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Performance Improvement, vol. 49, no. 10, November/December 2010©2010 International Society for Performance Improvement

Published online in Wiley Online Library (wileyonlinelibrary.com) • DOI: 10.1002/pfi.20181

LEARNING STYLES FRAY: BRILLIANT OR BATTY?

Atena Bishka

Many school educators, instructional designers, and corporate training specialists believe

that learning styles are important and that much of training success relies on the craft of

incorporating learning styles into learning materials. But how do common views and popular

wisdom on learning styles align with what the psychological sciences tell us today? Does

matching instructional design to learning styles really result in learning enhancement? This

article seeks to examine such questions based on current research in psychological sciences.

Leaders in education direct their choices of methods by the results of scientifi c investigation rather than general opinion.

Edward Lee Thorndike (1906)

Basing education on scientifi c evidence is the hallmark of sound professional practice, and should be encouraged within the educational profession wherever possible.

John Geake (2008)

IN THE MULTICULTURAL WORLD in which we live, our individual differences define us as much as our similarities. In the industry of adult education and cor-porate training, learning styles or cognitive styles are not only ubiquitous, but also among the most unquestioned differences of all. So much so, that there is no train-ing manual that would not begin with a section (often spread through several pages) specifically reserved to learning styles assessment and its impact on knowledge acquisition.

But is learning a true function of learning styles? Does matching instructional design to learning styles really result in learning enhancement? How scientifically grounded are the prevailing assumptions about learning styles? And is there a gap between practice and theory?

To answer such questions, let us start with a quick view on the popularity of learning styles. A simple search on

Google will produce millions of entries and numerous Web sites that offer learning styles information, assess-ment tools, and questionnaires. As of 2008, Lilienfield, Lynn, Ruscio, and Beyerstein (2010) counted 1,984 jour-nal articles (3,604 entries), 919 conference presentations, and 701 books or book chapters.

The learning styles field is vast, but not unified. According to Coffield, Moseley, Hall, and Eccleston (2004), it is divided into three linked areas of activity: theoretical, pedagogical, and commercial.

The first area of activity is a growing body of theo-retical and empirical research on learning styles in the United Kingdom, the United States, and Western Europe that began in the early 20th century. It is still producing ideas and an ever-proliferating number of instruments.

The second area of activity is a vast body of research on teaching and learning, which draws researchers from diverse disciplines including psychology, sociology, business studies, management, and education. These disciplines interpret evidence and theories on their own terms, rather than on common, established criteria.

The third area of activity consists of a large, thriving commercial industry that promotes particular invento-ries and instruments. The most popular learning style schemes used in the workplace, as identified by Pashler, McDaniel, Rohrer, and Bjork (2008), include Dunn and Dunn’s Learning Styles Model in the United States,

10 www.ispi.org • DOI: 10.1002/pfi • NOVEMBER/DECEMBER 2010

Kolb’s Learning Styles Inventory in the United Kingdom, and Honey and Mumford’s Learning Styles Questionnaire. The researchers point out that the com-mercial gains for creators of successful learning styles instruments are so large that critical engagement with the theoretical and empirical bases of their claims tends to be unwelcome. (For example, how credible can such entities be when they conduct research on the instru-ments that they sell?)

WHAT ARE LEARNING STYLES?Learning styles refer to the concept that individuals differ as to what mode of instruction or study is most effective for them. The basic idea of learning styles is that different people have different ways of learning, and if instruc-tion is matched to the individual’s style, he or she should learn better. It is appealing and natural to think that all people have the potential to learn effectively and easily, if only the instruction is tailored to their individual style. The logic is that we become more motivated to learn by knowing more about our own strengths and weaknesses. In addition, if learning designers and facilitators respond to such strengths and weaknesses, then we could achieve better learning and attention.

