Early classroom reading gains moderate shared environmental influences on reading comprehension in adolescence

Gene-environment interaction analysis of school quality and educational inequality

We study to what extent schools increase or decrease environmental and genetic influences on educational performance. Building on behavioral genetics literature on gene-environment interactions and sociological literature on the compensating and amplifying effects of schools on inequality, we investigate whether the role of genes and the shared environment is larger or smaller in higher-quality school environments. We apply twin models to Dutch administrative data on the educational performance of 18,384 same-sex and 11,050 opposite-sex twin pairs, enriched with data on the quality of primary schools. Our results show that school quality does not moderate genetic and shared-environmental influences on educational performance once the moderation by SES is considered. We find a gene-environment interplay for school SES: genetic variance decreases with increasing school SES. This school SES effect partly reflects parental SES influences. Yet, parental SES does not account for all the school SES moderation, suggesting that school-based processes play a role too.

The nature-nurture of academic achievement at the intersection between gender, family background, and school context

We investigate the role of gender, family SES, school SES, and their intersection in educational achievement using a twin design. Drawing on theories of gene-environment interaction, we test whether high-SES environments compensate genetic risks or enhance genetic potential, and its dependency on gender. Using data on 37,000 Danish twin and sibling pairs from population-wide administrative registers, we report three main findings. First, for family SES, but not for school SES, we find that genetic influences play a slightly smaller role in high-SES environments. Second, this relationship is moderated by child gender: in high-SES families, the genetic influence is considerably lower for boys than for girls. Third, the moderating effect of family SES for boys is almost entirely driven by children attending low-SES schools. Our findings thus point to significant heterogeneity in gene-environment interactions, highlighting the importance of considering the multiplicity of social contexts.

Exploring the Machine Learning Paradigm in Determining Risk for Reading Disability

Purpose

Researchers have developed a constellation model of decoding-related reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation model framework. However, some issues may arise with applying the logistic regression method (e.g., multicollinearity). Machine learning techniques, such as random forest (RF), might assist in overcoming these limitations. They can better deal with complex data relations than traditional approaches. We examined the prediction performance of RF and compared it against LR to determine RD risk.

Method

The sample comprised 12,171 students from Florida whose third-grade RD risk was operationalized using the constellation model with one, two, three, or four RD indicators in first and second grade.

Results

Results revealed that LR and RF performed on par in accurately predicting RD risk. Regarding predictor importance, reading fluency was consistently the most critical predictor for RD risk.

Conclusion

Findings suggest that RF does not outperform LR in RD prediction accuracy in models with multiple linearly related predictors. Findings also highlight including reading fluency in early identification batteries for later RD determination.

Developmental behavioral genetics research on school achievement is missing vulnerable children, to our detriment

Gene-environment processes tell us how genetic predispositions and environments work together to influence children in schools. One type of gene-environment process that has been extensively studied using behavioral genetics methods is a gene-by-environment interaction. A gene-by-environment interaction shows us when the effect of your context on a phenotype differs depending on your genetic predispositions, or vice versa, when the effect of your genetic predispositions on a phenotype differs depending on your context. Developmental behavioral geneticists interested in children's school achievement have examined many different contexts within the gene-by-environment interaction model, including contexts measured from within children's home and school environments. However, this work has been overwhelmingly focused on WEIRD samples children, leaving us with non-inclusive scientific evidence. This can lead to detrimental outcomes when we overgeneralize this non-inclusive scientific evidence to racialized groups. We conclude with a call to include racialized children in more research samples.

Annual Research Review: Reading disorders revisited - the critical importance of oral language

This paper discusses research on reading disorders during the period since their classification within the overarching category of neurodevelopmental disorders (Journal of Child Psychology and Psychiatry, 53, 2012, 593). Following a review of the predictors of learning to read across languages, and the role of language skills as critical foundations for literacy, profiles of reading disorders are discussed and putative causal risk factors at the cognitive, biological, and environmental levels of explanation considered. Reading disorders are highly heritable and highly comorbid with disorders of language, attention, and other learning disorders, notably mathematics disorders. The home literacy environment, reflecting gene-environment correlation, is one of several factors that promote reading development and highlight an important target for intervention. The multiple deficit view of dyslexia (Cognition, 101, 2006, 385) suggests that risks accumulate to a diagnostic threshold although categorical diagnoses tend to be unstable. Implications for assessment and intervention are discussed.

Exploring the Influence of Early Childhood Education and Care on the Etiology of Achievement

The present study used a genetically-sensitive quantile regression approach to examine the relation between participation in early childhood education and care (ECEC) and subsequent school performance in literacy and numeracy at grades 3, 5, 7, and 9. The sample consisted of 1255 twin pairs (596 MZ; 659 DZ) with information on both ECEC and the National Assessment Program-Literacy and Numeracy (NAPLAN) scores from the Twin Study of NAPLAN. Results indicated variation in heritability estimates across the distributions of achievement, suggesting that different patterns of etiological influences may exist among children of different ability levels. Additionally, the results provided no evidence that ECEC significantly influenced achievement, and in the genetically-sensitive analyses, no evidence that ECEC moderated the influences of heritability of achievement for typically advantaged children. These results suggest that ECEC may not provide the levels of environmental support for later achievement that advocates claim, although we acknowledge that ECEC quality, which was not measured in the current study, may make a difference in whether or not ECEC influences achievement.