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. 2012 Feb 1;22(1):37-45.
doi: 10.1016/j.lindif.2011.11.015. Epub 2011 Dec 9.

Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

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Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

Elliot M Tucker-Drob et al. Learn Individ Differ. .
Free PMC article

Abstract

There is accumulating evidence that genetic influences on achievement are more pronounced among children living in higher socioeconomic status homes, and that these gene-by-environment interactions occur prior to children's entry into formal schooling. We hypothesized that one pathway through which socioeconomic status promotes genetic influences on early achievement is by facilitating the processes by which children select, evoke, and attend to learning experiences that are consistent with genetically influenced individual differences in their motivation to learn. We examined this hypothesis in a nationally representative sample of approximately 650 pairs of four-year old identical and fraternal twins who were administered a measure of math achievement, and rated by their parents on a broad set of items assessing learning motivation. Results indicated a genetic link between learning motivation and math achievement that varied positively with family socioeconomic status: Genetic differences in learning motivation contributed to math achievement more strongly in more advantaged homes. Once this effect of learning motivation was controlled for, gene-by-socioeconomic status interaction on math achievement was reduced from previously significant levels, to nonsignificant levels.

Figures

Figure 1
Figure 1
Panel A: Path diagram for a univariate gene-by-SES interaction model for math achievement. For ease of presentation, only one twin from each pair is represented. Panel B: Path diagram for a bivariate gene-by-SES interaction model. This model represents a Cholesky decomposition of the variation in math achievement into genes and environments shared with, and unique of, motivation. For ease of presentation, only one twin from each pair is represented.
Figure 2
Figure 2
Amounts of variance in early math skills accounted for by genes (A), the shared environment (C), and the nonshared environment (E), as functions of SES. Based on parameters reported in the last columns (Step 3) of Table 2. Note that the Y axis represents unstandardized variance.
Figure 3
Figure 3
Genetic and environmental components of motivation the regression of academic achievement on motivation (Motivation → Achievement), and the variance in academic achievement that is unique of motivation (Achievement.Motivation), as functions of SES. Based on parameters reported in the last columns (Step 3) of Table 3. Note that the Y axes represent unstandardized variance.
Figure 4
Figure 4
Genetic and environmental components of math achievement, the regression of motivation on math (Motivation → Achievement), and the variance in motivation that is unique of math achievement (Motivation.Achievement), as functions of SES. Based on parameters reported in the last columns (Step 3) of Table 4. Note that the Y axes represent unstandardized variance.

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