By nature, as cognitive psychologist Willingham (2009) concurs, our mind does not want to work hard. In every-thing we do, we tend to try the easiest and lowest cost solution first. The theory of learning styles is attractive, and it sounds like common sense. It is also convenient, offering a rationale of escaping accountability and get-ting rid of responsibility. For less than satisfactory learn-ing results, the reason could be that the instruction was inadequately tailored to fit the unique individual’s learn-ing style. However, after more than 30 years of research, no consensus has been reached about the most effective instrument for measuring learning styles and there is no agreement about the most appropriate pedagogical inter-ventions. For each study that supports this hypothesis, there is a study that rejects it. No substantial, uncontested, and hard empirical evidence has been found to prove that matching the styles of learner and instructor improves learning and attention.

THE LEARNING STYLES HYPOTHESIS— TRUE OR FALSE?Although there are numerous types and names of learn-ing styles in the literature, there are three styles that are most frequently encountered: visual (V), auditory (A), and kinesthetic (K)—sometimes collectively called VAK.

The hypothesis of the learning styles theory is as follows: Learning is optimal if the learning method is matched to the student’s learning style.

As with any scientific hypothesis, two key questions should be asked:

How would we know the hypothesis is true, or what 1. type of evidence would show that the hypothesis is true?

How would we know the hypothesis 2. is not true, or what type of evidence would show that the hypothesis is not true?

To answer the first question, the acceptable evidence that proves that the hypothesis is true should show that a different learning method optimizes learning for each type of learner. Examples of such interaction between learning method and type of learner would be as fol-lows: (a) auditory format of instruction is consistently good for the learner with auditory style; (b) visual format of instruction is consistently good for the learner with visual style; or (c) kinesthetic format of instruction is consistently good for the learner with kinesthetic style. Note that, as Willingham (2009) points out, it is impor-tant to not only show that a particular type of interaction exists but also prove that this unique interaction is also

The theory of learning styles is attractive, and it sounds like common sense. It is also convenient, offering a rationale of escaping accountability and getting rid of responsibility. For less than satisfactory learning results, the reason could be that the instruction was inadequately tailored to fit the unique individual’s learning style.

Performance Improvement • Volume 49 • Number 10 • DOI: 10.1002/pfi 11

consistent. In other words, a visual type of learner always (not just some times) learns better through a visual method of instruction.

The answer to the second question—what type of evidence would prove that the hypothesis is not true?—is the opposite. In other words, the unacceptable evidence would indicate that the same learning method optimizes learning for different types of learners.

So, what types of evidence do research studies provide?

The quest for evidence is not new, at least for the last 30 years or more. But, Pashler et al. (2008) con-ducted the most thorough review of experimental studies known to date, which sought to objectively find answers either in support of or against the hypothesis described above. Their review did not find evidence in favor of the learning styles hypothesis (i.e., that learning is more effective when teaching matches the learner’s style).

In addition, Massa and Mayer, who sought to find evidence for the same hypothesis, conducted a note-worthy and elegant experimental study, published in 2006:

This idea [that visualizers learn better with visual methods of instruction, whereas verbalizers learn better with verbal methods of instruction]—deeply ingrained in the folklore of educational practice—is one aspect of what can be called the attribute-treatment interaction (ATI) hypothesis ... In spite of the widespread popularity of the ATI hypothesis among educators, the search for research-based ATIs over the last 25 years has had a somewhat disappointing history. (p. 321)

In Massa and Mayer’s (2006) experimental study, college and noncollege students took a computer-based lesson that offered help screens that maintained infor-mation in either text format (intended for verbalizers) or pictorial illustrations (intended for visualizers). The students’ cognitive styles and preferences were also measured to distinguish verbalizers from visualizers. After the training, all students took the same learning test. The results showed that although it is possible to use instruments to distinguish between verbalizers and visualizers, there was no evidence to support the ATI hypothesis or the idea that different instructional methods should be used for visualizers and verbalizers. What is remarkable is that instead of finding support-ive evidence for the ATI hypothesis, the study showed that “adding pictorial aids to an on-line lesson that was heavily text-based tended to help both visualizers and verbalizers,” which is “consistent with what Mayer

(2001) calls multimedia effect: People learn better from words and pictures than from words alone!” (p. 334). In other words, learning methods that properly inte-grate visuals with textual or oral components work better—for any learner regardless of his or her learning styles—than those methods that are built on only one component.

