The Learning Styles Controversy – A “Neuromyth” or the Future of Individualized Education?

Dr. Donna L. Roberts

Simply defining the term learning style, as it turns out, is more difficult than it may seem.

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Photo by John Schnobrich on Unsplash

The term “learning style” began to appear in the educational literature in the 1970s. Since that time, researchers and educators have attempted to determine both a standardized defining construct and a functional assessment instrument. The result has been an inundation of differing models and commercial measurements yielding questionable and inconclusive empirical results.

The terms learning style, cognitive style, and learning strategy are used interchangeably and imprecisely throughout. Keefe (1979) defines learning styles as the “composite of characteristic cognitive, affective, and physiological factors that serve as relatively stable indicators of how a learner perceives, interacts with, and responds to the learning environment” (p. 1). Keefe and Ferrell (1990) later stated that a learning style represented “a complex of related characteristics in which the whole is greater than its parts. Learning style is a gestalt combining internal and external operations derived from the individual's neurobiology, personality and development, and reflected in learner behavior” (p. 57).

From a more concrete and practical orientation, Stewart and Felicetti (1992) define learning styles as those “educational conditions under which a student is most likely to learn.” With that definition we begin to see the proposed relationship between a learning style and the outcome, that is, the effectiveness of learning.

Dorothy MacKeracher (2004) added specificity and complexity to the definition. She agreed that “a learning style represents a relatively stable and consistent set of strategies that an individual prefers to use when engaged in learning” (p. 71), but also, more specifically indicated that “these strategies are used to: take in information through sensory organs; select information for further processing; store and retrieve information from memory; make sense of information to create new meanings, ideas, values, skills or strategies or revise existing meanings, ideas, values, skills or strategies; use meanings, ideas, values, skills and strategies to solve problems and make decisions; plan and act in accordance with such decisions, resulting in new experiences from which new information can be taken in; interact with others in the learning environment; and change any or all of the strategies referred to above” (p.76). With this definition she more fully described components of the learning process

MacKeracher further indicated that learning styles also relate to such factors as: the environmental conditions under which learners prefer to learn and report on that learning; their preferred activity level during learning; their preferred form and type of information; and their preferred strategies for processing information. In this way, she argued that learning styles incorporates both the concept of cognitive styles as well as affective, social and psychological styles of responding to learning tasks and learning environments.

In an attempt to clarify the ambiguity in various aspects of the phenomena Sadler-Smith (1996, p.186) created the distinctions described below.

  • Learning style - Learning style is a distinctive and habitual manner of acquiring knowledge, skills or attitudes through study or experience. This indicates that the style is reasonably static and is the typical way an individual learner approaches learning.
  • Learning preference - Learning preference is the favoring of one particular mode of teaching over another. These preferences can vary within the same learner depending on the task and context.
  • Learning strategies - Learning strategies represent the plan of action adopted in the acquisition of knowledge, skills or attitudes through study or experience. This is the way we decide to go about a learning task.

Clearly the researchers have struggled to pinpoint both a comprehensive and functional definition of the construct of learning styles. However, not only have the semantics of a definition proved elusive, so has the development of a measurement instrument with which to effectively determine the preferred style of the individual learner.

Curry (1983) identified 21 different theoretical models incorporating the term “learning style.” Similarly, a later meta-analytic literature review by authors from the University of Newcastle upon Tyne identified 71 different theories of learning styles (Coffield, Moseley, Hall & Ecclestone, 2004).

In short, research indicates that there is broad interest and intuitive acceptance of the general concept of learning styles, but also, significant disagreement on how to best characterize and measure the paradigm. Furthermore, despite the general intuitive appeal and widespread application of various learning style theories in venues such as schools and organizations, the scientific and academic communities generally regard most instruments with skepticism, criticizing their basic psychometric properties and lack of independent validation. So, we clearly see that there are problems with this construct, particularly with regard to empirical examination.

