Are Some Students Smarter Than Others?

What does "smart" mean anyway?

One year I was talking to an administrator about a student who was often disengaged in school. She would put her head down in class and give up across multiple subjects. We had tried a few different interventions and nothing had worked. I was throwing out ideas, trying to brainstorm what to do next. The administrator stopped me and said, "well…she isn't very smart..." That sentence hung in the air. The implication was clear: maybe we should give up. The student wasn’t in special education — that administrator supervised our special ed department and didn’t think that was necessary. The student was labeled “not smart” and that was that.

I still think about that moment a lot. What does it mean for a student to be smart? It's not something teachers talk about often, at least not openly. But my sense is that many teachers and administrators think that some students are smart, others are not, and make a bunch of assumptions to go with those labels.

This post has two parts. First, I want to share a few ideas from intelligence research that I think teachers should understand. These are pretty well-established ideas, but the research isn't specific enough to give helpful guidance to teachers. In part two I'll step out on a limb and try to articulate how I see the research impacting everyday teaching.

The Research

When researchers¹ talk about intelligence they generally talk about g, which represents a person’s general intelligence. There are lots of different ways of measuring g, and all of them are correlated with each other. The name for that correlation is the “positive manifold,” which means that doing well on one measure of cognitive ability means that person is likely to do well on a different measure of cognitive ability. IQ tests are the most well-recognized, standardized measure of intelligence, putting humans on a numerical scale where 100 is the mean and 15 is the standard deviation.

Does intelligence matter? In short, yes. Scoring higher on tests like IQ is correlated with lots of positive things, like lifetime earnings, educational attainment, lack of involvement with the criminal justice system, and more. It’s tough to separate correlation and causation here but the vast majority of people would agree that being more intelligent has real advantages, both in and out of academic contexts.

Researchers divide intelligence into two broad categories: crystallized intelligence and fluid intelligence. Crystallized intelligence is the name for all of the knowledge, skills, and experiences that help us to navigate the world. It increases, quickly at first and then more slowly, into old age. Fluid intelligence is the name for abstract reasoning, problem solving, and cognitive flexibility we use when we don’t have crystallized intelligence to draw on.

To give brief examples, fluid intelligence is often assessed with tasks like Raven’s Progressive Matrices, which look like this (answers in the footnote):²

Crystallized intelligence is typically assessed through items including vocabulary, general knowledge, verbal comprehension, and numerical tasks.

While there are lots of theories about what makes up fluid intelligence, two components researchers generally agree play a major role are processing speed and working memory capacity. Processing speed describes the rate that people can take in, interpret, and respond to information, and working memory capacity describes how many ideas we can hold in our mind at once. There’s more to fluid intelligence than those two things, but they play a major role and they’re worth focusing on.

Something I think isn’t always understood is that when we talk about intelligence and tools like IQ that attempt to measure intelligence, part of what those tests are measuring is how much you know. Intelligence increases as we learn things. This doesn’t mean that IQ scores go up as people get older because IQ scores are adjusted for age and everyone else is learning things too. Intelligence has also steadily increased as long as we have been measuring it. The name for this is the Flynn Effect, and it refers to the fact that IQ tests need to be re-normed every few years because, for instance, 12 year olds today score better on average than 12 year olds from 30 years ago. While the average IQ score stays the same, we really have gotten smarter.³

Implications

Here are a few conclusions I think teachers can draw from the research on intelligence. These are generally supported by the research, though in most cases I’m either making inferences or pulling a few different strands of research together to draw these conclusions. Take them with a grain of salt.⁴

It’s helpful for teachers to think in terms of crystallized intelligence, processing speed, and working memory, rather than “smart.” In my experience, describing students as smart or not smart tends to end the conversation: it assumes that successes or failures are predetermined by something innate. But crystallized intelligence is just how much a person knows, and teaching kids increases crystallized intelligence. Processing speed is something teachers already hear about in IEP meetings and elsewhere, and often know how to scaffold for. Working memory is less well known by many teachers, but it’s not hard to learn about and there are plenty of simple strategies teachers can use to reduce working memory load during learning. All of that is way more actionable than labeling a student as smart or not smart.

Crystallized intelligence is important, so teachers should teach kids stuff. This sounds obvious, but I think it’s not. Part of being intelligent is learning things. That’s why we invented schools. Teach kids things. Specific things that will open doors for them in the future, not abstract generalities like “problem solving” and “critical thinking.” Teaching people things makes them smarter.