WHAT DO NEUROIMAGING STUDIES REVEAL?

The brain sees with its ears and touch, and hears with its eyes.

Christoph Kayser (2007)

Going back to VAK, the claim is that everyone is a V, A, or K type of learner. Such a claim assumes that indi-vidual differences in perceptual acuity are maintained throughout higher order information processing. But this is a false assumption. Neuroimaging studies in crossmodal processing have demonstrated that input modalities in the brain are interlinked: visual with audi-tory, visual with motor, motor with auditory, visual with taste, and so on (Geake, 2008). According to such stud-ies, the central characteristic of brain function is neural functional interconnectivity. This means, says Geake, for example, that if you are in a dark tunnel and hear a sudden noise, both auditory and visual senses would activate and coordinate simultaneously—preferences and styles would simply not factor in. Without such a highly evolved intermodal facility, we never would have survived the challenges of savage life. And today, when we watch a live TV news report in which the reporter’s sound is not synchronized with the picture, we can tell there is a difference even when it is a matter of a fraction of a second.

REVIEW OF LEARNING STYLES LITERATURE—WHAT ELSE IS WRONG?Coffield et al. (2004), in a highly exhaustive review of learning styles literature, grouped the vast amount of learning styles models and instruments into 13 categories, based on several key themes. Each category was examined for evidence (provided by independent researchers) that the instrument could demonstrate internal consistency and test-retest reliability, as well as predictive validity. These researchers found that only 3 of the 13 examined learning styles models came close to meeting those criteria.

12 www.ispi.org • DOI: 10.1002/pfi • NOVEMBER/DECEMBER 2010

What adds more to the misconceptions and flaws in the learning styles research and popular literature is a certain confusion and overlap between learning styles and cognitive abilities. Cognitive psychologist Daniel Willingham (2009), in his well-known book Why Don’t Students Like School? draws attention to the differences between these two concepts. Learning styles represent a mode of learning, a bias, or a preference, and as such, it is quite a different concept from cognitive ability, which means capacity or proficiency. The stronger and the more developed the cognitive ability, the higher the possibility for achieving success at a certain skill or task. On the con-trary, any given learning style is no better or worse than any other learning style. For example, although the styles of two different investment brokers could be quite differ-ent (let’s say their style of risk tolerance), their abilities for success and high performance may be fairly similar. In fact, abilities can be measured and objectively evalu-ated, but learning styles assessed through self-reported inventories might not be accurate samplings of learning behavior. They simply represent learners’ impressions of how they learn and such impressions may be inaccurate, self-deluding, or influenced by what the respondent thinks the instructor wants to hear.

In addition, it is important to note that the field of learning styles research as a whole is characterized by a very large number of small-scale applications of par-ticular models to small samples of students in specific contexts. This makes it hard to evidence the true impact of learning styles on instruction and learning, because there are very few robust studies that offer reliable and valid evidence and clear implications for practice based on empirical findings.

LEARNING IS ABOUT MEANINGSeveral of the world’s prominent luminaries, philoso-phers, cognitivists, and linguists, from Heidegger to Korzybski to Lakoff, maintain that our primary way of making sense of the world is interacting with meaning. What captures our attention is meaning, and our brain takes in the world and understands it in the form of meaning and abstraction. Although some individuals tend to be better at remembering visual details while oth-ers tend to have a stronger auditory memory, fundamen-tally what we learn and remember are meaning based. As cognitive psychologist Daniel Willingham (2009) indicates, “most of the time students need to remember what things mean, not what they sound like or look like,” emphasizing that simplistic generalizations about the need to respond to individual learning styles will have limited impact on learning.

