meshing hypothesis learning styles

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Learning Styles: Concepts and Evidence

Affiliations.

1 University of California, San Diego [email protected].
2 Washington University in St. Louis.
3 University of South Florida.
4 University of California, Los Angeles.
PMID: 26162104
DOI: 10.1111/j.1539-6053.2009.01038.x

The term "learning styles" refers to the concept that individuals differ in regard to what mode of instruction or study is most effective for them. Proponents of learning-style assessment contend that optimal instruction requires diagnosing individuals' learning style and tailoring instruction accordingly. Assessments of learning style typically ask people to evaluate what sort of information presentation they prefer (e.g., words versus pictures versus speech) and/or what kind of mental activity they find most engaging or congenial (e.g., analysis versus listening), although assessment instruments are extremely diverse. The most common-but not the only-hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual presentation of information). The learning-styles view has acquired great influence within the education field, and is frequently encountered at levels ranging from kindergarten to graduate school. There is a thriving industry devoted to publishing learning-styles tests and guidebooks for teachers, and many organizations offer professional development workshops for teachers and educators built around the concept of learning styles. The authors of the present review were charged with determining whether these practices are supported by scientific evidence. We concluded that any credible validation of learning-styles-based instruction requires robust documentation of a very particular type of experimental finding with several necessary criteria. First, students must be divided into groups on the basis of their learning styles, and then students from each group must be randomly assigned to receive one of multiple instructional methods. Next, students must then sit for a final test that is the same for all students. Finally, in order to demonstrate that optimal learning requires that students receive instruction tailored to their putative learning style, the experiment must reveal a specific type of interaction between learning style and instructional method: Students with one learning style achieve the best educational outcome when given an instructional method that differs from the instructional method producing the best outcome for students with a different learning style. In other words, the instructional method that proves most effective for students with one learning style is not the most effective method for students with a different learning style. 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. Although the literature on learning styles is enormous, very few studies have even 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. We conclude therefore, that at present, there is no adequate evidence base to justify incorporating learning-styles assessments into general educational practice. Thus, limited education resources would better be devoted to adopting other educational practices that have a strong evidence base, of which there are an increasing number. However, given the lack of methodologically sound studies of learning styles, it would be an error to conclude that all possible versions of learning styles have been tested and found wanting; many have simply not been tested at all. Further research on the use of learning-styles assessment in instruction may in some cases be warranted, but such research needs to be performed appropriately.

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AEE Advances in Engineering Education

A Journal of Engineering Education Applications

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Main navigation, opinion: uses, misuses, and validity of learning styles.

In the past four decades, learning styles have progressed from being an interest of a few academics to a concept that has been applied by countless teachers and researchers at all levels of education. At the same time, a number of educational and cognitive psychologists have argued vehemently against taking learning styles into account when designing instruction, basing their arguments almost entirely on a lack of demonstrated validity of the “meshing hypothesis,” which asserts that matching instruction to students’ individual learning style preferences maximizes the students’ learning. This paper describes and reviews the origins of a learning style model that has been applied extensively in engineering education and an online instrument that has been accessed by millions of users to assess students’ preferences for different approaches to instruction defined by that model. The paper goes on to show that the challenges to learning styles are mostly fallacious, since they are based on statements (including the meshing hypothesis) the challengers attribute to learning style proponents which most proponents reject. The point of learning styles is not to match instruction to individual students’ learning style preferences, but rather to teach in a manner that balances the preferences of students with different learning styles. Strategies suggested for attaining such a balance are fully compatible with both cognitive science and empirical educational research.

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The problem with learning styles: debunking the meshing hypothesis in English language teaching

Perspective Article
Published on: February 22, 2018

Cognitive science |
English as an Additional Language |
Language and literacy |
Open Access |
Professional learning |
Psychology |
Research Engagement

The notion of perceptual learning styles – that is, the idea that learners prefer to receive information either visually, auditorily or kinaesthetically – has been scrutinised by neuroscientists in recent years (Dekker et al., 2012) ; (Howard-Jones, 2014) . In particular, the ‘meshing hypothesis’ (or ‘matching hypothesis’), the idea that catering to a learner’s favoured sensory preference, or ‘learning style’, will improve learning, has been exposed as a neuromyth. Yet belief in the meshing hypothesis is still extremely widespread (Howard-Jones, 2014) , and a recent study among English language teachers in the US and Canada shows that almost 90% of the teachers surveyed are also still convinced by it (Lethaby and Harries, 2016) .

The meshing hypothesis certainly has intuitive appeal. If a learner prefers to hear information, it seems obvious that if they are given information auditorily they will learn better, and conversely that they will not learn as well if they are presented with the information as written text. The supposed benefits of catering to different learning styles Theories relating to the idea that individuals learn best in different ways and teaching should be tailored to their learning styles – these have been widely debunked by research became very influential in English language teaching (ELT) after the publication of a paper in TESOL Quarterly (Reid, 1987) . Reid ‘tested the styles’ of some 1,388 students, and suggests that both native speaking and non-native English speaking students ‘should be exposed to the concept of learning styles’, arguing that this may result in ‘greater classroom success’ (Reid, 1987) . It is concerning that assessing and accommodating learning styles in English language teaching has become accepted practice, when the evidence points to it largely being a waste of time, money and effort.

The history of the ‘meshing hypothesis’ in English language teaching

While there are several learning styles models (see Coffield et al. (Coffield et al., 2004) for details), the most commonly researched (Hattie and Yates, 2013) and best known is the Visual, Auditory and Kinaesthetic model (VAK for short), which was first proposed by Dunn and Dunn (Dunn and Dunn, 1972) . The diagnosis of a student’s learning style is usually made through a seemingly scientific questionnaire, but most of the questionnaires involve a high degree of self-report (evaluating one’s own study habits and preferences), which can be highly unreliable. Interestingly, concern with students’ individual learning styles was a relatively minor part of the Dunns’ original questionnaire, and associated learning programme; aside from determining VAK preferences, the questionnaire included sections on students’ preferred time of day for study, their dietary requirements and 18 other categories that teachers could test for (Dunn and Dunn, 1978) . It was only after VAK became such a success that the Dunns chose to focus on it, setting up the International Learning Styles Network.

Although the idea that it is effective to match teaching to preferred learning styles has existed since the creation of VAK, the term ‘meshing hypothesis’ is more recent. It seems to have first appeared in publication in the work of Pashler et al. (Pashler et al., 2008) . It is, however, a useful term to describe the central concept at the heart of the appeal of VAK learning styles. After the publication of Reid’s 1987 paper, which has been cited over a thousand times, there was no major peer-reviewed study questioning the legitimacy of the meshing hypothesis in English language teaching until a 2016 paper on neuromyths in the English language teaching journal (Lethaby and Harries, 2016) . However, many papers have been published that take the hypothesis for granted (for example, see (Hyland, 1994) and (Wong and Nunan, 2011) ), and it is still supported in much of the influential teacher training literature (for example, (Lightbown and Spada, 2013) ). It is worth considering how much effort has been spent by students and teachers carrying out VAK surveys and planning and design activities to match students’ learning styles.

Challenging the meshing hypothesis

Having considered the history of this idea, let’s examine why the hypothesis is not a helpful concept for teaching.

Pashler et al. (Pashler et al., 2008) give examples of research that suggests that learners may indeed have preferences for how they prefer to receive information, but go on to point out that ‘the existence of preferences says nothing about what these preferences might mean or imply for anything else, much less whether it is sensible for educators to take account of these preferences’ (Pashler et al., 2008) . They go on to discuss how such research would need to show that different learning methods optimise the test scores of different types of learners in order to provide credible evidence for the meshing hypothesis. In other words, self-identified ‘visual learners’ would have to show that they learned better being taught by visual means, while ‘auditory learners’ would need to show that they learned better when taught by listening, through outperforming the other type of learner on the corresponding test based on the way in which they received the information.

Research by Krätzig and Arbuthnott (Krätzig and Arbuthnott, 2006) , meanwhile, shows that there is little consistency and match between what learners consider to be their learning style and what specially designed questionnaires say, and secondly, that there is no relationship between established learning style and objective test performance. Rogowsky et al. (Rogowsky et al., 2015) explicitly sought to directly test the meshing hypothesis itself, using the design outlined by Pashler et al. (Pashler et al., 2008) , above. In this experiment, participants were first assigned as ‘auditory’ or ‘visual’ learners using standardised learning styles assessments. They were then presented with information through text or listening material, depending on their assigned style, and then tested on their learning. They were found to have no significant advantage when taught using their preferred learning style. So, the notion of VAK learning styles is problematic in that they are not consistent, measurable attributes, nor is there evidence to support the idea that teaching to preferred learning style will improve learning.

Another argument against the meshing hypothesis comes from the field of neuroscience. What we know about how the brain works does not support the idea of learners being better at learning through different sensory modalities. Different parts of the brain are specialised to receive different types of information, but the interconnection of the brain makes it impossible for learners to learn using only auditory or visual information (Dekker et al., 2012) . Despite the designation of the meshing hypothesis as a ‘neuromyth’ by leading scientists, the belief in this idea persists, and Dekker et al. have argued that introducing neuroscientific basics to teachers in initial teacher training Abbreviated to ITT, the period of academic study and time in school leading to Qualified Teacher Status (QTS) might help in this regard.

Wasted time, effort and money?

In the 30 years since Reid’s first paper in ELT, there have been developments in evidence-based teaching strategies and clear directions for teaching interventions that do have empirical support. Arbuthnott and Krätzig lament the fact that ‘the continued endorsement of learning styles theory interferes with the development of evidence-based practice in education and the wider community’ (Arbuthnott and Krätzig, 2015) . For example, Dunlosky et al. (Dunlosky et al., 2013) outline 10 classroom strategies that are supported by studies and that don’t require the financial investment that assessing and catering to perceptual learning styles does. In the face of teaching techniques that do have evidence to back their use, it is surely time to retire the meshing hypothesis, as well as the VAK learning styles concept around which it revolves.

From this issue

Issue 2: Science of Learning

Spring 2018

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Digital Commons @ USF > College of Arts and Sciences > Psychology > Faculty Publications > 1765

Psychology Faculty Publications

Learning styles: concepts and evidence.

H. Pashler Marshall D. McDaniel , Pennsylvania State University D. Rohrer R. Bjork

Document Type

Publication date, digital object identifier (doi).

https://doi.org/10.1111/j.1539-6053.2009.01038.x

The term “learning styles” refers to the concept that individuals differ in regard to what mode of instruction or study is most effective for them. Proponents of learning-style assessment contend that optimal instruction requires diagnosing individuals' learning style and tailoring instruction accordingly. Assessments of learning style typically ask people to evaluate what sort of information presentation they prefer (e.g., words versus pictures versus speech) and/or what kind of mental activity they find most engaging or congenial (e.g., analysis versus listening), although assessment instruments are extremely diverse. The most common—but not the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis , according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a “visual learner,” emphasizing visual presentation of information).

The learning-styles view has acquired great influence within the education field, and is frequently encountered at levels ranging from kindergarten to graduate school. There is a thriving industry devoted to publishing learning-styles tests and guidebooks for teachers, and many organizations offer professional development workshops for teachers and educators built around the concept of learning styles.

The authors of the present review were charged with determining whether these practices are supported by scientific evidence. We concluded that any credible validation of learning-styles-based instruction requires robust documentation of a very particular type of experimental finding with several necessary criteria. First, students must be divided into groups on the basis of their learning styles, and then students from each group must be randomly assigned to receive one of multiple instructional methods. Next, students must then sit for a final test that is the same for all students. Finally, in order to demonstrate that optimal learning requires that students receive instruction tailored to their putative learning style, the experiment must reveal a specific type of interaction between learning style and instructional method: Students with one learning style achieve the best educational outcome when given an instructional method that differs from the instructional method producing the best outcome for students with a different learning style. In other words, the instructional method that proves most effective for students with one learning style is not the most effective method for students with a different learning style.