The fundamental premise underlying the concept of individual differences in learning styles is that the differing learner preferences will result in learning being less effective in learning situations that require students to depart from their preferred or more comfortable learning strategies and styles. Some evidence suggests that the interaction among teaching styles, learning styles and the classroom environment is primary to the structure and process of learning (Anderson, 1995). However, while there is some measure of both intuitive agreement and empirical evidence that learning style affects learning effectiveness, there is also significant debate about the exact nature, validity and applicability of this relationship.

In other words, while most agree that this phenomenon of learning styles exist and matter, most cannot say how or why.

The literature on the subject is fraught with controversy and contradiction. Learning theorist Kolb (1976) posited that if one were able to diagnose the learning style of an individual, then it would seem logical to assume that matching the characteristics of instruction to that style would make the instruction more effective. However, in a later study Kolb (1984) concluded that there were potential long term benefits inherent in learning situations where there was an intentional mismatch between learning style and instructional style, on the grounds that: “The aim is to make the student self-renewing and self-directed; to focus on integrative development where the person is highly developed in each of the four learning modes; active, reflective, abstract and concrete. Here, the student is taught to experience the tension and conflict among these orientations, for it is from these tensions that creativity springs” (p. 76). This represents the popular modern concept of “stepping outside your comfort zone” as a necessary condition for growth.

Conversely, Matthews (1991) argues that: “While mismatching is appropriate for developmental reasons, students have more positive attitudes towards school and achieve more knowledge and skills when taught, counseled or advised through their natural or primary style rather than a style that is secondary or undeveloped, particularly when adjusting to a novel and new situation that creates stress such as beginning experiences in higher education” (p. 253). Clearly, there remains much debate over the effectiveness of matching learning style and instructional style.

As mentioned previously, in 2004, Coffield and colleagues identified 71 different theories of learning styles in a meta-analytic literature review. These included:

  • Curry’s Onion Model
  • Kolb’s Experiential Model
  • Honey and Mumford’s Model
  • VAK and VARK
  • Gregorc's Model
  • Dunn & Dunn Model
  • Allison & Haynes Model
  • Vermunt Model
  • Canfield Model
  • Gardner’s Multiple Intelligences
  • Myers-Briggs Type Indicator

Notice that the last two represent psychometric inventories that were not originally constructed to measure learning styles, but which have been applied to the construct.

Curry’s Onion Model

Curry (1983) developed the notion of an onion model to represent the idea of progressive layers or levels of learning. In Curry’s depiction, the inner-most layer is the cognitive personality level, which forms the foundation of thinking, represents the most stable temperament-based level. The middle layer of this construct represents the information processing realm, i.e., the strategies employed to process and assimilate information from the environment. This layer is not as fixed and thus can be influenced by the learning situation and instructional conditions. Finally, the outermost layer represents the most superficial and most adaptable level – that of instructional and environmental preferences. This context-based level may vary significantly over time and circumstance, with the clearest example being the changes in learning modalities influenced by technology.

This is a simple graphical depiction of Curry’s model:

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Curry, L. (1983) An organisation [sic] of learning style theory and constructs

Researchers Eagleton and Muller (2011) incorporated models of personality, brain hemispheric processing, and instructional/environmental preferences into the structure of the onion model to form a Model for Whole Brain Learning.

This is a diagram of the whole brain learning model:

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Eagleton, S. & Muller, A. (2011). Development of a model for whole brain learning of physiology.

Dunn & Dunn Model

One of the earliest and most widely used models of learning styles was proposed by Rita and Kenneth Dunn (1978, 1992a, 1992b, and Dunn, 1986). According to the model, learning style is comprised of five major components, referred to as stimuli – 1) environmental; 2) emotional; 3) sociological; 4) psychological and 5) physiological – which exert influence on the learning experience and thus affect the success of the learner. One of the basic principles in the Dunn and Dunn model is the premise that a portion of and individual’s potential achievement is heavily dependent on relatively fixed traits and characteristics (Dunn & Griggs, 1988). Thus, they claim that the purpose and strength of the model lies in its ability to assist in improving student attainment by facilitating the matching of instruction, environment and resources to students’ preferences.

