Have backward digits sunk Flynn?

Have backward digits sunk Flynn?
James Thompson (Nov 2014)

Vocabulary: humanity’s greatest achievement?

Vocabulary: humanity’s greatest achievement?
James Thompson (June 2013)


Some quotes:

"As a rough guide, teenagers have about 12,000 words and college students 17,000. Older adults have 17,000 to 21,000 words, and a minority have many more.  Some conceited person referred to 20,000 words as being “the incoherence boundary”. I eschew such contemptuous judgements."

"intelligence ranges from 0 to 45,000 words (the real upper limit if one avoids technical jargon)"

"Knowledge of the 3000 most frequent words in the English language will probably result in your understanding 95% of what is said to you, and knowledge of 5000 “word families” (the main word and its variants, like quick: quickly, quicker, quickest) should mean that you would be able to understand 99.9%. "

"much of good thinking depends on a powerful vocabulary."

[See also: test your vocabulary (part 1) & test your vocabulary (part 2) & Bias in Mental Testing p. 145-147]

The cognitive competences of immigrant and native students across the world: An analysis of gaps, possible causes and impact.

The cognitive competences of immigrant and native students across the world: An analysis of gaps, possible causes and impact.

Heiner Rindermann & James Thompson (Nov 2014)
Journal of Biosocial Science


Summary

Immigration, immigration policies and education of immigrants alter competence levels. This study analysed their effects using PISA, TIMSS and PIRLS data (1995 to 2012, N=93 nations) for natives' and immigrants' competences, competence gaps and their population proportions. The mean gap is equivalent to 4.71 IQ points. There are large differences across countries in these gaps ranging from around +12 to −10 IQ points. Migrants' proportions grow roughly 4% per decade. The largest immigrant-based ‘brain gains’ are observed for Arabian oil-based economies, and the largest ‘brain losses’ for Central Europe. Regarding causes of native–immigrant gaps, language problems do not seem to explain them. However, English-speaking countries show an advantage. Acculturation within one generation and intermarriage usually reduce native–immigrant gaps (≅1 IQ point). National educational quality reduces gaps, especially school enrolment at a young age, the use of tests and school autonomy. A one standard deviation increase in school quality represents a closing of around 1 IQ point in the native–immigrant gap. A new Greenwich IQ estimation based on UK natives' cognitive ability mean is recommended. An analysis of the first adult OECD study PIAAC revealed that larger proportions of immigrants among adults reduce average competence levels and positive Flynn effects. The effects on economic development and suggestions for immigration and educational policy are discussed.

Cognitive Human Capital and Economic Growth in the 21st Century

Cognitive Human Capital and  Economic Growth in the 21st Century
Gerhard Meisenberg (2014)


Abstract

This chapter explores the interdependency between economic growth and cognitive human capital, which is also described as cognitive skills or intelligence and is measured either as performance in scholastic achievement tests or IQ. It shows that unlike the mere amount of schooling, intelligence has been a robust predictor of economic growth in the recent past. Plausible mediators of the intelligence effect include greater labor productivity, better institutions, more competent management, lower fertility, and wider time horizons. 

Based on the observation of secular gains in intelligence that have become known as Flynn effects, a theory of economic growth is developed that is based on the trans-generational reinforcement between rising intelligence and economic, technological and institutional advances. It provides a parsimonious explanation for the sustained nature of economic growth since the Industrial Revolution, and a conceptual framework for more specific theories and hypotheses.

The chapter arrives at projections of economic growth for the first half of the 21st century that are based on the empiric relationship between current prosperity, human capital, and economic growth. Longer-term predictions are based on our knowledge of the conditions that are required for continued Flynn effects, and of genetic limits to human cognitive development. The conclusion is that in most countries of Europe and North America, the limits of cognitive growth are being approached or have been reached already by the younger generation. There are ongoing Flynn effects in developing countries today. These countries are now reducing the cognitive gaps separating them from the developed countries, but most of them are expected to reach their cognitive limits before the end of the 21st century. Long-term developments after the end of the Flynn effect will be driven primarily by demographic trends. Without major changes in demographic behavior, intelligence is predicted to eventually decline slowly, ending economic growth in most parts of the world within the next 3 to 4 generations.

