Learning styles

Based on Wikipedia: Learning styles

The Seductive Myth That Won't Die

Here's a belief that nearly everyone in education holds dear: people learn differently. Some of us are "visual learners." Others need to hear information spoken aloud. Still others must get their hands dirty, physically manipulating objects to truly understand.

It sounds reasonable. It feels true. And it's almost certainly wrong.

The idea of learning styles—that each person has a preferred mode of receiving information, and that matching instruction to that mode improves learning—became wildly popular in the 1970s. Since then, it has shaped how millions of teachers design their lessons, how students think about their own abilities, and how billions of dollars have been spent on educational materials.

There's just one problem. When researchers have rigorously tested whether teaching to someone's supposed learning style actually helps them learn better, they consistently find no evidence that it does.

This is one of those cases where intuition and evidence point in opposite directions. So let's untangle what the research actually shows, why the myth persists, and what might actually matter for how we learn.

The Birth of a Cottage Industry

The learning styles movement didn't emerge from a single source. By the time researchers surveyed the field, they identified seventy-one different models attempting to categorize how people learn. Seventy-one. Each with its own terminology, its own assessment tools, and often its own consultants ready to train teachers on implementation.

A few of these models gained particular traction and deserve closer examination—not because they're correct, but because understanding them helps reveal why the whole enterprise went off the rails.

Kolb's Experiential Learning Cycle

David Kolb, an educational theorist, proposed that effective learning moves through four stages: having a concrete experience, reflecting on that experience, forming abstract concepts from your reflections, and then actively experimenting with those concepts to create new experiences. Round and round you go, ideally engaging all four modes.

But here's where things get complicated. Kolb suggested that most people develop a preference for certain parts of this cycle, leading to four distinct learning styles:

• Accommodators prefer concrete experience combined with active experimentation. Think physical therapists who learn by doing hands-on work with patients.
• Convergers combine abstract thinking with active experimentation. Engineers might fit here—people who take theoretical knowledge and apply it practically.
• Divergers favor concrete experience paired with reflective observation. Social workers, perhaps, who draw on real interactions and then think deeply about what they mean.
• Assimilators prefer abstract conceptualization combined with reflective observation. Philosophers, in Kolb's framing—people who build theories through logical reasoning.

This spawned the Learning Style Inventory, an assessment tool that's been through four versions, each attempting to fix problems with the previous one. The current version has abandoned the original four categories entirely, replacing them with nine new ones: initiating, experiencing, imagining, reflecting, analyzing, thinking, deciding, acting, and balancing. If the goalposts keep moving, it might be because the original target never existed.

The VAK Model and Its Offspring

Perhaps the most culturally influential model came from Walter Burke Barbe and his colleagues, who proposed that learners fall into three modalities: visual, auditory, and kinesthetic. (The acronym VAK should tip you off that we're entering buzzword territory.)

Even the creators acknowledged problems. They noted that these modalities could occur independently or in combination, that they change over time, and—crucially—that what people say they prefer often doesn't match their actual measured strengths. You might call yourself a visual learner, but that doesn't mean visual presentation actually helps you learn more effectively.

Neil Fleming expanded this into the VARK model by adding a fourth category: reading and writing preference. (The R, naturally.) He also added a fifth category for people who didn't fit neatly into the others—multimodal learners who either adapt to whatever style is being used or who need input in all their preferred modes before they feel they've truly learned something.

Psychologist Scott Lilienfeld, who has made a career of debunking psychological myths, argued that much of the VAK model amounts to pseudoscience—what he called a "psychological urban legend." It sounds scientific, it gets repeated endlessly, and it has almost no empirical support.

Other Models Proliferate

Peter Honey and Alan Mumford renamed Kolb's stages to sound more business-friendly—having an experience, reviewing the experience, concluding from the experience, and planning the next steps—and created their own questionnaire. A 1999 survey found this was the most widely used system in UK local government.