This is a depiction of the Dunn & Dunn Model:

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Dunn, R. (2003). The Dunn and Dunn learning-style model and its theoretical cornerstone.

The Dunn and Dunn model has both staunch supporters and critical skeptics. Proponents argue that accommodating individual learning style preferences – mainly through complementary instructional and counseling interventions, environment design and resource availability – results in a significant increase in academic achievement and improved attitudes towards learning. The model has been heralded as a user-friendly construct, both with respect to the assessment phase and the practical application of results.

While some applaud its incorporation of motivational, physiological and environmental for its comprehensive consideration of the construct of learning, others criticize it as a model of preferences rather than one grounded in theories of learning (Coffield, Moseley, Hall & Ecclestone, 2004). As previously mentioned, disagreement exists as to whether matching teaching styles with the learning styles or instead, developing broader comfort zones through the use of alternative (i.e., non-matched) teaching styles is preferable. Finally, the model is perhaps most strongly criticized for conducting internal, non-independent research and making excessive claims of relevance and effectiveness (Coffield, Moseley, Hall & Ecclestone, 2004; Dunn, Beaudry & Klavas, 1989).

Gregorc Model

Gregorc specifically defined a learning style as “consisting of distinctive behaviors which serve as indicators of how a person learns from and adapts to his environment” (1979, p. 29). Thus, his instrument, the Gregorc Style Delineator (GSD) measures the preferred ways of receiving and expressing information – concrete sequential (CS), abstract sequential (AS), abstract random (AR) or concrete random (CR).

This is a graphical depiction of the Gregorc Model:

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Gregorc, A. F. (1979). Learning styles: Differences which the profession must address.

Gregorc argued that student performance diminishes when there is misalignment between their learning styles (also called adaptive abilities) and the demands of the teaching methods and delivery styles (Greogrc, 1982). While some studies have indicated a moderate level of correlation for criterion validity, independent studies raise doubts about other psychometrics aspects, especially reliability and construct validity and most reviewers consider it so seriously theoretically and methodologically flawed as to be unsuitable for individual assessment (Coffield, Moseley, Hall & Ecclestone, 2004).

The Kolb Model

Kolb (1976, 1984) posited that individuals learn and solve problems by progressing through a four-stage cycle of learning, each of which entails different processes and abilities in acquiring new information:

1) Concrete Experience (CE) – feeling; becoming fully involved in a new activity in order to understand it firsthand;

2) Reflective Observation (RO) – watching; viewing experiences impartially or from many different perspectives;

3) Abstract Concepts (AC) – thinking; creating concepts that integrate observations and experiences into theories and developing generalized explanations or hypotheses;

4) Active Experimentation (AE) – doing; using theories to make decisions and solve problems and testing and elaborating generalizations in different situations.

This is a graphical depiction of the Kolb model:

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Kolb D. (1984). Experiential learning: experience as the source of learning and development

The Kolb Learning Style Inventory (1984) differs from other tests of learning style and personality used in education fundamentally because it is based on a comprehensive theory of learning and development. - the Experiential Learning Theory (ELT). ELT attempts to develop a holistic model of the experiential learning process and a multi-linear model of adult development

Kolb’s model was one of the first to be firmly and clearly grounded in an explicit model of learning. Additionally, it proposes to provide not only assessment of learning styles, but also a framework for the design and development of effective learning experiences. However, research on its pedagogical application have been contradictory and inconclusive.

VAK & VARK Models

Walter Burke Barbe and colleagues (1979) proposed three learning modalities - identified by the acronym VAK:

• Visualizing modality

• Auditory modality

• Kinesthetic modality

They pointed out that learning modality strengths are different from preferences; a person's self-reported modality preference may not correspond to their empirically measured modality strength. This disconnect between strengths and preferences was confirmed by a subsequent study.

