What inspired you to investigate the interaction between school quality, genetic factors, and educational inequality?
This study was part of my PhD project, which overall looks at the interplay between schools, families, and genes. It started because we've seen in many countries that the quality and equality of education is under pressure. This raises questions for researchers, teachers, and policymakers about the drivers of educational performance differences and how these differences can be reduced.
Coming from a sociological background, I was initially focused on family background as one of the main drivers of performance differences and how school environments might exacerbate or compensate for these inequalities. But from other disciplines like behavioural genetics, we know that genetic differences also play a key role in shaping pupil performance, and these genetic factors are highly dependent on the environments children are in. While most behavioural genetics studies focus on the family environment, our study expands this to include the school environment.
Together with Antonie Knigge and Ineke Maas at Utrecht University, we combined sociological and behavioural genetics approaches to better understand how schools, families, and genes together play a role in educational inequality, particularly in the context of the Netherlands.
What were the most insightful or surprising insights of your study?
Maybe first it's good to elaborate on what we mean by "educational inequalities". There are obvious disparities in performance – some students perform better than others. With our behavioural genetics approach that relies on studying twins, we try to break this down by identifying the underlying sources of these differences. We categorise these into three broad sources: genetic differences, shared environmental differences (twins' shared experiences like family background), and non-shared environmental differences (individual experiences that make twins different, like peer influences).
We found that higher quality schools – measured by multiple indicators related to schools’ resources and climate – don’t necessarily reduce inequality. While these schools have a somewhat higher average student performance, the extent of educational inequality doesn't depend on school quality itself. But the socio-economic composition of the school does play a role. In schools with a higher socioeconomic status (SES) student body, there are fewer overall disparities, including genetic disparities. This aligns with other research suggesting that higher SES schools offer a less disruptive learning environment and positive influences of peers. These settings seem to be especially beneficial for students who are genetically inclined to have lower school performance, such as those with genetic risks towards ADHD or dyslexia.
How does your study challenge or confirm previous assumptions about educational inequality?
Quality differences between schools – in terms of school resources and climates – are often assumed to be important. The findings suggest that these aspects of school quality may be less crucial than we previously thought in reducing educational inequality, at least in the Dutch context. Instead, the socioeconomic composition of the school is more relevant in reducing educational inequality.
From the gene-environment interaction perspective, this study also challenges a dominant assumption in the field. There has been this long-standing idea that more resourceful and stable family environments increase genetic differences because children are better able to express their genetic potential in those environments. However, more and more research, particularly from non-US countries, is showing that this positive gene-environment interaction is either absent or sometimes even works in the reverse direction. This study contributes to that growing body of evidence by also finding a negative relationship.
In other words, in more advantaged environments, genetic differences actually seem to be smaller, rather than larger. And this applies not just to family environments but also to school environments. This means that children in lower SES families and schools may face a kind of double disadvantage. If they have genetic risks that contribute to lower educational performance, these children are less likely to be in family environments where those risks are compensated for, and they’re also less likely to attend schools where these risks are mitigated.
What’s unique about this study is that it integrates both family and school environments when examining these genetic and social interactions, which hasn't been done extensively in previous research. This combination of factors extends and contrasts some of the earlier findings in the field.
How can educators and policymakers apply the findings from your study to address disparities in educational outcomes?
That's a big and complex question, but I think there are lessons we can take from this research. Policymakers should consider what kind of inequality they want to address – whether it's social inequality, genetic inequality, or both. If this is undefined, policies could be ineffective in reducing inequality or unintendedly increase genetic and/or social inequalities. To reduce genetic inequality, more research is needed into the underlying mechanisms including the role of specific inherited vulnerabilities like health problems or learning difficulties. Schools, especially those with a low-SES population, could then be provided with the needed financial resources and knowledge to support the children who are more at risk of lower educational performance.
A more concrete takeaway is that equalising school quality alone might not be sufficient to reduce educational inequality. Instead, we may need to focus more on selection into schools, rather than just trying to reduce differences in school quality. For example, children from disadvantaged backgrounds might benefit more from attending schools with higher socio-economic status peers, where the school environment could help mitigate some of the genetic risks that affect educational performance.
In addition to this, another area I am exploring now is whether it's not the quality differences between schools, but the quantity of schooling that plays a role. Together with EUI Professor Herman G. Van de Werfhorst, we're looking at differences in school exposure – whether students have more or less schooling – and how that affects inequality along socioeconomic, migration, and gender lines. I think this is a particularly exciting direction to continue exploring, as it may shed more light on how education policies can be structured to address disparities more effectively.
Read the paper 'Gene-environment interaction analysis of school quality and educational inequality', published in npj | science of learning.
Kim Stienstra is a sociologist with a research interest in educational inequality, social stratification, and gene-environment interplay. She obtained her PhD at the Department of Sociology at Utrecht University. She is currently a fellow at the EUI’s Max Weber Programme for Postdoctoral Studies, the largest international postdoctoral programme in the social sciences and humanities in Europe. She is affiliated with the EUI Department of Political and Social Sciences.