Davies (1999) called for an ‘evidence-based’ approach to education, arguing that the design of new interventions in education was not sufficiently informed by rigorous evidence and that new interventions are then poorly evaluated. Although this was one in a series of such calls, the very idea of evidence-based education continues to be criticized (e.g., see Biesta, 2010), often on the basis that education is complex (allegedly more so than medicine, to which it is often compared). For example, what does it mean to say that something has ‘worked’, and for whom has it ‘worked’ and in what context?
Despite this complexity, there are some concepts in education for which there is abundant clear evidence to show that they are not effective. One of these is Learning Styles, such as the ‘VAK’ classification, which classifies individuals as one or more of ‘Visual, Auditory, or Kinesthetic’ learners (Geake, 2008). Other classifications include those by (separately) Kolb, Felder and Honey and Mumford; in total there are over 70 different classification systems (Coffield et al., 2004). The concept of ‘Learning Styles’ as an educational tool is fairly straightforward, and follows three steps: (1) individuals will express a preference regarding their ‘style’ of learning, (2) individuals show differences in their ability to learn about certain types of information (e.g., some may be better at learning to discriminate between sounds while others may be better at discriminating between pictures), and (3) the ‘matching’ of instructional design to an individual’s Learning Style, as designated by one of the aforementioned classifications, will result in better educational outcomes (e.g., visual learners should have information presented visually, while auditory learners would do better with an emphasis on audio).
The utility of step 2 for education is debatable, as most learning is constructed from multiple types of information, and to acquire ‘meaning’ and ‘understanding’ arguably goes beyond a specific sensory domain. However, it is the last step, the ‘matching hypothesis’, where the concept of Learning Styles completely falls down. A comprehensive review by Pashler et al. (2008) determined that there was no evidence to support the use of Learning Styles in education, based upon a lack of evidence to support ‘matching’. Coffield et al. (2004) reviewed the literature pertaining to 71 different Learning Styles classifications, with the aim of answering the question “should we be using them in post-16 education.” The answer was a resounding ‘no’.
The use of an ineffective educational technique is potentially associated with harm – students who are labeled as having a dominant Learning Style (e.g., ‘visual learners’) may then choose not to pursue subjects which they perceive as being dominated by a different learning style (e.g., music), or may develop a false sense of confidence in their abilities to master subjects which they perceive as matching their style. Perhaps most importantly, the use of ineffective techniques such as Learning Styles can detract from the use of techniques which are demonstrably effective (Riener and Willingham, 2010; Willingham et al., 2015).
Despite this, amongst educators, there appears to be widespread belief in the use of Learning Styles. A survey by Dekker et al. (2012) showed that 93% of UK schoolteachers believed the (unsupported) statement that “individuals learn better when they receive information in their preferred Learning Style”. Follow-up studies have shown similar results in other countries (Howard-Jones, 2014). A study conducted using faculty in Higher Education in the USA found similar results, with 64% rating ‘yes’ to the statement “does teaching to a student’s learning style enhance learning” (Dandy and Bendersky, 2014). This is reflected at the institutional level – a survey of 39 Higher Education institutions in the US found that 29 of them (72%) taught ‘learning style theory’ as part of faculty development for online teachers (Meyer and Murrell, 2014).
Learning Styles have been designated a ‘neuromyth’ (Lilienfeld et al., 2011, p. 92; Dekker et al., 2012; Howard-Jones, 2014) and the lack of evidence to support them has been the subject of reviews and commentaries (Riener and Willingham, 2010; Rohrer and Pashler, 2012; Willingham et al., 2015). Alongside this formal literature are blogs and online videos debunking the ‘myth.’ I wrote one myself, motivated, as I am sure others have been, by my personal experience of meeting numerous students and educators who accepted the concept of Learning Styles as an established, textbook principle. However, with the wealth of strong research studies and social media, it seemed reasonable to hypothesize that the use of Learning Styles may now be in decline, and that this would be seen most keenly in the current research literature.
Alternately, Learning Styles may represent the educational equivalent of homeopathy: a medical concept for which no evidence exists, yet in which belief and use persists. There has been a significant body of research aimed at understanding why such beliefs persist, a simple summary of which is that people often seek out information which aligns with their existing worldview, akin to a prospective confirmation bias (Colombo et al., 2015). Confirmation bias has been suggested as one reason why Learning Styles and other myths appear to persist (Riener and Willingham, 2010; Pasquinelli, 2012).