[via E. Kirkegaard]

Goodness and Speed of Response

The Abilities of Man - Their Nature and Measurement
Chapter XIV - Goodness and Speed of Response | p. 243 - 258
Charles Spearman (1927)


The Chapter's Conclusion:

On the whole, ..., g has shown itself to measure a factor both in goodness and in speed of cognitive process. Such "goodness" is here taken as at bottom indicating clearness. The connection between the goodness and the speed is that of being inter-changeable. If the conditions of the case are such as to eliminate the influence of speed, then g measures goodness, and vice versa. When - as is most usual - both influences are in play, then g measures the efficiency compounded of both. In agreement with this complete inter-changeability between goodness and speed of response, neither of them constitutes a group factor or produces specific correlation. The almost unanimous view that some persons are on the whole unable to think quickly and yet are quite able to think clearly would seem to be a most grave error.

Genetics and intelligence differences: five special findings

Genetics and intelligence differences: five special findings
Robert Plomin & Ian J. Deary (2014)


Abstract

Intelligence is a core construct in differential psychology and behavioral genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics’. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the ‘missing heritability’ gap.

The Importance of Intraindividual Variation in Reaction Time

The Importance  of Intraindividual Variation in Reaction Time
Arthur R. Jensen (1992)


Abstract

Individual differences in the trial-to-trial variability of reaction time (RT), indexed by the standard deviation of the individual's RTs over n trials (RTSD), generally has a larger negative correlation with psychometric g than does the median RT (RTmd) over n trials. Large data sets are brought to bear on the question of whether RTmd and RTSD, which are highly correlated, reflect one and the same source of variance, but with different reliability and validity for predicting g, or represent independent processes. Several lines of evidence consistently lead to the conclusion that RTmd and RTSD, though having a substantial proportion of their variance in common even when measured separately in experimentally independent sets of RT trials, also have significant independent components of variance, each of which is correlated with psychometric g. Hypotheses about the neurophysiological basis of individual differences in the independent components of RTmd and RTSD are discussed.


[It's likely that RTSD reflects "neural noise" and that individual intelligence differences are partly caused by individual differences in "neural noise".]

Everyday Life as an Intelligence/Personality Test

(A) Everyday Life as an Intelligence Test

"Every semantic discrimination, every decision, every choice-point, every challenge, every opportunity for performance in everyday life has some degree of g loading, however slight it may be." Arthur R. Jensen

(B) Everyday Life as a Personality/Willpower Test

~Every decision, every choice-point, every challenge, every opportunity for performance in everyday life has some degree of "p"/"w" loading, however slight it may be.

[Perhaps also the second point makes sense...]

Task Complexity and the Speed and Efficiency of Elemental Information Processing: Another Look at the Nature of Intellectual Giftedness

"According to much contemporary research and theory in human information-processing, the main difference between intellectually gifted and normal individuals is the effectiveness of higher-order or metacognitive processes ... . A relatively minor role is attributed to differences in the lower-order cognitive processes (e.g., encoding, short-term memory scanning, and retrieval of information from long-term memory) that un­derlie all thought and action and are orchestrated by the metacognitive processes ... . A considerable amount of recent evidence, however, suggests that ele­mental information-processing abilities may be more importantly related to intellectual giftedness than previously considered ......" 

J. H. Kranzler, P. H. Wang & A. R. Jensen (1994)

Understanding g in Terms of Information Processing

Understanding g in Terms of Information Processing
Arthur R. Jensen (1992)


Abstract

Psychometric g, the general factor in individual differences in all types of tests and performances involving any mental ability, has much wider importance and implications than are encompassed by the field of psychometrics. It is argued that the nature of g must be understood in terms of information processes rather than in terms of the specific knowledge and skills that are seen in the content of conventional mental tests. The wide range of individual differences in g and disparities in the distribution of g in different subpopulations have important implications for understanding some of the major problems confronting public education.

[See also: Arthur Robert Jensen memorial site]

Intelligence moderates neural responses to monetary reward and punishment

Intelligence moderates neural responses to monetary reward and punishment
D.R. Hawes , C.G. DeYoung, J.R. Gray, A. Rustichini (2014)


Abstract

The relation between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal BOLD signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects’ behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex-ante.