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. Although the literature on learning styles is enormous, very few studies have even 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.

We conclude therefore, that at present, there is no adequate evidence base to justify incorporating learning-styles assessments into general educational practice. Thus, limited education resources would better be devoted to adopting other educational practices that have a strong evidence base, of which there are an increasing number. However, given the lack of methodologically sound studies of learning styles, it would be an error to conclude that all possible versions of learning styles have been tested and found wanting; many have simply not been tested at all. Further research on the use of learning-styles assessment in instruction may in some cases be warranted, but such research needs to be performed appropriately.

Was this content written or created while at USF?

Citation / publisher attribution.

Psychological Science in the Public Interest , v. 9, issue 3, 105–119.

Scholar Commons Citation

Pashler, H.; McDaniel, Marshall D.; Rohrer, D.; and Bjork, R., "Learning Styles: Concepts and Evidence" (2008). Psychology Faculty Publications . 1765. https://digitalcommons.usf.edu/psy_facpub/1765

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Posted on April 28, 2016

Learning styles: what does the research say?

Dylan Wiliam

Category: Cognitive Science

This post is the third in a periodic series exploring common misconceptions around how students learn. We first touched on these misconceptions in our September 2015 report, The Science of Learning , and will be exploring them in more depth over the next few months.

In today’s post, Dr. Dylan Wiliam explores what the research tells us about learning styles. Dylan Wiliam is Emeritus Professor of Educational Assessment at the Institute of Education, University College London. He served as dean and head of the School of Education (and later assistant principal) at King’s College London, senior research director at the Educational Testing Service in Princeton, New Jersey, and deputy director (provost) of the Institute of Education, University of London. Since 2010, he has devoted most of his time to research and teaching.

Since the beginning of Psychology as a field of study, psychologists have been categorizing people: as introverts and extroverts, in terms of their conscientiousness, their openness to experience, and so on. While many of these classification systems examine general personality, a number of classifications look specifically at the way people think—what is sometimes called their cognitive style. When solving problems, for example, some people like to focus on getting the evidence that is most likely to be relevant to the problem at hand, while others have a tendency to “think out of the box.”

More specifically still, many psychologists have moved from cognitive style—how people think—to the idea of learning style—how people learn (Adey, Fairbrother, Wiliam, Johnson, & Jones, 1999).

The basic idea is, of course, very attractive. We know that a particular piece of instruction might be effective for some students, and not for others, so it seems plausible that if the instruction was specifically designed to take into account a particular student’s preferred learning style, then it would be more effective for that student. This is what psychologists call the general learning-styles hypothesis—the idea that instruction students receive will be more (or less) effective if the instruction takes (or does not take) into account the student’s learning-style preferences.

Within education, a version of the learning-styles hypothesis, known by psychologists as the meshing hypothesis, has been of particular interest: the idea that students will learn more if they receive instruction that specifically matches their learning-style preferences. In other words, visual learners will learn better if they receive instruction that emphasizes visual ways of presenting information, and auditory learners will learn best by listening.

In their review of research on learning styles for the Association for Psychological Science, Pashler, McDaniel, Rohrer, and Bjork (2008) came to a stark conclusion: “If classification of students’ learning styles has practical utility, it remains to be demonstrated.” (p. 117)

Pashler et al pointed out that experiments designed to investigate the meshing hypothesis would have to satisfy three conditions:

Based on some assessment of their presumed learning style, learners would be allocated to two or more groups (e.g., visual, auditory and kinesthetic learners).
Learners within each of the learning-style groups would be randomly allocated to at least two different methods of instruction (e.g., visual and auditory based approaches).
All students in the study would be given the same final test of achievement.

In such experiments, the meshing hypothesis would be supported if the results showed that the learning method that optimizes test performance of one learning-style group is different than the learning method that optimizes the test performance of a second learning-style group.

In their review, Pashler et al found only one study that gave even partial support to the meshing hypothesis, and two that clearly contradicted it.

Now, the fact that there is currently no evidence that knowing students’ learning styles helps us design more effective instruction does not mean that learning styles will never be useful in the future—absence of evidence is not the same as evidence of absence. Some psychologists are no doubt likely to continue to look for new ways to look at learning styles, even though there are at least 71 different learning-style classification systems already in existence (Coffield, Moseley, Hall, & Ecclestone, 2004). However, it could be that the whole idea of learning-styles research is misguided because its basic assumption—that the purpose of instructional design is to make learning easy—may just be incorrect.

Over the last 30 years, psychologists have found that performance on a learning task is a poor predictor of long-term retention. More precisely, when learners do well on a learning task, they are likely to forget things more quickly than if they do badly on the learning task; good instruction creates “desirable difficulties” (Bjork, 1994 p. 193) for the learner. In Daniel Willingham’s memorable phrase, “memory is the residue of thought” (Willingham, 2009). By trying to match our instruction to our students’ preferred learning style, we may, in fact, be reducing learning. If students do not have to work hard to make sense of what they are learning, then they are less likely to remember it in six weeks’ time.

Attempting to synthesize such a large and complex body of research is almost certainly a fool’s errand, but it seems to me that the important “takeaway” from the research on learning styles is that teachers need to know about learning styles if only to avoid the trap of teaching in the style they believe works best for them. As long as teachers are varying their teaching style, then it is likely that all students will get some experience of being in their comfort zone and some experience of being pushed beyond it. Ultimately, we have to remember that teaching is interesting because our students are so different, but only possible because they are so similar. Of course each of our students is a unique individual, but it is extraordinary how effective well-planned group instruction can be.

Adey, P. S., Fairbrother, R. W., Wiliam, D., Johnson, B., & Jones, C. (1999). A review of research related to learning styles and strategies . London, UK: King’s College London Centre for the Advancement of Thinking.

Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 188-205). Cambridge, MA: MIT Press.

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

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

Willingham, D. T. (2009). Why don’t students like school: A cognitive scientist answers questions about how the mind works and what it means for your classroom . San Francisco, CA: Jossey-Bass.

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The Learning Styles Neuromyth Is Still Thriving in Medical Education

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The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author/s.

Learning Styles theory promises improved academic performance based on the identification of a personal, sensory preference for informational processing. This promise is not supported by evidence, and is in contrast to our current understanding of the neuroscience of learning. Despite this lack of evidence, prior research shows that that belief in the Learning Styles “neuromyth” remains high amongst educators of all levels, around the world. This perspective article is a follow up on prior research aimed at understanding why belief in the neuromyth of Learning Styles remains so high. We evaluated current research papers from the field of health professions education, to characterize the perspective that an educator would be given, should they search for evidence on Learning Styles. As in earlier research on Higher Education, we found that the use of Learning Style frameworks persist in education research for the health professions; 91% of 112 recent research papers published on Learning Styles are based upon the premise that Learning Styles are a useful approach to education. This is in sharp contrast to the fundamental principle of evidence-based practice within these professions. Thus any educator who sought out the research evidence on Learning Styles would be given a consistent but inaccurate endorsement of the value of a teaching technique that is not evidence based, possibly then propagating the belief in Learning Styles. Here we offer perspectives from both research and student about this apparent mismatch between educational practice and clinical practice, along with recommendations and considerations for the future.

Introduction

In educational theory, an individual’s Learning Style is normally identified via a questionnaire which asks learners about their preferences for the way they learn, often using terms and theories that give the impression of being derived from the neuroscience of cognition ( Coffield et al., 2004 ). Up to 70 different instruments are used in this way ( Coffield et al., 2004 ). Amongst the most common are the VARK (Visual, Auditory, Read/Write, Kinesthetic) classification, along with Kolb’s Learning Styles Inventory and a similar system developed by Honey and Mumford ( Newton, 2015 ). Upon identification of a preferred style, one interpretation of the theory is then that learners will achieve more if they are taught, and study, using their preferred style. This hypothesis, known as the Meshing or Matching hypothesis ( Pashler et al., 2008 ) has been tested repeatedly and shown not to result in improved learning ( Krätzig and Arbuthnott, 2006 ; Massa and Mayer, 2006 ; Pashler et al., 2008 ; Papanagnou et al., 2016 ; Aslaksen and Lorås, 2019 ; Rogowsky et al., 2020 ), and the reliability of the underlying preferences is often weak ( Coffield et al., 2004 ). This misapplication of the neuroscience of learning to education has led to Learning Styles being portrayed as a “neuromyth” ( Dekker et al., 2012 ). Belief in neuromyths has been extensively studied. Findings from our recent systematic review suggested that ∼89% of educators believe that matching instruction to Learning Styles will result in improved instruction, although there some methodological concerns about the studies reviewed ( Newton and Salvi, 2020 ).

There is much we do know about the neuroscience of learning that could and should be applied to medical education. We know that human working memory is very limited, and that this represents a bottleneck for learning which can be managed via the techniques used in Cognitive Load Theory ( Young et al., 2014 ). We know that the use of practice tests and other strategies that promote retrieval from long-term memory are very effective when studying clinically related topics ( Dobson et al., 2017 , 2018 ) and their use is associated with improved performance on clinical licensing exams ( Deng et al., 2015 ). Unfortunately there is often a disconnect between good research evidence, policy and practice in Higher Education ( Newton et al., 2020 ), and in particular, a gap between the neuroscience of learning, and educational practice ( Howard-Jones, 2014 ).

Healthcare is a field where evidence-based practice is the gold standard ( Sackett et al., 1996 ). It would seem reasonable to assume that the teaching of clinical practice would be held to a similar standard. However, a recent survey of educators showed that the most widely used teaching technique, by far, was based upon Learning Styles ( Piza et al., 2019 ).

Thus the concept of Learning Styles appears to be an appealing one, perhaps in part due to its perceived focus on the student as an individual, even though individuals end up being lumped into 3–4 “styles.” However, healthcare training is complex. There are multiple avenues of learning required: physical dexterity, for clinical examinations and procedures; a broad understanding of multiple sciences, to be easily recalled and applied to understand complex, highly specified subjects; retention and recall of minute details of investigations and pathologies; and finally, the communication, research, compassion, empathy and diplomacy skills required for patient care. This list is by no means exhaustive. However, it does highlight one of the obvious limitations with Learning Styles theory; the mastery of these topics requires multiple sensory domains. A student who is diagnosed as an auditory learner and then tries to master dermatology using podcasts is unlikely to succeed.

One potential explanation for the persistent belief in Learning Styles is that the evidence base is itself dominated by papers which mistakenly endorse the approach, and so an educator who seeks out the “evidence” for the use of Learning Styles is given a misleading perspective. Testing this hypothesis was the basis for some of our earlier work in Higher Education ( Newton, 2015 ), where 89% of research papers identified, about Learning Styles, in 2013–2015, mistakenly endorsed their use.

Here we repeat and extend that 2015 study, with a particular focus healthcare education. We also offer the perspective of both education research, and medical student, considering the impact of our findings on the field healthcare education as a whole.

We followed methods used in an earlier study about Higher Education ( Newton, 2015 ). Thus our basic research question was to characterize the picture that a Health Professions Educator would encounter were they to search the education research literature for papers about Learning Styles. As in the previous study, the inclusion criteria and analysis questions were initially applied to the abstract. If they could not be answered from the abstract, then the full text was consulted. Full text was only assessed where freely available via PubMed Central, ERIC or Google Scholar; if a subscription or payment was required, then the result was not included because access to them would vary considerably between individual health professions educators.

Two major databases were used to identify research papers; PubMed, a database focused on biomedical and life sciences, and Education Resources Information Centre (ERIC), focused on education research and information.

