Understanding Intelligence: Moving Beyond Myths
17 January, 2026
Author Dr Will Zoppellini
We use the word intelligence with remarkable confidence. We say it about children, to children, and between ourselves in everyday conversation, often as though its meaning is obvious and shared… But it isn’t.
I once sat in a school meeting where a child was described as “very intelligent but not applying themselves.” Minutes later, another child was described as “not particularly bright, but hardworking.” No one paused to question the language. No one asked what intelligent meant in either case. Did it refer to reasoning, memory, speed, confidence, language, or simply how comfortable a child appeared in that particular learning moment.
By the end of the meeting, decisions had been made. Expectations had been set. Pathways quietly narrowed. Moments like this reveal how slippery the word intelligence really is. We use it confidently in schools, sports, and parenting. Yet rarely stop to ask what we actually mean by it.
Table of Contents
This matters because the way we talk about intelligence shapes the way children are taught, challenged, and supported.
All humans differ in how they understand ideas, adapt, learn, and solve problems. But intellectual performance is not constant. It shifts with context, situation, and moment. What looks like “ability” in one setting may look very different in another.
This variability is one reason intelligence has proven so difficult to define scientifically, and why there has never been full agreement on what it really means to be intelligent.
In this post, I’ll explore what intelligence is as a scientific idea, how it has been understood over time, what research from psychology, genetics, and neuroscience tell us, and why misunderstandings persist.
So, take a moment, settle in with your coffee, and let’s begin by asking what the science really means when it talks about intelligence.
Intelligence: one idea, many explanations
Generally speaking, intelligence is thought to involve cognitive processes such as memory, problem solving, and thinking2. To describe someone as intelligent is often to suggest that they process information efficiently, solve problems effectively, and adapt or learn from experience2.
Yet, after more than a century of scientific study, there is still no universally agreed definition of intelligence. The lack of consensus has long been acknowledged within the scientific community. In 1998 Dr Arthur Jensen3 noted that disagreements about whether intelligence is best understood as a single general capacity or as multiple distinct abilities remains unresolved, to the extent that some have argued the term itself is too imprecise to be useful. Rather than disappearing, these debates have persisted, precisely because intelligence touches something fundamental about how humans learn, adapt, and function in the world1.
Scientific interest in intelligence originally emerged from a simple but persistent observation that people who performed well on one cognitive task often performed well on others too. This pattern, noticed repeatedly across early studies, prompted psychologist Charles Spearman4 to propose the idea of a general factor of intelligence, commonly known as ‘g’.
Crucially, g was not a single mental skill or a specific brain function. It was a statistical concept5. In other words, Spearman was not claiming that intelligence lived in one place or took one form. He was describing a pattern in the data that suggested cognitive abilities tend to be connected.
This distinction matters, because the idea of g has often been misunderstood. Over time, however, the pattern Spearman identified proved remarkably strong. Across different tests, cultures, and generations, connections between cognitive abilities continued to appear, which is why g remains a feature of many contemporary models of intelligence6.
However, g has never gone unchallenged. Prominent researchers such as Dr Robert Sternberg have argued that while general patterns exist, they do not fully capture how intelligence operates in real-world contexts or across diverse forms of human activity1. The debate, for how best to explain intelligence continues.
While Spearman was working at a theoretical and statistical level, Alfred Binet approached intelligence from a very different direction. His concern was practical and educational and asked “how could schools identify children who needed additional support?” Binet’s work laid the foundations for intelligence testing, but his intentions were developmental. He warned repeatedly against treating intelligence as fixed or innate, emphasising that cognitive performance was shaped by instruction, experience, and opportunity7. That caution has been lost, and it is something I will return to directly in this blog series when I examine IQ testing in more depth.
As intelligence research progressed, models became more layered and sophisticated. Most contemporary psychologists now endorse hierarchical models of intelligence, such as Carroll’s three-stratum theory8, which places g at the top, broader cognitive abilities (including fluid reasoning, verbal comprehension, and processing speed) beneath it, and more specific skills at lower levels.
Alongside these approaches, alternative theories also emerged. Howard Gardner’s theory of Multiple Intelligences9, for example, sought to broaden how intelligence is discussed in educational settings by emphasising diverse domains of human capability. While such theories do not align neatly with traditional measurement models, they have had a lasting influence on how educators and parents think about ability, talent, and learning.
Part of the reason a consensus has been so difficult to achieve is that intelligence is currently defined, assessed, and researched across at least three distinct areas that include psychometric, physiological, and social. Each discipline brings its own concepts, methods, and conclusions. Neuroscientists examine brain structure and function, psychometricians analyse test performance, social and educational researchers study how intelligence operates in real-world contexts.