Solving the puzzle of why Finns have the highest IQ, but one of the lowest number of Nobel prizes in Europe

Solving the puzzle of why Finns have the highest IQ, but one of the lowest number of Nobel prizes in Europe
Edward Dutton, Jan te Nijenhuis, Eka Roivainen
Intelligence (Sept - Oct 2014)

Highlights

•

Finland does very well in PISA, but has very few Nobel Prize winners.

•

Finns have the highest IQ in Europe but the smallest SD.

•

Finns have high Conscientiousness and Agreeableness.

•

This explains why they do well in education, but not in measures of significant creative achievement.

Abstract

Finland has been noted to perform consistently very well in the international PISA assessments for many years, but it also has a relatively low per capita number of Nobel Prize winners. We draw upon a large body of proxy data and direct evidence, including the first ever use of RTs to calculate the Finnish IQ and the first ever use of the WAIS IV and PISA scores in the same capacity. Based on these data, we hypothesize that Finns perform so consistently well in PISA because they have a higher IQ overall than other European countries and exhibit a specialized slow life history strategy characterized by high Agreeableness and Conscientiousness, and low Psychoticism and Extraversion. Most of these traits predict educational success but all would suppress genius and creativity amongst this population. We connect the present distribution of phenotypic traits amongst the Finnish population with evolutionary change starting in the Pleistocene, accelerating in the Holocene, and continuing into the present day. We argue that this profile explains why Finns are relatively poorly represented in terms of science Nobel laureates.

Spearman's "Fundamental Laws"

(I) ... a person has more or less power to observe what goes on in his own mind.

(II) ... when a person has in mind any two or more ideas (using this word to embrace any items of mental content, whether perceived or thought of), he has more or less power to bring to mind any relations that essentially hold between them.

(III) ... when a person has in mind any idea together with a relation, he has more or less power to bring up into mind the correlative idea.

Source:
The Abilities of Man (1927) (p. 164-166)
Charles Spearman

Incorporating General Intelligence Into Epidemiology and the Social Sciences

Incorporating General Intelligence Into Epidemiology and the Social Sciences
D. Lubinski & L. G. Humphrey (1997)
https://my.vanderbilt.edu/smpy/files/2013/02/Intelligence.pdf


Abstract

The purpose of this article is to demonstrate the value of examining a variety of pressing behavioral, medical, and social phenomena as they relate to gradations in general intelligence. Although few (if any) variables in the social sciences can compete with the construct of general intelligence in its ability to forecast an array of socially valued attributes and outcomes, measures of general intelligence are seldom incorporated into correlational and experimental designs aimed at understanding maladaptive behavior (e.g., crime, dropping out of high school, unwise financial planning, health-risk behaviors, poor parenting, and vocational discord) or its opposite, highly adaptive behavior. We contend that, if consulted more often, the construct of general intelligence would contribute to understanding many puzzling human phenomena, because successive gradations of intelligence reflect successive degrees of risk. A method is provided for uncovering group trends, one expressly designed to reveal the range and prevalence of the many different kinds of human phenomena that vary as a function of intellectual gradations. By employing this method, policymakers and the public can more readily apprehend the significant, but often unsuspected, contribution made by general intelligence to many socially important outcomes. Our approach is similar to traditional epidemiological research aimed at ascertaining antecedents to maladies through the defining features of high-risk groups (e.g., for lung cancer, smokers and passive smokers; for AIDS victims, participants in unsafe sex; for academic mediocrity, among the intellectually gifted in nonaccelerative educational tracks; for mental retardation, high blood-lead levels). Once such high-risk groups are defined (i.e., groups of persons whose behavioral dispositions predispose them, and often others around them, to unfortunate outcomes), policymakers and scientists are in a better position to disentangle genuine causes from families of correlations and can concentrate ameliorative resources more effectively. Data from educational and medical contexts are analyzed to show how measures of general intelligence, and other dimensions from differential psychology, can complement epidemiological and social science inquiry. We also argue that by incorporating such measures of human variation into policy development and research, policymakers are more likely to forestall “iatrogenic effects” (maladies caused by treatment).