The term “learning styles” was the only search term used for both databases. The search was undertaken in September 2020.

Inclusion Criteria

1. Published in the English language.
2. Published after July 2015, so as to avoid overlap with the previous study.
3. Study population from healthcare professions, e.g., medical students or qualified professionals. This included disciplines such as anatomy, pharmacy, dental, and veterinary. Review papers about health professions education were included.
4. Paper included reference, within the text of the paper, to a defined Learning Styles instrument, as listed in Coffield et al. (2004) , or obviously derived from one of these instruments (e.g., the “Paragon Learning Styles Instrument” derived from the Myers-Briggs Type Indicator; Yielder et al., 2021 ). We did not include papers that were about “styles of learning” or other forms of personalized learning.
(a) Did the study begin with positive intent? Would a health professions educator be more likely than not to conclude that a premise of the study was that the use of a learning styles instrument was a useful educational approach. This could be explicit or implicit.
(b) Did the study end with a positive view of learning styles? Would a health professions educator be more likely than not to conclude, having read the study, that the use of a learning styles instrument was a useful educational approach. This could be explicit or implicit. Thus studies which tested (for example) a relationship between academic achievement and Learning Styles, and found no relationship, but then advocated for further research on the topic, would be considered to have a positive outcome.
(c) Did the study test the “matching hypothesis”? The matching (or meshing) hypothesis states that matching instructional activities to a supposed Learning Style will improve outcomes for individual students. This has been tested repeatedly and been shown not to work as cited earlier. Here we determined whether any studies also tested the matching hypothesis, and if so whether the results contradicted the established findings cited above that matching does not result in improved educational outcomes.

One important difference between the present study and the 2015 study was that included studies did not have to be explicitly about Learning Styles, just that the study had to name a specific Learning Styles instrument from Coffield et al. (2004) . This change was made to test the research question more fully; a paper which endorses and encourages (or not) the use of Learning Styles will still perpetuate the myth even if it is not specifically about Learning Styles, for example papers which are testing an educational intervention and ask participants to complete a Learning Styles questionnaire as part of the evaluation.

We also identified the specific study population, country of origin and Learning Style framework used. All data were extracted by a minimum of two assessors. Any disagreement was resolved through discussion.

The initial search returned 337 results. After eliminating duplicates and studies that were included in Newton (2015) , 308 results remained. Of these, 112 met the inclusion criteria for analysis. Of note was that only 10 papers were excluded for being behind a Paywall, suggesting that the bulk of the Learning Styles literature is freely available and thus there would be little incentive for a casual reader to pursue paywalled research.

Positive Intent

109/112 (97%) of the papers started with a positive intent toward Learning Styles, i.e., a health professions educator reading the paper would, on balance, conclude that the authors initiated the study with a view that to use a Learning Styles instrument was a useful thing to do.

Positive Outcome

102/112 (91%) of the papers concluded with a positive intent toward Learning Styles, i.e., a health professions educator would, on balance having read the paper, conclude that to use a Learning Styles instrument was a useful thing to do.

Did the Study Test, and If So Contradict, the Meshing Hypothesis?

Only one study ( Papanagnou et al., 2016 ) tested the Meshing Hypothesis using a recognized Learning Styles instrument. This study found no evidence to support the Meshing Hypothesis.

The most common Learning Styles instruments were the VARK system or variants thereof (e.g., VAK) (40/112, 36% of papers) and Kolb Learning Styles Inventory (35/112, 31%). Students were the most common study population, in particular Medical (36/112, 32%) and Nursing (17/112, 15%) students. The papers were from all over the world, but the United States was the most common study site (26/112, 23%).

Discussion—Student Perspective (HNL)

As a medical student, the attraction of learning style frameworks are abundantly clear. Whilst my voice may at times appear discerning, I have personally—and multiple times—resorted to varying learning style quizzes and frameworks, seeking illumination and higher decile rankings in the form of colorful infographics… Ones often paired with promises of maps to academic success being a paywall of “only $70!” away.

Whilst amusing to reflect on, the reality of such instances is that they are borne of anxiety; paired, more often than not, with an uncomfortable need for academic validation which learning styles can offer in easy abundance. The personal preference for not wanting to run on a treadmill whilst reading from a textbook suddenly becomes proof of not being a “kinesthetic learner”; active listening becomes an auditory learning style. Clouded judgment at the hands of stress, anxiety and an overwhelming study load are waived away by the promise of a definitive answer, one that we, as medical and healthcare students, are taught to seek. In a field where such a vast body of information is required to be approached, digested and mentally filed at breakneck speed, such personalized, definitive answers may easily appear as a welcome relief.

The notion that such an innate aspect of the approach to clinical teaching is poorly evidenced is shocking, even bordering the hurtful and alarming. This is particularly true within a profession taught to rely so heavily on peer-reviewed evidence and learning.

Establishing the extent of this myth and responding accordingly is vital not only to medical and healthcare students’ wellbeing, but also the future of careers—including teaching—of many. To consider that the entire basis of our education is not as thoroughly examined as the curriculum itself, feels like a failure; and in a world of increasing fake news and hostility toward scientific evidence, seems irresponsible to perpetuate.

General Discussion

Our findings demonstrate that an educator who was interested in understanding the evidence base for Learning Styles in Health Professions Education, and thus searched for relevant research literature, would be presented with a very misleading picture with 91% of papers presenting a positive view of the use of Learning Styles instruments.

This picture is compounded by studies in respectable journals that appeared to use experimental designs, finding significant results, but without directly testing the matching hypothesis. For example, Micheel et al. (2017) undertook a trial to test the effect of modifying an existing learning resource into multiple revised versions which were designed to accommodate preferred Learning Styles. A control group using the existing, text-based learning resource. The group that utilized a version of the resource that matched their preferred learning style did significantly better on a knowledge post-test ( P = 0.004). Using the data presented by the authors we were able to calculate a standardized effect size which suggested that the effect was very modest ( d = 0.06). These sorts of findings are nevertheless persuasive; this was an experimental study, conducted using a trial methodology, showing a significant improvement when participants engage with resources that match their preferred Learning Style? However, these data fail the key criteria articulated by Pashler and co; the control resource is all text. The versions used in the intervention are multimedia presentations that appear to be much more engaging; thus any improvement seen may simply be because the revised versions are just better educational resources, independent of Learning Style. Similar findings were published by Anbarasi et al. (2015) who compared the effects of a variety of different instructional materials, matched to VAK learning styles, with a “traditional group” “taught with the routine didactic lecture using PowerPoint images without pictures, videos, or animations.”

The picture is further complicated by the apparent similarities between the terminology of Learning Styles, and the language of educational neuroscience and psychology. For example, one study proposed to test the meshing hypothesis ( Lehmann and Seufert, 2020 ) but did not use a Learning Styles instrument as defined by Coffield et al. (2004) However, they did test learners “preferences for auditive versus visual stimuli” using a 12-item questionnaire previously published in the German language. They then randomly assigned participants to receive visual (text) or auditory versions of a 661-word text passage, followed by measures of comprehension and cognitive load. Visual learners appeared to perform better with visual (text) material with no effect in the auditive/auditive learners. The sample here was small ( N = 19 for auditive, 23 for visual, then split into two groups for analysis) and there is a risk of both type-1 and type-2 error (e.g., the auditory material appears to be more difficult to comprehend for all learners according to the cognitive load scores). Differential preference for, specifically, visual versus verbal content does seem to be supported by evidence, in a literature that refers specifically to cognitive “style” ( Mayer and Massa, 2003 ), although it does not appear to impact learning achievement ( Massa and Mayer, 2006 ).

However, the vast majority of studies did not actually test the efficacy of Learning Styles, they were instead based upon an assumption that the use of Learning Styles was a good thing. For example, a common approach was for researchers to use a Learning Styles instrument with a particular group of students studying a particular topic, and then make recommendations for changes to the teaching of that topic based upon the results.

What could, or should, be done about the persistence of this neuromyth, in a discipline for which evidence-based practice is the gold standard? A recent survey study of health professions educators found that Learning Styles was the most popular teaching technique, even when compared to aforementioned techniques which are obviously effective ( Piza et al., 2019 ). The fact that future doctors, nurses, pharmacists etc. are still being taught using ineffective methods, supported by misleading research, is alarming. Telling educators that the techniques they believe in are ineffective is a painful message, and one that can backfire ( Newton and Miah, 2017 ), but Learning Styles show no sign of going away. The very high belief in Learning Styles demonstrated by educators around the world does not appear to be declining over time ( Newton and Salvi, 2020 ). The bias of research toward Learning Styles is similarly not declining; in 2015 we found that 89% of papers about Learning Styles presented a misleading positive view, and most of those were from medical education ( Newton, 2015 ). Here 5 years later it is 91%, with dozens of papers still being published every year.

If you have got this far in reading our Perspective paper then it is likely that you also care about this, and care about teaching generally. Spread the word. Advocate for teacher development sessions where fellow educators are taught about effective approaches to Learning and Teaching ( Newton et al., 2020 ), and maybe gently, constructively, kindly, steer your peers in a different direction when they propose the use of Learning Styles.

Data Availability Statement

Author contributions.

PN designed the study, extracted data from every manuscript, analyzed the data, and wrote the manuscript. HN-L extracted data from every manuscript and wrote initial draft of the manuscript. GS undertook database searches and undertook pilot data analysis. AS undertook pilot data analysis. All authors reviewed the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum.2021.708540/full#supplementary-material

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The truth about learning styles – Myth AND Fact?

Aditya Shukla | September 29, 2023 August 11, 2023 | Disclaimer: Links to some products earn us a commission

Home » Learning » The truth about learning styles – Myth AND Fact?

Some people like reading content. Some people like watching videos. Some people like listening to audio podcasts. For decades, this observation has sustained a psychological myth; I examine how much of it is a myth.

So… if you like one sensory format, it must mean you have a unique preference, right? Yes. And if you prefer it, you will grasp the content in your preferred format better, right? While you might say “yes,” research says otherwise. We must differentiate between Judgments of Learning and Proof of Learning to find the real facts hidden within the fiction.

Learning styles – the concept

The meshing hypothesis – proof it’s a myth, why the myth became immortal, for teachers, for students.

A common notion is that people are auditory, visual, or kinesthetic learners – the 3 modes of learning are called “learning styles.” Many students believe they are auditory learners – better learning through talking or audiobooks, or visual learners – better learning through videos and text, or kinesthetic learners – better learning through experiences or play.

The most popular version of this is called VARK, which categorizes people as visual, aural, read/write, and kinesthetic learners. Charles C. Bonwell and Neil Fleming spearheaded the idea in the early 1990s and created the VARK system, quite successfully. But let’s look deeper.

The VARK idea is intuitive for many, but it doesn’t mean they learn better through their preferred learning style. They feel they learn better because it’s their preferred format, so it influences something called “Judgments of learning.” That differs from “learning,” which I prefer to call “Proof of learning.”

You might be wondering if there is any real difference between the 2. Judgments of learning are based on emotions. And learning is based on some proof that you have acquired or implemented some knowledge.

In everyday conversation, the idea of learning styles is simple – if you like videos, watch videos. If you like reading, read. If you like hands-on experience, get hands-on experience. But, education, EdTech companies, and many students and teachers take it too far by prescribing students content in their preferred sensory format. This creates the illusion of improving learning but just improves judgments of learning.

Experimental psychology has tested this for 3 decades – does matching your preferred learning style to content in that style help? It’s so popular that it has a name – the meshing hypothesis.

The meshing hypothesis [1] , which states that auditory learners learn better through auditory content or visual learners learn better through visual content , is not supported by evidence. And by extension, tailoring educational instruction to match a learner’s learning style is largely a wasted effort.

