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SMPY directory


“Identifying and Nurturing Future Innovators in Science, Technology, Engineering, and Mathematics: A Review of Findings From the Study of Mathematically Precocious Youth”, Benbow 2021

2012-benbow.pdf: “Identifying and Nurturing Future Innovators in Science, Technology, Engineering, and Mathematics: A Review of Findings From the Study of Mathematically Precocious Youth”⁠, Camilla Persson Benbow (2021-02-01; backlinks; similar):

Calls to strengthen education in science, technology, engineering, and mathematics (STEM) are underscored by employment trends and the importance of STEM innovation for the economy. The Study of Mathematically Precocious Youth (SMPY) has been tracking over 5,000 talented individuals longitudinally for 40 years, throwing light on critical questions in talent identification and development in STEM. SMPY includes individuals identified in 7th/​8th grade as in the top 1% or higher in mathematical or verbal ability, and a comparison group identified as top STEM graduate students.

SMPY findings cover the educational and occupational attainments of participants, including a large percentage earning a degree or pursuing high powered careers in STEM; gender differences; the extent to which high school experiences, abilities, and interests predict later outcomes; and subsequent creative production. Mathematical reasoning ability as measured by standardized tests is a reliable predictor for later math/​science engagement and achievement in adulthood, and spatial ability adds predictive value. Exposure to appropriate educational opportunities do correlate with career achievement and creative production.

SMPY researchers have concluded that potential future STEM innovators can be identified early and that educational interventions can increase their chances of success.

“Social-Emotional Characteristics and Adjustment of Accelerated University Students: A Systematic Review”, Schuur et al 2020

2020-schuur.pdf: “Social-Emotional Characteristics and Adjustment of Accelerated University Students: A Systematic Review”⁠, Jolande Schuur, Marjolijn van Weerdenburg, Lianne Hoogeveen, Evelyn H. Kroesbergen (2020-11-09; backlinks; similar):

Gifted students who experienced grade-based acceleration in primary or secondary education have to meet the challenges of adjusting to university at a younger age than students who did not accelerate. This systematic review critically evaluates the research on social-emotional characteristics and adjustment of these gifted accelerated university students. Based on a review of 22 studies, we may conclude that accelerated students did not differ very much in domains of social-emotional characteristics from their nonaccelerated gifted and nongifted peers. Factors that facilitated adjustment and well-being were cheerfulness, resilience, self-efficacy, a positive self-concept, high prior academic achievement, and supportive family environment. Furthermore, it was found that studies were incomplete in reporting the previous acceleration experiences of the students and that research on students who individually accelerated by 1 or 2 years was scarce. Future research should include individually accelerated students, previous acceleration experiences, gender differences, and comparison groups.

“In Search of Excellence: An Interview With Linda Brody”, Henshon 2020

2020-henshon.pdf: “In Search of Excellence: An Interview With Linda Brody”⁠, Suzanna E. Henshon (2020-07-30; backlinks; similar):

[Short interview with Linda Brody, current director of Study of Exceptional Talent (SET) at the Johns Hopkins Center for Talented Youth (CTY); she originally started working for SMPY in the 1970s along with Cohn/​Pyryt/​Benbow and for Lynn Fox & Julian Stanley, leaving in 1991 for CTY. She specialized in “twice-exceptional students” (both gifted & disabled). SET is currently studying its alumni.]

“Intellectual Precocity: What Have We Learned Since Terman?”, Lubinski & Benbow 2020b

2020-lubinski-2.pdf: “Intellectual Precocity: What Have We Learned Since Terman?”⁠, David Lubinski, Camilla P. Benbow (2020-07-28; backlinks; similar):

Over the past 50 years, eight robust generalizations about intellectual precocity have emerged, been empirically documented, and replicated through longitudinal research. Within the top 1% of general and specific abilities (mathematical, spatial, and verbal) over one third of the range of individual differences are to be found, and they are meaningful. These individual differences in ability level and in pattern of specific abilities, which are uncovered by the use of above-level assessments, structure consequential quantitative and qualitative differences in educational, occupational, and creative outcomes. There is no threshold effect for abilities in predicting future accomplishments; and the concept of multipotentiality evaporates when assessments cover the full range of all three primary abilities. Beyond abilities, educational/​occupational interests add value in identifying optimal learning environments for precocious youth and, with the addition of conative variables, for modeling subsequent life span development. While overall professional outcomes of exceptionally precocious youth are as exceptional as their abilities, educational interventions of sufficient dosage enhance the probability of them leading exceptionally impactful careers and making creative contributions. Findings have made evident the psychological diversity within intellectually precocious populations, their meaningfulness, and the environmental diversity required to meet their learning needs. Seeing giftedness and interventions on their behalf categorically has held the field back.

[Keywords: basic interpretive, mixed methods, psychometrics, assessment, creativity, gifted]

  1. Is there an ability threshold, beyond which more ability doesn’t matter? No.

  2. Does the pattern of specific abilities matter? Yes.

    Is there evidence for multipotentiality? No.

  3. Is ability pattern important for students with especially profound intellectual gifts? Yes.

  4. Do educational/​occupational interests add value to ability assessments of intellectually precocious youth? Yes.

  5. Given the contemporary emphasis placed on the identification and development of human capital in STEM disciplines, are there other important findings from the gifted field germane to this need? Yes.

  6. Can educational interventions enhance learning and ultimate levels of creative expression? Yes.

  7. Beyond ability, interest, and opportunity, are conative attributes important? Yes.

  8. Has the study of intellectual precocity contributed to its parent disciplines in the educational and psychological sciences? Is there a common theme that cuts across the above empirical generalizations, which have been replicated over multiple decades? Yes. And yes.

“Academic Acceleration in Gifted Youth and Fruitless Concerns Regarding Psychological Well-Being: A 35–Year Longitudinal Study”, Bernstein et al 2020

2020-bernstein.pdf: “Academic Acceleration in Gifted Youth and Fruitless Concerns Regarding Psychological Well-Being: A 35–Year Longitudinal Study”⁠, Brian O. Bernstein, David Lubinski, Camilla P. Benbow (2020-07-02; backlinks; similar):

Academic acceleration of intellectually precocious youth is believed to harm overall psychological well-being even though short-term studies do not support this belief. Here we examine the long-term effects. Study 1 involves three cohorts identified before age 13, then longitudinally tracked for over 35 years: Cohort 1 gifted (top 1% in ability, identified 1972–1974, n = 1,020), Cohort 2 highly gifted (top 0.5% in ability, identified 1976–1979, n = 396), and Cohort 3 profoundly gifted (top 0.01% in ability, identified 1980–1983, n = 220). Two forms of educational acceleration were examined: (a) age at high school graduation and (b) quantity of advanced learning opportunities pursued prior to high school graduation. Participants were evaluated at age 50 on several well-known indicators of psychological well-being. Amount of acceleration did not covary with psychological well-being. Study 2, a constructive replication of Study 1, used a different high-potential sample—elite science, technology, engineering, and mathematics graduate students (n = 478) identified in 1992. Their educational histories were assessed at age 25 and they were followed up at age 50 using the same psychological assessments. Again, the amount of educational acceleration did not covary with psychological well-being. Further, the psychological well-being of participants in both studies was above the average of national probability samples. Concerns about long-term social/​emotional effects of acceleration for high-potential students appear to be unwarranted, as has been demonstrated for short-term effects.

[Keywords: gifted, acceleration, replication, appropriate developmental placement, psychological well-being]

Impact Statement: Best practices suggest that acceleration in one of its many forms is educationally efficacious for meeting the advanced learning needs of intellectually precocious youth. Yet, parents, teachers, academic administrators, and psychological theorists worry that this practice engenders negative psychological effects. A three-cohort study of intellectually precocious youth followed for 35 years suggests that there is no cause for concern. These findings were replicated on a sample of elite STEM graduates whose educational histories were assessed at age 25 and tracked for 25 years.

“Does More Mean Less? Interest Surplus and the Gender Gap in STEM Careers”, Cardador et al 2020

2020-cardador.pdf: “Does More Mean Less? Interest Surplus and the Gender Gap in STEM Careers”⁠, M. Teresa Cardador, Rodica Ioana Damian, Justin P. Wiegand (2020-06-08; backlinks; similar):

The persistent gender gap in STEM (Science, Technology, Engineering, and Math) career choice represents a perplexing problem for researchers and policy makers alike. We contribute to the body of research on the gender gap in STEM careers by testing a “surplus model” of vocational interests as a predictor of STEM career choice. The model suggests that, controlling for ability, female adolescents with strong STEM-related interest should be less likely to pursue STEM careers when they also have strong interests in other areas, due to wider career options. We tested the surplus model in a large national longitudinal data set and translated the results into differences in annual wages. Our findings illuminate the predictive validity of a surplus model of interests on STEM career choice across gender, provide insight into the gender gap in STEM, and suggest opportunities for future research.

[Keywords: vocational interests, surplus model, stem gender gap, stem career choice]

“Understanding Educational, Occupational, and Creative Outcomes Requires Assessing Intraindividual Differences in Abilities and Interests”, Lubinski 2020

2020-lubinski.pdf: “Understanding educational, occupational, and creative outcomes requires assessing intraindividual differences in abilities and interests”⁠, David Lubinski (2020; similar):

Stoet and Geary (1) report important cross-cultural findings on how the advantage of females in reading proficiencies relative to males combined with more equitable educational opportunities have contributed to the recent overrepresentation of women in tertiary education. Developed nations vary in the extent to which males are underrepresented as a function of these two determinants, yet that they jointly contribute to a clear cross-cultural trend is undeniable. Hence, it is critical to assess personal proficiencies and the environmental contexts within which they operate to understand individual and gender differences in educational outcomes.

Further refinements in how far students progress in educational systems, why group disparities exit, and which specific disciplines students pursue are provided by examining other aspects of their individuality more holistically and simultaneously. This commentary places the assessment of human individuality into a broader (multidimensional) context. Major reviews of psychological research show that individual differences in both level and pattern of cognitive abilities and educational/​occupational interests are critical for understanding educational, occupational, and creative outcomes across the lifespan (2⇓–4). Incorporating cognitive abilities and interests into longitudinal research demonstrates how these two categories of psychological attributes give rise to different real-world accomplishments. That information allows us to understand each student’s individuality, their learning needs, and develop policies for best practices. This commentary is to give readers a better understanding of why both interindividual and intraindividual differences in abilities and interests must be considered when conceptualizing individual and group differences in real-life learning and work outcomes.

