Nature vs Nurture in Education: What Teachers Need to Know

Nature and nurture both contribute to learning, but neither gives a teacher a fixed reading of a learner. "Nature" covers inherited differences, while "nurture" covers the settings and experiences that shape growth. They work together, so their effects cannot be split into a personal percentage. Studies can estimate sources of differences across groups. They cannot reveal one learner's ceiling or prescribe support. In school, assess the present task, remove access barriers, teach well, listen to the learner and family, and review progress over time.

Nature and Nurture in Education: The Direct Answer

The debate matters less as a contest and more as a warning against two errors. Genetic fatalism says, "this learner was born this way, so progress is limited". Environmental blame says, "the right teaching or parenting should remove every difference". Neither claim follows from the data. A review of more than 600,000 people found that more time in school improved scores on tests of thinking skills (Ritchie and Tucker-Drob, 2018).

In this guide

• What nature and nurture mean
• What heritability does and does not mean
• Correlation, interaction and genetic nurture
• What school studies can show
• What the evidence means for teaching
• A starting-point, support and review sequence
• Primary, secondary, SENCO and leadership examples
• Setting and streaming in England
• Genetic data and school ethics
• Limits, questions and references

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What Nature and Nurture Mean

Nature refers to inherited differences and the biological processes in which they take part. Nurture refers to the physical, social and cultural settings in which growth occurs. In school, nurture includes language, food, relationships, teaching, the curriculum, practice, culture, access and material conditions.

These terms are useful, but they do not describe two separate forces. Genes work in cells and bodies that develop in real settings. Each person meets those settings with their own history, interests and responses.

A learner also acts on the world around them. They may seek a book, avoid a task, ask for help or prompt a new response from an adult. Bronfenbrenner's ecological model can map layers of context, though it is not a genetic model.

The familiar question "which matters more?" is therefore incomplete. The answer depends on the outcome, age, group, measure and range of settings being studied. It may also change over time.

Consider reading. Learners differ in language, teaching, attention, hearing, memory, prior knowledge, health and many other traits. Some measured differences are statistically associated with inherited variation. Teaching still changes what learners know and can do.

A gene link does not make teaching optional. A teaching effect does not make learners the same.

This both-and view fits several accounts of growth, but it is not one simple process. Child development theories differ in what they explain and how they treat the body, action, relationships and culture. A broad claim that nature and nurture work together is not the same as a statistical gene-environment interaction.

The distinction also protects teachers from fixed language. "Innate", "natural", "hardwired", "gifted", "low ability" and "not academic" can sound like descriptions, but they often carry an untested forecast. A learner's current attainment is evidence about current performance under particular conditions. It is not a direct measure of future potential.

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What Heritability Does and Does Not Mean

Heritability is one of the most misunderstood words in the nature and nurture debate. In behavioural genetics, it is a group statistic. It estimates how much variation in a measured trait, within a specific population and environment, is associated with genetic variation.

It does not mean that a set share of one learner's attainment came from genes. It does not divide a person into inherited and setting-based shares. It does not show that a trait is fixed, natural, inevitable or resistant to teaching. It does not identify the biological pathway behind a difference.

A simple thought test helps. If every learner in a group had much the same teaching, differences in teaching would add little to the spread of scores in that group. A heritability figure could be high even though teaching was vital for all.

If access to teaching varied a great deal, the setting could account for more of the score gaps. The figure changes with the group and the setting.

Visscher, Hill and Wray describe these conceptual limits in their review of heritability. They also distinguish heritability from genetic determination. A trait can be highly heritable and still change when the environment changes. Conversely, a low heritability figure does not tell a teacher which intervention will work.

Twin studies often compare identical and non-identical twins. Identical twins share nearly all inherited DNA variants, while non-identical twins share about half on average. Researchers use differences in similarity between the pairs to model genetic, shared-environment and non-shared-environment components.

That figure depends on assumptions. These include how settings are shared, how twins are selected and how the trait is measured. They also include whether genetic and setting effects are additive and whether findings transfer to another place or age. "Non-shared environment" also contains measurement error. It is not a list of identifiable experiences unique to each twin.

De Zeeuw and colleagues reviewed 61 twin studies from 11 cohorts on primary-school results. They found substantial genetic and setting components in the included measures. This is valuable group evidence. It does not tell a Year 4 teacher why one learner is struggling with inference, spelling or number facts.