In the study linked above, college-educated participants classified as auditory or visual learners based on a standard learning styles test were randomly given an e-book or audio-book style non-fiction content to study. So, 4 groups were formed: auditory learners who got an e-book, auditory learners who got an audiobook, visual learners who got an e-book, and visual learners who got an audiobook. Their comprehension was tested immediately and 2 weeks later. As expected – no group showed any statistically significant difference in their performance. They all performed equally well immediately and also 2 weeks later, although the performance dropped roughly 10% for all groups when checked 2 weeks later. Matching the learning style to the mode of instruction made no difference to anything. They did not perform at the score “ceiling,” nor was the test too difficult – all 4 groups averaged around 30 out of 48 points on the test.

Research shows learning styles do not have a meaningful impact on learning. According to many studies, the concept of learning styles is an invalid way [2] to describe how most people learn, how most people prefer to learn, and how effective or persuasive the learning material is. While students have their preferred formats for learning [3] , their preference does not affect how effective the learning material is. The most accepted explanation for this is that students’ beliefs about their learning style [4] affect their “judgments of learning” more than the actual objective learning. Judgments of learning (feeling good or bad about the quality of learning) affect confidence, which could influence test scores.

Frank Coffield, who authored a 182-page report on learning styles [5] , says researchers have forever studied learning orientations as dichotomies – auditory vs. visual, abstract vs. concrete learners, deep processors vs. surface learners, etc. 30 such dichotomies have been found in the research. So, at the very least, 2 30 combinations of those dichotomies can apply to every learning, which is about 1 billion different combinations – aka 1 billion “learning styles.” If 1 billion learning styles exist, that categorization is meaningless.

Judgment of learning (JoL) is quite important in the broad sense. JoL is a metacognitive process – it is literally evaluating how well we have learned using feelings about the learning experience. We tend to conclude – if it feels like real learning, it must be real learning. 5 experiments studied the effect of JoLs on reading comprehension [6] and found that a positive JoL does not enhance comprehension by default. But if students are asked to make JoL based on remembering what they have learned, there is a direct improvement in their score. Technically, this is a benefit coming from “ retrieval practice ” – attempting to remember something as proof of learning. So by passing a JoL by actually remembering, JoL becomes PoL – Proof of Learning.

Positive JoLs improve learning motivation [7] , confidence, and eventual scores. It also reduces anxiety. But having too positive a JoL when academic skill is very high can also turn into overconfidence that later harms test performance. For highly competent students, who also have a very positive JoL, their goals should ideally reflect mastering a topic and pushing specific boundaries of learning to NOT lose to overconfidence.

There are 3 additional reasons apart from judgments of learning that explain why we are still obsessed with learning styles. First, our analysis of the world depends on our decision-making errors and judgment errors. Daniel Kahneman won a Nobel prize for showing this mathematically. He and his colleague Amos Tversky describe something called the representativeness heuristic . It says we tend to believe some things belong together better because one thing represents a core component of another thing. The logic of thinking someone good at science should be a scientist and someone good at writing should take arts is the representativeness heuristic at play.

Since we have limited senses through which we consume content, we tend to apply the representativeness heuristic to it and believe matching the sense to the content format should make sense.

Second, a far simpler secondary reason is – we love organizing information and finding patterns. It’s probably the only way we assign meaning to something, and it gives us a sense of control over that information. Because the idea of learning is so complex and vast, learning styles have become an elegant (but flawed) way to describe a whole educational system in a simple pattern.

And third, if it is repeated a lot, it feels true. The aptly named – illusory truth effect [8] . A technique used in building narratives, gaslighting, manipulation, propaganda, etc. If something is repeated over and over again for decades, we assume it’s true. The explanation researchers offer is that familiar ideas are processed easily, and ease of processing is equated to truthfulness.

So categorizing people with their learning style now meets 4 criteria for a “sticky” learning theory:

It creates judgments of learning (essentially a feeling).
It uses the representativeness heuristic (it feels correct).
It reduces ambiguity in a complex concept called “learning”.
Repeating it makes it feel true.

Considering these 4 problems, we see evidence of companies thriving on the concept, educators swearing by it, young intelligent learners “overusing” their introspection with a confirmation bias, etc., making the myth stick around in society.

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If it feels like it works, it must be true right? It’s not that simple!

The meshing hypothesis – matching learning style to content formats – may not help students in actual learning. But a holistic sense of learning requires proof of learning and the feeling of learning. Emotions play a role and having a likeable format or preferred format does affect the motivation to learn. So, while learning styles are more of an illusion and not worthy of being a firm theory of learning, it is valuable in some significant but minor sense – for the feeling it creates while learning.

Resources can be better spent on teaching students with fun and engagement so they get a positive judgment of learning, instead of spending on learning styles custom content and apps. Fun, sensory engagement, liveliness, and curiosity improve learning by default , and that makes students’ brains welcome new information more easily.

Action: Use a brain-based system that covers everything by aligning with how the brain works and where individual differences emerge from, instead of crudely classifying students.

Learn in any way you like, but don’t limit yourself to beliefs like you must learn only with your learning style. That would be self-sabotage. Combination learning is far more effective. Read and Listen and Watch and Experience your learning materials.

Action: Use specific and obvious studying best practices and avoid obvious bad habits.

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Hey! Thank you for reading; hope you enjoyed the article. I run Cognition Today to paint a holistic picture of psychology. My content here is referenced and featured in NY Times, Forbes, CNET, Entrepreneur, Lifehacker, about 15 books, academic courses, and 100s of research papers.

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MINI REVIEW article

The modality-specific learning style hypothesis: a mini-review.

$\r\nKaroline Aslaksen$

1 Department of Psychology, Faculty of Social and Educational Sciences, Norwegian University of Science and Technology, Trondheim, Norway
2 Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway

The impact on learning outcome of tailoring instruction and teaching toward modality-specific learning style preferences has been researched and debated for decades. Several topical reviews have concluded that there is no evidence to support the meshing hypothesis and that it represents a persistent neuromyth in education. The concept, however, is still utilized in educational practice and favored by many academics. This mini-review presents literature, which has applied explicit and rigorous methodological criteria, in relation to the meshing hypothesis. In order to demonstrate evidence for the meshing hypothesis, studies had to screen participants for their preferred learning style, assign participants to matched or non-matched conditions, and then provide the same test to assess learning for all participants, as well as presenting statistical crossover-interaction effects. Across studies that have applied these methodological criteria, the overall effect sizes were very low and non-significant, indicating that there is still no replicable statistical evidence for enhanced learning outcome by aligning instruction to modality-specific learning styles.

Introduction

The concept of matching instructional strategies to an individual’s learning style in order to enhance learning outcome and achieve better academic success is a well-known concept among educators and the general population ( Pashler et al., 2008 ; Dekker et al., 2012 ; Howard-Jones, 2014 ). Learning styles are considered to have an impact in any learning situation regardless of content and this “refers to the concept that individuals differ in regard to what mode of instruction or study is most effective to them” ( Pashler et al., 2008 ). The term learning styles first appeared in the literature many decades ago (e.g., Thelen, 1954 ) and has been the focus of extensive research for the past three decades, especially in Western Europe and the United States ( Coffield et al., 2004 ).

Amongst a plethora of concepts and perspectives on learning styles (see Coffield et al., 2004 , for a tour de force on learning style concepts), one of the most cited and well-known learning style perspectives concerns modality-specific preferences ( Coffield et al., 2004 ; Howard-Jones, 2014 ; Cuevas, 2015 ). The overall prediction is that if individuals are given instruction in their preferred modality (visual, auditory, or kinesthetic), they will experience enhanced learning outcomes. This has been termed the meshing hypothesis ( Pashler et al., 2008 ). A related perspective that offers basically the same prediction states that people who are “verbalizers” will perform better if they are given verbal instructions and that “visualizers” will perform better if instructions are presented visually ( Massa and Mayer, 2006 ; Kollöffel, 2012 ). In either perspective, the instructional method should mesh with the preferred modality-specific learning style. The learning style concept, in general, and the meshing hypothesis, in particular, have been subjects of tremendous scrutiny in the recent years that continues to the present. Several independent authors have advanced the view that the latter represents a neuromyth , a term applied to educational applications argued to be based upon popular perspectives of brain functioning ( Geake, 2008 ; Riener and Willingham, 2010 ; Dekker et al., 2012 ; Howard-Jones, 2014 ; Newton, 2015 ; Newton and Miah, 2017 ). Typically, the evidence for neuromyths does not correspond to the findings of studies from cognitive psychology and the neurosciences, and sometimes the scientific evidence contradicts the brain-based claims ( Geake, 2008 ). In terms of the meshing hypothesis, the implicit assumption is that the learning material delivered via one sensory modality (i.e., visual, auditory, or kinesthetic) is processed in the brain independently from material delivered via other sensory modalities. However, substantial scientific evidence shows support for cross-modal processing and interconnectivity that contradicts the meshing perspective and demonstrates that input modalities in the brain are always interlinked ( Calvert et al., 2000 ).

The overall claim for improving learning by matching the mode of instruction to modality-specific learning preferences independent of both ability and content ( Riener and Willingham, 2010 ), as reflected by the meshing hypothesis, has also been scrutinized in several literature reviews. At first sight, modality-specific instruction appears to be supported by a large body of empirical literature ( Rohrer and Pashler, 2012 ). However, upon closer inspection, few of these studies have been found to have an appropriate research design ( Pashler et al., 2008 ). First, subjects need to be divided according to their preferred learning style, e.g., visual or auditory learners, based upon some sort of learning style assessment. Second, studies with an appropriate design must then randomize subjects (regardless of their assessed learning style) to receive either instruction tailored to their style or instruction tailored for other learning styles. This asserts that some subjects were presented with the “correct” kind of instruction (i.e., aligned with their preferred learning modality) and some with the “incorrect” instruction. Finally, all participants must be administered the same test to assess learning, and the results would support the efficacy of the practice of aligning instruction with modality-specific learning style if, and only if, the test scores reveal that, e.g., visual learners do better if instruction is presented visually rather than auditorily, and likewise, auditory learners do better if instruction is presented auditorily rather than visually (crossover-interaction effects; Pashler et al., 2008 ). In previous reviews, it has been stated repeatedly that there is a lack of studies that employ this rigorous design and that the few available at the time have, overall, generated no evidence to support the meshing hypothesis ( Coffield et al., 2004 ; Kozhevnikov, 2007 ; Pashler et al., 2008 ; Willingham et al., 2015 ).

The disappointing outcome of all these empirical and theoretical endeavors and efforts is that the modality-specific learning style concept is, as stated by Newton (2015) , thriving across all levels of education. This is reflected in the findings of 89% of research papers published from 2013 to 2015 and located in ERIC and PubMed databases support the application of learning styles to instructional methodology ( Newton, 2015 ). Furthermore, a survey by Dekker et al. (2012) showed that 93% of United Kingdom primary and secondary school teachers assumed that “individuals learn better when they receive information in their preferred learning style.” Later studies have revealed similar findings in other countries, K-12 teachers responding positively to statements favoring modality-specific learning styles ( Howard-Jones, 2014 ; Gleichgerrcht et al., 2015 ; Ferrero et al., 2016 ). In addition, when faculty working in higher education in the United States were given the following question: Does teaching to a student’s learning style enhance learning? , approximately two-thirds answered in the affirmative ( Dandy and Bendersky, 2014 ). At the institutional level, Meyer and Murrell (2014) found that, across 39 educational institutions in the United States, more than 70% taught “learning style theory” as a topic in teacher education.