“Personality and School Functioning of Intellectually Gifted and Nongifted Adolescents: Self-perceptions and Parents' Assessments”, Wirthwein et al 2019

2019-wirthwein.pdf: “Personality and school functioning of intellectually gifted and nongifted adolescents: Self-perceptions and parents' assessments”⁠, Linda Wirthwein, Sebastian Bergold, Franzis Preckel, Ricarda Steinmayr (2019-01-01)

“Who Shines Most among the Brightest?: A 25-year Longitudinal Study of Elite STEM Graduate Students”, McCabe et al 2019

2019-mccabe.pdf: “Who shines most among the brightest?: A 25-year longitudinal study of elite STEM graduate students”⁠, Kira O. McCabe, David Lubinski, Camilla P. Benbow (2019-01-01; backlinks)

“Psychological Constellations Assessed at Age 13 Predict Distinct Forms of Eminence 35 Years Later”, Bernstein et al 2019

2019-bernstein.pdf: “Psychological Constellations Assessed at Age 13 Predict Distinct Forms of Eminence 35 Years Later”⁠, Brian O. Bernstein, David Lubinski, Camilla P. Benbow (2019; backlinks; similar):

This investigation examined whether math/​scientific and verbal/​humanistic ability and preference constellations, developed on intellectually talented 13-year-olds to predict their educational outcomes at age 23, continue to maintain their longitudinal potency by distinguishing distinct forms of eminence 35 years later. Eminent individuals were defined as those who, by age 50, had accomplished something rare: creative and highly impactful careers (eg. full professors at research-intensive universities, Fortune 500 executives, distinguished judges and lawyers, leaders in biomedicine, award-winning journalists and writers). Study 1 consisted of 677 intellectually precocious youths, assessed at age 13, whose leadership and creative accomplishments were assessed 35 years later. Study 2 constituted a constructive replication—an analysis of 605 top science, technology, engineering, and math (STEM) graduate students, assessed on the same predictor constructs early in graduate school and assessed again 25 years later. In both samples, the same ability and preference parameter values, which defined math/​scientific versus verbal/​humanistic constellations, discriminated participants who ultimately achieved distinct forms of eminence from their peers pursuing other life endeavors.

“Right-Tail Range Restriction: A Lurking Threat to Detecting Associations between Traits and Skill among Experts”, Kell & Wai 2019

“Right-Tail Range Restriction: A Lurking Threat to Detecting Associations between Traits and Skill among Experts”⁠, Harrison J. Kell, Jonathan Wai (2019; backlinks; similar):

It has been claimed by prominent authors that there is no relationship between differences in some human traits (eg. cognitive ability, physical ability) and differences in skill among experts. We assert that the failure to detect such associations is often due to an extreme form of range restriction that particularly plagues research focused on expert samples: right-tail range restriction (RTRR). RTRR refers to a lack of representation of data from the far right segment of the normal distribution, inhibiting the observation of statistical associations.

Using 2 example studies we demonstrate that, when RTRR is not present, relationships between differences in experts’ traits and differences in their degree of skill can be observed. Based on the characteristics of these studies we make recommendations for methodological practices that can be followed to help investigators overcome RTRR and facilitate the continued development of a robust and replicable science of expertise.

[Keywords: Range restriction, expertise, traits, cognitive ability, physical ability, performance, athletics, psychological attributes]

“SMPY Bibliography”, Branwen 2018

SMPY: “SMPY Bibliography”⁠, Gwern Branwen (2018-07-28; ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ; backlinks; similar):

An annotated fulltext bibliography of publications on the Study of Mathematically Precocious Youth (SMPY), a longitudinal study of high-IQ youth.

SMPY (Study of Mathematically Precocious Youth) is a long-running longitudinal survey of extremely mathematically-talented or intelligent youth, which has been following high-IQ cohorts since the 1970s. It has provided the largest and most concrete findings about the correlates and predictive power of screening extremely intelligent children, and revolutionized gifted & talented educational practices.

Because it has been running for over 40 years, SMPY-related publications are difficult to find; many early papers were published only in long-out-of-print books and are not available in any other way. Others are digitized and more accessible, but one must already know they exist. Between these barriers, SMPY information is less widely available & used than it should be given its importance.

To fix this, I have been gradually going through all SMPY citations and making fulltext copies available online with occasional commentary.

“Individual Differences at the Top: Mapping the Outer Envelope of Intelligence”, Lubinski 2018

2018-lubinski.pdf: “Individual Differences at the Top: Mapping the Outer Envelope of Intelligence”⁠, David Lubinski (2018-01-01; backlinks)

“Gifted Kids and High-Achievers Stay Fresh: Health Outcomes of Four SMPY Cohorts at Age 50”, Kell et al 2017

“Gifted Kids and High-Achievers Stay Fresh: Health Outcomes of Four SMPY Cohorts at Age 50”⁠, Harrison Kell, David Lubinski, Camilla Benbow (2017-07-14; backlinks; similar):

Over a century of research has demonstrated that intelligence is associated with positive health outcomes (Terman⁠, 1925, Mental and physical traits of a thousand gifted children). Nonetheless, some still doubt whether gifted children grow up to be (on average) healthy, well-adjusted adults (eg. Neihart, 1999). This study compares medical and psychological health outcomes of middle-aged adults from the general population (n = 3,652) to four SMPY cohorts. Cohort 1 (n = 1,159) score in the top 1% of ability and Cohort 2 (n = 491) score in the top 0.5% of ability. Four decades after identification, both cohorts were administered a comprehensive biographical survey, which included many health questions (Lubinski, Benbow, & Kell, 2014). Across 23 items, gifted males evinced more positive outcomes than males of average intelligence on 22 (96%). The mean odds ratio (OR) was 5.32, meaning males of average intelligence were over five times more likely to experience a negative health outcome than those in the top 1%. Gifted females evinced more positive outcomes in 65% of the categories, with a mean odds ratio of 2.52.

Comparisons of health outcomes within the top 1% are complicated by the higher mean age of Cohort 1 (53) relative to Cohort 2 (48). Only 2 statistically-significant differences emerged between gifted females: Those in the top 1% were more likely than those in the 0.5% to have felt calm and peaceful and less likely to have had emotional or physical problems interfere with their activities recently (average d = 0.12). Results were less consistent for males. Males in the top 1% were statistically-significantly more likely to experience chest pains, hypertension, and arthritis (OR = 2.23), while males in the top 0.5% were more likely to experience asthma, depression, and non-depressive psychiatric problems (OR = 1.2).

As a replication, 2 additional SMPY samples were administered the same survey. Cohort 3 consists of young adolescents identified as being in the top 0.01% in the early 1980s (anticipated n > 300). Cohort 4 consisted of first-year and second-year students attending top 15 U.S. math/​science graduate programs in 1992 (anticipated n > 400). Health outcomes of these two cohorts will be compared not only to those of the general population, but to those of the top 1% and 0.5% as well. The size, scope, and quality of these data represent an unprecedented opportunity for examining the well-being of intellectually talent adults. Finally, these data also allow for the comparison of health outcomes between three high ability groups explicitly identified in young adolescence and a group of extraordinarily capable individuals identified as extraordinary achievers in early adulthood. Note: Preliminary data from Cohorts 3 and 4 are not ready for analysis, but the survey is well underway. Preliminary findings would be presented at ISIR 2017 for the first time.

“A Genome-wide Association Study for Extremely High Intelligence”, Zabaneh et al 2017

“A genome-wide association study for extremely high intelligence”⁠, D. Zabaneh, E. Krapohl, H. A. Gaspar, C. Curtis, S. H. Lee, H. Patel, S. Newhouse, H. M. Wu, M. A. Simpson et al (2017-07-04; ; backlinks; similar):

We used a case-control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and statistically-significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide statistical-significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was statistically-significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.

“Developing Talents: A Longitudinal Examination of Intellectual Ability and Academic Achievement”, McCoach et al 2017

2017-mccoach.pdf: “Developing talents: A longitudinal examination of intellectual ability and academic achievement”⁠, D. Betsy McCoach, Huihui Yu, Allen W. Gottfried, Adele Eskeles Gottfried (2017-03-14; ; backlinks; similar):

The Fullerton Longitudinal Study offers an unique opportunity to model the stability of intelligence and achievement and their relations from elementary through secondary school.

Using latent variable modeling, we fit a cross-lagged panel model to examine the relations between intelligence and achievement in 2 academic domains: mathematics and reading.

Findings: revealed that students’ achievement is highly stable across the school years. Childhood intelligence is a strong predictor of initial mathematics and reading achievement. After age 7-years, intelligence is not predictive of either mathematics or reading achievement after accounting for prior achievement. Students who enter school with strong academic skills tend to maintain their academic advantage throughout their elementary and secondary education.

We discuss the implications of these results for talent development.

[Keywords: intelligence, academic achievement, longitudinal model, ability, IQ]

“What Innovations Have We Already Lost?: The Importance of Identifying and Developing Spatial Talent”, Wai & Kell 2017

2017-wai.pdf: “What Innovations Have We Already Lost?: The Importance of Identifying and Developing Spatial Talent”⁠, Jonathan Wai, Harrison J. Kell (2017-01-01; backlinks)

“When Lightning Strikes Twice”, Makel et al 2016

2016-makel.pdf: “When Lightning Strikes Twice”⁠, Matthew C. Makel, Harrison J. Kell, David Lubinski, Martha Putallaz, Camilla P. Benbow (2016-07-01; ; backlinks; similar):

The educational, occupational, and creative accomplishments of the profoundly gifted participants (IQs ⩾ 160) in the Study of Mathematically Precocious Youth (SMPY) are astounding, but are they representative of equally able 12-year-olds? Duke University’s Talent Identification Program (TIP) identified 259 young adolescents who were equally gifted. By age 40, their life accomplishments also were extraordinary: 37% had earned doctorates, 7.5% had achieved academic tenure (4.3% at research-intensive universities), and 9% held patents; many were high-level leaders in major organizations. As was the case for the SMPY sample before them, differential ability strengths predicted their contrasting and eventual developmental trajectories—even though essentially all participants possessed both mathematical and verbal reasoning abilities far superior to those of typical Ph.D. recipients. Individuals, even profoundly gifted ones, primarily do what they are best at. Differences in ability patterns, like differences in interests, guide development along different paths, but ability level, coupled with commitment, determines whether and the extent to which noteworthy accomplishments are reached if opportunity presents itself.