Subjective Judgments of Intelligence and IQ-Tests:

>It is helpful to think of the subjective perception of intelligence as analogous to the subjective perception of temperatures ... . Before the invention of the thermometer, temperature was a matter of subjective judgment. The invention of the thermometer made it possible to objectify the attribute of temperature, to quantify it, and to measure it with a high degree of reliability. With some important qualifications, the situation is similar in the case of intelligence tests.<

Arthur R. Jensen

IQ and Retention:

>... When persons are equated in degree of original learning of simple material, their retention measured at a later time is only slightly if at all correlated with IQ. The retention of more complex learning, however, involves meaningfulness and the way in which the learner has transformed or encoded the material. This is related to the degree of the learner’s under­standing, the extent to which the learned material is linked into the learner’s preexisting associative and conceptual network, and the learner’s capacity for conceptual reconstruc­tion of the whole material from a few recollected principles. The more that these aspects of memory can play a part in the material to be learned and later recalled, the more that retention measures are correlated with IQ.<

Arthur R. Jensen

Bias in Mental Testing - p. 329 (1980)

[See also: The myth of “they weren’t ever taught….”]

IQ and somatic health in late adolescence

IQ and somatic health in late adolescence
Alma Sörberg, Peter Allebeck, Tomas Hemmingsson
Intelligence (May - June 2014)


Highlights

•

IQ is associated with somatic health and early death later in life.

•

Less is known about the relationship between IQ and somatic health in youth.

•

IQ was associated with a range of diagnoses/health indicators already in youth.

•

Lower IQ was mostly associated with higher risk for diagnoses/poor health indicators.

•

The associations were not explained by differences in socioeconomic background.

Abstract

Intelligence quotient (IQ) is associated with mental health in youth onwards, as well as somatic health and longevity later in life. However, little is known about the association with somatic health in youth. We aimed to investigate the cross-sectional association between IQ and a range of somatic diagnoses and health indicators in late adolescence. In a cohort comprising 49 321 Swedish men, IQ test performance and health status were recorded at conscription in 1969–70, at ages 18–20. Information on socioeconomic factors in childhood was obtained from the national census. Odds ratios (ORs) were estimated by logistic regression. With adjustment for socioeconomic background, each step decrease in IQ test performance on a nine-point scale was associated with an increased OR for the following somatic diagnoses: impaired hearing (1.14, 1.12–1.16), endocrine disorders (1.13, 1.10–1.17), symptoms and ill-defined conditions (1.11, 1.08–1.14), back pain (1.10, 1.08–1.12), digestive system diseases (1.08, 1.05–1.10) and injuries (1.02, 1.00–1.05); and a decreased OR for hayfever (0.87, 0.85–0.90) and refractive errors (0.87, 0.86–0.88). IQ was also associated with increased ORs for low physical capacity (1.12, 1.10–1.14), signs of inflammation (1.07, 1.06–1.09) and low self-rated health (1.03, 1.02–1.05). Several diagnoses were not associated with IQ. In conclusion, lower IQ at conscription was associated with a higher risk for several diagnoses and indicators of poor health, but the risk was decreased for a few of the diagnoses. The mechanisms underlying the associations presumably differ. However, socioeconomic factors in childhood could not explain the associations.

Major Findings on g’s Impact on Job Performance

Utility of g

1. Higher levels of g lead to higher levels of performance in all jobs and along all dimensions of performance. The average correlation of mental tests with overall rated job performance is around .5 (corrected for statistical artifacts).

2. There is no ability threshold above which more g does not enhance performance. The effects of g are linear: successive increments in g lead to successive increments in job performance.

3. (a) The value of higher levels of g does not fade with longer experience on the job. Criterion validities remain high even among highly experienced workers. (b) That they sometimes even appear to rise with experience may be due to the confounding effect of the least experienced groups tending to be more variable in relative level of experience, which obscures the advantages of higher g.

4. g predicts job performance better in more complex jobs. Its (corrected) criterion validities range from about .2 in the simplest jobs to .8 in the most complex.

5. g predicts the core technical dimensions of performance better than it does the non-core “citizenship” dimension of performance.

6. Perhaps as a consequence, g predicts objectively measured performance (either job knowledge or job sample performance) better than it does subjectively measured performance (such as supervisor ratings).