A recent study showed a downward trend for the general belief in learning styles among academics working in higher education in the United Kingdom ( n = 114), although 58% still report believing in the concept and about a third report using learning styles actively in their work ( Newton and Miah, 2017 ). Thus, there appears to be widespread acceptance among educators, students, and academics globally and across all levels of education that the concept of learning styles is an established, textbook principle. Indeed, texts used in teacher education courses present learning style theory as a way to differentiate instruction for students ( Cuevas, 2015 ).

The presented considerations demonstrate that there exists a substantial continuum of perspectives on the application of modality-specific learning styles, ranging from viewing the concept as a neuromyth that should be abandoned in pedagogical practice to those who speak in favor of the concept and might use it as part of their routine practices. The principal aim of this mini-review is to provide a contribution toward narrowing this gap in perspectives by providing an updated overview of the available empirical studies that have applied rigorous methodological criteria as outlined by Pashler et al. (2008) . To the best of the authors’ knowledge, although previous reviews touching upon modality-specific learning styles have been both thorough and in-depth, they have been mostly narrative and have not been accompanied by a focus on specific effect sizes. This latter approach can be important for disentangling divergences in results, as there might be disagreements among studies. Pooling methodological and conceptually similar studies that all involve a certain degree of error allows for deriving an estimate of overall effect size that considers contrasting results from different studies. Such an update seems timely, given that several studies with methodological rigor have been published since the previous reviews.

Scope of the Mini-Review: Selection Criteria for Reporting of Evidence

The aim of this mini-review was to present literature in relation to the meshing hypothesis. Consequently, the authors independently performed database searches in EBSCO (including ERIC, Academic Search Complete, Psychology and Behavioral Sciences Collection) and Ovid (including Medline, EMBASE, and PsychINFO) using combinations of the terms learning styles ∗ , visual ∗ , and auditory ∗ . The searches were conducted up to January 2018. The reference lists from previous reviews were also examined, as well as citation-based searches in Google Scholar. A total of 1215 records were initially scanned, and 10 studies ( Constantinidou and Baker, 2002 ; Massa and Mayer, 2006 ; Kassaian, 2007 ; Korenman and Peynircioglu, 2007 ; Slack and Norwich, 2007 ; Tight, 2010 ; Kollöffel, 2012 ; Hansen and Cottrell, 2013 ; Rogowsky et al., 2015 ; Papanagnou et al., 2016 ) were found that had applied the appropriate methodology according to the criteria by Pashler et al. (2008) .

Tailoring Instruction for Modality-Specific Preferences: No Statistical Evidence for the Meshing Hypothesis

Statistical evidence for the meshing hypothesis could potentially be found in crossover-interaction effects, i.e., visual learners demonstrate improved learning if instruction is visual rather than auditory, and likewise, auditory learners show improvements if instruction is auditory rather than visual. The 10 publications amounted to 13 experiments, from which it was possible to extract means (SD) for computation of effect sizes (Hedges’ g ) for 11 of them. Altogether, 22 effect sizes from post-test data representing the differences in scores between the matched groups and the mismatched groups were analyzed by a random effects model. This resulted in a small and non-significant effect size for visual matching ( g = -0.09, 95% CI [-0.74–0.58], p = 0.80, n = 484) as well as for auditory matching ( g = -0.27, 95% CI [-0.87–0.32], p = 0.37, n = 356). In the paper by Constantinidou and Baker (2002) , the authors did not report data that allow for the computation of Hedges’ g . The authors did state, however, that no significant correlation between learning style and experimental task performance was found. Similarly, Papanagnou et al. (2016) reported only mean values for matched/non-matched learning outcomes and stated that both matched and non-matched groups achieved similar learning outcomes. Based on these data, it thus appears that there is no replicable evidence for a statistical crossover-interaction effect where participants systematically show higher learning outcomes when they are in a condition in which their preferred learning style modality matches the instructional mode and a lower learning outcome when there is a mismatch.

The overall (non-significant) effect sizes obtained across studies appears to be, by any standard, too small to be interpreted as signifying any modality-matching effect on learning outcomes. Although the interpretation of effect sizes is not a straightforward scientific endeavor ( Cohen, 1992 ), the effect size cut-offs indicating a practically relevant effect provided in the literature represent a much more substantial magnitude. For example, Ferguson (2009) recommended that a minimum effect size representing a “practically” significant effect amounts to g ≥ 0.41, and Hattie (2009) has advanced the view that effect sizes ≥0.40 represent a “hinge-point” at which deliberate interventions provide relevant outcomes for teaching and learning. Adding to the overall interpretation of the effect sizes obtained in the current meta-analysis, the 95% confidence intervals demonstrate crossings of zero both for the overall effect size and in data from some individual studies. This latter finding is a strong indicator that the null hypothesis (no effect of modality matching) should not be rejected ( Wilkinson et al., 1999 ).

An often-stated problem in the learning style literature is the plethora of inventories designed and applied for both research and commercial purposes ( Coffield et al., 2004 ; Peterson et al., 2009 ; Scott, 2010 ; Armstrong et al., 2012 ). At first sight, this might appear as a methodological challenge toward the pooling of results across studies. In particular, the VAKT classification vs. the verbalizer–visualizer dimension have previously been advocated as different and non-comparable approaches toward learning styles; e.g., it has been claimed that the verbalizer–visualizer dimension should be defined as a cognitive style and not included among the “family” of learning styles ( Massa and Mayer, 2006 ; Kollöffel, 2012 ). However, the latter perspective involves modality-specific content. Written material is considered proper instruction for verbalizers, as it is processed as spoken words, and therefore, a verbalizer can be considered synonymous to an auditory learner ( Felder and Silverman, 1988 ). Based on these contentions, there are strong theoretical arguments for a comparison of studies applying inventories based upon either perspective. Furthermore, rarely is any theoretical or methodological argument for the inclusion of a specific inventory in studies given, and in addition, some authors advance the view that one should apply the inventories that are most used (or most popular) in order to generate comparable results ( Hansen and Cottrell, 2013 ).

There still appear to be relatively few studies adhering strictly to the methodological criteria outlined by Pashler et al. (2008) . In particular, the participants’ learning styles are not necessarily established before they are separated into groups (e.g., Korenman and Peynircioglu, 2007 ), and participants can be randomly assigned to either one ( Massa and Mayer, 2006 ; Rogowsky et al., 2015 ) or all conditions (e.g., Kassaian, 2007 ). The only study located through the systematic literature search across six different databases and the screening of more than a 1000 records that was totally aligned with Pashler’s criteria was Rogowsky et al. (2015) . These authors report no statistically significant relationship or crossover-interaction effect between modality-specific learning styles and modes of instruction. Here, the authors assessed the participants’ learning styles and randomly assigned participants to either listening to a digital audiobook or reading an e-text, and all participants completed the same achievement test. Interestingly, the effect sizes from this latter study (visual-matching: g = -0.11, auditory-matching: g = -0.256) were similar to the overall effect size across studies.

The experimental tasks applied in studies varied considerably. The pooling of such various approaches can be justified by the modality-specific learning style theory. Here, the basic contention is that modality matching introduces more efficient learning irrespective of content and contexts. Indeed, the concept of a modality-specific learning style has been featured in the literature as a hardwired and more or less inherited preference in the cognitive system that should be taken into consideration in any learning situation ( Coffield et al., 2004 ). One methodological concern, however, arises when examining learning tasks more closely. It appears that some tasks have a “built-in” stronger visual or auditory component, which could potentially introduce an additive bias in favor of both a particular instructional mode and a learning style ( Fiorina et al., 2007 ; Hansen and Cottrell, 2013 ; Willingham et al., 2015 ). Although this could potentially lead to inflated effect sizes, the overall pattern of results across studies suggested no statistical effect of modality matching.

As stated in the introduction, the modality-specific learning style hypothesis is still a favored concept amongst the general public, educators, and in the research literature ( Pashler et al., 2008 ; Dekker et al., 2012 ; Howard-Jones, 2014 ). In previous reviews, it has been systematically addressed that there is, in general, no evidence to support the application of the learning style concept ( Coffield et al., 2004 ; Desmedt and Valcke, 2004 ; Kozhevnikov, 2007 ; Pashler et al., 2008 ; Peterson et al., 2009 ; Cuevas, 2015 ; Willingham et al., 2015 ). The present study responds to a call from the much-cited review (>1,500 citations in Google Scholar) of Pashler et al. (2008) , who stated that, in order for the learning styles hypothesis to be supported, several well-designed studies would have to test, amongst other elements, the modality-matching hypothesis and show significant interaction effects. Although the total number of studies ( n = 10) with appropriate methodology is not large at this time, the pattern of results clearly leans toward showing that tailoring instruction/teaching toward preferred modality-specific learning styles has no effect on learning outcome/rate.

Concluding Remarks

This mini-review has demonstrated that, across studies that have applied equivalent quantitative empirical research designs, no overall improvement in learning outcome when applying modality-specific matching of instruction was found. This conclusion of the presented meta-analysis of an element of the modality-specific learning style literature appears to add to further evidence-based refutations of the meshing hypothesis. Interestingly, some early meta-analysis on other elements of learning styles presented similar conclusions ( Tamir, 1985 ; Kavale and Forness, 1987 ). This appears in contrast to the recent literature review by Newton (2015) , in which it was demonstrated that a considerable percent (89%) of published studies in the period from 2013 to 2015 was positive toward learning styles. It thus appears important to continue to critically scrutinize different aspects of the learning style literature and to conduct pattern-type explanations ( Derry, 1999 ) involving conceptual syntheses of insights emerging from diverse disciplines. For example, connections have been found between visual-spatial strengths and superior abilities in other cognitive domains ( O’Boyle et al., 2005 ; Root-Bernstein et al., 2008 ). This latter work is not typically connected with modality-specific learning styles in the academic literature and highlights the need for further work on the credibility of the meshing hypothesis in order to prevent potential misuse of what might appear to be a persistent neuromyth.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : modality-specific, instruction, teaching, learning styles, meshing hypothesis, neuromyth

Citation: Aslaksen K and Lorås H (2018) The Modality-Specific Learning Style Hypothesis: A Mini-Review. Front. Psychol. 9:1538. doi: 10.3389/fpsyg.2018.01538

Received: 17 April 2018; Accepted: 02 August 2018; Published: 21 August 2018.

Reviewed by:

Copyright © 2018 Aslaksen and Lorås. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Håvard Lorås, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Learning styles refer to a range of competing and debunked theories that aim to account for differences in individuals' learning. Many theories share the proposition that humans can be classified according to their 'style' of learning, but differ in how the proposed styles should be defined, categorized and assessed.:8 A common concept is that individuals differ in how they learn.:266 The idea of individualized learning styles became popular in the 1970s, and has greatly influenced education despite the criticism that the idea has received from some researchers.:107–108 Proponents recommend that teachers have to run a needs analysis to assess the learning styles of their students and adapt their classroom methods to best fit each student's learning style. Although there is ample evidence that individuals express personal preferences for how they prefer to receive information,:108 few studies have found any validity in using learning styles in education.:267 Critics say there is no consistent evidence that identifying an individual student's learning style and teaching for specific learning styles produces better student outcomes.:33 Since 2012, Learning Styles have often been referred to as a "neuromyth" in education. There is evidence of empirical and pedagogical problems related to forcing learning tasks to "correspond to differences in a one-to-one fashion". 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. However, a 2020 systematic review suggested that a majority (89%) of educators around the world continue to believe that the meshing hypothesis is correct. Studies further show that teachers cannot assess the learning style of their students accurately.

1. Overview of Models

There are many different learning styles models; one literature review identified 71 different models. [ 1 ] :166–168 Only a few models are described below.

