When teaching is tailored to a person’s preferred learning style, they will learn better than when it is not. At least that is the thought promoted by many educators, students, and parents. I have spoken with numerous educators (high school and college) who assert that one of the biggest problems in education is the mismatch between teaching style and individual learning preference. Are you visual learner? Are you an auditory learner? Do you learn best by doing? Those are a few questions sometimes addressed when determining learning style. But are these questions meaningful? Should educators be more concerned with identifying learning styles and teaching to those styles?
It has been suggested that the conceptualization of learning styles is rooted in research into cognitive styles (also known as thinking dispositions). Cognitive styles reflect different ways of thinking in various contexts. People may incorporate fast or slower deliberate thinking strategies. There is a large body of research describing cognitive styles (Holmes 2016). Some people think in concrete terms, while others think and solve problems using abstract models. Examples of thinking dispositions that have been researched include need for cognition, actively open-minded thinking, considering future consequences, anti-scientific attitudes, dogmatism, need for closure, and superstitious thinking (Stanovich 2016). Thus thinking dispositions are not synonymous with learning styles.
What’s Your Learning Style?
Do a Google search for the words learning styles, and you will find many people claiming they can identify your preferred learning style. Those with expertise in the VAK (visual, auditory, kinesthetic) classification system of learning claim they can provide a diagnosis regarding your best learning style.
The VAK system is one of many that claims to be able to identify learning style. In one review, researchers identified over seventy different learning style (LS) classification systems (Coffield et al. 2004). The definition of learning styles varies, but most in the education field seem to agree that at the very least it involves identifying an individual’s preferred style of learning and matching instruction with that style.
A survey administered by Dekker and colleagues found that 93 percent of teachers in the U.K. believed that individuals learn better when they are instructed according to their preferred learning style (Dekker et al. 2012).
A study conducted using a sample of higher education faculty (in the United States) found that 64 percent of the study participants answered yes to the question “does teaching to a student’s learning style enhance learning” (Dandy & Bendersky 2014). A search of the Educational Resources Information Center (ERIC) found almost 2,000 journal articles, approximately 900 conference presentations, and 700 books or book chapters on learning styles (Lilienfeld et al. 2010). With such a widespread belief in the merits of learning styles, surely there must be strong evidence to support the belief … right?
The attribute-treatment interaction (ATI) hypothesis predicts that visualizers will perform best on tests when they receive visual rather than verbal methods of instruction, and verbalizers will perform best on tests when they receive verbal rather than visual methods of instruction. Massa and Mayer conducted a set of experiments to test the ATI hypothesis (2006). The results of the study did not support the hypothesis.
“Overall, our results do not provide a convincing rationale for customizing different on-line instruction programs for visualizers and verbalizers.”
In another study, Kratzig and Arbuthnott (2006) tested whether learning style preference correlated with memory in each of the three sensory modalities: visual, auditory, and kinesthetic. The results indicate test performance did not correlate with learning style preference. The researchers concluded that their results challenge the claim that individuals learn best when instructed according to their preferred sensory modality.
Some proponents of the learning styles approach argue that the reason for the lack of evidence to support learning styles is that students do so much of their learning outside of class. According to this view, researchers have failed to find evidence for learning styles because their focus has been too narrow.
In addition to asking whether it is beneficial to match teaching style and preferred learning style, researchers should also look for the beneficial effects of learning styles regarding studying outside of class. A study was conducted at Indiana University School of Medicine to address this (Husmann & Dean O’Loughlin 2018). At the start of term, researchers asked undergrads taking an anatomy course to take one of the most popular online learning styles surveys, the VARK survey. The VARK categorizes students according to how much they prefer to learn visually, through auditory information, through reading and writing, or through kinaesthetics (by doing or by practical example). The VARK website offers study tips based on preferred learning style(s). The researchers advised their students to take the survey and to use the study practices consistent with their learning style. Later in the term the researchers surveyed students about the practices they used when studying outside of class, to see if they used suggested congruent with their dominant (preferred) learning style. The researchers reviewed the students’ end-of-year grades to see if there was a correlation between grade performance, dominant learning style, and/or studying outside of class in a way consistent with preferred learning style. Results showed that most students did not report study strategies that correlated with the VARK assessment, and that student performance in anatomy was not correlated with their score in any VARK categories. The researchers did find that some specific study strategies (such as use of the “virtual microscope,”) were positively correlated with final class grade. However, the alignment of these study strategies with VARK results had no correlation with anatomy course outcomes. Thus, this research provides further evidence that the conventional wisdom about learning styles should be rejected by educators and students alike.