[Keywords: intelligence, creativity, giftedness, replication, blink comparator]

“‘Genius Revisited’ Revisited”, Branwen 2016

Hunter: “‘Genius Revisited’ Revisited”⁠, Gwern Branwen (2016-06-19; ⁠, ⁠, ⁠, ⁠, ⁠, ; backlinks; similar):

A book study of surveys of the high-IQ elementary school HCES concludes that high IQ is not predictive of accomplishment; I point out that results are consistent with regression to the mean from extremely early IQ tests and small total sample size.

Genius Revisited documents the longitudinal results of a high-IQ/​gifted-and-talented elementary school, Hunter College Elementary School (HCES); one of the most striking results is the general high education & income levels, but absence of great accomplishment on a national or global scale (eg. a Nobel prize). The authors suggest that this may reflect harmful educational practices at their elementary school or the low predictive value of IQ.

I suggest that there is no puzzle to this absence nor anything for HCES to be blamed for, as the absence is fully explainable by their making 2 statistical errors: base-rate neglect⁠, and regression to the mean⁠.

First, their standards fall prey to a base-rate fallacy and even extreme predictive value of IQ would not predict 1 or more Nobel prizes because Nobel prize odds are measured at 1 in millions, and with a small total sample size of a few hundred, it is highly likely that there would simply be no Nobels.

Secondly, and more seriously, the lack of accomplishment is inherent and unavoidable as it is driven by the regression to the mean caused by the relatively low correlation of early childhood with adult IQs—which means their sample is far less elite as adults than they believe. Using early-childhood/​adult IQ correlations, regression to the mean implies that HCES students will fall from a mean of 157 IQ in kindergarten (when selected) to somewhere around 133 as adults (and possibly lower). Further demonstrating the role of regression to the mean, in contrast, HCES’s associated high-IQ/​gifted-and-talented high school, Hunter High, which has access to the adolescents’ more predictive IQ scores, has much higher achievement in proportion to its lesser regression to the mean (despite dilution by Hunter elementary students being grandfathered in).

This unavoidable statistical fact undermines the main rationale of HCES: extremely high-IQ adults cannot be accurately selected as kindergartners on the basis of a simple test. This greater-regression problem can be lessened by the use of additional variables in admissions, such as parental IQs or high-quality genetic polygenic scores⁠; unfortunately, these are either politically unacceptable or dependent on future scientific advances. This suggests that such elementary schools may not be a good use of resources and HCES students should not be assigned scarce magnet high school slots.

“Embryo Selection For Intelligence”, Branwen 2016

Embryo-selection: “Embryo Selection For Intelligence”⁠, Gwern Branwen (2016-01-22; ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ⁠, ; backlinks; similar):

A cost-benefit analysis of the marginal cost of IVF-based embryo selection for intelligence and other traits with 2016-2017 state-of-the-art

With genetic predictors of a phenotypic trait, it is possible to select embryos during an in vitro fertilization process to increase or decrease that trait. Extending the work of Shulman & Bostrom 2014⁠/​Hsu 2014⁠, I consider the case of human intelligence using SNP-based genetic prediction, finding:

  • a meta-analysis of GCTA results indicates that SNPs can explain >33% of variance in current intelligence scores, and >44% with better-quality phenotype testing
  • this sets an upper bound on the effectiveness of SNP-based selection: a gain of 9 IQ points when selecting the top embryo out of 10
  • the best 2016 polygenic score could achieve a gain of ~3 IQ points when selecting out of 10
  • the marginal cost of embryo selection (assuming IVF is already being done) is modest, at $1,822.7[^\$1,500.0^~2016~]{.supsub} + $243.0[^\$200.0^~2016~]{.supsub} per embryo, with the sequencing cost projected to drop rapidly
  • a model of the IVF process, incorporating number of extracted eggs, losses to abnormalities & vitrification & failed implantation & miscarriages from 2 real IVF patient populations, estimates feasible gains of 0.39 & 0.68 IQ points
  • embryo selection is currently unprofitable (mean: -$435.0[^\$358.0^~2016~]{.supsub}) in the USA under the lowest estimate of the value of an IQ point, but profitable under the highest (mean: $7,570.3[^\$6,230.0^~2016~]{.supsub}). The main constraints on selection profitability is the polygenic score; under the highest value, the NPV EVPI of a perfect SNP predictor is $29.2[^\$24.0^~2016~]{.supsub}b and the EVSI per education/​SNP sample is $86.3[^\$71.0^~2016~]{.supsub}k
  • under the worst-case estimate, selection can be made profitable with a better polygenic score, which would require n > 237,300 using education phenotype data (and much less using fluid intelligence measures)
  • selection can be made more effective by selecting on multiple phenotype traits: considering an example using 7 traits (IQ/​height/​BMI/​diabetes/​ADHD⁠/​bipolar/​schizophrenia), there is a factor gain over IQ alone; the outperformance of multiple selection remains after adjusting for genetic correlations & polygenic scores and using a broader set of 16 traits.

“On the Genetic Architecture of Intelligence and Other Quantitative Traits”, Hsu 2014

“On the genetic architecture of intelligence and other quantitative traits”⁠, Stephen D. H. Hsu (2014-08-14; backlinks; similar):

How do genes affect cognitive ability or other human quantitative traits such as height or disease risk? Progress on this challenging question is likely to be significant in the near future. I begin with a brief review of psychometric measurements of intelligence, introducing the idea of a “general factor” or g score. The main results concern the stability, validity (predictive power), and heritability of adult g. The largest component of genetic variance for both height and intelligence is additive linear), leading to important simplifications in predictive modeling and statistical estimation. Due mainly to the rapidly decreasing cost of genotyping, it is possible that within the coming decade researchers will identify loci which account for a significant fraction of total g variation. In the case of height analogous efforts are well under way. I describe some unpublished results concerning the genetic architecture of height and cognitive ability, which suggest that roughly 10k moderately rare causal variants of mostly negative effect are responsible for normal population variation. Using results from Compressed Sensing (L1-penalized regression), I estimate the statistical power required to characterize both linear and nonlinear models for quantitative traits. The main unknown parameter s (sparsity) is the number of loci which account for the bulk of the genetic variation. The required sample size is of order 100s, or roughly a million in the case of cognitive ability.

“Life Paths and Accomplishments of Mathematically Precocious Males and Females Four Decades Later”, Gelman 2014

“Life Paths and Accomplishments of Mathematically Precocious Males and Females Four Decades Later”⁠, Andrew Gelman (2014-01-08):

Anyway, I was interested in this paper (by David Lubinski, Camilla Benbow, and Harrison Kell) because . . . I’m one of the kids in the study⁠. I was 11 years old at the time.

What’s happened since then? According to the abstract of the paper:

Across the 2 cohorts, 4.1% had earned tenure at a major research university, 2.3% were top executives at “name brand” or Fortune 500 companies, and 2.4% were attorneys at major firms or organizations; participants had published 85 books and 7,572 refereed articles, secured 681 patents, and amassed $464.6$358.02014 million in grants. . . .

Wow, we’ve really cost the taxpayer a lot of money!…Recall that the “mathematically precocious youths” were identified by scoring high on the SAT. So it could well be labeled a study of “youths who were talented at standardized tests.” (But it’s not quite as bad as it sounds. Back in the 1970s, we didn’t see standardized tests very often, so we were taking the SAT cold. It’s not like we were sitting there in elementary school taking practice tests every year.)

“Experts Are Born, Then Made: Combining Prospective and Retrospective Longitudinal Data Shows That Cognitive Ability Matters”, Wai 2014

2014-wai.pdf: “Experts are born, then made: Combining prospective and retrospective longitudinal data shows that cognitive ability matters”⁠, Jonathan Wai (2014-01-01; backlinks)

“Genetics of Intellectual and Personality Traits Associated With Creative Genius: Could Geniuses Be Cosmobian Dragon Kings?”, Johnson & Jr. 2014

2014-johnson.pdf: “Genetics of Intellectual and Personality Traits Associated with Creative Genius: Could Geniuses Be Cosmobian Dragon Kings?”⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2014; ⁠, ; backlinks; similar):

[Behavioral genetics discussion of eminence/​genius: intelligence, developmental processes, psychopathology, and creativity scales all contribute to accomplishment but leave much unexplained, in particular, the odd pattern of inheritance where genius runs in families but highly sporadically and not following any standard Mendelian or polygenic inheritance pattern.

The authors refer to the concept of ‘emergenesis’⁠, where emergenic traits are not additive combinations of subtraits (as is strongly the case for traits like intelligence) but rather are multiplicative combinations, which are epistatic at the genetic level. Because all subtraits must be present to have a chance of producing the overall trait, emergenic traits can be highly genetically influenced yet still rare and sporadically appearing within families. (The Wiley Handbook of Genius 2014, chapter 14)]

“Expanding Talent Search Procedures by Including Measures of Spatial Ability: CTY's Spatial Test Battery”, Stumpf et al 2013

2013-stumpf.pdf: “Expanding Talent Search Procedures by Including Measures of Spatial Ability: CTY's Spatial Test Battery”⁠, Heinrich Stumpf, Carol J. Mills, Linda E. Brody, Philip G. Baxley (2013-10-10; backlinks; similar):

The importance of spatial ability for success in a variety of domains, particularly in science, technology, engineering, and mathematics (STEM), is widely acknowledged. Yet, students with high spatial ability are rarely identified, as Talent Searches for academically talented students focus on identifying high mathematical and verbal abilities. Consequently, students with high spatial abilities who do not also have high math or verbal abilities may not qualify.

In an effort to identify students with spatial talent, the Center for Talented Youth developed a Spatial Test Battery to supplement its mathematical and verbal Talent Searches. This article traces the development of the battery; describes its components, important psychometric properties, and continuing development; and encourages its use by researchers and educators interested in developing spatial talent.

[Keywords: block rotation test, CTY Spatial Test Battery, spatial ability, spatial test, STEM, surface development test, talent search, visual memory test]

“Who Rises to the Top?: Early Indicators”, Kell et al 2013

2013-kell.pdf: “Who Rises to the Top?: Early Indicators”⁠, Harrison J. Kell, David Lubinski, Camilla P. Benbow (2013-03-26; ; backlinks; similar):

Youth identified before age 13 (n = 320) as having profound mathematical or verbal reasoning abilities (top 1 in 10,000) were tracked for nearly three decades. Their awards and creative accomplishments by age 38, in combination with specific details about their occupational responsibilities, illuminate the magnitude of their contribution and professional stature.

