The linear relations between math anxiety and math cognition have been frequently studied. However, the relations between anxiety and performance on complex cognitive tasks have been repeatedly demonstrated to follow a curvilinear fashion. Given the lack of attention to the possibility of such complex interplay between emotion and cognition in the math learning literature, the current study aimed to address this gap via exploring the relations between math anxiety, math motivation, and math cognition. The current study consisted of two samples. One sample included 262 pairs of young adolescent twins and the other included 237 adult college students. Participants self-reported their math anxiety and math motivation. Math cognition was assessed using a comprehensive battery of mathematics tasks. In both samples, results showed inverted-U relations between math anxiety and math performance in students with high intrinsic math motivation, and modest negative associations between math anxiety and math performance in students with low intrinsic math motivation. However, this pattern was not observed in tasks assessing student’s nonsymbolic and symbolic number estimation. These findings may help advance our understanding of mathematics learning processes and may provide important insights for treatment programs that target improving mathematics learning experiences and mathematical skills.

Background Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem-solving and achievement. The present study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Methods Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Results Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and non-familial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. Conclusions The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics, and may extend to other areas of academic achievement.

Traditionally, mathematical anxiety has been utilized as a unidimensional construct. However, math-specific anxiety may have distinguishable factors, and taking these factors into account may better illuminate the relationship between anxiety and mathematics performance. Drawing from the Western Reserve Reading and Math Project (N = 244 children, mean age = 12.28 years), the present study examined math-specific anxiety and mathematics problem evaluation, utilizing a structural equation modeling approach with an item-level measurement model structure. Results suggested math-specific anxiety tapped into three factors: anxiety about performing mathematical calculations, anxiety about math in classroom situations, and anxiety about math tests. Among the three math anxiety factors, only calculation anxiety was significantly and negatively related to math performance while holding other anxiety factors constant. Implications for the measurement of math-specific anxiety are discussed.

Socioeconomic risks (SES risks) are robust risk factors influencing children’s academic development. However, it is unclear whether the effects of SES on academic development operate universally in all children equally or whether they vary differentially in children with particular characteristics. The current study aimed to explore children’s temperament as protective or risk factors that potentially moderate the associations between SES risks and academic development. Specifically, latent growth modeling (LGM) was used in two longitudinal datasets with a total of 2236 children to examine how family SES risks and children’s temperament interactively predicted the development of reading and math from middle childhood to early adolescence. Results showed that low negative affect, high effortful control, and low surgency mitigated the negative associations between SES risks and both reading and math development in this developmental period. These findings underline the heterogeneous nature of the negative associations between SES risks and academic development and highlighted the importance of the interplay between biological and social factors on individual differences in development.

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Approximate number sense (ANS), the ability to rapidly and accurately compare quantities presented non-symbolically, has been proposed as a precursor to mathematics skills. Earlier work reported low heritability of approximate number sense, which was interpreted as evidence that approximate number sense acts as a fitness trait. However, viewing ANS as a fitness trait is discordant with findings suggesting that individual differences in approximate number sense acuity correlate with mathematical performance, a trait with moderate genetic effects. Importantly, the shared etiology of approximate number sense, mathematics, and general cognitive ability has remained unexamined. Thus, the etiology of approximate number sense and its overlap with math and general cognitive ability was assessed in the current study with two independent twin samples (N = 451 pairs). Results suggested that ANS acuity had moderate but significant additive genetic influences. ANS also had overlap with generalist genetic mechanisms accounting for variance and covariance in mathematics and general cognitive ability. Furthermore, ANS may have genetic factors unique to covariance with mathematics beyond overlap with general cognitive ability. Evidence across both samples was consistent with the proposal that the etiology of approximate number sense functions similar to that of mathematics and general cognitive skills.

Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 – 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct.

The strategy choice model (SCM) is a highly influential theory of human problem-solving. One strength of this theory is the allowance for both item and person variance to contribute to problem-solving outcomes, but this central tenet of the model has not been empirically tested. Explanatory item response theory (EIRT) provides an ideal approach to testing this core feature of SCM, as it allows for simultaneous estimation of both item and person effects on problem-solving outcomes. We used EIRT to test and confirm this central tenet of the SCM for adolescents’ (n = 376) solving of addition problems. The approach also allowed us to identify the strategy choices of adolescents who still struggle with basic arithmetic. The synthesis of SCM theory and EIRT modeling has implications for more fully investigating the sources of individual differences in students’ problem solving, and for identifying problem-solving patterns associated with poor academic achievement.