Are Learning Styles Bullshit?

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Chances are you've been labeled—or have labeled yourself—as a "visual," "auditory," or "kinesthetic" learner. These are Learning Styles, which morphed from a series of tentative theoretical frameworks into gospel for corporate training programs.

Research by Coffield et al. (2004) identified over 70 different learning style models. You’ve probably heard of a handful of these, like the aforementioned infamous AVK Theory. We have a knack for latching onto educational theories and inflating them beyond their empirical support.

Origins of Learning Styles

The concept of learning styles gained significant traction in the 1970s and 1980s with roots in various psychological theories. Frameworks emerged proposing that as learners we have distinct preferences for receiving information. Further, matching instruction to these preferences would optimize learning outcomes. This became known as the “Meshing Hypothesis” (Pashler et al., 2008). It makes intuitive sense.

The biggest splash came in 1992 with the publication of Rita and Kenneth Dunn's "Teaching Elementary Students Through Their Individual Learning Styles", which identified 21 different elements affecting how individuals learn (Dunn & Dunn, 1992).

Schools rushed to adapt pedagogy to these findings. Teachers were trained around learning styles and taught to adjust to their students. Soon, learning styles rapidly transitioned from intriguing childhood educational theory to a cornerstone of corporate training methodologies.

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Corporate learning departments embraced this “research-backed” approach, investing heavily in learning style inventories, sometimes assessing entire departments or companies. Training programs were redesigned to accommodate different styles, often tripling development costs as facilitators created separate materials for visual, auditory, and kinesthetic learners (Ribbens, 1997)! Onboarding programs began featuring learning style assessments, with new hires promptly tagged and routed into supposedly style-appropriate training pathways.

The intuitive appeal was and is undeniable: we all feel we learn better in certain ways. Some professionals swear they need to see information visualized, others prefer to hear concepts explained, while still others want to get hands-on with simulations or role-playing.

But is it legit?

So... are Learning Styles Bullshit?

The central claim that learning improves when we match teaching to styles simply doesn't hold up under scientific scrutiny.

A seminal study by Pashler et al. (2008) found that despite thousands of studies reifying learning styles, very few employed methodologically sound research designs. Many others have since found that when rigorously tested under controlled conditions, the predicted interactions between learning style and instructional method consistently fail to materialize (Husmann & O'Loughlin, 2019; Kraemer et al., 2014; Kirschner & van Merriënboer, 2013; Massa & Mayer, 2006; Rogowsky et al., 2015).

The evidence is so overwhelming that Kirschner (2017) called learning styles one of workplace learning's most enduring "neuromyths."

So in short, yes, these classic ‘styles’ are bullshit.

But someone reading this right now, maybe even you, is undoubtedly giving this post the side-eye.

“I don’t care whether the large-scale research backs this up… I know I’m a visual learner!” – Someone reading this right now, possibly you.

So here’s the thing… we do have learning style preferences. You may genuinely prefer to learn by watching a lecture, or from listening to content that’s humorous, or while you’re skydiving or whatever. Our preferences are real.

But despite very real preferences, there’s almost no decent evidence that learning in your preferred style has an impact on effectiveness.

Now, learning in your preferred style may attract you to an experience that you might otherwise avoid. So there is some value in learning style preferences: they may get you in the door. But once you’re there, there’s no evidence they really matter.

What Actually Works

Not all frameworks addressing learner differences are worthless! Kolb's Experiential Learning Theory or Gardner's Multiple Intelligences can serve as useful reflection tools, helping L&D professionals and learners think intentionally about variety, personal strengths, and preferences. But these should function as lenses for reflection, not as rigid prescriptions or talent classification systems.

Evidence-Based Alternatives

If learning styles are largely bullshit, what should organizations invest in instead? There are several empirically supported methods:

Dual coding theory: Combining words and visuals enhances memory—not because some employees are "visual learners," but because human brains process information through multiple channels simultaneously. Well-designed training integrates verbal explanations with relevant visualizations (Paivio, 2013). (Note: this does not mean you should read words aloud off a slide, which creates a redundancy effect and should be avoided).

Cognitive load theory: Presenting information in manageable chunks reduces unnecessary mental burden. This means structuring content complexity based on employees' prior knowledge, not their purported learning style (Sweller, 2011).

Multimodal learning: Using varied formats benefits everyone, especially when reinforcing key concepts through different approaches. Your sales training program should include discussions, demonstrations, practice scenarios, and case studies—not because it covers all styles, but because this integrated approach enhances learning for everyone (Mayer, 2014).

Most importantly, specific learning strategies have demonstrated robust effectiveness across contexts:

1. Retrieval practice: Having employees actively recall information through scenarios, case discussions, or knowledge checks strengthens memory far more effectively than passive review (Roediger & Butler, 2011).

2. Spaced repetition: Distributing learning over time through follow-up modules, application assignments, and refresher sessions produces better retention than concentrated training events (Cepeda et al., 2008).

3. Elaboration: Providing opportunities for employees to explain concepts in their own words and connect them to their work context deepens understanding (Willoughby et al., 1994).

4. Interleaving: By mixing up related subjects instead of focusing on one at a time, employees can use what they've learned in real-life situations more effectively (Schorn & Knowlton, 2021).

So What?

As a general rule, beware of attempts to codify human experience into simple, neat categories.

Clear and engaging learning design built on sound learning principles benefits everyone, regardless of their self-reported style preference. Our organizations deserve learning interventions based on how human cognition actually works, not on intuitive but ultimately misguided myths.

That's it for this edition - please reach out if I can be at all helpful.
Be compassionate and intentional.

References

Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological Science, 19(11), 1095-1102.

Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. Learning and Skills Research Centre.

Geake, J. (2008). Neuromythologies in education. Educational Research, 50(2), 123-133.

Howard-Jones, P. A. (2014). Neuroscience and education: myths and messages. Nature Reviews Neuroscience, 15(12), 817-824.

Husmann, P. R., & O'Loughlin, V. D. (2019). Another nail in the coffin for learning styles? Disparities among undergraduate anatomy students' study strategies, class performance, and reported VARK learning styles. Anatomical Sciences Education, 12(1), 6-19.

Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers & Education, 106, 166-171.

Kirschner, P. A., & van Merriënboer, J. J. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 169-183.

Kraemer, D. J., Hamilton, R. H., Messing, S. B., DeSantis, J. H., & Thompson-Schill, S. L. (2014). Cognitive style, cortical stimulation, and the conversion hypothesis. Frontiers in Human Neuroscience, 8, 15.

Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? Learning and Individual Differences, 16(4), 321-335.

Mayer, R. E. (2014). Multimedia instruction. In Handbook of research on educational communications and technology (pp. 385-399).

Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309-326.

Paivio, A. (2013). Imagery and verbal processes. Psychology Press.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.

Ribbens, B. A. (1997). Organizational learning styles: Categorizing strategic capabilities. Career Development International, 2(1), 36-41.

Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20-27.

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249-255.

Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. Journal of Educational Psychology, 107(1), 64-78.

Schorn, J., & Knowlton, B. (2021). Interleaved practice benefits implicit sequence learning and transfer. Memory & Cognition, 49, 1436-1452.

Sweller, J. (2011). Cognitive load theory. Psychology of Learning and Motivation, 55, 37-76.

Willoughby, T., Wood, E., & Khan, M. (1994). Isolating variables that impact on or detract from the effectiveness of elaboration strategies. Journal of Educational Psychology, 86(2), 279-289.