Intuitively, there is much that is attractive about the concept of Learning Styles. People are obviously different and Learning Styles appear to offer educators a way to accommodate individual learner differences. They also allow individuals to self-test and determine what ‘type’ of learner they are. These intuitive attractions may ‘set up’ an educator to fall into the trap of confirmation bias – approaching the research literature having already formed a view that Learning Styles are ‘a good thing’. Therefore, I also set out to characterize the picture an educator would encounter were they to search the education research literature for evidence to support, or not, the use of Learning Styles.
Two major databases of life sciences/education research were used as the datasets. PubMed is a database of research publications in the life sciences and biomedicine While ERIC (Education Information Resources Center) is ‘an online library of education research and information’
A search of the PubMed database was carried out for the term “learning styles”, with the date range July 23, 2013 to July 23, 2015 (to reflect current research). Only papers studying Higher Education were selected for analysis. The term “learning styles” was also used to search the ERIC database, with results filtered to be positive for the criteria ‘peer reviewed’ and ‘Higher Education’ for 2015, then 2014, then 2013 (July–December).
The analysis was restricted to Higher Education on the basis that (1) one of the most comprehensive reviews regarding the use of Learning Styles in education was focused specifically on post-16 education (Coffield et al., 2004) and (2) a lecturer in Higher Education is normally appointed as a subject-matter expert on the basis of their research expertise, and so would normally be familiar with using research literature.
For every search result, the following questions were asked (further detail below) –
• (Inclusion criteria for further analysis)
◦ Was the study about Learning Styles?
◦ Were participants students/staff in Higher Education or beyond?
◦ Was the full text in English?
• What was the specific study population (e.g., medical students)?
• In which country was the study conducted?
• What Learning Style(s) was being used or tested?
• Does the study begin with positive view toward Learning Styles?
• Does the study conclude with positive view toward Learning Styles?
• Does the study test the matching hypothesis as put forward by Pashler et al. (2008)?
• Do the study results challenge the conclusions of Pashler/Coffield?
This study was aimed at providing a snapshot of the Learning Styles research available to the ‘casual’ inquirer – an academic considering the use of these methods in their teaching. Thus the questions asked were initially of the study abstract. If the answers were clear from the abstract, then the full text was not consulted. If the answers were not clear from the abstract, then the full text was consulted. Only full text papers that were freely available were consulted; if a subscription or payment was required, then the result was not included because access to them would vary considerably between individual educators.
Details about the questions asked:
Was the Study About the Use of Learning Styles?
The term ‘Learning Styles’ was taken to mean of one of the 71 Learning Styles inventories described in Figure 4 of Coffield et al. (2004). The studies analyzed had to use Learning Styles in a manner which attempted to understand something about student learning (including the training of educators).
Examples of studies which did not meet this criterion included those about ‘learning styles’ rather than ‘Learning Styles’, i.e., they used the term learning styles as a normal grammatical construct or talked in broad terms about ‘learning styles’. For example, an article may discuss the need to ‘accommodate different learning styles’ without it being conclusively clear that this referred to Learning Styles as defined by Coffield et al. (2004).
What Learning Style is Being Used or Tested?
This was classified using the aforementioned review by Coffield et al. (2004), with appropriate adaption [e.g., studies using variations on the VAK Learning Styles classification (such as ‘VARK’ and ‘VAKT’) were all grouped together].
Does the Study Begin with Positive View Toward Learning Styles?
Yes - Did the study start with a premise that the use/identification of Learning Styles was a useful aim. This could be implicit (e.g., the premise of the study includes an assumption that it is useful to identify a learner’s Learning Style even if the finding is then that Learning Styles are not effective in that context).
No – The study was setting out to test Learning Styles themselves, e.g., to determine whether their use was valid.
Does the Study Conclude with Positive View Toward Learning Styles?
Yes – The study concluded that the use of Learning Styles was effective for student learning. This again could be implicit – for example, studies where a group of participants are classified using a Learning Styles inventory and the conclusion is then that the dominant Learning Styles in this group are X and Y.
No – The study concluded that the use of Learning Styles by educators was not effective for student learning.
Did the study test the ‘matching hypothesis’ as described in Pashler et al. (2008). That is, does matching instruction to a students Learning Style result in improved outcomes?