Many have been entrusted with obligations and resources for making critical decisions about individual and organizational well-being. Their leadership positions in business, health care, law, the professoriate, and STEM (science, technology, engineering, and mathematics) suggest that many are outstanding creators of modern culture, constituting a precious human-capital resource. Identifying truly profound human potential, and forecasting differential development within such populations, requires assessing multiple cognitive abilities and using atypical measurement procedures.

This study illustrates how ultimate criteria may be aggregated and longitudinally sequenced to validate such measures.

[Keywords: cognitive abilities, creativity, human capital, intelligence, profoundly gifted, STEM]

“Spatial Ability: A Neglected Talent in Educational and Occupational Settings”, Kell & Lubinski 2013c

2013-kell-3.pdf: “Spatial Ability: A Neglected Talent in Educational and Occupational Settings”⁠, Harrison J. Kell, David Lubinski (2013-01-01; backlinks)

“History and Development of Above-Level Testing of the Gifted”, Warne 2012

2012-warne.pdf: “History and Development of Above-Level Testing of the Gifted”⁠, Russell T. Warne (2012-01-01)

“The Center for Talented Youth Identification Model: A Review of the Literature”, Tourón & Tourón 2011

2011-touron.pdf: “The Center for Talented Youth Identification Model: A Review of the Literature”⁠, Javier Tourón, Marta Tourón (2011-01-01; backlinks)

“_Human Intelligence_: Chapter 10, What Use Is Intelligence?”, Hunt 2011

2011-hunt-ch10-whatuseisintelligence.pdf: “_Human Intelligence_: chapter 10, What Use Is Intelligence?”⁠, Earl Hunt (2011-01-01; backlinks)

“A Theory Explaining Sex Differences in High Mathematical Ability Has Been around for Some Time”, Thomas 2010

1993-thomas.pdf: “A theory explaining sex differences in high mathematical ability has been around for some time”⁠, Hoben Thomas (2010-03-05; backlinks)

“Sex Differences in Mathematical Reasoning Ability in Intellectually Talented Preadolescents: Their Nature, Effects, and Possible Causes”, Benbow 2010

1988-benbow.pdf: “Sex differences in mathematical reasoning ability in intellectually talented preadolescents: Their nature, effects, and possible causes”⁠, Camilla Persson Benbow (2010-03-05; backlinks)

“Spatial Ability and STEM: A Sleeping Giant for Talent Identification and Development”, Lubinski 2010

2010-lubinski.pdf: “Spatial ability and STEM: A sleeping giant for talent identification and development”⁠, David Lubinski (2010-01-01; backlinks)

“Talent Sleuth Extraordinaire: An Interview With Camilla P. Benbow”, Henshon & Benbow 2010

2010-henshon.pdf: “Talent Sleuth Extraordinaire: An Interview With Camilla P. Benbow”⁠, Suzanna E. Henshon, Camilla P. Benbow (2010-01-01; backlinks)

“Issues in Early Prediction and Identification of Intellectual Giftedness”, Gottfried et al 2009

2009-gottfried.pdf: “Issues in Early Prediction and Identification of Intellectual Giftedness”⁠, Allen W. Gottfried, Adele Eskeles Gottfried, Diana Wright Guerin (2009-01-01; ; backlinks)

“Development of Gifted Motivation: Longitudinal Research and Applications”, Gottfried & Gottfried 2009b

2009-gottfried-2.pdf: “Development of gifted motivation: Longitudinal Research and Applications”⁠, Adele Eskeles Gottfried, Allen W. Gottfried (2009-01-01; ; backlinks)

“Cognitive Epidemiology: With Emphasis on Untangling Cognitive Ability and Socioeconomic Status”, Lubinski 2009

2009-lubinski.pdf: “Cognitive epidemiology: With emphasis on untangling cognitive ability and socioeconomic status”⁠, David Lubinski (2009-01-01; backlinks)

“The Johns Hopkins Talent Search Model for Identifying and Developing Exceptional Mathematical and Verbal Abilities”, Brody 2009

2009-brody.pdf: “The Johns Hopkins Talent Search Model for Identifying and Developing Exceptional Mathematical and Verbal Abilities”⁠, Linda E. Brody (2009-01-01; backlinks)

“Extending Sandra Scarr’s Ideas about Development to the Longitudinal Study of Intellectually Precocious Youth”, Benbow & Lubinski 2009

2009-benbow.pdf: “Extending Sandra Scarr’s Ideas about Development to the Longitudinal Study of Intellectually Precocious Youth”⁠, Camilla P. Benbow, David Lubinski (2009-01-01; backlinks)

“Spatial Ability for STEM Domains: Aligning over 50 Years of Cumulative Psychological Knowledge Solidifies Its Importance”, Wai et al 2009

2009-wai.pdf: “Spatial Ability for STEM Domains: Aligning over 50 years of Cumulative Psychological Knowledge Solidifies Its Importance”⁠, Jonathan Wai, David Lubinski, Camilla P. Benbow (2009; ; backlinks; similar):

The importance of spatial ability in educational pursuits and the world of work was examined, with particular attention devoted to STEM (science, technology, engineering, and mathematics) domains.

Participants were drawn from a stratified random sample of U.S. high schools (Grades 9–12, n = 400,000) and were tracked for 11+ years; their longitudinal findings were aligned with pre-1957 findings and with contemporary data from the Graduate Record Examination and the Study of Mathematically Precocious Youth⁠.

For decades, spatial ability assessed during adolescence has surfaced as a salient psychological attribute among those adolescents who subsequently go on to achieve advanced educational credentials and occupations in STEM.

Results: solidify the generalization that spatial ability plays a critical role in developing expertise in STEM and suggest, among other things, that including spatial ability in modern talent searches would identify many adolescents with potential for STEM who are currently being missed.

[Keywords: spatial ability, talent searches, longitudinal study, STEM, constructive replication]

Figure B1: ✱ For education and business, masters and doctorates were combined because the doctorate samples for these groups were too small to obtain stability (n 30). For the specific n for each degree by sex that composed the major groupings, see Appendix A. Average z scores of participants on spatial, mathematical, and verbal ability for bachelor’s degrees, master’s degrees, and PhDs are plotted by field in Figure B1. The groups are plotted in rank order of their normative standing on g (verbal [V] + spatial [S] + mathematical [M]) along the x-axis, and each arrow indicates on the continuous scale where each field lies on general mental ability. All x-axis values are based on the weighted means across each degree grouping. This figure is standardized in relation to all participants with complete ability data at the time of initial testing. Respective ns for each group (males + females) were as follows (for bachelor’s, master’s, and doctorates, respectively): engineering (1,143, 339, 71), physical science (633, 182, 202), math/​computer science (877, 266, 57), biological science (740, 182, 79), humanities (3,226, 695, 82), social science (2,609, 484, 158), arts (615, masters + doctorates = 171), business (2,386, masters + doctorates = 191), and education (3,403, masters + doctorates = 1,505).

[The graph is based on data from Project TALENT, a study of a representative sample of about 400,000 high school students in the 1960s and which continued for 11 years after their high school graduations. The students were divided into 9 groups according to the field in which they earned a college or graduate degree. These fields are arranged (from left to right) in order of the average overall IQ for degree earners in each field. They are education, business, arts, social science, humanities, biological science, math and computer science, physical science, and engineering. The overall IQ (“General Ability Level”) is listed as z-scores, which means that every 0.1-unit increment in the graph is equal to 1.5 IQ points.

Therefore, the average IQ for a person who earned an education degree was about 108. In the social sciences, it was 112. In physical sciences and engineering, the average IQ is about 119. Because most of these students self-selected into college majors, it seems that some areas of study are attracting very smart students and others . . . are not so much.

But overall IQ is not the whole story. (It rarely is in education.) The 3 dots connected by lines within each group indicate the pattern of broad abilities: verbal, spatial, and mathematical ability. Notice how different disciplines have different patterns of ability. Education, social sciences, and humanities tend to attract people with spatial abilities that are much lower compared to their verbal and math abilities. For math and computer science, physical science, and engineering, mathematical abilities tend to be highest and verbal abilities are lowest (though still well above the general population’s average).]

“A Great Man Standing With Terman and Hollingworth: Julian C. Stanley (1918-2005)”, Benbow 2005

2005-benbow.pdf: “A Great Man Standing With Terman and Hollingworth: Julian C. Stanley (1918-2005)”⁠, Camilla P. Benbow (2005-01-01; backlinks)

“The Duke University Talent Identification Program”, Putallaz et al 2005

2005-putallaz.pdf: “The Duke University Talent Identification Program”⁠, Martha Putallaz, Joy Baldwin, Hollace Selph (2005; backlinks; similar):

The Duke University Talent Identification Program (Duke TIP) holds the distinguished position of being the first ‘transplant’ of the Center for Talented Youth (CTY) regional talent search model developed by Professor Julian Stanley at Johns Hopkins University. Duke TIP was established in 1980, one year after CTY officially began.

This article describes the history of Duke TIP and the evolution of its talent searches and various formats of its educational programming models as well as the complementary role that research has played at Duke TIP. The success of Duke TIP stands as a truly remarkable tribute to Julian Stanley and to the robustness of the talent search model that he created at Johns Hopkins University.

Although the specific types of programs and initiatives may have taken different forms at Duke TIP, the underlying philosophy and commitment to identify and further the development of gifted and talented youth remains steadfast.

“Long-term Effects of Educational Acceleration”, Lubinski 2004b

2004-lubinski-2.pdf: “Long-term Effects of Educational Acceleration”⁠, David Lubinski (2004-01-01; backlinks)

“Scholastic Assessment or G? The Relationship Between the Scholastic Assessment Test (SAT) and General Cognitive Ability”, Frey & Detterman 2004

2004-frey.pdf: “Scholastic Assessment or g? The Relationship Between the Scholastic Assessment Test (SAT) and General Cognitive Ability”⁠, Meredith C. Frey, Douglas K. Detterman (2004; backlinks; similar):

There is little evidence showing the relationship between the Scholastic Assessment Test (SAT) and g (general intelligence). This research established the relationship between SAT and g, as well as the appropriateness of the SAT as a measure of g, and examined the SAT as a premorbid measure of intelligence. In Study 1, we used the National Longitudinal Survey of Youth 1979. Measures of g were extracted from the Armed Services Vocational Aptitude Battery and correlated with SAT scores of 917 participants. The resulting correlation was .82 (.86 corrected for nonlinearity). Study 2 investigated the correlation between revised and recentered SAT scores and scores on the Raven’s Advanced Progressive Matrices among 104 undergraduates. The resulting correlation was .483 (.72 corrected for restricted range). These studies indicate that the SAT is mainly a test of g. We provide equations for converting SAT scores to estimated IQs; such conversion could be useful for estimating premorbid IQ or conducting individual difference research with college students.