Reviews across many human traits find links with both genes and settings. Cross-trait means are even further from a single school choice. They cannot support a "50% rule" for IQ, personality or attainment.

For a teacher, the correct translation is modest: learners will differ even after similar instruction, and those differences can have many related sources. Continue to teach, assess access, look for patterns over time and adapt provision. Do not calculate a learner's heritability.

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How Genes and Environments Can Be Related

Saying "genes and environment interact" can hide several ideas. Scholars need the distinction because each idea needs a different study design. Teachers need it because none of these terms reveals the cause of one learner's needs.

Gene-environment correlation can be passive, evocative or active in classic accounts. Parents provide genes and settings, a learner's traits may evoke responses, and a learner may select activities that fit their interests. These labels describe patterns at a research level. They should not be used to claim that a reluctant reader "created" a poor reading environment or that family input is genetically caused.

Hart, Little and van Bergen show why environment research needs genetically sensitive designs. Home reading, household order and parental education can be linked with children's outcomes while sharing genetic and social causes. An observed association cannot tell us how much is a direct environmental effect.

That caution cuts in both directions. Genetic confounding does not prove that books, routines, relationships or income do not matter. It means the causal question needs a stronger design.

Genetic nurture is another reminder that genes are not sealed instructions inside the learner. Wang and colleagues reviewed family studies that used passed-on and non-passed-on variants. They found a small mean indirect link with school outcomes.

Parent education and social position explained much of that link. Later work by Nivard and colleagues found that some indirect links reflected social patterns across generations, not only life in the close family.

This evidence makes simple labels less credible. What looks like "nature" can contain social structure. What looks like "nurture" can be correlated with inherited traits. The practical need in school remains observable: what is the learner being asked to learn, what access do they have, and what happens when support changes?

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What the Educational Evidence Shows

School studies show that measured outcomes have links with both genes and settings. No one design can split the causes for a learner. Twin, family and genome studies describe group patterns. Trials and natural experiments are often more useful when a school wants to know whether a change in teaching or policy works.

Twin and family studies model sources of score gaps by comparing relatives with differing degrees of genetic similarity. They are useful for describing groups and testing models. They do not assign causes to one learner.

Adoption and sibling designs can separate some inherited and rearing pathways. Adoption is not random, conditions before birth still matter, and adoptive families are often selected. A resemblance is therefore not a pure genetic or setting readout.

Genome-wide association studies find statistical links between many genetic variants and an outcome. Each variant usually has a very small association. A polygenic score combines many weighted variants. It is a prediction from a particular discovery sample, not a biological explanation.

Within-family genomic designs compare siblings or transmitted and non-transmitted parental variants. They can reduce some population stratification, assortative mating and family-level confounding. They still have measurement, statistical-power and interpretation limits.

Quasi-experiments and trials are often more useful for school action because they test changes in schooling or teaching. They answer what happened under the studied conditions, not whether every learner began with the same traits.

School-level gene-environment findings are mixed and context-sensitive. Stienstra and colleagues analysed Dutch administrative data on 18,384 same-sex and 11,050 opposite-sex twin pairs. Measured school quality did not moderate genetic and shared-environment influences once socioeconomic moderation was considered. School socioeconomic composition showed a more complex pattern.

A Norwegian study of a whole population found a compensatory pattern. The link between an education polygenic index and scores was smaller in higher-performing schools. The authors used within-family analysis, but could not find which school practice caused the pattern.

These results do not support the slogan that good teaching makes genes matter more, or the opposite slogan that good teaching makes genes matter less. The answer varies with the measure, model and context. Direct studies of instruction remain necessary.

The distinction is central to learning theories. Behavioural, cognitive, social and constructivist accounts offer processes that can be studied in teaching and learning. A gene link does not replace those accounts, and a learning theory does not erase inherited differences.

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Intelligence, Achievement and the Effect of Schooling

IQ test scores and school results are related, but they are not the same construct. Achievement reflects what a learner has learned in specific domains. Cognitive tests sample performance on selected tasks. Both are affected by test design, access and context.

Genetic links with cognitive and school measures are well established at group level. That does not mean that IQ is a fixed substance passed from parent to child. Nor does it mean that an IQ score contains an untouched measure of "nature". The learner reached the test through growth, language, culture, health and education.