Neil Fleming's VARK model (Fleming & Mills, 1992) expanded upon earlier notions of sensory modalities such as the VAK model of Barbe and colleagues

• Visual learning

• Auditory learning

• Reading/Writing learning

• Kinesthetic learning

Students can use the model to identify their preferred learning style and, it is claimed, maximize their learning by focusing on the mode that benefits them the most. 

This is a graphical depiction of the VARK model:

https://img.particlenews.com/image.php?url=3BY0Zs_0atnewon00
Fleming, N.D. & Mills, C. (1992). Not Another Inventory, Rather a Catalyst for Reflection.

Intuitive and Popular, But Highly Criticized

The learning-styles theory acquired great popularity within the education field and was applied in settings from kindergarten to graduate school. The concept of learning styles evolved into a thriving set of commercial activities that is largely centered around the publishing and selling of tests and measurements to help teachers assess individual learning styles. In addition, many organizations offer professional development workshops for teachers and educators built around the concept of designing learning experiences based on learning styles.

The assessment measures developed according to the Dunn and Dunn Model are particularly popular and highly commercialized.

Claims on their website are overstated and undocumented, such as:

It works! – The Dunn & Dunn Model is one of the most extensively tested learning-styles systems to date backed by 40+ years of quantitative, qualitative and experiential research, with over 850 studies conducted by 135 universities worldwide. The learning-style model has worked repeatedly for children and adults of all ages.

You will see immediate improvement – When matching teaching style to students' predominant learning strengths, joy for learning and improved behavior and test scores become immediately apparent.

It is inexpensive – For only $5 per person (the approximate cost of a designer coffee that has an effect for hours), one gains insight into a lifetime of benefits.

• One of the most well-researched learning style models in the world. With more than 30 years of research work with over 850 studies conducted in more than 135 institutions, it has a solid research base, along with ongoing studies of best practices in learning centers around the world.

• Every piece of research has consistently testified that when anyone is taught according to this model, their academic achievement improves, as does their attitude, self-discipline and outlook towards the future.

In contrast to the sensationalized Dunn & Dunn commercial website, the VARK site presents a more balanced picture. While the site offers products such as books and training resources for sale, it provides the questionnaire, interpretation of results and preference strategies free of charge. The site offers both disclaimers and statistics about the measure, including,

• The results indicate a ‘rule of thumb’ and should not be rigidly applied. Rather, it is designed to initiate discussion about, and reflection upon, learning preferences.

• It is not expected that any one preference will be dominant or that all participants will be multimodal.

• The results indicate preferences not strengths.

• Learning is a complex neurological experience and we cannot detect (yet) why and how learning occurs or to what it can be attributed.

This supports the empirical findings that while learners do seem to have a preferred modality, that preference does not strongly correlate with performance or effectiveness measures.

So, in light of the overwhelming popularity of both the theory and its application, which contradicts the empirical evidence, the question becomes, is the concept of learning styles a viable educational construct, or merely a widely held neuromyth?

Today, the overarching concepts related to learning styles are the subject of continued controversy and debate. Proponents argue that the effective application of style preferences can enhance learning, engagement and motivation. Conversely, critics claim these constructions are at best unsupported and ineffective, and at worst a potentially dangerous practice.

Critics call the continued belief and popularity of Learning Styles a “Neuromyth” i.e., an incorrect assertion about how the brain is involved in learning. They cite the work of cognitive psychologist Dr. Harold Pashler and colleagues (Pashler, McDaniel, Rohrer, & Bjork, 2008) who reviewed decades of research and found no compelling evidence that matching instruction to preferred styles enhanced learning.

Specifically, they noted:

• Our review of the literature disclosed ample evidence that children and adults will, if asked, express preferences about how they prefer information to be presented to them.

• There is also plentiful evidence arguing that people differ in the degree to which they have some fairly specific aptitudes for different kinds of thinking and for processing different types of information.

• However, we found virtually no evidence for the interaction pattern mentioned above, which was judged to be a precondition for validating the educational applications of learning styles.