“Nowicka, R”, Robinson 2003

2003-gross.pdf: “Nowicka, R”⁠, Carmen Robinson (2003-01-01; backlinks)

“The Progress and Problems of an Incredibly Talented Sister and Brother”, Moore 2002

2002-moore.pdf: “The progress and problems of an incredibly talented sister and brother”⁠, Nancy Delano Moore (2002-01-01; backlinks)

“PSCI13124”, Management 2002

2002-hill.pdf: “PSCI13124”⁠, Frame Management (2002-01-01; backlinks)

“Tending the Special Spark: Accelerated and Enriched Curricula for Highly Talented Art Students”, Clark & Zimmerman 2002

2002-clark.pdf: “Tending the special spark: Accelerated and enriched curricula for highly talented art students”⁠, Gilbert Clark, Enid Zimmerman (2002-01-01; backlinks)

“A Genome-Wide Scan of 1842 DNA Markers for Allelic Associations With General Cognitive Ability: A Five-Stage Design Using DNA Pooling and Extreme Selected Groups”, Plomin et al 2001

2001-plomin.pdf: “A Genome-Wide Scan of 1842 DNA Markers for Allelic Associations with General Cognitive Ability: A Five-Stage Design Using DNA Pooling and Extreme Selected Groups”⁠, Robert Plomin, Linzy Hill, Ian W. Craig, Peter McGuffin, Shaun Purcell, Pak Sham, David Lubinski, Lee A. Thompson et al (2001-11-01; ; backlinks; similar):

All measures of cognitive processes correlate moderately at the phenotypic level and correlate substantially at the genetic level. General cognitive ability (g) refers to what diverse cognitive processes have in common. Our goal is to identify quantitative trait loci (QTLs) associated with high g compared with average g.

In order to detect QTLs of small effect size⁠, we used extreme selected samples and a 5-stage design with nominal alpha levels that permit false positive results in early stages but remove false positives in later stages. As a first step toward a systematic genome scan for allelic association, we used DNA pooling to screen 1842 simple sequence repeat (SSR) markers approximately evenly spaced at 2 cM throughout the genome in a 5-stage design:

  1. case-control DNA pooling (101 cases with mean IQ of 136 and 101 controls with mean IQ of 100),
  2. case-control DNA pooling (96 cases with IQ >160 and 100 controls with mean IQ of 102),
  3. individual genotyping of Stage 1 sample,
  4. individual genotyping of Stage 2 sample,
  5. transmission disequilibrium test (TDT; 196 parent-child trios for offspring with IQ >160).

The overall Type I error rate is 0.000125, which robustly protects against false positive results. The numbers of markers surviving each stage using a conservative allele-specific directional test were 108, 6, 4, 2, and 0, respectively, for the 5 stages. A genomic control test using DNA pooling suggested that the failure to replicate the positive case-control results in the TDT analysis was not due to ethnic stratification.

Several markers that were close to statistical-significance at all stages are being investigated further. Relying on indirect association based on linkage disequilibrium between markers and QTLs means that 100,000 markers may be needed to exclude QTL associations. Because power drops off precipitously for indirect association approaches when a marker is not close to the QTL, we are not planning to genotype additional SSR markers. Instead we are using the same design to screen markers such as cSNPs and SNPs in regulatory regions that are likely to include functional polymorphisms in which the marker can be presumed to be the QTL.

“Importance of Assessing Spatial Ability in Intellectually Talented Young Adolescents: A 20-year Longitudinal Study”, Shea et al 2001

2001-shea.pdf: “Importance of assessing spatial ability in intellectually talented young adolescents: A 20-year longitudinal study”⁠, Daniel L. Shea, David Lubinski, Camilla P. Benbow (2001-01-01; backlinks)


2001-lubinski.pdf: “1247” (2001-01-01; backlinks)

“Relationship between Levels of Giftedness and Psychosocial Adjustment”, Norman et al 1999

1999-norman.pdf: “Relationship between levels of giftedness and psychosocial adjustment”⁠, Antony D. Norman, Shula G. Ramsay, Carl R. Martray, Julia L. Roberts (1999; backlinks; similar):

This study compares 2 groups of gifted students, highly (n = 74) and moderately (n = 163) gifted, on a number of scales including self-concept, emotional autonomy, and anxiety.

Although a measure of academic ability was used to create distinctive ability groups, the results did not support the hypotheses that highly gifted students would be more likely to display lower self-concepts and more adjustment problems than the moderately gifted group.

These findings are examined in light of past research on differences in highly and moderately gifted students.

“A Quantitative Trait Locus Associated With Cognitive Ability in Children”, Chorney et al 1998

1998-chorney.pdf: “A Quantitative Trait Locus Associated With Cognitive Ability in Children”⁠, M. J. Chorney, K. Chorney, N. Seese, M. J. Owen, J. Daniels, P. McGuffin, L. A. Thompson, D. K. Detterman et al (1998-05-01; backlinks; similar):

Quantitative trait loci (QTLs) associated with general cognitive ability (g) were investigated for several groups of children selected for very high or for average cognitive functioning.

A DNA marker in the gene for insulin-like growth factor-2 receptor (IGF2R) on Chromosome 6 yielded a statistically-significantly greater frequency of a particular form of the gene (allele) in a high-g group (0.303; average IQ = 136, n = 51) than in a control group (0.156; average IQ = 103, n = 51).

This association was replicated in an extremely-high-g group (all estimated IQs > 160, n = 52) as compared with an independent control group (average IQ = 101, n = 50), with allelic frequencies of 0.340 and 0.169, respectively. Moreover, a high-mathematics-ability group (n = 62) and a high-verbal-ability group (n = 51) yielded results that were in the same direction but only marginally statistically-significant (p = 0.06 and 0.08, respectively).

[Warning: despite the replication, these candidate-gene hits were all false positives.]

“My Education”, Plotinck 1996

1996-plotinck.pdf: “My Education”⁠, Alexander Plotinck (1996-01-01; backlinks)

“Entering a Women’s College Two Years Early”, Cargain 1996

1996-cargain.pdf: “Entering a Women’s College Two Years Early”⁠, Michele J. Cargain (1996-01-01; backlinks)

“Optimal Development Of Talent: Respond Educationally To Individual Differences In Personality”, Lubinski & Benbow 1995b

1995-lubinski-2.pdf: “Optimal Development Of Talent: Respond Educationally To Individual Differences In Personality”⁠, David Lubinski, Camilla P. Benbow (1995; ; backlinks; similar):

…How do we develop the talents of gifted children while maintaining equity? Based upon the long and celebrated history of individual differences research (Dawis 1992) from educational and vocational counseling (Brayfield 1950; Dawis & Lofquist 1984; Patterson 1938; Williamson 1939; 1965), we believe that optimal utilization of talent depends upon responding to individual differences in personalities. Specifically, children must be placed in educational environments that are congruent with, and build upon, their most salient abilities and preferences (Benbow & Lubinski 1994; in press; Lubinski & Benbow 1994; Lubinski, Benbow, and Sanders 1993; Stanley 1977). This approach, which is advocated by the Study of Mathematically Precocious Youth (SMPY) (Benbow & Lubinski 1994; in press; Stanley 1977), serves as the focus of this article.

We argue and present evidence that individuals possess certain attributes that make them differentially suited for excelling, with fulfillment, in contrasting educational and vocational tracks. That is, only a limited set of learning environments is educationally optimal for anyone individual, even a gifted individual. Students, for example, put forth their best effort when they intrinsically enjoy what they are doing, and world-class achievement is most likely to develop when gifted individuals are allowed to pursue what they love at their desired pace. Indeed, learning can be optimized and achievement motivation enhanced if students are presented with tasks that are not only challenging (ie. slightly above the level already mastered) but also personally meaningful to them (Lofquist & Dawis 1991)…

“The Munich Longitudinal Study of Giftedness”, Christopher et al 1994

1994-perleth.pdf: “The Munich Longitudinal Study of Giftedness”⁠, Christopher, Perleth und Kurt A., Heller (1994-01-01; ; backlinks)

“Competence and Responsibility: The Third European Conference of The European Council for High Ability Held in Munich (Germany), October 11-14, 1992; Volume 2: Proceedings of the Conference”, A. et al 1994

1994-heller-competenceandresponsibility3rdconference.pdf: “Competence and Responsibility: The Third European Conference of The European Council for High Ability held in Munich (Germany), October 11-14, 1992; Volume 2: Proceedings of the Conference”⁠, Kurt A., Heller und Ernst A., Hany (1994-01-01; backlinks)

Beyond Terman: Contemporary Longitudinal Studies of Giftedness and Talent”, Subotnik & Arnold 1994

1994-subotnik-beyondterman.pdf: Beyond Terman: contemporary longitudinal studies of giftedness and talent⁠, Rena F. Subotnik, Karen D. Arnold (1994; ; backlinks; similar):

Beyond Terman: Contemporary Longitudinal Studies of Giftedness and Talent is an important contribution to the literature in two fields—those of gifted education and educational research. It is important for the former in terms of the insights and understandings it provides about giftedness and its nurture. It is important for the latter for its elucidations of the methodology associated with longitudinal research. The editors point out that “[the] volume presents recent collected works that demonstrate the fit between longitudinal methodology and the central issues of gifted education. Collectively, the studies investigate the early determinants of later academic and career achievement and creativity while employing varied identification practices, perspectives, theoretical orientations, and populations.”

The studies described vary along many dimensions, including research problem, sample size and character, length of study, data collection procedures and sources, and longitudinal orientation (ie. emergent/​developmental or retrospective). The studies deal with a variety of talent areas, such as academic achievement, science, technical creativity, music, creative and productive thinking, and career development. The samples include gifted and talented children, youths, and adults, both males and females. Although most of the studies deal with identified gifted/​talented individuals, one is a retrospective look at the achievements of graduate students in an university-level leadership education program. Studies originating in Germany and Israel add an international flavor and, more importantly, remind us that there is good research being conducted beyond the borders of the U.S.