Anthony Gregorc proposed that people differ in two dimensions: whether they perceive the world concretely or abstractly, and whether they organize information sequentially or randomly. This gives you four types: concrete sequential, abstract random, abstract sequential, and concrete random. When researchers questioned the validity of his model, Gregorc responded that his critics had "scientifically-limited views" and were wrongly dismissing the "mystical elements" of "the spirit." When a theorist invokes mysticism to defend against empirical criticism, you might reasonably question the foundations.

Grasha and Riechmann developed a scale measuring six student attitudes: avoidant, participative, competitive, collaborative, dependent, and independent. Unlike most learning style models, this one explicitly judged some styles as better than others—"adaptive" versus "maladaptive."

The National Association of Secondary School Principals formed a task force that identified thirty-one variables across three categories: cognitive (how you think), affective (what motivates you), and physiological (whether you prefer bright lights, cool temperatures, or studying at particular times of day).

With seventy-one models to choose from, a school administrator could pick whichever one felt most intuitive, spend money training teachers on it, and feel confident they were doing something scientific. The proliferation itself should have been a warning sign. When a field can't converge on a basic framework, it might be because the underlying phenomenon doesn't exist in the way proponents imagine.

What the Evidence Actually Shows

In 2004, Frank Coffield and his colleagues conducted a systematic review of the thirteen most influential learning style models. They examined each model's theoretical foundations, its assessment instruments, and the empirical evidence for its claims. Their conclusion was damning: none of the popular learning style theories had been adequately validated through independent research.

This bears repeating. The most widely used learning style assessments don't reliably identify stable traits in learners. And even when they do classify people into categories, teaching to those supposed styles doesn't improve learning outcomes.

The research design needed to test learning styles is straightforward. First, assess learners to classify them into types—visual versus auditory, for instance. Then randomly assign some learners to instruction that matches their supposed style and others to mismatched instruction. If learning styles matter, the matched learners should outperform the mismatched ones.

Study after study fails to find this effect.

What researchers do find is that certain presentation methods work better for certain types of content, regardless of the learner's supposed style. Teaching geography through maps helps everyone, not just "visual learners." Teaching pronunciation through audio helps everyone, not just "auditory learners." The content should drive the method, not some hypothetical trait of the student.

Why the Myth Persists

If learning styles don't hold up under scrutiny, why do so many educators, students, and parents believe in them?

First, people genuinely do have preferences. You might prefer reading to listening, or watching videos to reading text. These preferences are real, and they feel meaningful. The error lies in assuming that preference equals effectiveness. You might prefer eating cake to vegetables, but that doesn't mean cake is more nutritious.

Second, learning styles offer a comforting explanation for academic struggles. If a student is having trouble, learning styles theory suggests the problem isn't with the student's effort or ability—it's that instruction isn't matching their style. This shifts blame away from the individual and toward the system. It feels kind, even if it's not accurate.

Third, the assessment process itself can be motivating. Taking a learning style quiz and receiving a personalized result makes you feel seen and understood. It gives you language to talk about your experience. Even if the category doesn't actually predict anything about your learning, it can still feel meaningful in the moment.

Fourth, teachers who believe in learning styles may simply be doing better teaching. If thinking about learning styles causes a teacher to vary their instruction—sometimes using visuals, sometimes hands-on activities, sometimes discussion—that variety itself might help students stay engaged. The improvement would come from variety, not from matching styles to instruction.

What Actually Matters

If learning styles are a dead end, what should educators focus on instead?

Research points to several factors that actually do improve learning:

Spacing practice over time. Rather than cramming, spreading study sessions out leads to better long-term retention. This works for virtually everyone.

Retrieval practice. Testing yourself—actively pulling information from memory—strengthens learning more than passively reviewing material. Again, this appears to be universal.

Interleaving different topics. Rather than practicing one skill until mastery before moving to the next, mixing different types of problems in the same study session improves the ability to discriminate between problem types and select appropriate strategies.

Elaboration. Connecting new information to things you already know, explaining concepts in your own words, and generating examples all strengthen understanding.

Concrete examples. Abstract concepts become clearer when illustrated with specific, tangible examples. This works across domains and learner types.

None of these require diagnosing a student's learning style. They're general principles that apply broadly.