They therefore argued that although the literature on learning styles is extensive, very few studies used an experimental methodology capable of testing the validity of learning styles applied to education. Moreover, of those that did use an appropriate method, several found results that flatly contradict the popular “meshing” hypothesis. Therefore, they concluded that, at present, there is no adequate evidence base to justify incorporating learning styles assessments into general educational practice (Pashler, McDaniel, Rohrer, & Bjork, 2008).

They acknowledged the widespread anecdotal evidence and testimonials, noting,

• It is undoubtedly the case that a particular student will sometimes benefit from having a particular kind of course content presented in one way versus another.

• However, the contrast between the enormous popularity of the learning-styles approach within education and the lack of credible evidence for its utility is, in our opinion, striking and disturbing.

• If classification of students’ learning styles has practical utility, it remains to be consistently demonstrated.

Based on these findings, critics contend that teachers who claim to see universal and significant positive effects are suffering from “Confirmation Bias.” Those who strongly believe that matching instruction to learning styles is necessary are more inclined to notice situations that seem to confirm that, and disregard or downplay instances that are at odds with the myth. They argue that the brain works as an integrated whole, not discrete, closed off compartments.

So, in conclusion, we are left with strong opposing opinions.

Proponents recommend that teachers assess the learning styles of their students and adapt their classroom methods to best fit each student's learning style (Pritchard, 2014). Although there is ample evidence that individuals express preferences for how they prefer to receive information, few studies have found any validity in using learning styles in education (Pashler, McDaniel, Rohrer & Bjork, 2008). There are substantial criticisms of learning-styles approaches from scientists who have reviewed extensive bodies of research (Coffield, Moseley, Hall & Ecclestone, 2004; Pashler, McDaniel, Rohrer & Bjork, 2008). A more recent 2015 peer reviewed article concluded: "Learning styles theories have not panned out, and it is our responsibility to ensure that students know that.” (Willingham, Hughes & Dobolyi, 2015, p. 269). 

Critics contend that there is no consistent evidence that identifying an individual student's learning style, and teaching for specific learning styles, produces better student outcomes (Pashler, McDaniel, Rohrer & Bjork, 2008; Vasquez, 2009). Conversely, they argue that there is evidence of empirical and pedagogical problems related to forcing learning tasks to "correspond to differences in a one-to-one fashion” (Klein, 2003). Well-designed studies contradict the widespread "meshing hypothesis" that a student will learn best if taught in a method deemed appropriate for the student's learning style (Pashler, McDaniel, Rohrer & Bjork, 2008).

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Photo by note thanun on Unsplash

So what does all this mean, in practice?

Far from being an irrelevant concept, the differences among learning styles remains an important consideration. As the amount of information and the skills necessary to process and apply that information expand at rates never before imagined, effective learning strategies are of paramount importance. Additionally, as learning environments have become more diverse and inclusive, especially with respect to the varying modes of delivery facilitated by technology, the impact of different learning styles may be considered even more relevant and critical to success. Now, more than ever, we have the means to individually tailor learning to produce the most effective results, if, in fact, tailoring the style of delivery is meaningful.

For every harsh critic of the various learning style paradigms, there is also a staunch supporter arguing for the effective utilization of the constructs in the learning environment. This leaves one with only one logical, yet relatively unsatisfying, conclusion – much more research is necessary to unravel the complexities of human learning.

Conversely, perhaps we are trying too hard to find a concrete, universal comprehensive model, for the still mysterious workings of the human mind and the process of learning. Perhaps the answer is as simple, and as timeless, as universal and as individualistic, as the inscription at Delphi – γνῶθι σεαυτόν - know thyself.

References

Anderson, J.A. (1995). Toward a framework for matching teaching and learning styles for diverse populations. In R.R. Sims and S.J. Sims (Eds.), The importance of learning styles: Understanding the implications for learning, course design, and education (pp. 69-78). Westport, CT: Greenwood Press.

Barbe, W.B., Swassing, R.H. & Milone, M.N. (1979). Teaching through modality strengths: concepts and practices. Columbus, OH: Zaner-Bloser.