Some students learn faster than others, but we can minimize those differences by being structured and systematic in our teaching. This is a complex one, and I wrote about the research at length previously. Here’s the short version. Some kids learn faster than others. We can observe that in any school or learning environment. But those differences are largest in unstructured contexts. Think kids who teach themselves to read, or kids who seem to pick up every little thing they’ve ever heard. A number of studies suggest that when teachers break skills down into small, manageable parts, teach those parts one at a time, and systematically build up to bigger and bigger ideas, differences in learning speed are narrower. Some kids are like sponges and just soak stuff up from the world around them. It’s reasonable to conjecture that having higher processing speed and spare working memory capacity help with that type of learning. But when teachers break learning down into chunks and teach chunks one at a time, we help all students learn. Phonics is the best example of this. Some kids learn to read without ever needing phonics. Others need the structured, systematic teaching of phonics — and when all students get that instruction, far fewer are diagnosed with dyslexia or have other persistent reading difficulties.⁵

Crystallized intelligence is more important than fluid intelligence. The world often values being bright and being a quick thinker — things that are associated with fluid intelligence. But I think crystallized intelligence should be what we value the most. A good example of this is when people who aren’t educators talk about education. People who are clearly intelligent and have been successful in other fields say and do incredibly stupid things when they try to meddle in education. Similarly, I’d rather see a doctor with a lot of experience and knowledge than one who is right out of med school but has a lot of fluid intelligence. There’s also a cognitive reason why crystallized intelligence matters. Knowledge in long-term memory — crystallized intelligence — reduces demands on working memory and processing speed. We think faster when we draw on stuff we know. We can hold more in our mind when we have knowledge in long-term memory. The more we know, the less fluid intelligence matters. There will always be contexts where we need to rely on fluid intelligence; it’s impossible to have knowledge for every possible situation, and when we work at the limits of our knowledge we rely more and more on fluid intelligence. Still, a huge part of living a fulfilling life is finding a niche where you become knowledgeable and useful to people around you. That’s crystallized intelligence.

The biggest barrier to developing crystallized intelligence is when skill gaps go unaddressed. The most important factor that determines whether students learn is what they already know. Knowledge is sticky: the more you know, the more you learn. Conversely, if a student doesn’t know something about a topic that the teacher assumes they do know, their learning will be compromised. Recasting this idea in terms of intelligence, if we want to make students more intelligent, we need to make sure they aren’t being held back by these gaps. This is something typical schools aren’t very good at. If a student is having a tough time in school we often give them more help, but we don’t often figure out where the gaps are and try to address them. Students might be put in a lower track that learns the same material a bit more slowly, or get tutoring that gives them extra help with whatever they’re supposed to learn, or get put on some garbage computer program that pretends to “meet them where they are,” or in some cases get an IEP that means they sit close to the front and the teacher checks in to clarify directions and they take tests in a small group setting. None of that addresses the basic problem: if students don’t know something we assume they know, they won’t learn as much. This isn’t easy to solve. It takes resources, time, and patience. But most schools (I say most, there are exceptions!) don’t even try.

Labels don’t help. It might be tempting to say, “well ok, but some things require a lot of fluid intelligence. We shouldn’t make kids think they can be quantum physicists if they don’t have the requisite fluid intelligence.” Maybe that’s true. I don’t know. Here are a few things I do know. There is no evidence of hard ceilings, where a person of x intelligence cannot learn y concept. There is evidence of students who struggled for years until someone with some expertise met them where they were and taught them something others thought they were incapable of learning. Teachers don’t exist to predict which students will be quantum physicists. Teachers exist to teach things. Labeling doesn’t help us teach things. Instead, do a good job teaching things, and help students who seem stuck by going back to fill in gaps in their prior knowledge that are holding them back. I occasionally hear arguments along the lines of, “well some students just can’t learn x topic.” In general, I think those students are held back by gaps in prior knowledge. That’s not an easy problem to solve, but it is solvable. Labeling those students doesn’t help to solve it.⁶

Learning is what makes people smart, but we convince lots of kids they can’t learn. Too many students feel dumb in school. They feel like the learning moves too fast, they never seem to get it before the class moves on, and they’re struggling to stay afloat. Some students feel like this for years, and eventually conclude that learning isn’t for them. One of my strongest beliefs about education is that we could change this. Better teaching that doesn’t just hope students soak stuff up but teaches key ideas systematically. That means schoolwide systems to identify when a student missed a key skill and go back to address it. It’s not easy, but it’s possible. If schools can do that, students will learn more, and they will also leave school with a belief in their own ability as learners.