Do the research findings challenge the conclusions drawn by Pashler et al. (2008) and Coffield et al. (2004)? That is, does the reported evidence support the idea that matching instructional design to individual student Learning Style is effective?
Number of Search Results
The data for search results are shown in Figure 1. The ERIC research database returned more results than PubMed, but both demonstrate that an educator conducting a simple search for “learning styles” would be presented with abundant, modern, results, although there is a suggestion that the numbers of studies may be declining in the ERIC database. These data do not necessarily reflect an increase in use of Learning Styles or in Learning Styles research; there may be a concurrent increase in the total number of publications listed in these databases.
FIGURE 1.Research database search results for the term “Learning Styles” filtered by individual calendar year.
Endorsement of Learning Styles
For ERIC, the initial search for recent papers returned 110 unique results, of which 54 met the inclusion criteria. For PubMed, the initial search returned 126 unique results; 57 of these met the inclusion criteria. ‘Unique results’ refers to results that appeared only once within that database. Two studies were present in both databases and so were excluded from any pooled analysis (N = 109). The results of the subsequent analysis are shown in Table 1.
TABLE 1.The majority of current research findings in the PubMed and ERIC databases endorse the use of Learning Styles.
Most (94%) of the current research papers start out with a positive view of Learning Styles, despite the aforementioned research which discredits their use. Six papers started out with positive intent, but reached a negative conclusion regarding the use of Learning Styles.
One study, not shown in Table 1, described testing a ‘matching hypothesis’ and appeared to show that matching had some benefit, but from the data presented it was not clear whether it was truly a matching hypothesis as proposed by Pashler et al. (2008), or which specific Learning Style inventory was being tested, or how the data were analyzed (Surjono, 2015).
Type of Learning Style
The majority of papers featured a single Learning Style. The Kolb classification accounted for 34% of all papers, while VAK-type classifications accounted for 33%. The Felder–Silverman (and Felder–Soloman) classifications accounted for (12%). Other featured classifications included Vermunt (2 of the 109 studies) Honey and Mumford (itself derived from Kolb) (3), Grasha–Reischmann (4), Myers–Briggs type (4), Biggs Study Process Questionnaire (2), Dunn and Dunn (1), and Gregorc (1). Five publications addressed Learning Styles generally.
Type of Participant
The studies included participants from across a wide variety of disciplines. Notably, for the studies obtained using PubMed, students in health professions programs (medicine, nursing, dentistry, etc.,) dominated, accounting for a total of 53 out of 57 studies (93%).
Country of Origin
The studies represented a total of 29 different countries around the world, with the single biggest contribution coming from the USA (41 studies, 33%) followed by Turkey (10, 8%).
Approximately half (125) of the search results were not analyzed. More than half of these (66) were not demonstrably about ‘Learning Styles’, while the full text was not available for 22. Other reasons for exclusion included study populations other than students/teachers in higher education (12), non-English language (6) and the use of ‘Learning Styles’ other than those listed in Coffield et al. (2004) (5).
The data presented here demonstrate that the use of Learning Styles is thriving in Higher Education. This result is somewhat surprising given the rigorous research (Coffield et al., 2004; Pashler et al., 2008) demonstrating the ineffectiveness of Learning Styles, alongside an abundance of critical material in social media. The use of Learning Styles may cause harm through ‘pigeon-holing’ and the diversion of resources away from evidence-based practices (Riener and Willingham, 2010; Willingham et al., 2015). Why, then, is the recent research literature so overwhelmingly misleading?
The literature on cognitive bias indicates that we will seek, or at least be sympathetic to, information which confirms our existing worldview. Confirmation bias has been suggested as a reason for the success of Learning Styles (Riener and Willingham, 2010; Pasquinelli, 2012) and there is much that is attractive about the basic idea of Learning Styles. Thus an educator might reasonably approach the literature with an expectation that Learning Styles are a useful tool. The present study demonstrates that this view would be overwhelmingly confirmed, thus encouraging and perpetuating the use of Learning Styles.