1.1. David Kolb's Model

David A. Kolb's model is based on his experiential learning model, as explained in his book Experiential Learning . [ 2 ] Kolb's model outlines two related approaches toward grasping experience: Concrete Experience and Abstract Conceptualization , as well as two related approaches toward transforming experience: Reflective Observation and Active Experimentation . [ 2 ] :145 According to Kolb's model, the ideal learning process engages all four of these modes in response to situational demands; they form a learning cycle from experience to observation to conceptualization to experimentation and back to experience. In order for learning to be effective, Kolb postulated, all four of these approaches must be incorporated. As individuals attempt to use all four approaches, they may tend to develop strengths in one experience-grasping approach and one experience-transforming approach, leading them to prefer one of the following four learning styles: [ 2 ] :127 [ 3 ]

Accommodator = Concrete Experience + Active Experiment : strong in "hands-on" practical doing (e.g., physical therapists)
Converger = Abstract Conceptualization + Active Experiment : strong in practical "hands-on" application of theories (e.g., engineers)
Diverger = Concrete Experience + Reflective Observation : strong in imaginative ability and discussion (e.g., social workers)
Assimilator = Abstract Conceptualization + Reflective Observation : strong in inductive reasoning and creation of theories (e.g., philosophers)

Kolb's model gave rise to the Learning Style Inventory, an assessment method used to determine an individual's learning style. According to this model, individuals may exhibit a preference for one of the four styles—Accommodating, Converging, Diverging and Assimilating—depending on their approach to learning in Kolb's experiential learning model. [ 2 ]

Although Kolb's model is widely used, a 2013 study pointed out that Kolb's Learning Style Inventory, among its other weaknesses, incorrectly dichotomizes individuals on the abstract/concrete and reflective/action dimensions of experiential learning (in much the same way as the Myers-Briggs Type Indicator does in a different context), and proposed instead that these dimensions be treated as continuous rather than dichotomous/binary variables. [ 4 ] :44

In an article that addressed Kolb's work through 2005, Mark K. Smith reviewed some critiques of Kolb's model, and identified six key issues regarding the model: [ 5 ]

The model doesn't adequately address the process of reflection;
The claims it makes about the four learning styles are extravagant;
It doesn't sufficiently address the fact of different cultural conditions and experiences;
The idea of stages/steps doesn't necessarily match reality;
It has only weak empirical evidence;
The relationship between learning processes and knowledge is more complex than Kolb draws it.

1.2. Peter Honey and Alan Mumford's Model

Peter Honey and Alan Mumford adapted Kolb's experiential learning model. First, they renamed the stages in the learning cycle to accord with managerial experiences: having an experience, reviewing the experience, concluding from the experience, and planning the next steps. [ 6 ] :121–122 Second, they aligned these stages to four learning styles named: [ 6 ] :122–124

These four learning styles are assumed to be acquired preferences that are adaptable, either at will or through changed circumstances, rather than being fixed personality characteristics. Honey and Mumford's Learning Styles Questionnaire (LSQ) [ 7 ] is a self-development tool and differs from Kolb's Learning Style Inventory by inviting managers to complete a checklist of work-related behaviours without directly asking managers how they learn. Having completed the self-assessment, managers are encouraged to focus on strengthening underutilised styles in order to become better equipped to learn from a wide range of everyday experiences.

A MORI survey commissioned by The Campaign for Learning in 1999 found the Honey and Mumford LSQ to be the most widely used system for assessing preferred learning styles in the local government sector in the UK.

1.3. Learning Modalities

Walter Burke Barbe and colleagues proposed three learning modalities (often identified by the acronym VAK): [ 8 ]

Visualising modality
Auditory modality
Kinesthetic modality

Descriptions of learning modalities
Visual	Kinesthetic/tactile	Auditory
Picture	Gestures	Listening
Shape	Body movements	Rhythms
Sculpture	Object manipulation	Tone
Paintings	Positioning	Chants

Barbe and colleagues reported that learning modality strengths can occur independently or in combination (although the most frequent modality strengths, according to their research, are visual or mixed), they can change over time, and they become integrated with age. [ 9 ] They also 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. [ 9 ] :378 This disconnect between strengths and preferences was confirmed by a subsequent study. [ 10 ] Nevertheless, some scholars have criticized the VAK model. [ 11 ] [ 12 ] Psychologist Scott Lilienfeld and colleagues have argued that much use of the VAK model is nothing more than pseudoscience or a psychological urban legend. [ 13 ]

1.4. Neil Fleming's VAK/VARK Model

Neil Fleming's VARK model and inventory [ 14 ] expanded upon earlier notions of sensory modalities such as the VAK model of Barbe and colleagues [ 8 ] and the representational systems (VAKOG) in neuro-linguistic programming. [ 15 ] The four sensory modalities in Fleming's model are: [ 16 ]

Visual learning
Auditory learning
Physical learning
Social learning

Fleming claimed that visual learners have a preference for seeing (visual aids that represent ideas using methods other than words, such as graphs, charts, diagrams, symbols, etc.). Subsequent neuroimaging research has suggested that visual learners convert words into images in the brain and vice versa, [ 17 ] but some psychologists have argued that this "is not an instance of learning styles, rather, it is an instance of ability appearing as a style". [ 18 ] :268 Likewise, Fleming claimed that auditory learners best learn through listening (lectures, discussions, tapes, etc.), and tactile/kinesthetic learners prefer to learn via experience—moving, touching, and doing (active exploration of the world, science projects, experiments, etc.). [ 16 ] Students can use the model and inventory to identify their preferred learning style and, it is claimed, improve their learning by focusing on the mode that benefits them the most. [ 16 ] Fleming's model also posits two types of multimodality. [ 16 ] This means that not everyone has one defined preferred modality of learning; some people may have a mixture that makes up their preferred learning style. [ 16 ]

1.5. Anthony Gregorc's Model

Anthony Gregorc and Kathleen Butler organized a model describing different learning styles rooted in the way individuals acquire and process information differently. [ 19 ] This model posits that an individual's perceptual abilities are the foundation of his or her specific learning strengths, or learning styles. [ 20 ]

In this model, there are two perceptual qualities: concrete and abstract , and two ordering abilities: random and sequential . [ 20 ] Concrete perceptions involve registering information through the five senses, while abstract perceptions involve the understanding of ideas, qualities, and concepts which cannot be seen. In regard to the two ordering abilities, sequential ordering involves the organization of information in a linear, logical way, and random ordering involves the organization of information in chunks and in no specific order. [ 20 ] The model posits that both of the perceptual qualities and both of the ordering abilities are present in each individual, but some qualities and ordering abilities are more dominant within certain individuals. [ 20 ]

There are four combinations of perceptual qualities and ordering abilities based on dominance: concrete sequential , abstract random , abstract sequential , and concrete random . The model posits that individuals with different combinations learn in different ways—they have different strengths, different things make sense to them, different things are difficult for them, and they ask different questions throughout the learning process. [ 20 ]

The validity of Gregorc's model has been questioned by Thomas Reio and Albert Wiswell following experimental trials. [ 21 ] Gregorc argues that his critics have "scientifically-limited views" and that they wrongly repudiate the "mystical elements" of "the spirit" that can only be discerned by a "subtle human instrument". [ 22 ]

1.6. Cognitive Approaches

Anthony Grasha and Sheryl Riechmann, in 1974, formulated the Grasha-Reichmann Learning Style Scale. [ 23 ] It was developed to analyze the attitudes of students and how they approach learning. The test was originally designed to provide teachers with insight on how to approach instructional plans for college students. [ 24 ] Grasha's background was in cognitive processes and coping techniques. Unlike some models of cognitive styles which are relatively nonjudgmental, Grasha and Riechmann distinguish between adaptive and maladaptive styles. The names of Grasha and Riechmann's learning styles are:

participative
competitive
collaborative
independent

Aiming to explain why aptitude tests, school grades, and classroom performance often fail to identify real ability, Robert Sternberg listed various cognitive dimensions in his book Thinking Styles . [ 25 ] Several other models are also often used when researching cognitive styles; some of these models are described in books that Sternberg co-edited, such as Perspectives on Thinking, Learning, and Cognitive Styles . [ 26 ] [ 27 ] [ 28 ]

1.7. NASSP Model

In the 1980s, the National Association of Secondary School Principals (NASSP) formed a task force to study learning styles. [ 29 ] The task force defined three broad categories of style—cognitive, affective, and physiological—and 31 variables, including the perceptual strengths and preferences from the VAK model of Barbe and colleagues, [ 9 ] but also many other variables such as need for structure, types of motivation, time of day preferences, and so on. [ 29 ] :141–143 They defined a learning style as "a gestalt —not an amalgam of related characteristics but greater than any of its parts. It is a composite of internal and external operations based in neurobiology, personality, and human development and reflected in learner behavior." [ 29 ] :141

Cognitive styles are preferred ways of perception, organization and retention.
Affective styles represent the motivational dimensions of the learning personality; each learner has a personal motivational approach.
Physiological styles are bodily states or predispositions, including sex-related differences, health and nutrition, and reaction to physical surroundings, such as preferences for levels of light, sound, and temperature. [ 29 ] :141

According to the NASSP task force, styles are hypothetical constructs that help to explain the learning (and teaching) process. They posited that one can recognize the learning style of an individual student by observing his or her behavior. [ 29 ] :138 Learning has taken place only when one observes a relatively stable change in learner behavior resulting from what has been experienced.

2. Assessment Methods

A 2004 non-peer-reviewed literature review criticized most of the main instruments used to identify an individual's learning style. [ 1 ] In conducting the review, Frank Coffield and his colleagues selected 13 of the most influential models of the 71 models they identified, [ 1 ] :8–9 including most of the models described in this article. They examined the theoretical origins and terms of each model, and the instrument that purported to assess individuals against the learning styles defined by the model. They analyzed the claims made by the author(s), external studies of these claims, and independent empirical evidence of the relationship between the learning style identified by the instrument and students' actual learning. Coffield's team found that none of the most popular learning style theories had been adequately validated through independent research. This means that even if the underlying theories were sound, educators are frequently unable to correctly identify the theoretically correct learning style for any given student, so the theory would end up being misapplied in practice.

2.1. Learning Style Inventory

The Learning Style Inventory (LSI) is connected with David A. Kolb's model and is used to determine a student's learning style. [ 3 ] Previous versions of the LSI have been criticized for problems with validity, reliability, and other issues. [ 4 ] [ 30 ] [ 31 ] Version 4 of the Learning Style Inventory replaces the four learning styles of previous versions with nine new learning styles: initiating, experiencing, imagining, reflecting, analyzing, thinking, deciding, acting, and balancing. [ 32 ] The LSI is intended to help employees or students "understand how their learning style impacts upon problem solving, teamwork, handling conflict, communication and career choice; develop more learning flexibility; find out why teams work well—or badly—together; strengthen their overall learning." [ 32 ]

A completely different Learning Styles Inventory is associated with a binary division of learning styles, developed by Richard Felder and Linda Silverman. [ 33 ] In Felder and Silverman's model, learning styles are a balance between pairs of extremes such as: Active/Reflective, Sensing/Intuitive, Verbal/Visual, and Sequential/Global. Students receive four scores describing these balances. [ 34 ] Like the LSI mentioned above, this inventory provides overviews and synopses for teachers.

2.2. NASSP Learning Style Profile

The NASSP Learning Style Profile (LSP) is a second-generation instrument for the diagnosis of student cognitive styles, perceptual responses, and study and instructional preferences. [ 35 ] The LSP is a diagnostic tool intended as the basis for comprehensive style assessment with students in the sixth to twelfth grades. It was developed by the National Association of Secondary School Principals research department in conjunction with a national task force of learning style experts. The Profile was developed in four phases with initial work undertaken at the University of Vermont (cognitive elements), Ohio State University (affective elements), and St. John's University (physiological/environmental elements). Rigid validation and normative studies were conducted using factor analytic methods to ensure strong construct validity and subscale independence.