LEARNING DEPENDS ON PRIOR KNOWLEDGE AND BACKGROUNDAnother decisive factor in learning is prior knowledge and background. Research shows that conditions of instruc-tion that are optimal differ depending on students’ prior knowledge. According to Willingham (2009), cognitive processes (such as analyzing, synthesizing, and critiquing) cannot operate alone, as they need background knowl-edge to make them work. Such an opinion is in complete congruence with Mayer’s (2008), who maintains that “the single most important individual differences measure for learning is prior knowledge” (p. 507). New learning builds on old learning, so prior knowledge is bound to determine what level and type of instruction activities are optimal for the learner.

CONCLUSION AND IMPLICATIONS FOR PRACTICELearners are not all alike. They may have differences in preferences and styles. They live in particular socio-economic settings, where age, gender, race, and class all interact to influence their attitudes toward learning. Their social lives with partners, families, and friends and their economic lives with their employers and fellow workers influence their learning in significant ways. However, no substantial, uncontested, and hard empirical evidence has been found to indicate that matching learner styles and instruction styles improves learning and attention. Basic psychological science can assist instructional designers and learning developers by helping them distinguish between myths and truths. Psychological research informs us that people, regardless of other differences, do not learn differently. Therefore, although differences do exist and may be measured, limited education resources would be better devoted to adopting educational practices that are scientifically proven to be sound.

Those research findings and practices tell us that performance improvement professionals should direct

What captures our attention is meaning, and our brain takes in the world and understands it in the form of meaning and abstraction.

Performance Improvement • Volume 49 • Number 10 • DOI: 10.1002/pfi 13

attention to not only individual differences in learners but also, first and foremost, (a) prior and existing knowl-edge, (b) meaning and content, and (c) practice and drill-ing to retain learning. Those, and other implications, for human performance improvement will be discussed in another article to be published in an upcoming issue of this journal.

References

Coffield, F., Moseley, D., Hall, E., & Eccleston, K. (2004). Should we be using learning styles? Retrieved April 24, 2010, from http://www.lsnlearning.org.uk/search/Resource-32188.aspx.

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

Kayser, C. (2007). Listening with your eyes. Scientific American Mind, 18(2), 24–29.

Lilienfield, S.O., Lynn, S.J., Ruscio, J., & Beyerstein B.L. (2010). 50 great myths of popular psychology—Shattering widespread misconceptions about human behavior. West Sussex, UK: Wiley-Blackwell.

Massa, L.J., & Mayer, R.E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? Learning and Individual Differences, 16, 321–336.

Mayer, R.E. (2001). Multimedia learning. New York: Cambridge University Press.

Mayer, R.E. (2008). Incorporating individual differences into the science of learning: Commentary on Sternberg et al. (2008). Perspectives on Psychological Science, 3(6), 507–508.

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

Thorndike, E. L. (1906). The principles of teaching based on psychology. New York: Seiler.

Willingham, D.T. (2009). Why don’t students like school? San Francisco: Jossey-Bass.

Related Readings

Kavale, K.A., & Forness, S.R. (1987). Substance over style: Assessing the efficacy of modality testing and teaching. Exceptional Children, 54(3), 228–239.

Reynolds, M. (1997). Learning styles: A critique. Management Learning, 28, 115–133.

Sharp, J.G., Bowker, R., & Byrne, J. (2008). VAK or VAK-uous? Towards the trivialisation of learning and the death of scholar-ship. Research Papers in Education, 23, 293–314.

Stahl, S. (1999, Fall). Different strokes for different folks. American Educator, 1–5.

Advanced Technical Related Readings

Heidegger, M. (1968). What is called thinking? New York: Harper Perennial.

Korzybski, A. (1933). Science and sanity (5th ed. 1994, 3rd printing 2005). Fort Worth, TX: Institute of General Semantics.

Lakoff, G. (1987). Women, fire, and dangerous things—What categories reveal about the mind. Chicago: The University of Chicago Press.

ATENA BISHKA is a consultant, speaker, and author who specializes in learning design and devel-opment as well as evaluation of learning initiatives and impact on business goals and work perfor-mance. Her key areas of interest include design of instruction and assessment of learning, which best respond to how people learn, quantitative and qualitative evaluation, and relationships among media, message, and instruction. She may be reached at atena.bishka@gmail.com.