As the premiere longitudinal investigation of a gifted population, the Terman study set a standard of comprehensiveness, large study sample, and societal influence that is difficult to supersede. In spite of the Terman study’s large number of research associates and rich sources of funding support, the data are still being organized for more accurate statistical analysis and examined for more challenging research questions. Further, the Genetic Studies of Genius and its more current follow-ups did not address key questions of concern in today’s social, political, and historical climate, or issues of central importance in the future. The investigations in this book have established a groundwork for answering previously unanswered questions: Are we identifying the “right” people? What are the outcomes associated with various forms of identification and intervention?

Over the course of his long career, Terman’s perspective on high IQ as a source for potential genius changed to allow personality, interest, special abilities, and opportunity to play a growing role in adult achievement. In filling a vacuum left by Terman, this collection of contemporary studies can guide policy and program development based on the conditions and interventions that contribute to the fulfillment of talent.

“Follow-up Insights on Rapid Educational Acceleration”, Charlton et al 1994

1994-charlton.pdf: “Follow-up insights on rapid educational acceleration”⁠, Jane C. Charlton, Donald M. Marolf, Julian C. Stanley (1994; backlinks; similar):

Too little is known about what happens, when they grow up, to youths who reason extremely well mathematically. Few tell their story to specialists in education of the gifted, either in writing or orally.

Julian Stanley brought 2 successful former “radical accelerants” to the November 1993 annual meeting of the National Association for Gifted Children in Atlanta and also provided some information about 12 other mathematically precocious youths.

Jane C. Charlton and Donald M. Marolf, the 2 young adults featured, told the symposium audience about themselves and answered questions. They were amazingly frank, insightful, and humorous about their lives thus far.

Both are convinced, and are convincing, that rapid progress through school grades all the way to the Ph.D. degree is the nearly optimal way for persons like themselves to enrich their education and prepare for adulthood. All 3 speakers agreed, however, that extremely fast educational advancement might not be the ideal curriculum path for some other equally capable boys and girls.

“Programs for Mathematically Gifted Students: A Review of Empirical Research”, Sowell 1993

1993-sowell.pdf: “Programs for Mathematically Gifted Students: A Review of Empirical Research”⁠, Evelyn J. Sowell (1993; backlinks; similar):

This paper summarizes and critiques the empirical research of the 1970s and 1980s on programs for mathematically gifted students. Much research has shown that accelerating the mathematics curriculum provides a very good program for precocious students. Organizational plans that place mathematically gifted students together for mathematics instruction also offer opportunities for these students to perform well. Although technology-based instruction also appears to provide an efficacious way of providing instruction for mathematically gifted elementary students, this method should be examined further with older students and in long-term studies. Research with enriched curricula and non-computer-based instruction provided inconclusive evidence of efficacy for mathematically gifted students.

“The Origins and Development of High Ability”, Bock et al 1993

1993-bock-theoriginanddevelopmentofhighability.pdf: “The Origins and Development of High Ability”⁠, Gregory R. Bock, Kate Ackrill, R. C. Atkinson, Robert J. Sternberg, Douglas K. Detterman, C. P. Benbow et al (1993-01-01; backlinks)

“Psychological Profiles of the Mathematically Talented: Some Sex Differences and Evidence Supporting Their Biological Basis”, Benbow & Lubinski 1993

1993-benbow.pdf: “Psychological profiles of the mathematically talented: some sex differences and evidence supporting their biological basis”⁠, Camilla Persson Benbow, David Lubinski (1993-01-01; backlinks)

“Consequences of Gender Differences in Mathematical Reasoning Ability and Some Biological Linkages”, Benbow & Lubinski 1993b

1993-benbow-2.pdf: “Consequences of Gender Differences in Mathematical Reasoning Ability and Some Biological Linkages”⁠, C. P. Benbow, D. Lubinski (1993-01-01; backlinks)

“The Pipeline Is Leaking Women All the Way Along”, Alper 1993

1993-alper.pdf: “The Pipeline is Leaking Women All the Way Along”⁠, Joe Alper (1993-01-01)

“Selected Results of the Munich Longitudinal Study of Giftedness: The Multidimensional/typological Giftedness Model”, Perleth et al 1993

1993-perleth.pdf: “Selected results of the Munich longitudinal study of giftedness: The multidimensional/typological giftedness model”⁠, Christopher Perleth, Wolfgang Sierwald, Kurt A. Heller (1993; ; backlinks; similar):

The Munich Longitudinal Study of Giftedness (carried out from 1985 to 1989), the most comprehensive giftedness study ever conducted in Germany, covers 6 cohorts at 3 points of measurement. In this article, the study’s multidimensional and typographical conception of giftedness is explained.

After a short overview, results concerning the validation of the multidimensional giftedness model as well as attempts to establish a giftedness typology are presented. While the multidimensional model proved to be useful for predicting achievement behavior, the typological attempts failed. Finally, it is demonstrated that intelligent and creatively gifted students differ strongly in their achievement behavior.

Consequences for fostering the gifted, especially the creatives, in school are discussed.

“A Decade of Longitudinal Research On Academic Acceleration Through the Study of Mathematically Precocious Youth”, Swiatek 1993

1993-swiatek.pdf: “A Decade of Longitudinal Research On Academic Acceleration Through the Study of Mathematically Precocious Youth”⁠, Mary Ann Swiatek (1993; backlinks; similar):

Over the past decade, several longitudinal studies pertaining to the education of intellectually gifted students were produced through the Study of Mathematically Precocious Youth (SMPY). One area that was emphasized, in keeping with SMPY’s history, is academic acceleration.

SMPY’s studies, which consider various groups of students, methods of acceleration, and types of outcomes, support acceleration as an educational method. Their results are in keeping with the work of other authors in this area. In this article, the subjects, methods, and outcomes of SMPY’s studies are described and plans for future research are outlined.

“Personality, Learning Style And Cognitive Style Profiles Of Mathematically Talented Students”, Mills 1993

1993-mills.pdf: “Personality, Learning Style And Cognitive Style Profiles Of Mathematically Talented Students”⁠, Carol J. Mills (1993; ; backlinks; similar):

Clear personality differences were found for a sample of academically talented students when compared to a general population of same age students.

On the Myers-Briggs dimensions⁠, the academically talented students differed statistically-significantly from the comparison group on all 4 dimensions. Specifically, the academically talented group expressed greater preferences for introversion, intuition, and thinking. Although there were more judging types in this group than in the comparison group, overall more academically talented students expressed a preference for a perceptive style.

They also tended to be higher on achievement motivation and lower on interpersonal and social concerns.

In particular, a cognitive style that emphasizes a thinking over a feeling mode appears to mediate gender differences in mathematics ability and achievement.

“An Interview With Julian C. Stanley”, Kirschenbaum 1992

1992-kirschenbaum.pdf: “An Interview with Julian C. Stanley”⁠, Robert J. Kirschenbaum (1992-01-01; backlinks)

“The Nature and Development of Giftedness. A Longitudinal Study”, A. & Heller 1991

1991-heller.pdf: “The Nature and Development of Giftedness. A Longitudinal Study”⁠, Kurt A., Heller (1991-01-01; ; backlinks)

“Tribute to Halbert B. Robinson (1925-1981)”, Stanley 1991c

1991-stanley-3.pdf: “Tribute to Halbert B. Robinson (1925-1981)”⁠, Julian C. Stanley (1991-01-01; backlinks)

“Educational Productivity Predictors Among Mathematically Talented Students”, Benbow et al 1991

1991-benbow.pdf: “Educational Productivity Predictors Among Mathematically Talented Students”⁠, Camilla Persson Benbow, Olya Arjmand, Herbert J. Walberg (1991; backlinks; similar):

Walberg 1984 identified 9 correlates of the educational achievement displayed by students in the United States and in a dozen other countries and called them “productivity factors”.

Using data from the Study of Mathematically Precocious Youth’s longitudinal survey of its students 10 years after identification, we tested 5 of the productivity factors for their ability to predict educational achievement and educational and career aspirations of mathematically talented students. We also examined the validity of the prevailing belief that gifted children achieve highly regardless of the educational experiences provided. 13-year-old students (1,247) in the top 1% to 2% nationwide in ability were followed until age 23.

Students’ achievements and aspirations were uniformly high at that time. Nonetheless, the 5 productivity factors could statistically-significantly predict their educational achievements and aspirations. The predictors were, in order of usefulness, quality of instruction, home environment, motivation, ability, attitudes, and quantity of instruction. Generally, the productivity factors appeared to operate similarly for males and females, but had stronger impacts on female aspirations.

The results indicate that, even among gifted students, environmental interventions may enhance educational achievement, especially that of females.

“Eight Considerations for Mathematically Talented Youth”, Stanley et al 1990

1990-stanley.pdf: “Eight Considerations for Mathematically Talented Youth”⁠, Julian Stanley, Ann E. Lupkowski, Susan G. Assouline (1990-01-01; backlinks)

“Applying: A Mentor Model: For Young Mathematically Talented Students”, Lupkowski et al 1990

1990-lupkowski.pdf: “Applying: A Mentor Model: For Young Mathematically Talented Students”⁠, Ann E. Lupkowski, Susan G. Assouline, Julian C. Stanley (1990-01-01; backlinks)

“Leta Stetter Hollingworth: A Pilgrim in Research in Her Time and Ours”, Benbow 1990

1990-benbow.pdf: “Leta Stetter Hollingworth: A pilgrim in research in her time and ours”⁠, Camilla Persson Benbow (1990; backlinks; similar):

Leta Hollingworth’s research program spanned 3 decades (1912–1939) and 3 areas: psychology of women, mental retardation, and intellectual talent. The last area captured her greatest attention; she completed more than twice as many publications on this topic than in the other 2 areas combined.

This article presents an analysis and characterization of her research, especially her research dealing with gifted children. Leta Hollingworth’s research contributions must be viewed as a model to be aspired to even today. She addressed her research questions with scientific rigor, and the best journals published her articles.

Yet Hollingworth was committed to both research and service. She tried to enhance the potential of gifted students by providing them with appropriate educational programming. Her research through service to gifted students serves as a cornerstone for the gifted child movement in the 1980s.