Utility of g Relative to Other “Can Do” Components of Performance

7. Specific mental abilities (such as spatial, mechanical, or verbal ability) add very little, beyond g, to the prediction of job performance. g generally accounts for at least 85-95% of a full mental test battery’s (cross-validated) ability to predict performance in training or on the job.

8. Specific mental abilities (such as clerical ability) sometimes add usefully to prediction, net of g, but only in certain classes of jobs. They do not have general utility.

9. General psychomotor ability is often useful, but primarily in less complex work. Its predictive validities fall with complexity while those for g rise. 

Utility of g Relative to the “Will Do” Component of Job Performance

10. g predicts core performance much better than do “non-cognitive” (less g-loaded) traits, such as vocational interests and different personality traits. The latter add virtually nothing to the prediction of core performance, net of g.

11. g predicts most dimensions of non-core performance (such as personal discipline and soldier bearing) much less well than do “non-cognitive” traits of personality and temperament. When a performance dimension reflects both core and non-core performance (effort and leadership), g predicts to about the same modest degree as do non-cognitive (less g-loaded) traits.

12. Different non-cognitive traits appear to usefully supplement g in different jobs, just as specific abilities sometimes add to the prediction of performance in certain classes of jobs. Only one such non-cognitive trait appears to be as generalizable as g: the personality trait of conscientiousness/integrity. Its effect sizes for core performance are substantially smaller than g’s, however.

Utility of g Relative to the Job Knowledge

13. g affects job performance primarily indirectly through its effect on job-specific knowledge.

14. g’s direct effects on job performance increase when jobs are less routinized, training is less complete, and workers retain more discretion.

15. Job-specific knowledge generally predicts job performance as well as does g among experienced workers. However, job knowledge is not generalizable (net of its g component), even among experienced workers. The value of job knowledge is highly job specific; g’s value is unrestricted.

Utility of g Relative to the “Have Done” (Experience) Component of Job Performance

16. Like job knowledge, the effect sizes of job-specific experience are sometimes high but they are not generalizable.

17. In fact, experience predicts performance less well as all workers become more experienced. In contrast, higher levels of g remain an asset regardless of length of experience.

18. Experience predicts job performance less well as job complexity rises, which is opposite the trend for g. Like general psychomotor ability, experience matters least where g matters most to individuals and their organizations.

Source:

Where and Why g Matters: Not a Mystery - Appendix 1

Linda S Gottfredson (2002)

The Distribution of Mental Ability:

...

>The “retarded” category is traditionally described as IQ below 70, but this is rather arbitrary. Psychologists, educators, and social workers, however, show little disagree­ment that the vast majority of persons with IQs below 70 have unusual difficulties in school and generally have difficulties of an intellectual nature as adults. There are few jobs in a modern industrial society for which persons below IQ 70 are capable without making allowances for their intellectual disability or restructuring the usual requirements of the job so as to bring it within the capabilities of the retarded person. Persons below IQ 70 have difficulty in managing their financial affairs and other ordinary demands involv­ing arithmetic and reading comprehension. Many school systems set the retarded classification at IQ 75 or even 80, because such children so often require special instruction to learn the basic school subjects. Even then these children find it very difficult to keep pace with their classmates, because, with a mental age a year or more below the average of their classmates, they lack the conceptual readiness for the scholastic subjects that are taught in a given grade. The armed forces exclude most persons who score below an equivalent of about IQ 75 or 80 on the Armed Forces Qualification Test. There are too few useful occupations that these low-IQ recruits can be successfully trained to perform, with limited time for training.

The American Association of Mental Deficiency has recommended that the border­line of mental retardation be set at between IQ 70 to 85, defining as “ subnormal " IQ deviations of more than one standard deviation below the general mean of the population. But this is a matter of statistical definition and does not agree with the general practice of basing classification as retarded not only on IQ but on various criteria of the individual’s social adjustment and adaptive behavior. The majority of adults with IQs between 70 and 85 are not retarded by ordinary criteria of social adjustment. In one large study, for example, it was found that 84 percent of such persons had completed at least eight years of school, 83 percent had held a job, 65 percent had a semiskilled or higher occupation, 80 percent were financially independent or a housewife, and almost 100 percent were able to do their own shopping and travel alone (Mercer, 1972a).