Ritchie and Tucker-Drob reviewed quasi-experimental evidence on education and cognitive-test results. Across 142 effect sizes from 42 data sets involving more than 600,000 participants, an additional year of education produced an estimated gain of about one to five IQ points. The designs included policy changes and school-entry cut-offs, which make the causal case stronger than a simple correlation.

The figure is an average across designs. It does not promise a fixed gain for a learner or show which part of schooling caused it. It does show why "highly heritable" and "affected by education" can both be true.

The same restraint applies to the Flynn effect, the historical change in mean test scores across cohorts. The pattern shows that group test results can change too quickly to be explained by genetic evolution alone. Researchers debate its causes, size, reversal in some settings and meaning for other abilities. It is not one clean experiment proving that nutrition, schooling or epigenetics caused a three-point gain each decade.

Teachers should avoid both fixed-IQ thinking and claims that drive or mindset always matters more than test results. Theories of intelligence use several constructs and types of data. For teaching, current subject knowledge, errors, task demands and access give a better starting point than a global label. Cognitive load theory can help analyse task demands, but it does not reveal a genetic learning type.

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What This Means for Teaching

The data support a clear school stance. Learners differ, and some differences can persist. Teaching and access still matter. No group statistic tells a teacher what one learner can ultimately learn.

High expectations do not mean pretending every learner will reach the same point at the same time. They mean not reducing curriculum entitlement because of an untested ceiling. An ambitious curriculum can be made accessible through careful sequencing, explanation, modelling, practice, feedback and scaffolding.

Adaptive teaching is not genetic personalisation. It responds to evidence from learning. A teacher may re-explain a concept, reduce an unnecessary language demand, provide a worked example or change the amount of guided practice. The reason is observable need, not a presumed genetic profile.

Support should also be checked against a clear goal. More adult help can increase task completion while reducing independence. A different worksheet can improve access while narrowing the curriculum. Record both benefit and cost.

Good formative assessment makes the cycle faster. It identifies what the learner understood, not just whether an answer was correct. It then links the error to a teaching response and checks again. This is more useful than deciding whether the error came from nature or nurture.

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A Starting-Point, Support and Review Sequence

The following sequence turns the evidence boundary into everyday practice. It can sit inside normal classroom planning or the SEND graduated approach. It does not require a diagnosis before support begins, and it does not make response to support the only evidence considered.

1. Name the learning concern precisely. Replace "low ability" with an observable description, such as "cannot yet compare fractions with unlike denominators without a model".
2. Check the task and access. Identify the knowledge, language, memory, sensory, motor and organisational demands. Check whether the learner could perceive, understand and respond to the task.
3. Review teaching and access. Record what was taught, how explicitly, how much guided and independent practice occurred, and whether absence or transition affected access.
4. Gather more than one view. Use work over time, learner voice, family knowledge and relevant staff observations. Consider differences across subjects, settings and times.
5. Choose one proportionate support. State what will change, who will provide it, how often and for how long. Keep the curriculum goal visible.
6. Set success evidence before starting. Define the accuracy, independence, retention or participation that would count as progress. Also note possible burden or harm.
7. Teach, observe and record. Use enough occasions to distinguish a pattern from a good or difficult day. Record implementation as well as outcome.
8. Review with the learner and family. Decide what improved, what did not, what remains uncertain and what the next action is.
9. Use the correct school route. Continue, adapt or stop the support. Involve the SENCO or relevant specialist. Make reasonable adjustments. Follow pastoral, health or safeguarding procedures where needed.

This sequence resembles assess, plan, do and review because the practical question is the same: what is the learner experiencing now, what support is reasonable, and what does the next evidence show? It avoids a false choice between "the child" and "the environment".

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Primary, Secondary, SENCO and Leadership Examples

Across all four cases, the pattern is the same. Name the concern. Collect data that can change a choice. Give support that is justified now.

Then review its effect. Keep the learner's rights and normal school routes in place.

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Setting and Streaming in England

Nature and nurture language can quietly turn attainment groups into "ability" groups. The terms are not interchangeable. Attainment is current results on selected measures. Ability suggests a broader and often more stable capacity.

The Education Endowment Foundation's current review reports zero extra months of progress for setting or streaming on average. It rates the data as very limited and includes 58 studies. The mean pattern is a small loss for low-attaining learners and a small gain for high-attaining learners, with mixed results among studies.