“Leta Hollingworth's Contributions to Above-level Testing of the Gifted”, Stanley 1990b

1990-stanley-2.pdf: “Leta Hollingworth's contributions to above-level testing of the gifted”⁠, Julian C. Stanley (1990; backlinks; similar):

Leta S. Hollingworth (1886–1939) pioneered in above age-and grade-level testing of boys and girls in the New York City area whose IQs were extremely high.

Her deep insights about measuring general and special abilities led to numerous current academic activities on behalf of intellectually highly talented young persons, especially including above-level curricula for them.

“Most Fare Better”, Stanley 1989c

1989-stanley-3.pdf: “Most Fare Better”⁠, Julian C. Stanley (1989-01-01; backlinks)

“On Being a Misfit”, Lindblad 1989

1989-lindblad.pdf: “On Being a Misfit”⁠, Jeanette D. Lindblad (1989-01-01; backlinks)

“Media Review: Books: Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”, Wood & Bransky 1987

1987-wood.pdf: “Media Review: Books: Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”⁠, Frank H. Wood, Trish Bransky (1987-01-01; backlinks)

“Extreme Mathematical Talent: A Hormonally Induced Ability?”, Benbow & Benbow 1987b

1987-benbow-2.pdf: “Extreme Mathematical Talent: A Hormonally Induced Ability?”⁠, Camilla Persson Benbow, Robert Michael Benbow (1987-01-01; backlinks)

“SAT-M Scores of Highly Selected Students in Shanghai Tested When Less Than 13 Years Old”, Stanley et al 1986b

1986-stanley-2.pdf: “SAT-M scores of highly selected students in Shanghai tested when less than 13 years old”⁠, Julian C. Stanley, Jia-fen Huang, Xue-min Zu (1986-01-01; backlinks)

“Systems and Models for Developing Programs for the Gifted and Talented”, Renzulli 1986

1986-renzulli-systemsandmodelsforprogramsforgiftedtalented.pdf: “Systems and Models for Developing Programs for the Gifted and Talented”⁠, Joseph S. Renzulli (1986-01-01; backlinks)

“Chapter 1: SMPY's Model for Teaching Mathematically Precocious Students”, Benbow 1986b

1986-benbow-2.pdf: “Chapter 1: SMPY's Model for Teaching Mathematically Precocious Students”⁠, Camilla Persson Benbow (1986-01-01; backlinks)

“A Baker’s Dozen of Years Applying All Four Aspects of the Study of Mathematically Precocious Youth (SMPY)”, Stanley 1985b

1985-stanley-2.pdf: “A baker’s dozen of years applying all four aspects of the Study of Mathematically Precocious Youth (SMPY)”⁠, Julian C. Stanley (1985-01-01; backlinks)

“Visual Thinking: The Art of Imagining Reality”, Root-Bernstein 1985

1985-rootbernstein.pdf: “Visual Thinking: The Art of Imagining Reality”⁠, Robert Scott Root-Bernstein (1985-01-01; backlinks)

“The Exceptionally Talented”, Stanley 1984b

1984-stanley-2.pdf: “The exceptionally talented”⁠, Julian C. Stanley (1984-01-01; backlinks)

“Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”, Reynolds et al 1984

1984-reynolds-writinginstructionforverballytalentedyouthjhumodel.pdf: “Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”⁠, Ben Reynolds, Kendra Kopelke, William G. Durden (1984-01-01; backlinks)

“Fast-Paced Classes: Challenging Gifted Students”, Tursman 1983

1983-tursman.pdf: “Fast-Paced Classes: Challenging Gifted Students”⁠, Cindy Tursman (1983-01-01; backlinks)

“Opening Doors for the Gifted: A Flexible Curriculum Will Provide Valuable Learning Options for Gifted Students, according to Directors of the Study of Mathematically Precocious Youth at the Johns Hopkins University”, Benbow & Stanley 1983i

1983-benbow-9.pdf: “Opening Doors for the Gifted: A flexible curriculum will provide valuable learning options for gifted students, according to directors of the Study of Mathematically Precocious Youth at the Johns Hopkins University”⁠, Camilla Persson Benbow, Julian C. Stanley (1983-01-01; backlinks)

“Duke University’s Talent Identification Program”, Sawyer & Daggett 1982

1982-sawyer.pdf: “Duke University’s Talent Identification Program”⁠, Robert N. Sawyer, Lynn M. Daggett (1982-01-01; backlinks)

“The Joys and Challenges in Raising a Gifted Child”, Moore 1982

1982-moore.pdf: “The Joys and Challenges in Raising a Gifted Child”⁠, Nancy Delano Moore (1982-01-01; backlinks)

“Consequences in High School and College of Sex Differences in Mathematical Reasoning Ability: A Longitudinal Perspective”, Benbow & Stanley 1982b

1982-benbow-2.pdf: “Consequences in High School and College of Sex Differences in Mathematical Reasoning Ability: A Longitudinal Perspective”⁠, Camilla Persson Benbow, Julian C. Stanley (1982; backlinks; similar):

Between 1972 and 1974 the Study of Mathematically Precocious Youth (SMPY) identified over 2,000 7th and 8th graders who scored as well as a national sample of 11th and 12th grade females on the College Board’s Scholastic Aptitude Test (SAT) Mathematics or Verbal tests. A substantial sex difference in mathematical reasoning ability was found (Benbow & Stanley, 1980b, 1981). The consequences and development of this sex difference over the following 5 years were investigated longitudinally. Over 91% (1,996 out of 2,188 SMPY students) participated. This study established that the sex difference persisted over several years and was related to subsequent sex differences in mathematics achievement. The sex difference in mathematics did not reflect differential mathematics course taking. The abilities of males developed more rapidly than those of females. Sex differences favoring males were found in participation in mathematics, performance on the SAT-M, and taking of and performance on mathematics achievement and Advanced Placement Program examinations. SMPY females received better grades in their mathematics courses than SMPY males did. Few significant sex differences were found in attitudes toward mathematics.

“Development of Superior Mathematical Ability During Adolescence”, Benbow 1981

1981-benbow.pdf: “Development of Superior Mathematical Ability During Adolescence”⁠, Lena Camilla Persson Benbow (1981-01-01; backlinks)

“Exceptionally Gifted Boys and Their Parents”, Albert 1980

1980-albert.pdf: “Exceptionally Gifted Boys and Their Parents”⁠, Robert S. Albert (1980-10-01; ; backlinks; similar):

In an effort to explore some of the possible early-experiential and family variables involved in the achievement of eminence we have developed a model of cognitive and personality development and have undertaken a longitudinal study of two distinct groups of exceptionally gifted boys and their families. In this report, early similarities and differences between two groups of exceptionally gifted boys and their families will be explored. Methodology: This is a longitudinal study of two samples of healthy, exceptionally gifted boys and their families. One group consisted of 26 of the highest scorers in the 1976 Math Talent Search conducted by Julian Stanley (1974, 1977); the second group of 26 boys living in southern California were selected only on the basis of IQ’s of 150 or higher.

…Factors included for study were parents’ and grand-parents’ educational attainment, parents’ and subjects’ birth-order, subjects’ and parents’ creative potential, and subjects’ cognitive giftedness.

  • Both samples were well-educated and had attained statistically-significantly more formal education than the national norms.
  • The birth-orders of the two samples are what one would expect from the literature of gifted children and they are not statistically-significantly different from one another.
  • A surprisingly remarkable similarity exists between the two samples of cognitively gifted boys, although they were selected a year apart, a continent apart, and on the basis of distinctly different test performances. We expected them to perform better on the figural and the math/​science subtests of the Wallach-Kogan and BIC measures, respectively, and the high-IQ sample to perform statistically-significantly better on the verbal and the art/​writing subtests. Instead, the differences between the samples are slight and not statistically-significant. At minimum, these results suggest that the two samples are each made of highly talented, cognitively gifted boys in the ares of art/​writing and math/​science as measured by standard instruments. Second, these results further indicate the versatility that accompanies exceptional giftedness…Table 1 shows that the parents of both groups of exceptionally gifted boys are themselves exceptionally creative. Parents of both groups outperformed Duke University subjects. Furthermore, the parents definitely showed more creative potential than their children. It is the parents of the high-IQ boys who have the highest creativity scores of all.

…We believe the results of the present study and those of Milgram et al show that cognitive giftedness and creative giftedness are very much related to one another and may be manifestations of the same complex, multi-faceted abilities. Therefore, it should not surprise us that there is a large degree of family cognitive and creative similarity.

“A Plea for Visual Thinking”, Arnheim 1980

1980-arnheim.pdf: “A Plea for Visual Thinking”⁠, Rudolf Arnheim (1980-01-01; ; backlinks)

“German for Verbally Gifted Youngsters at Hopkins: The First Year”, McClain & Durden 1980

1980-mcclain.pdf: “German for Verbally Gifted Youngsters at Hopkins: The First Year”⁠, William H. McClain, William G. Durden (1980-01-01; backlinks)

“Manipulate Important Educational Variables”, Stanley 1980b

1980-stanley-2.pdf: “Manipulate important educational variables”⁠, Julian C. Stanley (1980; backlinks; similar):

For 9 years personnel of the Study of Mathematically Precocious Youth (SMPY) at Johns Hopkins have found thousands of youths, chiefly 7th-graders, who reason extremely well mathematically. SMPY strives in various ways to help these students proceed considerably faster and better in mathematics and related subjects than is usually permitted or encouraged. Its work is offered as an example of important problems that, in the judgment of the author, educational psychologists should attack vigorously.

SMPY’s 4-D model is described, which emphasizes educational acceleration of youths who are highly able and eager to move ahead quickly.

“The Talent-Search Concept: an Identification Strategy for the Intellectually Gifted”, George 1979

1979-george.pdf: “The Talent-Search Concept: an Identification Strategy for the Intellectually Gifted”⁠, William C. George (1979-10-01; backlinks; similar):

Using the empirically based evidence that has resulted from the previous five Talent Searches of the Study of Mathematically Precocious Youth, the article develops the rationale and success behind the talent-search concept as an useful strategy for identifying the intellectually gifted. Its practicality as a model is further demonstrated through the systematic curricular programming that has resulted at school-district levels after students have been identified as talented in a specific aptitude area. The identification issue is discussed as it pertains to efficiency and effectiveness related to cost, predictive validity, and feasibility.

