactile, kinesthetic and movement/sport, olfactory and gustatory modalities. Perceptual tests, like the Line Length test (Kleitman & Stankov, 2001; Stankov, Pallier et al., 2012) can be used in studies of developmental changes during childhood since measures of Gf and Gc may be much more sensitive to age-related changes during childhood.

Although psychometric properties of online measures of confidence are satisfactory, some educational psychologists have been reluctant to embrace their use. A common reason appears to be the perceived close temporal proximity between the cognitive activity of solving a problem and confidence in the accuracy of the solution itself. It seems that those holding such views fail to appreciate empirical evidence showing that typical correlations of .40 to .60 between accuracy and confidence are similar in size to the correlations between measures of fluid and crystallized intelligence and that a separate confidence factor has been repeatedly reported (e.g., Stankov, 2000).

Below we present two scale examples employing different online measures of confidence. The first, the Proverbs Matching Test – a subtest of the Stankov Test of Cognitive Ability (STOCA) battery that measures both crystallized and fluid intelligence – uses a discrete, categorical, numerical scale (Stankov & Dolph, 2000). The second, the Future Life Events Scale (Kleitman, 2008; Kleitman & Stankov, 2007), employs a discrete verbal scale based on Sureness, rather than confidence itself. The sureness scale is presented here in order to illustrate that cognitive processing may be minimal, and yet the validity of the Sureness scale is comparable to the online assessment used in the Proverbs Matching Test.

Proverbs Matching Test

Directions:

In this test you will be given proverbs. Your task is to choose a proverb that is the closest in meaning to the first. Here is an example:

‘Birds of a feather flock together.’

(a)

Opposites attract

(b)

Tell me what company you keep and I will tell you who you are

(c)

There is little friendship in the world and least of all between equals

(d)

To check an elephant, inspect its tail

(e)

Shared joy is doubled joy

In this example the correct answer is (b) since ‘Tell me what company you keep and I will tell you who you are’ is closer in meaning to the ‘Birds of a feather flock together’ than any other alternative answer.

After each item you will be asked to state how confident you are that your answer is correct. A guess corresponds closely to 0% confidence so you should give this as your rating. Absolute certainty corresponds to 100% confidence. Please make your choice from the ratings provided on the sheet. Please work as quickly and accurately as you can.

1.

The truth is immortal, but the man who tells the truth will become dead.

Truth lies at the bottom of a well.

Better a lie that heals than a truth that wounds.

One is always wrong, but with two, truth begins.

Truth is mighty and will prevail.

The truth of a word depends on how you understand it.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

2.

A fisherman of shallow seas uses a short line; a fisherman of deeper seas uses a long line.

No bird soars too high, if she soars with her own wings.

Those who say it cannot be done are usually interrupted by others doing it.

You will only reach as far as you aim and prepare yourself to reach.

Vision is not seeing things as they are, but as they will be.

One can never consent to creep when one feels an impulse to soar.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

3.

Empty vessels make the most sound.

Tall trees often have shallow roots.

Still waters run deep.

A tiger hides its claws.

Better to remain silent and be thought a fool than to speak out and remove all doubt.

If the beard were all, goats might preach.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

4.

Virtue is its own reward

Some rise by sin, others by virtue fall.

There are no fans in hell.

In social life, we please more often by our vices than our virtues.

Be good and you will be lonesome.

Virtue is goodness, not material or money.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

5.

The journey of a thousand miles begins with one step.

To travel hopefully is better than to arrive.

Traveler, there is no trail: you blaze the trail as you travel.

A man travels the world over in search of what he needs and returns home to find it.

One may not reach the dawn save by the path of night.

He who is outside the door already has a good part of the trip behind him.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

6.

Better to understand little than to misunderstand a lot.

The difference between genius and stupidity is that genius has its limits.

The opinion of the intelligent is better than the certainty of the ignorant.

A great many people think they are thinking when they are merely rearranging their prejudices.

What he doesn't know would make a library anybody would be proud of.

It isn't what a man doesn't know that makes him a fool, but what he does know that isn't so.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

7.

A careless watch invites the thief.

A full cup must be carried steadily.

A greedy eye never got a good bargain.

He that shows his purse longs to be rid of it.

Everyone carries a fool under his coat, but some hide it better than others.

Great possessions depend on fate; small possessions come from diligence.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

8.

Silence is one great art of conversation

Silence is the only thing that can't be misquoted.

When the mouth stumbles, it is worse than the foot.

When you are arguing with an idiot, make sure the other person isn't doing the same thing.

Silence is the ultimate weapon of power.

You can win more friends with your ear than you can with your mouth.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

9.

The smallest leak sinks the largest ship.

A chain is only as strong as its weakest link.