This does not prove that mixed-attainment teaching is always better. It means the average attainment case for setting or streaming is weak and the risks deserve attention.

If a school uses sets, leaders should keep movement possible, review allocation regularly, protect an ambitious curriculum and consider teacher distribution. They should check whether disadvantage, race, language, SEND, relative age or prior access is linked with placement after current attainment is considered.

If a school uses mixed-attainment classes, leaders still need a credible plan for variation in prior knowledge, practice, explanation, pace and support. Simply placing learners together does not guarantee access or challenge.

The nature and nurture lesson is not "never group". It is "do not mistake a grouping decision for a discovery of fixed potential".

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Genetic Data, Polygenic Scores and School Ethics

A polygenic score combines links from many genetic variants into one number. Scores are built for a defined outcome and discovery sample. They capture direct genetic links, indirect family and social effects, population structure and measurement choices. They do not identify a learning mechanism.

Morris and colleagues tested whether an education polygenic score could predict learner achievement in a UK cohort. They concluded that the score did not provide suitable value for routine use by teachers or schools. Prediction also transfers poorly across ancestry groups when the discovery data are less representative, creating a risk of systematic inequality.

Even an improved prediction would not answer the school question on its own. Prediction is not explanation. A score linked with later attainment does not say which concept to teach, which barrier to remove or which support a learner prefers.

Genetic details are special-category personal data under UK data rules. Any use would need a lawful purpose, a clear need, safeguards, open notice and a named owner. A research tool does not give a school a sound reason or lawful basis to collect learner DNA.

Schools should not use a genetic test or polygenic score for entry, sets, predicted grades, SEND, behaviour, seating, lighting, sensory support or course access. They should also be wary of direct-to-consumer reports brought into school. A family may need health or clinical genetics advice; the teacher should not read the report as a school plan.

This boundary is not anti-science. Genome methods can help scholars test mixed causes, study group patterns and improve cause-and-effect designs. Routine use for one learner needs a different standard: valid action, fair use, consent, data care and proof that the choice helps more than it harms.

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Limits of the Evidence

No single design settles the nature and nurture question. Twin studies rely on model assumptions. Adoption studies involve selection and events before birth. Genome-wide studies are sensitive to ancestry, population structure and the outcome used.

Polygenic scores can combine social and direct genetic pathways. Studies of settings can also mix genetic and social causes.

School measures also change. Years of education, examination grades, reading tests, teacher judgements and cognitive tasks are not interchangeable. A finding from one country, cohort or policy may not transfer to another.

Gene-environment interaction studies need large samples and repeat tests. Candidate-gene findings from small samples have often been weak. The much-discussed MAOA and maltreatment work is not a classroom model of aggression. It cannot explain a single learner and has no role in support.

Epigenetics is a real field of molecular biology, but classroom translations commonly run far ahead of evidence. It is not accurate to say that a calm room, teacher relationship, wall display or intervention switches a learner's genes on or off. Responsive teaching is justified by learning and wellbeing evidence without an epigenetic story.

Research also cannot set one right goal for every learner. High aims should sit with honest review, fair support and real learner involvement. A claim of limitless growth can become blame when progress is slow.

A claim of fixed nature can take access away. Well-tested support avoids both traps.

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Nature and Nurture Study Note and Review Record

The one-page study note keeps the key terms, study limits and professional red lines in one place. The two-page starting-point, support and review record helps a teacher or SENCO capture the task, access, teaching, learner and family view, support tried, success signs, review date and next route.

Read the study note as text

Direct answer: nature and nurture work together. Group research cannot give one learner a personal ratio, cause or fixed ceiling. Heritability is a group statistic, not a diagnosis.

Use in school: define the task. Check access. Teach clearly. Listen to the learner and family. Track more than one occasion. Review benefit and burden. Follow SEND, health, pastoral or safeguarding routes when needed.

Red lines: gene-environment correlation, interaction and genetic nurture are different research ideas. None tells a teacher what caused one learner's need. Do not use a gene, epigenetic story or polygenic score to explain attainment, allocate support or delay reasonable adjustments.

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Frequently Asked Questions

Genes and settings both matter. No group study can give one learner a personal percentage or fixed ceiling. Teachers should use current school evidence to choose support, review progress and keep the right professional routes open.