There is another interpretation – if the majority of studies endorse the use of Learning Styles, then maybe Coffield et al. (2004) and Pashler et al. (2008) are wrong? The lack of any evidence base to support the use of Learning Styles was acknowledged by some of the studies found here, despite their overall endorsement of the use of Learning Styles. Some even cite the works of Coffield et al. (2004), Pashler et al. (2008), Willingham et al. (2015), and others. Some engage the literature and defend the use of Learning Styles as identifying ‘learner preferences’ rather than a basis for matching instruction, or as a prompt for students to reflect on how they learn. Overall though, most studies appear generally uncritical – a very common approach is to simply apply a Learning Style classification to a particular type of student, and then make recommendations based upon the findings. These studies do not really engage the aforementioned evidence.
There is an obvious limitation to the findings presented here – a single researcher has analyzed the papers and made a subjective judgment as to whether or not they endorse the use of Learning Styles. This methodology may lack sufficient rigor to be fully endorsed by many advocates of evidence-based education. However, the papers are all in the Supplementary Data Sheet S1. I approached the analysis with an open mind, half expecting to find an abundance of studies decrying Learning Styles. In the end this was overwhelmingly not the case, and I found it relatively straightforward to decide whether a study endorsed the use of Learning Styles.
Conclusion and Recommendations
Learning Styles do not work, yet the current research literature is full of papers which advocate their use. This undermines education as a research field and likely has a negative impact on students.
If you have got this far in reading this perspective, you likely care about education, and about education research. It is in everyone’s interests for educational research and resources – time, money, effort, to be directed toward those educational interventions which demonstrably improve student learning, and away from those which do not. Take a second to run a Google search on your own institution – put in the domain name – youruniversity.edu or.ac.uk or whatever it is, alongside the term “learning styles”. Chances are, something will come up. Start there!
Conflict of Interest Statement
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/article/10.3389/fpsyg.2015.01908
Biesta, G. J. J. (2010). Why “what works” still won’t work: from evidence-based education to value-based education. Stud. Philos. Educ. 29, 491–503. doi: 10.1007/s11217-010-9191-x
CrossRef Full Text | Google Scholar
Coffield, F., Moseley, D., Hall, E., and Ecclestone, K. (2004). Learning Styles and Pedagogy in Post 16 Learning: A Systematic and Critical Review. London: Learning and Skills Research Centre.
Colombo, M., Bucher, L., and Inbar, Y. (2015). Explanatory judgment, moral offense and value-free science. Rev. Philos. Psychol. 1–21. doi: 10.1007/s13164-015-0282-z
CrossRef Full Text | Google Scholar
Dandy, K., and Bendersky, K. (2014). Student and faculty beliefs about learning in higher education: implications for teaching. Int. J. Teach. Learn. High. Educ. 26, 358–380.
Dekker, S., Lee, N. C., Howard-Jones, P., and Jolles, J. (2012). Neuromyths in education: prevalence and predictors of misconceptions among teachers. Front. Psychol. 3:429. doi: 10.3389/fpsyg.2012.00429
PubMed Abstract | CrossRef Full Text | Google Scholar
Lilienfeld, S. O., Lynn, S. J., Ruscio, J., and Beyerstein, B. L. (2011). 50 Great Myths of Popular Psychology: Shattering Widespread Misconceptions about Human Behavior. West Sussex: John Wiley & Sons.
Pashler, H., McDaniel, M., Rohrer, D., and Bjork, R. (2008). Learning styles: concepts and evidence. Psychol. Sci. Public Interest 9, 105–119. doi: 10.1111/j.1539-6053.2009.01038.x
PubMed Abstract | CrossRef Full Text | Google Scholar
Pasquinelli, E. (2012). Neuromyths: why do they exist and persist? Mind Brain Educ. 6, 89–96. doi: 10.1111/j.1751-228X.2012.01141.x
CrossRef Full Text | Google Scholar
Surjono, H. D. (2015). The effects of multimedia and learning style on student achievement in online electronics course – ProQuest. Turk. Online J. Educ. Technol. 14, 116–122.
Keywords: learning styles, evidence-based education, Vark, Kolb, higher education
Citation: Newton PM (2015) The Learning Styles Myth is Thriving in Higher Education. Front. Psychol. 6:1908. doi: 10.3389/fpsyg.2015.01908
Received: 10 September 2015; Accepted: 26 November 2015;
Published: 15 December 2015.