These approaches do not always align neatly, but they are not necessarily competing explanations. Rather they are different lenses on the same phenomenon. Encouragingly, there has been increasing exchanges between disciplines in recent years, offering hope for greater coherence in how intelligence is understood.
I should highlight that this disagreement is not a failure of intelligence research. It is evidence that scholars are still grappling seriously with a complex idea that continues to shape how learners are perceived, supported, and challenged.
These unresolved questions matter because as long as humans continue to differ in their capacity to learn and adapt, the concept of intelligence will endure socially, scientifically, and educationally. The goal is not to reduce intelligence to a single number or theory, but to understand it with greater care, precision, and humility.
Intelligence over time: what changes, what stays, and what’s misunderstood
One of the most important insights from intelligence research is also one of the least reflected in everyday conversations. That is that intelligence is developmental and not fixed1.
It does not appear fully formed at a single moment in childhood. It does not look the same at different ages, and it does not express itself independently of experience, opportunity, or context2.
In early childhood, measures of intelligence are relatively unstable. Young children are undergoing rapid neurological, linguistic, and emotional development, and their cognitive performance is strongly influenced by immediate conditions such as language exposure, familiarity with tasks, confidence, fatigue, and the environment in which learning takes place5,11,12. As a result, early assessments often tell us as much about the context of a learner as they do about their cognitive capacity11.
As children grow older, cognitive abilities begin to differentiate. Skills such as working memory, verbal comprehension, processing speed, and reasoning become more distinct and more reliably measured1. By late childhood and adolescence, patterns of performance start to show greater consistency, particularly in relation to peers2.
By adulthood, intelligence tends to become more stable. This means people often keep a similar position compared to others over time. However, this is commonly misunderstood. Stability does not mean intelligence stops changing. People continue to learn, adapt, and develop throughout their lives14. What stays similar is how people compare to one another, even as everyone’s abilities continue to grow.
Developmental research also makes clear that intelligence reflects accumulated experience. Education, practice and occupational demands all matter. Opportunities to engage with complex ideas, solve problems, and stretch thinking shape how cognitive abilities are expressed over time.
This perspective reframes how we should think about early performance. A child who appears capable at a young age is not revealing a finished product, just as a child who struggles early on is not revealing a limit. Intelligence is better understood as a journey over time, not a single moment.
For educators, parents, and coaches, this matters deeply. When intelligence is treated as fixed, early impressions harden into expectations. When it is understood developmentally, the focus shifts from judging ability to shaping conditions for growth.
Genetic influence, heritability, and what they really mean
Key terms Explained
- G
An abbreviated way of referring to general intelligence, the common factor believed by some to underpin performance on all intelligence tests.
- Heritable
The extent to which differences between people in a trait, such as intelligence, are related to genetic differences, like height or eye colour.
- Polygenic
A polygenic trait is influenced by many different genes, not just one. Traits like skin colour and intelligence are polygenic, and they are also shaped by environment.
There is no longer serious controversy about whether intelligence has a genetic component. Decades of research using twin, family, and population studies show consistently that genetic differences contribute to variation in cognitive performance5,15. Because genes exert their influence through biology, intelligence must have a biological basis, a point that has driven much of the search to understand how brain systems support thinking, reasoning, and learning1.
Yet this is where some misunderstandings continue.
Few topics in psychology are as widely misinterpreted as the genetics of intelligence. Acknowledging the influence of genetics is often mistaken for an inevitable outcome. In reality, no complex human trait is 100% heritable13. Several researchers in behavioural genetics emphasise13,16 that all traits show a large environmental influence, and intelligence is no exception. Accepting this should lead us to deeper interest in how genes and environments work together.
Intelligence is also highly polygenic17. There is no “gene for intelligence”. Instead, thousands of genetic variants each contribute very small effects, interacting continuously with experience, education, health, stress, and opportunity13. Genetic influence does not operate in isolation from context.
One interesting finding is that genetic influence on intelligence appears to increase with age. This does not mean genes become more powerful over time. Instead, as people grow older and gain more independence, they tend to choose environments and activities that suit them, which allows their natural tendencies to show more clearly11.
The takeaway message is simple: genes matter, but they do not decide outcomes. Biology sets possibilities, while experience shapes how those possibilities develop.
Neuroscience and intelligence: from brain regions to brain systems
As with the other areas, the perspective of intelligence in neuroscience has evolved over time. Early work in this area focused on efficiency rather than structure. In the 1980s, studies using brain imaging (electroencephalography/EEG) examined how the brain responded to repeated or expected stimuli.