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

Coffield, F. C., Moseley, D. V. M., Hall, E., & Ecclestone, K. (2004b). Should we be using Learning Styles? What research has to say to practice. London, UK: Learning and Skills Research Centre.

Curry, L. (1983) An organisation [sic] of learning style theory and constructs, In: L. Curry (Ed) Learning Style in Continuing Education. Montreal, Canada: Dalhousie University.

Dunn, R. (1987). Research on instructional environments: Implications for student achievement and attitudes. Professional School Psychology, 2, 43-52.

Dunn, R. (2003). The Dunn and Dunn learning-style model and its theoretical cornerstone. In R. Dunn & S. A. Griggs (Eds.), Synthesis of the Dunn and Dunn learning-style model research: Who, what, when, where, and so what? (pp. 1- 6). NY: St. John's University's Center for the Study of Learning and Teaching Styles.

Dunn, R., & Griggs, S.A. (1988). High school dropouts: Do they learn differently from those who remain in school. The Principal, 34, 1-8.

Dunn, R., Beaudry, J. S. & Klavas, A. (1989). Survey of research on learning styles. Educational Leadership, 47(7), 50-58.

Dunn, R., Dunn, K., & Price, G. E. (1984). Learning style inventory. Lawrence, KS: Price Systems.

Eagleton, S. & Muller, A. (2011). Development of a model for whole brain learning of physiology. Advances in Physiological Education 35:421-426, 2011. doi:10.1152/advan.00007.2011

Fleming, N.D. & Mills, C. (1992). Not Another Inventory, Rather a Catalyst for Reflection. To Improve the Academy, 11, 137-155.

Gregorc, A. F. (1979). Learning styles: Differences which the profession must address. Reading through content, 29-34.

Gregorc, A. (1982). Gregorc Style Delineator. Columbia, CT: Gregorc Associates, Inc.

Gregory, R. J., (2004). Psychological testing: History, principles and Applications, 4e. New York, NY: Pearson.

Keefe, J. W. (1979). Learning style: An overview. In NASSP's Student learning styles: Diagnosing and proscribing programs (pp. 1-17). Reston, VA.National Association of Secondary School Principals.

Keefe, J.W. (1987). Learning style theory and practice. Reston, VA: National Association of Secondary School Principals.

Keefe, J. W. & Ferrell, B. G. (1990) Developing a defensible learning style paradigm. Educational Leadership, 48 (2) pp. 57-61.

Klein, P. D. (January 2003). Rethinking the multiplicity of cognitive resources and curricular representations: alternatives to 'learning styles' and 'multiple intelligences’. Journal of Curriculum Studies, 35 (1): 45–81. doi:10.1080/00220270210141891.

Kolb, D. A. (1976). The Learning Style Inventory: Technical Manual. Boston, MA: McBer.

Kolb D. (1984). Experiential learning: experience as the source of learning and development. Englewood Cliffs, New Jersey: Prentice Hall.

Kolb D. (1999). The Kolb Learning Style Inventory, Version 3. Boston, MA: Hay Group.

MacKeracher, D. (2004). Making sense of adult learning. Toronto: Culture Concepts.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9(3), 105–119. https://doi.org/10.1111/j.1539-6053.2009.01038.x

Pritchard, A. (2014). Ways of Learning: Learning theories and learning styles in the classroom, 3e. New York, NY: Routledge.

Sadler-Smith, E. (1996). Learning Styles: a holistic approach. Journal of European Industrial Training, 20: 29-36.

Stewart, K. L., & Felicetti, L. A. (1992). Learning styles of marketing majors. Educational Research Quarterly, 15(2), 15-23.

Vasquez, Kris (2009). Learning styles as self-fulfilling prophecies. In Gurung, Regan A. R.; Prieto, Loreto R. (eds.). Getting culture: incorporating diversity across the curriculum. Sterling, VA: Stylus. pp. 53-63.  

Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The Scientific Status of Learning Styles Theories. Teaching of Psychology, 42(3), 266–271. https://doi.org/10.1177/0098628315589505

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