The AAMD further subdivides the retarded classification as follows:

IQ 85-70                Borderline retardation

IQ 69-55                Mild retardation

IQ 54-40                Moderate retardation

IQ 39-25                Severe retardation

IQ 24 and below   Profound retardation 

The vast majority, some 70 percent to 80 percent, of persons below IQ 70 are biologically normal; no brain damage, disease, or genetic defect is detectable. They are apart of normal variation in the combination of polygenic and environmental factors that contribute to variance in IQ. The remaining 20 percent to 30 percent show “ clinical” signs, either due to brain damage from injury or disease, or they show the medically recognizable signs of one or another of the more than eighty specifically identifiable syndromes associated with a single defective gene or chromosomal anomaly. The bulk of such individuals are found in the IQ range below 50 and nearly all persons with IQs below 35 or 40 are the “ clinical” type.

All levels of retardation, except perhaps some of those at the “profound” level, are amenable to various forms of therapy, conditioning, or training that can make their social behavior and their lives more satisfactory, both to themselves and to those who must take care of them, although such training has no appreciable effect on the IQ. The mildly or educably retarded can benefit from schooling when it is properly geared to their level of readiness and conceptual capabilities.

Moving up the IQ scale to the 80 to 90 range, which is traditionally but unfortu­nately labeled "dull normal", the typical picture is that of quite normal children or adults whose only consistently distinguishing feature is greater than average difficulty in the more academic school subjects. Such children are generally slower to “catch on” to whatever is being taught if it involves symbolic, abstract, or conceptual subject matter. In the early grades in school they most often have problems in reading and arithmetic and are sometimes labeled “slow learners.” But it is really not that they learn slowly as that they lag behind in developmental readiness to grasp the concepts that are within easy reach of the majority of their age mates. Such children will eventually grasp these basic subjects fairly easily, but about a year or two later than their age mates. They are better thought of as “ slow developers” than as “ slow learners. ” The child with an IQ of 80 to 90, it seems, has to be explicitly taught more of what he must learn, in or out of school, than the brighter child, who picks up much more knowledge and skills on his own, without need of direct intervention by parents or teachers. The lower-IQ child does not as readily absorb as much from his own experiences as the brighter child. Most low-IQ children do not eventually catch up with their age mates. Because of the fairly high degree of constancy of the IQ (...), low-IQ children differ increasingly from their average age mates in mental age as they advance in school. Children in the IQ range of 80 to 90 are usually not noticed to be intellectually different in any way until they enter school. Their scholas­tic problems become more evident with each higher grade, since they are further behind their classmates in mental age.

Because of this increasing lag in the academic subjects, most of these children, when they reach junior or senior high school, elect the less academic courses. The elective system allows them to choose courses in which they are more apt to succeed and from which they are more apt to profit in the world of work when they leave school. By high school age many such children, because of their earlier scholastic difficulties, have already acquired a definite dislike for the academic subjects and tend to drop out of high school if it has little else to offer besides the traditional curriculum. Algebra and geometry, foreign languages, English literature, and physics and chemistry are not these pupils’ forte; unless strenuously pressured by parents, they usually avoid these tra­ditionally college preparatory courses. They prefer the more practical and vocational courses, which are less symbolic and abstract. Not surprisingly, as adults they have few if any intellectual interests to speak of; they are generally poorly informed on world affairs, science, the arts, or other types of information gained through reading. They are usually employed in jobs that depend little on scholastic skills or in which advancement depends on individual study or training courses involving “book learning,” “examinations," or other school-like requirements.

The 50 percent of the population classed as “average” and falling between IQs 90 and 110 hardly needs description. They differ from those below and above on the IQ scale only in degree. The schools, the world of work, and the entertainment industry are largely geared to this average majority of the population. Persons with IQs closer to 110, because of their usually more favorable experiences in elementary and high school are more likely to seek advanced training or even college than those with IQs closer to 90. The myriad of occupations below the highly technical and professional levels are mostly occupied by persons in this IQ range. There is virtually no limitation on such persons in fields that are not dependent on university- or graduate-level education or in occupations that require special talents, such as athletics, art, acting, and musical performance. At least an average IQ is usually needed to compete successfully in such fields, but, beyond that, a high level in special talents and personal qualities are the crucial factors in success.