Another problem with the learning styles concept is a lack of agreement between teachers and students on the students’ preferred learning style. One study (Papadatou-Patou, et al. 2018) consisted of fifth- and sixth-grade students from five schools. The students chose their preferred learning style—visual, auditory, or kinaesthetic—and completed a short IQ test. Their teachers first provided an open-ended answer to the question “Does teaching that is tailor-made to the students’ learning style reinforce the students’ performance?” then they were asked to identify each of their students’ preferred learning style. All the teachers supported the concept of preferred learning styles. The results indicate that there wasn’t a statistically significant correlation between the teachers’ judgments of their students preferred learning style and the students’ preference; teachers and students didn’t agree on the students’ best mode for learning. The researchers concluded, “… if the identification of learning styles … is unreliable, as evidence by the findings of the present study, this should constitute an additional reason why teachers should abandon the use of learning styles in instruction.”
Evidence does not support the claim that students learn best when teaching style is matched with preferred learning style. This of course shouldn’t discourage educators from striving to improve teaching methods. Teaching beginners in a specific area might require different strategies than teaching those with high levels of knowledge. Different teaching strategies might be required for teaching different things; strategies may depend on context. There is a large body of research on strategies to maximize learning, and educators and students are advised to review and use information from that line of research instead of spending time trying to identify their illusive learning style.
Coffield, F., Moseley, D., Hall, E., and Ecclestone, K. 2004. Learning Styles and Pedagogy in Post 16 Learning: A Systematic and Critical Review. London: Learning and Skills Research Centre.
Dandy, K., and Bendersky, K. 2014. Student and faculty beliefs about learning in higher education: implications for teaching. International Journal of Teaching and Learning in Higher Education, 26, 358–380.
Dekker, S., Lee, N.C., Howard-Jones, P., and Jolles, J. 2012. Neuromyths in education: prevalence and predictors of misconceptions among teachers. Frontiers in Psychology, 3, 429.
Holmes, J.D. 2016. Great Myths of Education and Learning. Malden, MA: Wiley Blackwell.
Husmann, P.R., and Dean O’ Loughlin. 2018. 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. DOI https://doi.org/10.1002/ase.1777.
Kratzig, G.P., and Arbuthnott, K.D. 2006. Perceptual learning style and learning proficiency: A test of the hypothesis. Journal of Educational Psychology, 98(1), 238–246.
Lilienfeld, S.O., Lynn, S.J., Ruscio, J., and Beyerstein, B.L. 2010. 50 Great Myths Of Popular Psychology: Shattering Widespread Misconceptions about Human Behavior. Malden, MA: Wiley-Blackwell.
Massa, L.J., and Mayer, R.E. 2006. Testing the ATI hypothesis: Should multimedia instruction accomodate verbalizer-visualizer cognitive style. Learning and Individual Differences, 16, 321–335.
Papadatou-Patou, M., Gritzali, M., and Barrable, A. 2018. The Learning Styles Educational Neuromyth: Lack of Agreement Between Teachers’ Judgments, Self-Assessment, and Students’ Intelligence. Frontiers in Education. DOI https://doi.org/10.3389/feduc.2018.00105.
Stanovich, K., West, R., and Toplak, M. 2016. The Rationality Quotient. Cambridge, Massachusetts: The MIT Press.