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Is IQ nature or nurture?

Scores on thinking tasks reflect both inherited differences and the setting. Heritability figures apply to groups, not one person. Schooling can improve test scores, and no figure reveals one learner's ceiling. For teaching, assess subject knowledge, task demands and access rather than assigning a nature and nurture ratio.

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Does high heritability mean teaching has little effect?

No. Heritability describes range under current settings. A condition shared by everyone may be essential while explaining little of the range between people. Education can affect a highly heritable outcome, and the figure can change when settings change.

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Are dyslexia and ADHD caused by genes?

Both have genetic links, but neither is explained by one gene or one nature percentage. A school should not infer a diagnosis or provision from family history. Listen to the concern, assess need and access, make reasonable adjustments, use the SEND graduated approach and involve appropriate professionals.

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Can teachers change gene expression?

Teachers change learners' daily life and chances to learn. Claims that a classroom practice switches particular genes on or off are not sound school guidance. Use direct learning, participation and wellbeing data to justify practice.

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Should a school use genetic testing to personalise learning?

No routine school use is supported. Current polygenic scores do not provide a single teaching plan and can work less well across some groups. Genetic details are also specially protected personal data. Use current school data and normal school routes.

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What is the most useful classroom conclusion?

Describe the current learning need precisely, keep the curriculum goal ambitious, improve access and teaching, involve the learner and family, and review evidence over time. Do not turn a group finding into a learner label.

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References

1. Visscher, P. M., Hill, W. G. and Wray, N. R. (2008). Heritability in the genomics era: concepts and misconceptions. Nature Reviews Genetics, 9, 255-266. https://doi.org/10.1038/nrg2322
2. Polderman, T. J. C. et al. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47, 702-709. https://doi.org/10.1038/ng.3285
3. de Zeeuw, E. L., de Geus, E. J. C. and Boomsma, D. I. (2015). Meta-analysis of twin studies highlights the importance of genetic variation in primary school educational achievement. Trends in Neuroscience and Education, 4, 69-76. https://doi.org/10.1016/j.tine.2015.06.001
4. Hart, S. A., Little, C. and van Bergen, E. (2021). Nurture might be nature: cautionary tales and proposed solutions. npj Science of Learning, 6, 2. https://doi.org/10.1038/s41539-020-00079-z
5. Wang, B. et al. (2021). Robust genetic nurture effects on education: a systematic review and meta-analysis based on 38,654 families across 8 cohorts. The American Journal of Human Genetics, 108, 1780-1791. https://doi.org/10.1016/j.ajhg.2021.07.010
6. Nivard, M. G. et al. (2024). More than nature and nurture, indirect genetic effects on children's academic achievement are consequences of dynastic social processes. Nature Human Behaviour, 8, 771-778. https://doi.org/10.1038/s41562-023-01796-2
7. Stienstra, K., Knigge, A. and Maas, I. (2024). Gene-environment interaction analysis of school quality and educational inequality. npj Science of Learning, 9, 14. https://doi.org/10.1038/s41539-024-00225-x
8. Cheesman, R. et al. (2022). A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement. npj Science of Learning, 7, 29. https://doi.org/10.1038/s41539-022-00145-8
9. Ritchie, S. J. and Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological Science, 29, 1358-1369. https://doi.org/10.1177/0956797618774253
10. Morris, T. T. et al. (2020). Can education be personalised using pupils' genetic data? eLife, 9, e49962. DOI: 10.7554/eLife.49962.
11. Visscher, P. M. et al. (2022). Genetics of cognitive performance, education and learning: from research to policy? npj Science of Learning, 7, 33. https://doi.org/10.1038/s41539-022-00124-z
12. Byrd, A. L. and Manuck, S. B. (2014). MAOA, childhood maltreatment, and antisocial behavior: meta-analysis of a gene-environment interaction. Biological Psychiatry, 75, 9-17. https://doi.org/10.1016/j.biopsych.2013.05.004
13. Education Endowment Foundation (2021). Setting and streaming. Teaching and Learning Toolkit, reviewed July 2021.
14. Department for Education and Department of Health and Social Care (2015, updated 2024). SEND code of practice: 0 to 25 years.
15. Department for Education (2023, updated 2026). What data protection means for schools.