The Harm in a Harmless-Seeming Idea

You might wonder: even if learning styles don't work as advertised, what's the harm? If teachers think about student differences, isn't that still valuable?

The harm is subtle but real.

Learning styles can become limiting beliefs. A student labeled as a "kinesthetic learner" might conclude they simply can't learn from books, when in reality they just need to work harder at reading comprehension. A "visual learner" might dismiss lectures as useless for them, missing out on valuable instruction.

Learning styles waste resources. Money spent on learning style assessments, training programs, and specialized materials could fund approaches with actual evidence behind them.

Learning styles distract from what matters. Teachers have finite time and energy. Effort spent trying to diagnose and accommodate learning styles is effort not spent on evidence-based practices.

Perhaps most insidiously, learning styles give education a veneer of scientific legitimacy without the underlying rigor. They let everyone feel like they're doing something sophisticated and research-based, when in fact they're chasing an illusion.

The Deeper Issue

The learning styles phenomenon reveals something important about how education adopts ideas. The field has an appetite for simple frameworks that promise to explain complex phenomena. Seventy-one models! Each one offering a neat taxonomy, a catchy acronym, a quiz you can take in fifteen minutes.

Real learning is messier. It depends on prior knowledge, motivation, the clarity of instruction, the amount of practice, the quality of feedback, sleep, stress, environment, and dozens of other factors. There's no single dimension on which learners vary that unlocks effective teaching.

Richard Felder, who developed yet another learning style model, made an interesting observation even within his own framework. He noted that when professors don't teach to students' learning styles, students tend to lose interest, sometimes to the point of changing majors or dropping out entirely.

But this might have nothing to do with learning styles per se. If a professor only lectures and never demonstrates, never provides hands-on practice, never varies the pace or format, some students will disengage. The solution isn't to diagnose each student's style—it's to teach in a more varied and engaging way for everyone.

A Different Frame

What if, instead of asking "What type of learner is this student?" we asked better questions:

What does this student already know? Prior knowledge is the strongest predictor of learning. Building on what students already understand is far more valuable than matching sensory modalities.

What motivates this student? Motivation shapes attention, which shapes learning. Understanding what engages a particular student matters more than categorizing them by style.

What challenges is this student facing? Difficulty with reading comprehension, limited study time, test anxiety, gaps in foundational knowledge—these specific obstacles are addressable in ways that generic style labels are not.

What feedback does this student need? Learning improves through targeted feedback on specific misunderstandings. A good tutor doesn't figure out your learning style; they figure out where your thinking went wrong and help you correct it.

The Seduction of Certainty

The persistence of learning styles speaks to a broader human tendency: we prefer clean categories to messy reality. We want to be able to say "I'm a visual learner" the way we might say "I'm an introvert" or "I'm a morning person." These labels give us a sense of self-knowledge and belonging.

Education, in particular, is hungry for certainty. Teachers face impossible complexity—thirty different students with thirty different histories, needs, and capacities. A framework that reduces this complexity to a handful of types feels like a lifeline.

But the complexity is irreducible. The solution isn't better categories; it's accepting that teaching is craft, not algorithm. It requires constant adjustment, close attention to individual students, and a willingness to try different approaches until something works.

Learning styles offer false certainty. The truth is more humble: we don't have simple formulas for optimizing learning. We have principles that help, practices that work better than others, and the endless, rewarding challenge of trying to help each person understand something new.

Moving Forward

If you've spent years thinking of yourself as a particular type of learner, consider letting that identity go. You're not limited to one channel of understanding. You can learn from reading, from listening, from doing, from watching, from discussing, from teaching others. Different approaches work better for different content, and you can develop facility with all of them.

If you're an educator who has invested in learning styles training, don't despair. The underlying impulse—to pay attention to student differences, to vary instruction, to meet learners where they are—is sound. The specific framework was flawed, but the care and attention that motivated it remain valuable.

The goal isn't to stop thinking about individual differences. It's to think about them in more productive ways: What does this student know? What do they need? What isn't working, and what might work better?

These questions don't have simple answers. But they're the right questions to ask.