Online Short Spatial Ability Battery (OSSAB): Psychometric Norms for Older Students

The need for STEM specialists is growing in current technologically-oriented economy. This calls for new approaches in evaluation and development of relevant abilities and skills. However, the current educational systems might miss some students who have high potential for this field or who can develop such potential. For example, according to the results of one Russian study, gifted children may be missed by existing methods of talent search, partially due to the lack of standardised psychometric tests, especially of abilities beyond verbal and numerical abilities. One important predictor of STEM, often neglected in education, is spatial ability. Recently an online short spatial ability battery (OSSAB) for use in adolescent popula-tions was developed. However, no published norms are available. The aim of this study was to develop normalised thresholds for spatial ability testing using OSSAB battery with Russian 13-17 year old schoolchildren. Schoolchildren from the Sirius Educational Centre, demonstrating high achievement in 3 different areas: science (N = 640; 238 females), sports (N = 436; 67 females) and art (N = 260; 204 females), and schoolchildren (N = 752; 350 females) from general education schools of the Russian Federation participated in the study. Age of participants: 13-17 (M = 15.01; SD = 1.18). The study identified thresholds for 8 spatial ability levels: from Very low ability to Extraordinary giftedness. These thresholds can be used by teachers and school psychologists to determine the level of spatial ability in schoolchildren of 13-17 years of age. Based on individual students’ current levels of spatial ability, teachers can provide individual support and recommendations. For high performance recommendations may include additional clas-ses in STEM or natural sciences, for example, electronics, robotics, programming, physics or chemistry. For lower performance recommendations may include computer games containing spatial components; sports; playing musical instruments; origami classes; and studying the Chinese language. More broadly, school curricula in different subjects should include more spatial elements, such as: inclusion of stereometric tasks in learning materials; computer pro-grams for modelling in teaching geometry and other subjects; adding visualizations (graphs and tables) when explaining material. Overall, the results of this study suggest that a significant number of children have very low or very high level of spatial ability in both mainstream schools and in educational centres for high-preforming students. The norms developed in this study can be used for identification and individualized support in all educational settings.

Predicting educational achievement from DNA

This corrects the article DOI: 10.1038/mp.2016.107.

Predicting educational achievement from DNA

A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

Why do we differ in number sense? Evidence from a genetically sensitive investigation

Basic intellectual abilities of quantity and numerosity estimation have been detected across animal species. Such abilities are referred to as 'number sense'. For human species, individual differences in number sense are detectable early in life, persist in later development, and relate to general intelligence. The origins of these individual differences are unknown. To address this question, we conducted the first large-scale genetically sensitive investigation of number sense, assessing numerosity discrimination abilities in 837 pairs of monozygotic and 1422 pairs of dizygotic 16-year-old twin pairs. Univariate genetic analysis of the twin data revealed that number sense is modestly heritable (32%), with individual differences being largely explained by non-shared environmental influences (68%) and no contribution from shared environmental factors. Sex-Limitation model fitting revealed no differences between males and females in the etiology of individual differences in number sense abilities. We also carried out Genome-wide Complex Trait Analysis (GCTA) that estimates the population variance explained by additive effects of DNA differences among unrelated individuals. For 1118 unrelated individuals in our sample with genotyping information on 1.7 million DNA markers, GCTA estimated zero heritability for number sense, unlike other cognitive abilities in the same twin study where the GCTA heritability estimates were about 25%. The low heritability of number sense, observed in this study, is consistent with the directional selection explanation whereby additive genetic variance for evolutionary important traits is reduced.

A genome-wide association study identifies multiple loci associated with mathematics ability and disability

Numeracy is as important as literacy and exhibits a similar frequency of disability. Although its etiology is relatively poorly understood, quantitative genetic research has demonstrated mathematical ability to be moderately heritable. In this first genome-wide association study (GWAS) of mathematical ability and disability, 10 out of 43 single nucleotide polymorphism (SNP) associations nominated from two high- vs. low-ability (n = 600 10-year-olds each) scans of pooled DNA were validated (P < 0.05) in an individually genotyped sample of (*)2356 individuals spanning the entire distribution of mathematical ability, as assessed by teacher reports and online tests. Although the effects are of the modest sizes now expected for complex traits and require further replication, interesting candidate genes are implicated such as NRCAM which encodes a neuronal cell adhesion molecule. When combined into a set, the 10 SNPs account for 2.9% (F = 56.85; df = 1 and 1881; P = 7.277e-14) of the phenotypic variance. The association is linear across the distribution consistent with a quantitative trait locus (QTL) hypothesis; the third of children in our sample who harbour 10 or more of the 20 risk alleles identified are nearly twice as likely (OR = 1.96; df = 1; P = 3.696e-07) to be in the lowest performing 15% of the distribution. Our results correspond with those of quantitative genetic research in indicating that mathematical ability and disability are influenced by many genes generating small effects across the entire spectrum of ability, implying that more highly powered studies will be needed to detect and replicate these QTL associations.