“The Future of Education”, Stanley & George 1979

1979-stanley.pdf: “The Future of Education”⁠, Julian C. Stanley, William C. George (1979-01-01; backlinks)

“The Study of Mathematically Precocious Youth”, George & Stanley 1979b

1979-george-2.pdf: “The Study of Mathematically Precocious Youth”⁠, W. C. George, J. C. Stanley (1979-01-01; backlinks)

“Early Entrance to College: The Johns Hopkins Experience; Study of Mathematically Precocious Youth (SMPY), The Johns Hopkins University”, Eisenberg & George 1979

1979-eisenberg.pdf: “Early Entrance to College: The Johns Hopkins Experience; Study of Mathematically Precocious Youth (SMPY), The Johns Hopkins University”⁠, Ann R. Eisenberg, William C. George (1979-01-01; backlinks)

“Searching for Scientifically Talented Youth?”, Cohn 1979c

1979-cohn-3.pdf: “Searching for Scientifically Talented Youth?”⁠, Sanford J. Cohn (1979-01-01; backlinks)

“Now We Are Six: The Ever-Expanding SMPY”, Stanley & George 1978

1978-stanley.pdf: “Now We Are Six: The Ever-Expanding SMPY”⁠, Julian C. Stanley, William C. George (1978-01-01; backlinks)

“Educational Programs and Intellectual Prodigies”, Stanley et al 1978

1978-stanley-educationalprogramsandintellectualprodigies.pdf: “Educational Programs and Intellectual Prodigies”⁠, Julian C. Stanley, William C. George, Cecilia H. Solano (1978-01-01; backlinks)

“Is Sex Role Related To Intellectual Abilities?”, Mills 1978

1978-mills.pdf: “Is Sex Role Related To Intellectual Abilities?”⁠, Carol Mills (1978-01-01; backlinks)

“Cognitive Characteristics of the Top-Scoring Third of the 1976 Talent Search Contestants”, Cohn 1978

1978-cohn.pdf: “Cognitive Characteristics of the Top-Scoring Third of the 1976 Talent Search Contestants”⁠, Sanford J. Cohn (1978-01-01; backlinks)

“Books Tell The SMPY Story”, Stanley et al 1977b

1977-stanley-2.pdf: “Books Tell The SMPY Story”⁠, J. C. Stanley, S. J. Cohn, W. C. George (1977-01-01; backlinks)

“Parental Support - Time and Energ”, George 1977

1977-george.pdf: “Parental Support - Time and Energ”⁠, W. C. George (1977-01-01; backlinks)

“Youths Who Reason Extremely Well Mathematically: Smpy's Accelerative Approach”, Stanley 1976

1976-stanley.pdf: “Youths Who Reason Extremely Well Mathematically: Smpy's Accelerative Approach”⁠, Julian C. Stanley (1976-01-01; backlinks)

“College Courses and Educational Facilitation of the Gifted”, Solano & George 1976

1976-solano.pdf: “College Courses and Educational Facilitation of the Gifted”⁠, Cecilia H. Solano, William C. George (1976-01-01; backlinks)

“My Introduction To Computing”, Smith 1976

1976-smith.pdf: “My Introduction To Computing”⁠, Daniel W. Smith (1976-01-01; backlinks)

“Merrill Kenneth Wolf: a Bachelor's Degree At 14”, Montour 1976

1976-montour.pdf: “Merrill Kenneth Wolf: a Bachelor's Degree At 14”⁠, Kathleen Montour (1976-01-01; backlinks)

“Accelerating Mathematics Instruction for the Mathematically Talented”, George 1976

1976-george.pdf: “Accelerating Mathematics Instruction for the Mathematically Talented”⁠, William C. George (1976-01-01; backlinks)

“Individualizing Science Curricula for the Gifted”, Cohn 1976

1976-cohn.pdf: “Individualizing Science Curricula for the Gifted”⁠, Sanford J. Cohn (1976-01-01; backlinks)

“Teacher and Pupil Stereotypes of Gifted Boys and Girls”, Solano 1975b

1976-solano-2.pdf: “Teacher and Pupil Stereotypes of Gifted Boys and Girls”⁠, Cecelia H. Solano (1975-01-01; backlinks)

“Visual Thinking”, Arnheim 1967

1969-arnheim-visualthinking.pdf: “Visual Thinking”⁠, Rudolf Arnheim (1967-01-01; ; backlinks)

“Creativity in Science through Visualization”, Walkup 1965

1965-walkup.pdf: “Creativity in Science through Visualization”⁠, Lewis E. Walkup (1965-08-01; backlinks; similar):

Editors’ note: Mr. Walkup, an electrical engineer by training but an applied physicist by experience, has worked 12 yr. in research on explosives and ballistics and 19 yr. in the technology of the graphic arts, especially on the electrostatic photographic process called xerography. In this latter field he has been a major contributor of inventive ideas; he holds 37 U. S. and 60 foreign patents. The present article is a result of his personal study of creativity in his co-workers in a large industrial research institute.

The fact that attempts to gain insight into the creative process have been so unsuccessful suggests that they have overlooked at least one basic ingredient in the process. This ingredient may lie in the nature or way the individual mind goes about remembering and manipulating data. The hypothesis is advanced that the creative persons appear to have stumbled onto and then developed to a high degree of perfection the ability to visualize—almost hallucinate—in the area in which they are creative. And their visualizations seem to be of a sort that lend themselves to easy manipulation in the thinking process. This is illustrated by reports from many of the great inventors of the past and it is easy to demonstrate that individuals differ enormously in the kind and degree of their ability to think in such manipulable visualizations. If correct, this aspect of creativity suggests many research attacks and many potential changes in education for creative activity.

…It is interesting to ask a number of persons to solve a simple problem in mental arithmetic, say, to subtract 46 from 100, and then to ask them what went on in their heads as they solved the problem. I have found the following gamut of processes used. Some persons simply grope around with words, perhaps dividing the problem up into subtracting 6 from 10 and 4 from 10, which they do simply by remembering the words associated with these operations and then somehow combining these results to give the final answer. Others mentally write out 100 with 46 beneath it and picture the process of writing down the answer below the two. Finally, some individuals have specialized equipment for just this operation. They visualize two juxtaposed scales from zero to 100, one starting at the right and one at the left. With this mnemonic gadget the required subtraction involves simply finding 46 on one of the scales and reading off 54 on the other!

…Another interesting example involves the ability to visualize combinations of cubes. Try asking a number of persons to visualize a large cube made up of 27 smaller cubes, that is, three on each edge of the composite cube. Then, ask him to imagine painting the entire outer surface of the large cube. Finally, ask him how many of the smaller cubes he has painted on zero, one, two, or three sides. After he gives the result, ask him to describe the mental process he used in arriving at the answer. A surprising variety of answers come from this simple test. Some persons, even some professionally engaged in science and art, simply are unable to solve this problem mentally because they cannot visualize a cube in any way! Others stumble around with crude visualizations of a cube and end up by guessing at the answer. Some can visualize an opaque cube fairly well but must infer from the one view what is on the other side. The most potent approach seems to be that of the person who can visualize a transparent cube and simply count the smaller cubes whose sides are covered with paint, a process something like counting one’s fingers with his hands held up in front of him.

In still another provocative problem, persons may be asked co give verbal directions for driving a car from one location to another, and then asked what they visualized mentally as they were giving the directions. Again, a wide variety of mental processes will be disclosed. Surprisingly, many persons report seeing the route as from a low-flying helicopter. The fact that different persons use vastly different visualizations in thinking is suggested by some other informal reports. One person has declared that he dreams only in words, that he does not use any form of visualization in dream states. It has been claimed by some semanticists that the human being thinks only in words. This seems an utterly absurd statement to many of us who spend a large part of our waking hours in visualizing and thinking in pictorial representations. This, of course, does not deny the fact that it is quite possible that semanticists do, in fact, think only in words; it would be logical that “word thinkers” would be drawn to this specialized field.

…This is well illustrated by the now famous visualization by Kekule, as reported by Beveridge, which led him to the discovery of the benzene ring through a vision of a series of linked atoms biting its tail like a snake. Michael Faraday was one of the first to “see” the electrical and magnetic lines of force that now are standard tools for physicists to visualize otherwise mysterious phenomena in this area. Albert Einstein apparently believed that thought consisted entirely of dealing with mechanical images and not at all of words. The mathematician Jacques Hadamard reported that he thought exclusively in visual pictures. However, these men did not seem to realize the uniqueness of their ability to visualize in manipulable images. They seemed to assume that all persons had much the same ability. Inventors with whom I have talked report thinking visually about complex mechanisms and organic chemical molecules combining with other molecules. So, it appears that ideas which can be grasped when drawn on paper can be visualized without being put onto paper, perhaps with many shorthand approximations for unimportant parts. Also, the nature of the seeing or sensing is peculiar. It is almost a feeling like the object being visualized. One can feel the pressure of contacting objects, or the erosion of material by friction, or the flow of heat from one point to another, or the swing of the oscillating electrical circuit, or the bending of light as it passes from one medium to another, or the appropriateness of a well-designed structure co hold a maximum load, with every part equally strained in the process, or the eternal bouncing about of the molecules of a gas, or the almost physical transfer of energy from the gasoline, through the motor, transmission, and to the driving wheels of the automobile. It is as though one’s own kinesthetic sensing mechanisms were associated with the physical object and that he thus sensed directly what was going on in the external system. In highly-developed visualizers, this process probably is carried over for other than physical phenomena. Thus, poverty can be seen and felt as a pervading vapor that penetrates a house with its odors and depression, and history might be strung out along an imaginary line extending back as far as one wishes.

…At least here is a positive lead that is so apparent to the creative persons with whom I am familiar that they never stopped to consider whether or not it is special. When asked if they use life-like visualizations when they are inventing, they are inclined to say, “Why yes. Doesn’t everybody?” [See also: typical mind fallacy]

“Spatial Ability: Its Educational and Social Significance”, Smith 1964

1964-smith-spatialabilityitseducationalsocialsignificance.pdf: “Spatial Ability: Its Educational and Social Significance”⁠, I. Macfarlane Smith (1964-01-01; backlinks)

“Scientific Careers and Vocational Development Theory: A Review, a Critique and Some Recommendations”, Super & Bachrach 1957

1957-super-scientificcareersandvocationaldevelopmenttheory.pdf: “Scientific Careers and Vocational Development Theory: A review, a critique and some recommendations”⁠, Donald E. Super, Paul B. Bachrach (1957-01-01; backlinks)