One of the most common misunderstandings about VARK is that it is primarily a tool for matching teaching methods to learning preferences. While teaching certainly matters, VARK has always been equally concerned with what learners do themselves. Understanding your preferences can help you make better choices about how you engage with information, practise skills, and deepen your learning.
Recent research on VARK and multimodal learning highlights this distinction. Although the studies vary in their methods and conclusions, several common themes emerge. Learners often benefit from variety in how information is presented, opportunities for active engagement, and the freedom to choose learning approaches that work for them. In many cases, these factors appear to be more important than attempts to match teaching to a single learning preference.
Moving Beyond a Single Preferred Modality
Several of the studies explored the relationship between learning preferences and educational outcomes. They often found little evidence that learning preferences alone predict academic success. This supports a long-standing VARK message: anyone can succeed, no matter what their VARK preference is.
A 2025 study of medical students, by Akturan, Keski, Sağlam, et al. found no significant direct relationship between learning preferences and academic performance. Instead, intrinsic motivation was strongly associated with higher achievement. Students repeatedly emphasized the value of practical activities, simulations, and diverse teaching methods that allowed them to engage more actively with course material.
This finding is important because it shifts attention away from learning preferences as predictors of success and towards what learners actually do. Motivation, participation, and engagement play a major role in learning outcomes.
The implication is not that learners should be restricted to a single modality. Rather, understanding your preferences may help you identify strategies that encourage greater engagement and persistence — regardless of which modality you favor.
A note on this study’s VARK data: This study assigned each participant a single modality by taking whichever score was highest on the questionnaire, rather than applying the official VARK scoring algorithm — which identifies multimodal profiles and only assigns a single dominant preference when one modality is genuinely well ahead of the others. The paper’s descriptions of what counts as “Visual” and “Kinesthetic” also depart from VARK’s own definitions in ways that suggest a simplified or inaccurate reading of the model. Because of this, we haven’t included the study’s specific claims about which modality group was most engaged — the underlying VARK categories aren’t reliable enough to support that level of detail.
The Power of Active Learning
Perhaps the strongest theme running through these studies is the value of active learning.
Students, in the study by Akturan, Keski, Sağlam, et al., described lecture-heavy teaching and slide-based presentations as less engaging and less effective at promoting participation. In contrast, practical activities, laboratory sessions, simulations, and interactive learning experiences were associated with higher levels of motivation and engagement.
Another study, by Aslan, Ananda & Prayoga, found that students classified as Kinesthetic learners reported higher levels of academic anxiety. The authors suggested that students may become frustrated when learning environments provide limited opportunities for active participation and experiential learning.
While learning preferences alone cannot explain anxiety or achievement, the findings point to an important question: are learners being given enough opportunities to actively engage with ideas?
This is particularly relevant for VARK users. Learners with strong Kinesthetic preferences often benefit from examples, applications, practice, simulations, and real-world experiences. However, active learning is not valuable only for Kinesthetic learners. Learners with Visual, Aural, and Read/write preferences can also engage actively by creating diagrams, discussing ideas, teaching concepts to others, solving problems, writing summaries, and applying knowledge in meaningful contexts.
The common factor is not the modality itself but the level of active engagement.
Multimodal Environments in Practice
Several studies highlighted the benefits of multimodal learning environments.
A 2026 project by Nurmawati, Kadarwati, Purnomo et al. developed a STEM learning application that combined graphics, text, audio explanations, interactive activities, and problem-solving tasks. Students were able to access multiple forms of representation rather than being restricted to a single approach. The researchers reported improvements in problem-solving ability, particularly among students who had initially performed less strongly.
A study by Abaguhan, Alhashem, Alsaleh et al. investigated emergency medicine training and found high levels of curriculum satisfaction regardless of participants’ VARK preferences. The researchers suggested that this may be because the curriculum already incorporated multiple learning experiences, including lectures, simulations, and clinical practice. Rather than tailoring instruction to individual preferences, the programme provided multiple pathways through which learners could engage with the material.
These findings suggest that variety can be beneficial because different modalities often complement one another. A diagram may help clarify a concept, a discussion may expose misunderstandings, a written summary may reinforce key ideas, and practical application may deepen understanding.
Multimodal learning environments provide opportunities for learners to approach content from different angles and select the strategies that are most useful for them.
Choice and Learner Autonomy
In one of the most interesting studies, Brennan and Barbon replaced traditional assessments with a range of assignment options. Students could choose from activities such as quizzes, concept maps, video recordings, and case studies.
The results were overwhelmingly positive. Students reported greater confidence, stronger engagement, and a greater sense of success. They also valued the flexibility, reduced stress, and opportunity to choose approaches that suited their preferences and circumstances.
This finding resonates strongly with the philosophy behind VARK.
The goal of understanding learning preferences is not to place learners into categories. Rather, it is to give learners information that helps them make informed choices. When learners understand how they prefer to engage with information, they are often better positioned to select study strategies, learning activities, and assessment approaches that support their learning.
Choice encourages learners to take ownership of the learning process, and ownership is often closely linked to motivation and engagement.
What Can We Learn from These Studies?
Across these studies, a consistent pattern emerges: learning preferences alone don’t predict success. What matters more is what learners actually do — how motivated they are, how actively they engage, and how much say they have in their own learning.
Active learning helps. Choice helps. Variety helps. And a preference is only useful once you act on it.
That’s the real message behind VARK: your preferences are a starting point, not a verdict. The goal is not to sort learners into boxes — it’s to give them a way to reflect on how they engage with material, so they can make better choices about what to do next.
The studies reviewed here suggest that variety, active engagement, and learner choice may be among the most valuable ingredients in effective learning environments. These principles are not only compatible with VARK—they help explain why so many learners find VARK useful as a tool for reflection and self-directed learning.
References
Akturan, S., Keski, F., Sağlam, Ç. B., & Sezer, Z. B. (2025). Exploring the Role of Learning Styles and Motivation in Medical Student Engagement and Academic Performance: A Mixed Methods Study. The Eurasian journal of medicine, 57(2), 1–13.
https://doi.org/10.5152/eurasianjmed.2025.25862
Aslan, D., Ananda, R., & Prayoga, P. (2025). The Relationship Between Kinesthetic Learning Style and Academic Anxiety Levels of High School Students. Acta Psychologia, 4(1), 33–42. https://doi.org/10.35335/psychologia.v4i1.80
Nurmawati, N, Kadarwati, S, Purnomo, E, Mawarsari, V, Prihaswati, M, & Adnan, M. (2026). Development of STEM-Based VARK Learning Application to Improve Problem-Solving Skills in Calculus Courses. Jurnal Pendidikan MIPA, 29(2).
https://jpmipa.fkip.unila.ac.id/index.php/jpmipa/article/view/1250
Abuguyan F, Alhashem HM, Alsaleh GS, Alsalame N and Alnasser T (2026) Exploring VARK learning preferences, curriculum satisfaction, and the impact of demographic factors among emergency medicine residents at multiple training centers in Riyadh. Front. Educ. 11:1823232. doi: 10.3389/feduc.2026.1823232
https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2026.1823232/full
Lisa Brennan, Rachel Barbon (2026) Flexible, VARK-aligned pre/post module assignments in a hybrid pathophysiology & pharmacology course: A mixed-methods evaluation. Teaching and Learning in Nursing 21(3), e1145-e1149.
https://doi.org/10.1016/j.teln.2026.03.027