Generalist genes and the Internet generation: etiology of learning abilities by web testing at age 10

A key translational issue for neuroscience is to understand how genes affect individual differences in brain function. Although it is reasonable to suppose that genetic effects on specific learning abilities, such as reading and mathematics, as well as general cognitive ability (g), will overlap very little, the counterintuitive finding emerging from multivariate genetic studies is that the same genes affect these diverse learning abilities: a Generalist Genes hypothesis. To conclusively test this hypothesis, we exploited the widespread access to inexpensive and fast Internet connections in the UK to assess 2541 pairs of 10-year-old twins for reading, mathematics and g, using a web-based test battery. Heritabilities were 0.38 for reading, 0.49 for mathematics and 0.44 for g. Multivariate genetic analysis showed substantial genetic correlations between learning abilities: 0.57 between reading and mathematics, 0.61 between reading and g, and 0.75 between mathematics and g, providing strong support for the Generalist Genes hypothesis. If genetic effects on cognition are so general, the effects of these genes on the brain are also likely to be general. In this way, generalist genes may prove invaluable in integrating top-down and bottom-up approaches to the systems biology of the brain.

Overlap and specificity of genetic and environmental influences on mathematics and reading disability in 10-year-old twins

BACKGROUND

To what extent do genetic and environmental influences on reading disability overlap with those on mathematics disability? Multivariate genetic research on the normal range of variation in unselected samples has led to a Generalist Genes Hypothesis which posits that the same genes largely affect individual differences in these abilities in the normal range. However, little is known about the etiology of co-morbidity for the disability extremes of reading and mathematics.

METHOD

From 2596 pairs of 10-year-old monozygotic and dizygotic twins assessed on a web-based battery of reading and mathematics tests, we selected the lowest 15% on reading and on mathematics. We conducted bivariate DeFries-Fulker (DF) extremes analyses to assess overlap and specificity of genetic and environmental influences on reading and mathematics disability defined by a 15% cut-off.

RESULTS

Both reading and mathematics disability are moderately heritable (47% and 43%, respectively) and show only modest shared environmental influence (16% and 20%). There is substantial phenotypic co-morbidity between reading and mathematics disability. Bivariate DF extremes analyses yielded a genetic correlation of .67 between reading disability and mathematics disability, suggesting that they are affected largely by the same genetic factors. The shared environmental correlation is .96 and the non-shared environmental correlation is .08.

CONCLUSIONS

In line with the Generalist Genes Hypothesis, the same set of generalist genes largely affects mathematical and reading disabilities. The dissociation between the disabilities occurs largely due to independent non-shared environmental influences.

Overlap and specificity of genetic and environmental influences on mathematics and reading disability in 10-year-old twins

BACKGROUND

To what extent do genetic and environmental influences on reading disability overlap with those on mathematics disability? Multivariate genetic research on the normal range of variation in unselected samples has led to a Generalist Genes Hypothesis which posits that the same genes largely affect individual differences in these abilities in the normal range. However, little is known about the etiology of co-morbidity for the disability extremes of reading and mathematics.

METHOD

From 2596 pairs of 10-year-old monozygotic and dizygotic twins assessed on a web-based battery of reading and mathematics tests, we selected the lowest 15% on reading and on mathematics. We conducted bivariate DeFries-Fulker (DF) extremes analyses to assess overlap and specificity of genetic and environmental influences on reading and mathematics disability defined by a 15% cut-off.

RESULTS

Both reading and mathematics disability are moderately heritable (47% and 43%, respectively) and show only modest shared environmental influence (16% and 20%). There is substantial phenotypic co-morbidity between reading and mathematics disability. Bivariate DF extremes analyses yielded a genetic correlation of .67 between reading disability and mathematics disability, suggesting that they are affected largely by the same genetic factors. The shared environmental correlation is .96 and the non-shared environmental correlation is .08.

CONCLUSIONS

In line with the Generalist Genes Hypothesis, the same set of generalist genes largely affects mathematical and reading disabilities. The dissociation between the disabilities occurs largely due to independent non-shared environmental influences.

The Origins of Diverse Domains of Mathematics: Generalist Genes but Specialist Environments

The authors assessed 2,502 ten-year-old children, members of 1,251 pairs of twins, on a Web-based battery of problems from 5 diverse aspects of mathematics assessed as part of the U.K. national curriculum. This 1st genetic study into the etiology of variation in different domains of mathematics showed that the heritability estimates were moderate and highly similar across domains and that these genetic influences were mostly general. Environmental factors unique to each twin in a family (rather than shared by the 2 twins) explained most of the remaining variance, and these factors were mostly specific to each domain.

'Generalist genes' and mathematics in 7-year-old twins

Mathematics performance at 7 years as assessed by teachers using UK national curriculum criteria has been found to be highly heritable. For almost 3000 pairs of 7-year-old same-sex twins, we used multivariate genetic analysis to investigate the extent to which these genetic effects on mathematics performance overlap with genetic effects on reading and general intelligence (g) as predicted by the 'generalist genes' hypothesis. We found substantial genetic overlap between mathematics and reading (genetic correlation=0.74) and between mathematics and g (0.67). These findings support the 'generalist genes' hypothesis that most of the genes that contribute to individual differences in mathematics are the same genes that affect reading and g. Nonetheless, the genetic correlations are less than unity and about a third of the genetic variance on mathematics is independent of reading and g, suggesting that there are also some genes whose effects are specific to mathematics.