Do not draw your sword to kill a gnat.

The fish which you did not catch is always big.

The pitcher goes so often to the well that it is broken at last.

The last straw breaks the camel’s back.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

10.

In prosperity our friends know us; in adversity we know our friends.

Never speak ill of yourself; your friends will always say enough on that subject.

A real friend is one who walks in when the rest of the world walks out.

He who whips the dog of a friend whips the friend himself.

A good friend is worth more than money in your pocket.

A friend is someone that won't begin to talk behind your back the minute you leave the room.

How confident are you that your answer is correct?

20% 30% 40% 50% 60% 70% 80% 90% 100%

Future Life Events Scale

This scale will ask you to state what you believe the chance of a particular thing happening in future to be. You will also be asked to indicate how sure you are about your opinion.

The following statements describe various events that may or may not happen. On a scale between 0 and 100, please indicate how likely each event is to occur. Thus, if you felt that an event was very likely, you should write a number close to 100; if you felt an event was very unlikely, you’d write a number close to 0; and you felt an event was about equally likely and unlikely, you’d write a number close to 50.

We also want you to indicate how sure you are of your opinion. Please circle one of the options next to the sentence after you completed it.

Each question is accompanied by the following rating scale:

Not sure at all Slightly sure Moderately sure Quite sure Very sure

The chances that you’ll be successful in your chosen career are about_______ in 100.

The probability that a cure for cancer will be eventually found is about ________ in 100.

The chance that if you put some effort into mathematical training, you’d be able to do well in mathematics is about _______ in 100.

On average, the chance of passing a driving test at the first attempt is about _______ in 100.

The chances that the problem of terrorism will be solved are about _______ in 100.

The chance that if you put your mind into something, your goals would come true is about ______ in 100.

The chances that virtual reality will become the main entertainment in the future are about _______ in 100.

The probability that the human race will survive for another thousand years is about _____ in 100.

The chance that if you put your mind and effort into solving a problem, you would succeed is about _______ in 100.

The chance that if you open a business it would succeed is about _______ in 100.

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Intelligence Testing

Wilma C.M. Resing, in Encyclopedia of Social Measurement, 2005

Kaufman's Intelligence Batteries

In 1983, the Kaufman Assessment Battery for Children (K-ABC; American Guidance Service), an intelligence tests for children ages 2.5–12.5 years, was constructed from a theoretical perspective in which Cattell's distinction between fluid and crystallized intelligence was combined with the Luria's neuropsychological ideas about the importance of simultaneous versus sequential mental processing. Test scores on four intellectual domains can be administered: sequential processing, simultaneous processing, mental processing (which is the first two domains combined), and achievement. The scales have high reliability coefficients. Separate percentile norms have been presented for different ethnic and socioeconomic groups.

Kaufman constructed two other intelligence tests: the Kaufman Adolescent and Adult Intelligence Test (KAIT; 1993) and the Kaufman Brief Intelligence Test (K-BIT; 1990). The KAIT was designed for the age range 11–85 years. The test has a good reliability. Validity coefficients with WISC-R and WAIS-R can be interpreted as high. The K-BIT was designed as a screening instrument to get a quick estimation of the intelligence level of an examinee. The structure of the test differs from KAIT or K-ABC, consisting of only two subtests: a vocabulary test and a nonverbal subtest for inductive reasoning (matrices). The K-BIT is designed for the age range 4–90 years and takes only 15–20 minutes.

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Intelligence

M. LövdénU. Lindenberger, in Encyclopedia of Gerontology (Second Edition), 2007

Two-Component Models of Life Span Changes in Intelligence

Two-component models of life span changes in intelligence posit that development of intellectual abilities can be mapped onto biological versus cultural ensembles of influences (see Figure 1). Typical contemporary examples for two-component models are the distinction between fluid and crystallized intelligence advanced by Raymond B. Cattell and John Horn and the decomposition of cognition into mechanics and pragmatics proposed by Paul Baltes. Two-component models of life span changes in intelligence have a long history dating back to Johann Nicolaus Tetens (1736–1807), a philosopher and psychologist of the enlightenment era who noted that well-trained skills are less likely to decline with advancing age than the basic abilities underlying their acquisition. Thus, and most importantly, two-component theories dispute the validity of a unitary general intelligence construct in understanding intellectual development across the life span. Instead, at least two broad, ontogenetically intertwined but separable categories of abilities are needed to describe the basic properties of intellectual development.

Which term describes intelligence that reflects the ability to solve and reason about novel problems?

Figure 1. Two-component models of cognition. The top section defines the two categories of intellectual abilities and the bottom section illustrates postulated life span trajectories. In very old age, the trajectories become less differentiated because the fluid mechanics increasingly constrain the acquisition, expression, and representation of pragmatic knowledge.