IQs between 110 and 130 are typically found in children who do well in school subjects, who catch on easily to what is being taught at their grade level, and who take a liking to the academic curriculum. They are typically good readers from an early age, they enjoy reading, and they do more of it than most children without encouragement from others. There are great individual differences in interests and special abilities in this group, and these differences are reflected in the variability of these children’s perfor­mances in various scholastic subjects. But usually children with IQs above 115 or so can perform outstandingly in any school subject to which they may apply themselves, barring special disabilities such as aphasia and dyslexia. These above-average children show a wider range of interests than the average, they tend to be self-learners, and their hobbies are usually more complex, advanced, well planned, and long term than one sees in their more average age mates. Colleges and universities obtain their students almost entirely from the range above IQ 110. Entering freshmen in most selective colleges average in the 115 to 120 range, and graduates from these colleges average about 120 to 125. The vast majority of persons in skilled, managerial, and professional occupations are from this group. Manual or “ blue-collar” workers in this IQ range generally become the master carpenters, skilled mechanics, technicians, foremen, and contractors with earnings on a par with or exceeding those of many white-collar and professional workers.

Persons with IQs above 130 usually find school easy, or even perhaps boring for lack of intellectual challenge. Some are not very enthusiastic students until they reach college. With average interest, motivation, and application, they tend to be in the upper half of their college class in grade-point average. With better than average effort and persistence, they can succeed in virtually any occupation except those requiring special talents, among which I would include mathematics; at an advanced level mathematics seems to require not only a high level of general intelligence but also something more in the nature of a special talent. (As in high-level talent for musical composition and in playing chess, there is also a marked sex difference in high-level mathematical ability. Also, it is interesting that authentic child prodigies are found only in chess, music, and mathematics.) Beyond IQ 130, factors other than general intelligence largely account for what these persons make of their careers. Personality factors, interests, drive, stability, perseverance, general health, cultural background, educational opportunities, and special talents become the main determining factors once a high level of general intelligence is present. Outstanding achievement, as Galton noted, depends on at least three things: exceptional general mental ability, exceptional drive, and exceptional perseverance. These qualities are almost invariably illustrated, for example, in the biographies of per­sons whose achievements are judged sufficiently outstanding to be included in the Ency­clopaedia Britannica.<
...

Bias in Mental Testing -> p. 109-112
Arthur R. Jensen (1980)

[If you read this excerpt with interest, I highly recommend you to read the whole chapter (or at least p. 105-114). Perhaps I shouldn't have cut it into pieces.]

The Relationship between Learning and Intelligence

>In reviewing the then entire literature on the relation of learning to IQ I (Jensen 1979) arrived at a number of empirical generalizations regarding the conditions that seem most clearly related to the magnitude of the learning-IQ correlations, or the degree to which various learning tasks are g loaded. To summarize: Learning is more highly g loaded when:

1. learning is intentional and calls forth conscious mental effort;

2. the learning or practice trials are paced in such a way as to allow the subject time to think;

3. the material to be learned is hierarchical in the sense that the learning of later elements depends on mastery of earlier elements;

4. the material to be learned is meaningful in the sense of being related to other knowledge or experience already possessed by the learner;

5. the learning task permits transfer-from somewhat different but related past learning;

6. the learning is insightful, that is, it involves “catching on” or “getting the idea”;

7. the material to be learned is of moderate difficulty and complexity, in the sense of the number of elements that must be integrated simultaneously for the learning to progress;

8. the amount of time for learning a given amount of material to a specified criterion of mastery is fixed for all students;

9. the learning material is positively age-related, that is, some kinds of material are more readily learned (hence the concept of “readiness”) by older than by younger children; and

10. performance gains are measured at an early stage of learning something “new” than at a late stage of practice on the same task.<

Source:
The Relationship between Learning and Intelligence
Arthur R. Jensen (1989)
Learning and Individual Differences

[See also: http://meinnaturwissenschaftsblog.blogspot.co.at/2013/06/learning-iq.html]