In the early 1980s, Dr Schafer observed that people with higher IQ scores often showed smaller brain responses when dealing with familiar or predictable sensory information18. He suggested that this reflected greater neural efficiency, in that the brain was doing what it needed to do without unnecessary effort.
The idea of neural efficiency became an important focus, but it did not suggest that intelligence lived in a single “centre” of the brain. As brain imaging techniques such as MRI and PET scans developed in the 1990s and early 2000s, researchers began to look more closely at brain structure1. They examined overall brain size, the volume of different regions, and whether particular areas were linked to intelligent behaviour. While some relationships were found, the links were modest and explained only a small part of why people differ in cognitive performance19.
Over time, a different picture began to emerge. Rather than being tied to a single region, intelligence is now understood as a network. It reflects the efficiency and integration of distributed brain systems, particularly networks involving frontal and parietal regions working together20.
Crucially, these networks are not fixed. Brain structure and function are shaped continuously by experience. Learning, stress, nutrition, sleep, health, and environmental exposure all influence neural development across the lifespan. Practice can strengthen connections, chronic stress can weaken them, and enriched environments can reorganise how networks operate.
Once again, neuroscience reinforces a familiar theme. Biology matters, but it does not operate in isolation. Intelligence emerges from dynamic, adaptive systems that reflect both biological constraints and lived experience.
Final Thoughts
Across psychology, genetics, and neuroscience, one conclusion appears again and again: there is no single, concrete, universally agreed definition of intelligence. It is a dynamic, developing concept, shaped by biology, experience, context, and time. Yet, in everyday situations, we use the word as if it were fixed to label children, to sort them, to motivate or pressure them, and sometimes to explain their struggle.
In doing so, we do not just shape how children see themselves, but we also carry the weight of intelligence into our own lives, measuring our worth, potential, and success against an idea that science itself treats with caution.
Misunderstanding intelligence as fixed has shaped how education is organised, from assessment to expectations. This rests on a powerful myth rather than evidence. Engaging with theory allows us to challenge these assumptions and rethink how children learn. We should not be limiting children, or ourselves, by inherited beliefs about intelligence. The limits we were taught to accept are not the limits that science supports.
Until next time, stay curious
Dr Will Zoppellini
References
- Sternberg, R.J. and Kaufman, S.B. eds., 2011.The Cambridge handbook of intelligence. Cambridge University Press.
- Gillibrand, R. Lam, V. O’Donnell, V. 2016. Developmental Psychology. Pearson Education, Limited.
- Jensen, A.R. 1998. The g factor and the design of education. InIntelligence, instruction, and assessment (pp. 111-132). Routledge.
- Spearman, C. 1961. The abilities of man.
- Deary, I.J., Johnson, W. and Houlihan, L.M. 2009. Genetic foundations of human intelligence.Human genetics, 126(1), pp.215-232.
- Nisbett, R.E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D.F. and Turkheimer, E. 2012. ” Intelligence: New findings and theoretical developments”: Correction to Nisbett et al.(2012).
- Binet, A. and Simon, T. 1916. The development of intelligence in the child.(L’Année Psych., 1908, pp. 1-90).
- Carroll, J.B. 2013. A three-stratum theory of intelligence: Spearman’s contribution. InHuman abilities (pp. 1-17). Psychology Press.
- Gardner, H., 2015. The theory of multiple intelligences 1. InHandbook of Educational Ideas and Practices (Routledge Revivals) (pp. 930-938). Routledge.
- Flynn, J.R., 2007.What is intelligence?: Beyond the Flynn effect. Cambridge University Press.
- Nisbett, R.E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D.F. and Turkheimer, E., 2012. Intelligence: new findings and theoretical developments.American psychologist, 67(2), p.130.
- Goswami, U. and Bryant, P., 2007. Children’s cognitive development and learning.
- Plomin, R. and Deary, I.J. 2015. Genetics and intelligence differences: five special findings.Molecular psychiatry, 20(1), pp.98-108.
- Ritchie, S. 2015.Intelligence: All that matters. Hachette UK.
- Bouchard Jr, T.J. 2009. Genetic influence on human intelligence (Spearman’s g): How much?.Annals of Human Biology, 36(5), pp.527-544.
- Knopik, V.S., Neiderhiser, J.M., DeFries, J.C. and Plomin, R. 2017.Behavioral genetics (pp. p93-110). New York: Worth Publishers, Macmillan Learning.