Does matching teaching to learning styles improve learning?

Sorting people into visual, auditory or verbal learning styles is not a well-supported way to decide how to teach them. That does not mean no study has ever found a benefit. A 2024 meta-analysis found a small average advantage for instruction matched to a learner's style. But only about a quarter of its outcome measures showed the pattern the theory requires, and study quality was low. Clinton-Lisell and Litzinger, 2024. A 2025 review that pooled four earlier matching meta-analyses (143 studies) put the average matching effect at d = .04, close to zero; it did not include the 2024 meta-analysis. Hattie and O'Leary, 2025.

The practical point is the gap between having a preference and showing that teaching to it improves learning. Someone may enjoy diagrams, dislike lectures or choose to listen to a book. None of that tells you which method will help that person understand and remember a particular subject.

The claim that needs testing

The learning-styles matching claim is sometimes called the meshing hypothesis. In its familiar form, it says that visual learners benefit especially from visual instruction, verbal learners from verbal instruction, and auditory learners from auditory instruction.

Testing that claim takes more than a questionnaire and a test score. Researchers have to identify the proposed styles, assign learners within each style to different teaching methods, and test everyone on the same suitable outcome. The critical result is a crossover: the best teaching method switches with the learner's supposed style. Harold Pashler and colleagues made this the central requirement in a major review. Pashler and colleagues, 2008.

Take a hypothetical lesson on the water cycle, taught to self-described visual and verbal learners with either a diagram or a spoken explanation. If the diagram works better for both groups, that supports the diagram for this lesson. It does not support dividing the class by learning style. If the people who prefer diagrams score higher whichever way they are taught, that does not show a matching benefit either; the groups may differ in other ways. Only a crossover would: the visual learners doing better with the diagram while the verbal learners do better with the spoken explanation.

That is also why a lesson that feels good is not enough to settle the question. A learner may prefer a method that makes the material feel familiar. What counts is what the learner understands and can use afterward.

Why the classic critique still matters

Pashler and colleagues concluded that the available research did not provide adequate evidence for building learning-style assessments into teaching. Their argument was about the matching prescription, not about whether learners differ. Preferences and abilities were separate issues. Pashler and colleagues, 2008.

That distinction guards against overcorrecting. Evidence against style matching does not mean everyone has the same knowledge, reads equally well or can access the same materials. Captions, readable text and accessible documents do not need a learning-style theory to justify them. And explaining an unfamiliar concept another way after someone struggles is not the same as assigning that person a permanent learner category.

So the question is narrow: does a specific classification improve the choice of teaching method? Many good reasons to adapt teaching do not need that classification at all.

What newer evidence adds

The 2024 review by Virginia Clinton-Lisell and Christine Litzinger found a small average benefit for matched over unmatched instruction across 21 studies (g = 0.31, 95% confidence interval 0.05 to 0.57). Leaving this result out would make the evidence look more uniform than it is.

But the crossover pattern the theory requires appeared in only 26% of outcome measures, and most studies that showed it did not meet the review's quality standards. The included studies used single learning sessions, so longer-term effects remain uncertain. Given the costs of implementation and the low study quality, the authors judged the benefits too small and too infrequent to warrant widespread adoption. Clinton-Lisell and Litzinger, 2024.

In a separate experiment, Melzner and Kappes presented course material about motivational theories to 222 prospective teachers, as figures or as text. They did not find that matching the format to visual or verbal preferences improved learning. Nor did matching improve the learners' measured judgments about learning. This tests those preferences, materials and outcomes, not every possible form of personalization. Melzner and Kappes, published online 2024.

A 2026 study by Papadatou-Pastou and colleagues ran the crossover test with 194 primary school students aged 10 to 12. Each child learned about weather forecasts, climate change and clouds through visual, auditory and audiovisual presentations, and was classified by both self-report and a learning-style inventory. The outcome was immediate recognition of the material just taught, measured by multiple-choice questions after each format. Matched instruction gave no significant benefit, and there was no crossover. Audiovisual presentation beat both single formats for every style group. And the children's self-reported styles were not significantly associated with the inventory's classifications. Papadatou-Pastou, Touloumakos and Theotokatou, 2026. That is the pattern from the water-cycle example: a format that helps everyone supports the format, not the sorting.

The 2025 review cited at the top, by John Hattie and Timothy O'Leary, untangles another source of confusion. Drawing on 17 meta-analyses, they separated the four that tested matching (143 studies, average d = .04) from the 13 correlational ones linking learning preferences or strategies with achievement (average r = .24). They argue that the correlational studies often confuse learning styles with learning strategies. The two kinds of study answer different questions. A correlation between a reported preference and higher scores does not show that assigning instruction by that preference caused better learning. Hattie and O'Leary, 2025.

What to do with this evidence

If you teach, train or design courses, the evidence does not make a strong case for buying a questionnaire and building parallel learning-style tracks. Better starting questions are about the task and the learner's actual difficulties.

Does the material require seeing a spatial relationship? Does the learner understand the vocabulary? Can they explain the idea without copying it? Can they use it in an example that differs from the one demonstrated? The answers tell you something about learning that a preference label cannot.

Take a training course on reading charts. It could show the chart, explain the relationship that matters and ask learners to interpret a new case. If someone struggles, the fix might be explaining an unfamiliar axis or correcting a wrong inference. None of those decisions requires treating the person as permanently visual or verbal. This is an illustration, not a lesson design that has been tested as a package.

Learner choice still has value. People can choose a format for convenience, enjoyment or access without claiming that it is their scientifically best route to remembering. The mistake comes when a preference becomes a limit: “I am an auditory learner, so diagrams are not for me.” The matching evidence does not support that conclusion.

Retrieval practice and spacing raise other questions about how to design instruction, with their own boundaries and uncertainties. Whatever the method, the job is the same: check whether the teaching improves the intended learning, and change it when it does not. Learning-style labels have not proved to be a dependable shortcut for those decisions.