In Summary

The key idea for me is that intelligence isn’t some innate thing where some kids are smart and will do well in school, others are not smart and will do poorly, and that’s that. That’s neither correct nor helpful for teachers. A more relevant difference between students is that some students learn regardless of the quality of the teaching. They’re like sponges; they soak it all up. Teachers can get away with poor instruction and these students will still learn. Others need more systematic and structured teaching. Over time, a gap grows and that second group develops larger and larger conceptual gaps until they get stuck. I think teachers can ascribe a lot of those difference to fluid intelligence. That’s a helpful distinction because differences in fluid intelligence point to concrete scaffolds teachers can use so that students with slower processing speed and less working memory capacity can learn.

This distinction has become a huge part of how I look at teaching. There’s a version of teaching that sounds good on the surface and has become more popular in some places recently. In this version of teaching we use lots of real-world tasks, treat kids like little mathematicians or scientists, try to inspire them to see how their learning is useful in the real world, and spend lots of unstructured time working on projects. Some students learn. Others don’t. Teachers explain away the kids who don’t learn by saying they aren’t motivated or they need more rich tasks and projects or they look the other way entirely. This is exactly the kind of bad teaching that I now think about in terms of fluid intelligence. And to be clear, I’m not saying teachers shouldn’t ever use rich tasks or projects. What we should avoid is assigning those things and assuming that kids will just absorb what they need to know along the way. I use lots of rich tasks in my math class! But if I want students to do something complex, I break it down into lots of small manageable pieces, teach students the pieces, and build gradually toward the larger learning goal. That’s very different than putting complex tasks in front of students and hoping they will learn.

A lot of this sounds like “teach good and don’t give up on kids.” That’s really all I’m saying. No teacher wants to give up on a student, but we do. Even if the teacher doesn’t say it, you can see it in their face and their tone when they talk about certain kids they’re struggling with. I think of the ideas in this post as a roadmap for how not to give up on kids. Just saying you won’t give up isn’t specific enough. When you feel stuck, what do you do? My suggestions are:

• Scaffold so students with slower processing speed and less working memory capacity can access lessons.

• Teach kids stuff. Specific stuff. Teaching stuff is good.

• Break concepts down into small pieces and teach them systematically.

• Find time to go back and fill in gaps in prior knowledge that are holding kids back.

• Don’t assign labels unless that label helps to teach the student.

• Help kids feel successful in school.

I realize that all might still sound vague. This post is already over 3,000 words so I’m going to pause here but I’ll follow up with more specifics in a future post.

A final thought. I have a lot of optimism about education. I think we could do a lot better for our students than we do now. There’s lots of rhetoric in education about high expectations and believing that every kid can learn. That rhetoric is nice, but if it doesn’t translate into specific actions a teacher can take, it’s not very helpful. There’s always more we can do as teachers to help students learn. Don’t write kids off. We can do better.

1. The best reference for most of the research on intelligence is the very short book “Intelligence: All That Matters” by Stuart Ritchie. It’s a broad but clear overview and has great references to more specific studies

2. The answers are 8 and 4. In the first problem, the dots increase from left to right, and the triangles follow a pattern of 123, 231, or 312 from left to right. In the second problem, segments and circular arcs are “added” (or xor-ed if you’re into logic) so that, if a segment appears in only the first or second column, it appears in the third column. If a segment appears in both the first and second column it does not appear in the third column.

3. A perfectly valid criticism of this post is that I am oversimplifying complex processes. No argument here. But teachers need actionable ideas, and action requires simplification. If you think I’m oversimplifying, I would ask: what do you disagree with? Does your more complex model of intelligence give teachers specific things they can do to help students learn?

4. One general note. Here I’m focusing on differences in intelligence, but those aren’t the only differences between students that matter. There could be a whole post on differences in attention, motivation, and more. This is only one difference, though it is an important one.

5. There’s a counterargument, popularized by Freddie deBoer and Kathryn Paige Harden, that the utility of trying to make people smarter is limited because what really matters is our relative intelligence compared to other people. The logic is that we are all fighting for slices of the same pie, and making people smarter doesn’t make the pie any bigger. I’m not going to engage with that argument here; my focus is “what would teachers do if we wanted to make everyone smarter” not “what macroeconomic structures will help all humans flourish in a capitalist society.”

6. The possible exception to this is students with profound intellectual disabilities. It’s still worth pointing out that there are examples of students who were labeled uneducable, yet with the right support were able to learn. I recognize that there are some situations where a certain student truly can’t learn something. I would argue that 1) those situations are extremely rare, 2) we often underestimate students who are given this label.