The LSP contains 23 scales representing four higher order factors: cognitive styles, perceptual responses, study preferences and instructional preferences (the affective and physiological elements). The LSP scales are: analytic skill, spatial skill, discrimination skill, categorizing skill, sequential processing skill, simultaneous processing skill, memory skill, perceptual response: visual, perceptual response: auditory, perceptual response: emotive, persistence orientation, verbal risk orientation, verbal-spatial preference, manipulative preference, study time preference: early morning, study time preference: late morning, study time preference: afternoon, study time preference: evening, grouping preference, posture preference, mobility preference, sound preference, lighting preference, temperature preference. [ 35 ]

2.3. Other Methods

Other methods (usually questionnaires) used to identify learning styles include Neil Fleming's VARK Questionnaire [ 14 ] and Jackson's Learning Styles Profiler. [ 1 ] :56–59 Many other tests have gathered popularity and various levels of credibility among students and teachers.

3. In the Classroom

For a teacher to use the learning styles model, the teacher has to be able to correctly match each student to a learning style. This is a generally unsuccessful exercise due to inappropriate tools. For an assessment tool to be useful, it needs to be a valid test, which is to say that it actually has to put all of the "style A" students in the "A" group, all of the "style B" students in the "B" group, and so forth. Research indicates that very few, if any, of the psychometric tests promoted in conjunction with the learning styles idea have the necessary validity to be useful in practice. Some models, such as Anthony Gregorc's Gregorc Style Delineator, are "theoretically and psychometrically flawed" and "not suitable for the assessment of individuals". [ 1 ] :20

Furthermore, knowing a student's learning style does not seem to have any practical value for the student. In 2019, the American Association of Anatomists published a study that investigated whether learning styles had any effect on the final outcomes of an anatomy course. The study found that even when being told they had a specific learning style, the students did not change their study habits, and those students that did use their theoretically dominant learning style had no greater success in the course; specific study strategies, unrelated to learning style, were positively correlated with final course grade. [ 36 ]

3.1. Dunn and Dunn

Various researchers have attempted to hypothesize ways in which learning style theory can be used in the classroom. Two such scholars are Rita Dunn and Kenneth Dunn, who build upon a learning modalities approach. [ 1 ] :20–35 [ 37 ]

Although learning styles will inevitably differ among students in the classroom, Dunn and Dunn say that teachers should try to make changes in their classroom that will be beneficial to every learning style. Some of these changes include room redesign, the development of small-group techniques, and the development of "contract activity packages". [ 37 ] Redesigning the classroom involves locating dividers that can be used to arrange the room creatively (such as having different learning stations and instructional areas), clearing the floor area, and incorporating students' thoughts and ideas into the design of the classroom. [ 37 ]

Dunn and Dunn's "contract activity packages" are educational plans that use: a clear statement of the learning need; multisensory resources (auditory, visual, tactile, kinesthetic); activities through which the newly mastered information can be used creatively; the sharing of creative projects within small groups; at least three small-group techniques; a pre-test, a self-test, and a post-test. [ 37 ]

Dunn and Dunn's learning styles model is widely used in schools in the United States, and 177 articles have been published in peer-reviewed journals referring to this model. [ 1 ] :20 However, the conclusion of a review by Coffield and colleagues was: "Despite a large and evolving research programme, forceful claims made for impact are questionable because of limitations in many of the supporting studies and the lack of independent research on the model." [ 1 ] :35

3.2. Sprenger's Differentiation

Another scholar who believes that learning styles should have an effect on the classroom is Marilee Sprenger in Differentiation through Learning Styles and Memory . [ 38 ] She bases her work on three premises:

Teachers can be learners, and learners teachers. We are all both.
Everyone can learn under the right circumstances.
Learning is fun! Make it appealing. [ 38 ]

Sprenger details how to teach in visual, auditory, or tactile/kinesthetic ways. Methods for visual learners include ensuring that students can see words written, using pictures, and drawing timelines for events. [ 38 ] Methods for auditory learners include repeating words aloud, small-group discussion, debates, listening to books on tape, oral reports, and oral interpretation. [ 38 ] Methods for tactile/kinesthetic learners include hands-on activities (experiments, etc.), projects, frequent breaks to allow movement, visual aids, role play, and field trips. [ 38 ] By using a variety of teaching methods from each of these categories, teachers cater to different learning styles at once, and improve learning by challenging students to learn in different ways.

James W. Keefe and John M. Jenkins have incorporated learning style assessment as a basic component in their "personalized instruction" model of schooling. [ 39 ] Six basic elements constitute the culture and context of personalized instruction. The cultural components—teacher role, student learning characteristics, and collegial relationships—establish the foundation of personalization and ensure that the school prizes a caring and collaborative environment. The contextual factors—interactivity, flexible scheduling, and authentic assessment—establish the structure of personalization. [ 39 ]

According to Keefe and Jenkins, cognitive and learning style analysis have a special role in the process of personalizing instruction. The assessment of student learning style, more than any other element except the teacher role, establishes the foundation for a personalized approach to schooling: for student advisement and placement, for appropriate retraining of student cognitive skills, for adaptive instructional strategy, and for the authentic evaluation of learning. [ 39 ] Some learners respond best in instructional environments based on an analysis of their perceptual and environmental style preferences: most individualized and personalized teaching methods reflect this point of view. Other learners, however, need help to function successfully in any learning environment. If a youngster cannot cope under conventional instruction, enhancing his cognitive skills may make successful achievement possible. [ 39 ]

Many of the student learning problems that learning style diagnosis attempts to solve relate directly to elements of the human information processing system. Processes such as attention, perception and memory, and operations such as integration and retrieval of information are internal to the system. Any hope for improving student learning necessarily involves an understanding and application of information processing theory. Learning style assessment can provide a window to understanding and managing this process. [ 39 ]

At least one study evaluating teaching styles and learning styles, however, has found that congruent groups have no significant differences in achievement from incongruent groups. [ 40 ] Furthermore, learning style in this study varied by demography, specifically by age, suggesting a change in learning style as one gets older and acquires more experience. While significant age differences did occur, as well as no experimental manipulation of classroom assignment, the findings do call into question the aim of congruent teaching–learning styles in the classroom. [ 1 ] :122

Educational researchers Eileen Carnell and Caroline Lodge concluded that learning styles are not fixed and that they are dependent on circumstance, purpose and conditions. [ 41 ]

4. Criticism

Learning style theories have been criticized by many scholars and researchers. Some psychologists and neuroscientists have questioned the scientific basis for separating out students based on learning style. According to Susan Greenfield the practice is "nonsense" from a neuroscientific point of view: "Humans have evolved to build a picture of the world through our senses working in unison, exploiting the immense interconnectivity that exists in the brain." [ 42 ] Similarly, Christine Harrington argued that since all students are multisensory learners, educators should teach research-based general learning skills. [ 43 ]

Many educational psychologists have shown that there is little evidence for the efficacy of most learning style models, and furthermore, that the models often rest on dubious theoretical grounds. [ 44 ] [ 45 ] According to professor of education Steven Stahl, there has been an "utter failure to find that assessing children's learning styles and matching to instructional methods has any effect on their learning." [ 46 ] Professor of education Guy Claxton has questioned the extent that learning styles such as VARK are helpful, particularly as they can have a tendency to label children and therefore restrict learning. [ 47 ] Similarly, psychologist Kris Vasquez pointed out a number of problems with learning styles, including the lack of empirical evidence that learning styles are useful in producing student achievement, but also her more serious concern that the use of learning styles in the classroom could lead students to develop self-limiting implicit theories about themselves that could become self-fulfilling prophecies that are harmful, rather than beneficial, to the goal of serving student diversity. [ 48 ]

Some research has shown that long-term retention can better be achieved under conditions that seem more difficult, and that teaching students only in their preferred learning style is not effective. [ 49 ]

Psychologists Scott Lilienfeld, Barry Beyerstein, and colleagues listed as one of the "50 great myths of popular psychology" the idea that "students learn best when teaching styles are matched to their learning styles", and they summarized some relevant reasons not to believe this "myth". [ 13 ]

4.1. Other Critiques

Coffield and his colleagues and Mark Smith are not alone in their judgements. In 2005, Demos, a UK think tank, published a report on learning styles prepared by a group chaired by David Hargreaves that included Usha Goswami from the University of Cambridge and David Wood from the University of Nottingham. The Demos report said that the evidence for learning styles was "highly variable", and that practitioners were "not by any means always frank about the evidence for their work". [ 50 ] :11

Cautioning against interpreting neuropsychological research as supporting the applicability of learning style theory, John Geake, Professor of Education at the UK's Oxford Brookes University, and a research collaborator with Oxford University's Centre for Functional Magnetic Resonance Imaging of the Brain, commented in 2005: "We need to take extreme care when moving from the lab to the classroom. We do remember things visually and aurally, but information isn't defined by how it was received." [ 51 ]

The work of Daniel T. Willingham, a cognitive psychologist and neuroscientist, has argued that there is not enough evidence to support a theory describing the differences in learning styles amongst students. In his 2009 book Why Don't Students Like School , [ 52 ] he claimed that a cognitive styles theory must have three features: "it should consistently attribute to a person the same style, it should show that people with different abilities think and learn differently, and it should show that people with different styles do not, on average, differ in ability". [ 52 ] :118 He concluded that there are no theories that have these three crucial characteristics, not necessarily implying that cognitive styles don't exist but rather stating that psychologists have been unable to "find them". [ 52 ] :118 In a 2008 self-published YouTube video titled "Learning Styles Don't Exist", Willingham concluded by saying: "Good teaching is good teaching and teachers don't need to adjust their teaching to individual students' learning styles." [ 53 ]

4.2. 2009 APS Critique

In late 2009, the journal Psychological Science in the Public Interest of the Association for Psychological Science (APS) published a report on the scientific validity of learning styles practices. [ 54 ] The panel of experts that wrote the article, led by Harold Pashler of the University of California, San Diego, concluded that an adequate evaluation of the learning styles hypothesis—the idea that optimal learning demands that students receive instruction tailored to their learning styles—requires a particular kind of study. Specifically, students should be grouped into the learning style categories that are being evaluated (e.g., visual learners vs. verbal learners), and then students in each group must be randomly assigned to one of the learning methods (e.g., visual learning or verbal learning), so that some students will be "matched" and others will be "mismatched". At the end of the experiment, all students must sit for the same test. If the learning style hypothesis is correct, then, for example, visual learners should learn better with the visual method, whereas auditory learners should learn better with the auditory method. As disclosed in the report, the panel found that studies utilizing this essential research design were virtually absent from the learning styles literature. In fact, the panel was able to find only a few studies with this research design, and all but one of these studies were negative findings—that is, they found that the same learning method was superior for all kinds of students. [ 54 ] Examples of such negative findings include the research of Laura J. Massa and Richard E. Mayer, [ 55 ] as well as more recent research since the 2009 review. [ 18 ] [ 56 ] [ 57 ]

Furthermore, the panel noted that, even if the requisite finding were obtained, the benefits would need to be large, and not just statistically significant, before learning style interventions could be recommended as cost-effective. That is, the cost of evaluating and classifying students by their learning style, and then providing customized instruction would need to be more beneficial than other interventions (e.g., one-on-one tutoring, after school remediation programs, etc.). [ 54 ] :116–117

As a consequence, the panel concluded, "at present, there is no adequate evidence base to justify incorporating learning styles assessments into general educational practice. Thus, limited education resources would better be devoted to adopting other educational practices that have strong evidence base, of which there are an increasing number." [ 54 ] :105