The first collection of intellectual abilities represents measurable outcomes of the influence of the biological component on development. It manifests itself in cognitive processes involving extrapolation, reorganization, and transformation of novel information (i.e., reasoning) and in basic information processes such as working memory (i.e., the ability to maintain information online while manipulating it), processing speed (i.e., the speed with which elementary processing operations can be performed), and cognitive control (i.e., the top-down coordination and control of lower-level processing). Henceforth, these processes are referred to as the fluid mechanics of intelligence.

The second, more disparate category of intellectual abilities refers to procedural and declarative knowledge common to a given culture (e.g., verbal knowledge), but also to specialized and sometimes highly idiosyncratic (person-specific) knowledge such as occupational expertise, as well as to knowledge about the meaning and conduct of life. Henceforth, these processes are referred to as the crystallized pragmatics of intelligence. For examples of specific abilities and functions related to each of the two components, see Figure 2.

Which term describes intelligence that reflects the ability to solve and reason about novel problems?

Figure 2. Exemplary functions and abilities in the broad domains of the fluid mechanics and the crystallized pragmatics.

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Intelligence

Douglas Wahlsten, in Genes, Brain Function, and Behavior, 2019

Diversity of Tests

One perplexing fact about intelligence tests today is that the experts do not agree on the nature of intelligence or how many kinds of intelligence exist. Spearman and Burt argued that there was just one important kind—general intelligence. Raymond Cattell claimed there were two, fluid and crystallized intelligence. Robert Sternberg opts for a three-part (triarchic) conceptualization. Leon Thurstone believed that seven different factors combine to make a person intelligent. Howard Gardner sees evidence of perhaps eight and maybe even more kinds of intelligence. Daniel Goleman argues for the existence of emotional and cognitive intelligence. Many of the major theorists devised their own tests to tap the abilities featured in the theories. When the same children take two of these tests, there is usually a substantial positive correlation between the scores, but it never approaches a perfect correlation. Each test seems to weight the various features of the human mind a little differently.

Unlike the profession of psychiatry where there has been a decade-long effort to formulate a common diagnostic terminology and criteria, embodied in the DSM and ICD, psychology has its own professional organizations, usually a main one in each country, but no consensus version of an intelligence test to recommend. Instead, scientific psychology has developed an elaborate technology for constructing, evaluating, and using psychological tests. The American Psychological Association provides a number of standards for professional practice and education that are considered mandatory, but the APA website states emphatically that “APA's Testing Office does not maintain, sell, or endorse any tests.” The Buros Center at the University of Nebraska-Lincoln publishes a massive Mental Measurements Yearbook (Carlson, Geisinger, & Jonson, 2017) with in-depth reviews of many tests.

After more than 100 years of experience with many kinds of tests, there is at least a consensus that several of them are reasonably good (Table 15.3). They have been revised several times to correct shortcomings and restandardized to reflect continuing changes in the population of people where they will be applied. A full kit including a detailed instruction manual with norms and scoring sheets can be purchased from commercial websites, and several of them are making available much less costly versions that can be administered and scored via the Internet.

Table 15.3. Current Intelligence Tests

Test nameEditionStandardization sampleAges (years)Time (min)
Bayley Scales of Infant Development3 1409 1–42 months 30–90
Kaufman Assessment Battery for Children2 3025 3–18 25–55
Kaufman Brief Intelligence Test2 Based on US census 4–90 20
Naglieri Nonverbal Ability Test—Individual2 1500 5–17 25–30
Raven's Colored Progressive Matrices2003 No norms 5–11 15–30
Stanford-Binet Intelligence Scales5 4800 2–85 50
Wechsler Intelligence Scale for Children5 2200 6–16 60
Wechsler Adult Intelligence Scale4 2200 16–90 60–90

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What is meant by crystallized intelligence?

Definition. Crystallized intelligence (abbreviated Gc) is reflected in a person's general knowledge, vocabulary, and reasoning based on acquired information. It is contrasted with fluid intelligence (see Fluid Intelligence) as one of the two factors of general intelligence first proposed by Cattell (1971).

What is the meaning of fluid intelligence?

Fluid intelligence (Gf) is defined as reasoning ability, and the ability to generate, transform, and manipulate different types of novel information in real time. From: Aging and Decision Making, 2015.

What is an example of crystallized intelligence?

The use of crystallized intelligence involves the recalling of pre-existing information as well as skills. For example, knowing how to ride a bike or read a book. Horn (1969) explained that Crystallized Intelligence is a “precipitate out of experience” which stems from a prior application of fluid intelligence.

What are the two types of intelligence?

There are two specific types of intelligence, called fluid intelligence and crystallized intelligence.