The article incited critical comments from some defenders of learning styles. The Chronicle of Higher Education reported that Robert Sternberg from Tufts University spoke out against the paper: "Several of the most-cited researchers on learning styles, Mr. Sternberg points out, do not appear in the paper's bibliography." [ 58 ] This charge was also discussed by Science , which reported that Pashler said, "Just so... most of [the evidence] is 'weak'." [ 59 ] The Chronicle reported that even David A. Kolb partly agreed with Pashler; Kolb said: "The paper correctly mentions the practical and ethical problems of sorting people into groups and labeling them. Tracking in education has a bad history." [ 58 ]

4.3. Subsequent Critiques

A 2015 review paper [ 60 ] examined the studies of learning styles completed after the 2009 APS critique, [ 54 ] giving particular attention to studies that used the experimental methods advocated for by Pashler et al. [ 60 ] The findings were similar to those of the APS critique: the evidence for learning styles was virtually nonexistent while evidence contradicting it was both more prevalent and used more sound methodology. [ 60 ] Follow-up studies concluded that learning styles had no effect on student retention of material whereas another explanation, dual coding, had a substantial impact on it and held more potential for practical application in the classroom. [ 61 ]

A 2017 research paper from the UK found that 90% of academics agreed there are "basic conceptual flaws" with learning styles theory, yet 58% agreed that students "learn better when they receive information in their preferred learning style", and 33% reported that they used learning styles as a method in the past year. [ 62 ] It concluded that it might be better to use methods that are "demonstrably effective". [ 62 ] [ 63 ]

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Stahl, Steven A. (2004). "Different strokes for different folks?". in Abbeduto, Leonard. Taking sides: clashing views on controversial issues in educational psychology. Guilford, CT: Dushkin/McGraw-Hill. pp. 98–107. ISBN 0072917237. OCLC 53479331. http://linksprogram.gmu.edu/tutorcorner/NCLC495Readings/Stahl_DifferentStrokes.pdf.
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Willingham, Daniel T. (21 August 2008). "Learning Styles Don't Exist". https://www.youtube.com/watch?v=sIv9rz2NTUk.
Pashler, Harold; McDaniel, Mark; Rohrer, Doug; Bjork, Robert A. (December 2008). "Learning styles: concepts and evidence". Psychological Science in the Public Interest 9 (3): 105–119. doi:10.1111/j.1539-6053.2009.01038.x. PMID 26162104. https://dx.doi.org/10.1111%2Fj.1539-6053.2009.01038.x
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Kollöffel, Bas (February 2012). "Exploring the relation between visualizer–verbalizer cognitive styles and performance with visual or verbal learning material". Computers & Education 58 (2): 697–706. doi:10.1016/j.compedu.2011.09.016. https://dx.doi.org/10.1016%2Fj.compedu.2011.09.016
A 2015 study found no statistically significant improvement in student comprehension when instruction methods were related to learning style preferences; the researchers argued that "educators may actually be doing a disservice to auditory learners by continually accommodating their auditory learning style preference" (p. 77) since most testing is presented in a written word format only, and therefore all students should have strong visual word skills. See: Rogowsky, Beth A.; Calhoun, Barbara M.; Tallal, Paula (2015). "Matching learning style to instructional method: effects on comprehension". Journal of Educational Psychology 107 (1): 64–78. doi:10.1037/a0037478. https://zenodo.org/record/977853.
Glenn, David (15 December 2009). "Matching teaching style to learning style may not help students". The Chronicle of Higher Education. http://chronicle.com/article/Matching-Teaching-Style-to/49497/. Retrieved 24 February 2010.
Holden, Constance (8 January 2010). "Learning with style". Science 327 (5692): 129.2–129. doi:10.1126/science.327.5962.129-b. http://www.psychologicalscience.org/pdf/Learning_With_Style-Science.pdf.
Cuevas, Joshua (November 2015). "Is learning styles-based instruction effective?: a comprehensive analysis of recent research on learning styles". Theory and Research in Education 13 (3): 308–333. doi:10.1177/1477878515606621. https://dx.doi.org/10.1177%2F1477878515606621
Cuevas, Joshua; Dawson, Bryan L. (March 2018). "A test of two alternative cognitive processing models: learning styles and dual coding". Theory and Research in Education 16 (1): 40–64. doi:10.1177/1477878517731450. https://dx.doi.org/10.1177%2F1477878517731450
Newton, Philip M.; Miah, Mahallad (2017). "Evidence-based higher education—is the learning styles 'myth' important?". Frontiers in Psychology 8: 444. doi:10.3389/fpsyg.2017.00444. PMID 28396647. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5366351
Nancekivell, Shaylene E.; Shah, Priti; Gelman, Susan A. (2020). "Maybe they're born with it, or maybe it's experience: toward a deeper understanding of the learning style myth". Journal of Educational Psychology 112 (2): 221–235. doi:10.1037/edu0000366. https://www.apa.org/pubs/journals/releases/edu-edu0000366.pdf.

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Design based on two types of meshing theories.
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the learning styles hypothhes is false, but there are patterns of
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Learning Styles: Concepts and Evidence
The most common—but not the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual presentation of information).
PDF Matching Learning Style to Instructional Method
the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a 'visual learner,' emphasizing visual presentation of information; p. 105)." After reviewing the literature, they found
Learning Styles: Concepts and Evidence
The most common—but not the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual presentation of information).
PDF Learning Styles
about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a ''visual learner,'' emphasizing visual ... Learning style is the way in which each learner begins to con-centrate on, process, absorb, and ...
(PDF) Learning Styles: Concepts and Evidence
The most common—but not the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that ...
Why the learning styles myth appeals and how to persuade believers
A study by Pashler et al. (2009) reasoned that one of the best ways to test the core idea of learning styles theory would be an experiment that verifies what they called the "meshing hypothesis"—namely, the idea that if the teaching approach is 'matched' to the learning style of a student, that student will experience enhanced ...
Learning Styles: Concepts and Evidence
The most common-but not the only-hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual presentation of information). The learning-styles view has acquired ...
Exploring the development and impact of learning styles: An empirical
A renewed assessment of the meshing hypothesis seems reasonable due to 1) the conflicting opinions on the advantages of matching a learning style with relevant learning materials, and 2) the fact that the meshing hypothesis is still widely accepted in educational scientific areas and practical domains irrespective of the conflicting opinions ...
The persistence of matching teaching and learning styles: A review of
The only formal way to test this meshing hypothesis is by finding a statistical crossover interaction effect which shows that matching teaching and learning styles improves academic outcomes, while non-matching teaching and learning styles negatively affects academic outcomes. Several studies are reviewed and none of these yielded empirical ...
PDF Opinion: Uses, Misuses, and Validity of Learning Styles*
learning style assessment instruments or of two propositions the challengers ascribe to learning styles proponents: the invariance of learning styles with time and conditions of instruction, and the "meshing hypothesis" that students' learning in a class is maximized by matching instruction to the individual students' learning styles.
Matching learning style to instructional method: Effects on comprehension
While it is hypothesized that providing instruction based on individuals' preferred learning styles improves learning (i.e., reading for visual learners and listening for auditory learners, also referred to as the meshing hypothesis), after a critical review of the literature Pashler, McDaniel, Rohrer, and Bjork (2008) concluded that this hypothesis lacks empirical evidence and subsequently ...
Frontiers
"As the critics of learning styles correctly claim, the meshing hypothesis (matching instruction to students' learning styles maximizes learning) has no rigorous research support, but the existence and utility of learning styles does not rest on that hypothesis and most proponents of learning styles reject it." (Felder, 2020) and
OPINION: Uses, Misuses, and Validity of Learning Styles
At the same time, a number of educational and cognitive psychologists have argued vehemently against taking learning styles into account when designing instruction, basing their arguments almost entirely on a lack of demonstrated validity of the "meshing hypothesis," which asserts that matching instruction to students' individual learning ...
The problem with learning styles: debunking the meshing hypothesis in
The notion of perceptual learning styles - that is, the idea that learners prefer to receive information either visually, auditorily or kinaesthetically - has been scrutinised by neuroscientists in recent years (Dekker et al., 2012); (Howard-Jones, 2014).In particular, the 'meshing hypothesis' (or 'matching hypothesis'), the idea that catering to a learner's favoured sensory ...
The Modality-Specific Learning Style Hypothesis: A Mini-Review
The impact on learning outcome of tailoring instruction and teaching toward modality-specific learning style preferences has been researched and debated for decades. Several topical reviews have concluded that there is no evidence to support the meshing hypothesis and that it represents a persistent neuromyth in education.
Learning Styles: Concepts and Evidence
The most common—but not the only—hypothesis about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual presentation of information). The learning-styles view has ...
Learning styles: what does the research say?
Within education, a version of the learning-styles hypothesis, known by psychologists as the meshing hypothesis, has been of particular interest: the idea that students will learn more if they receive instruction that specifically matches their learning-style preferences. In other words, visual learners will learn better if they receive ...
The Learning Styles Neuromyth Is Still Thriving in Medical Education
Only one study (Papanagnou et al., 2016) tested the Meshing Hypothesis using a recognized Learning Styles instrument. This study found no evidence to support the Meshing Hypothesis. The most common Learning Styles instruments were the VARK system or variants thereof (e.g., VAK) (40/112, 36% of papers) and Kolb Learning Styles Inventory (35/112 ...
PDF Learning Styles: Concepts and Evidence
Learning Styles Concepts and Evidence Harold Pashler,1 Mark McDaniel,2 Doug Rohrer,3 and Robert Bjork4 ... about the instructional relevance of learning styles is the meshing hypothesis, according to which instruction is best provided in a format that matches the preferences of the learner (e.g., for a "visual learner," emphasizing visual ...
The truth about learning styles
The meshing hypothesis - matching learning style to content formats - may not help students in actual learning. But a holistic sense of learning requires proof of learning and the feeling of learning. Emotions play a role and having a likeable format or preferred format does affect the motivation to learn.
The Modality-Specific Learning Style Hypothesis: A Mini-Review
The impact on learning outcome of tailoring instruction and teaching toward modality-specific learning style preferences has been researched and debated for decades. Several topical reviews have concluded that there is no evidence to support the meshing hypothesis and that it represents a persistent neuromyth in education.
Learning Styles
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. However, a 2020 systematic review suggested that a majority (89%) of educators around the world continue to believe that the meshing hypothesis is correct. ... matched" and others will ...

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Learning styles: what does the research say?

The Learning Styles Neuromyth Is Still Thriving in Medical Education

Introduction

Inclusion Criteria

Positive Intent

Positive Outcome

Did the Study Test, and If So Contradict, the Meshing Hypothesis?

Discussion—Student Perspective (HNL)

General Discussion

Data Availability Statement

Conflict of Interest

Publisher’s Note

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The truth about learning styles – Myth AND Fact?

Learning styles – the concept

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MINI REVIEW article

Introduction

Scope of the Mini-Review: Selection Criteria for Reporting of Evidence

Tailoring Instruction for Modality-Specific Preferences: No Statistical Evidence for the Meshing Hypothesis

Concluding Remarks

Author Contributions

Conflict of Interest Statement

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1. Overview of Models

1.1. David Kolb's Model

1.2. Peter Honey and Alan Mumford's Model

1.3. Learning Modalities

1.4. Neil Fleming's VAK/VARK Model

1.5. Anthony Gregorc's Model

1.6. Cognitive Approaches

1.7. NASSP Model

2. Assessment Methods

2.1. Learning Style Inventory

2.2. NASSP Learning Style Profile

2.3. Other Methods

3. In the Classroom

3.1. Dunn and Dunn

3.2. Sprenger's Differentiation

4. Criticism

4.1. Other Critiques

4.2. 2009 APS Critique

4.3. Subsequent Critiques

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