Copyright © 2015 Newton. 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) or licensor 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: Philip M. Newton, email@example.com
Learning styles refer to a range of competing and contested theories that aim to account for differences in individuals' learning. These theories propose that all people can be classified according to their 'style' of learning, although the various theories present differing views on how the styles should be defined and categorized.: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 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 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 There is evidence of empirical and pedagogical problems related to forcing learning tasks to "correspond to differences in a one-to-one fashion". Well-designed studies contradict the widespread "meshing hypothesis" that a student will learn best if taught in a method deemed appropriate for the student's learning style.
There are substantial criticisms of learning-styles approaches from scientists who have reviewed extensive bodies of research. A 2015 peer reviewed article concluded: "Learning styles theories have not panned out, and it is our responsibility to ensure that students know that.":269
Overview of models
There are many different learning styles models; one literature review identified 71 different models.:166–168 Only a few models are described below.
David Kolb's model
David A. Kolb's model is based on his experiential learning model, as explained in his book Experiential Learning. 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.: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::127
- 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.
Although Kolb's model is widely accepted with substantial empirical support and has been revised over the years, a 2013 study sheds light on the model's pitfalls, and suggests that the Learning Style Inventory still "possesses serious weaknesses", which in turn limits the tool's usefulness and validity in measuring and determining a person's dominant learning styles.:44
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.:121–122 Second, they aligned these stages to four learning styles named::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) 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.
Walter Burke Barbe and colleagues proposed three learning modalities (often identified by the acronym VAK):
- Visualising modality
- Auditory modality
- Kinesthetic modality
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. 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.:378 This disconnect between strengths and preferences was confirmed by a subsequent study. Nevertheless, some scholars have criticized the VAK model. Psychologist Scott Lilienfeld and colleagues have argued that much use of the VAK model is nothing more than pseudoscience or a psychological urban legend.
Neil Fleming's VAK/VARK model
Neil Fleming's VARK model expanded upon earlier notions of sensory modalities such as the VAK model of Barbe and colleagues and the representational systems (VAKOG) in neuro-linguistic programming. The four sensory modalities in Fleming's model are:
- Visual learning
- Auditory learning
- Physical learning
- Social learning[disambiguation needed]
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, 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".: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.). Students can use the model to identify their preferred learning style and, it is claimed, maximize their learning by focusing on the mode that benefits them the most. Fleming's model also posits two types of multimodality.
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. This model posits that an individual's perceptual abilities are the foundation of his or her specific learning strengths, or learning styles.
In this model, there are two perceptual qualities: concrete and abstract, and two ordering abilities: random and sequential. 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. 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.
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.
The validity of Gregorc's model has been questioned by Thomas Reio and Albert Wiswell following experimental trials. 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".
Anthony Grasha and Sheryl Riechmann, in 1974, formulated the Grasha-Reichmann Learning Style Scale. 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. 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:
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. 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.
In the 1980s, the National Association of Secondary School Principals (NASSP) formed a task force to study learning styles. 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, but also many other variables such as need for structure, types of motivation, time of day preferences, and so on.: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.":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.: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.:138 Learning has taken place only when one observes a relatively stable change in learner behavior resulting from what has been experienced.
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. Previous versions of the LSI have been criticized for problems with validity, reliability, and other issues. 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. 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."
A completely different Learning Styles Inventory is associated with a binary division of learning styles, developed by Richard Felder and Linda Silverman. 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. Like the LSI mentioned above, this inventory provides overviews and synopses for teachers.
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. 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.
Other methods (usually questionnaires) used to identify learning styles include Neil Fleming's VARK Questionnaire and Jackson's Learning Styles Profiler.:56–59 Many other tests have gathered popularity and various levels of credibility among students and teachers.
In the classroom
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.:20–35
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". 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 student thoughts and ideas into the design of the classroom.
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.
Another scholar who believes that learning styles should have an effect on the classroom is Marilee Sprenger in Differentiation through Learning Styles and Memory. 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.[page needed]
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.[page needed] Methods for auditory learners include repeating words aloud, small-group discussion, debates, listening to books on tape, oral reports, and oral interpretation.[page needed] Methods for tactile/kinesthetic learners include hands-on activities (experiments, etc.), projects, frequent breaks to allow movement, visual aids, role play, and field trips.[page needed] 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. 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.[page needed]
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.[page needed] 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.[page needed]
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.[page needed]
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. 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.: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.
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."
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. 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." 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. 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.
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".
Critique made by Coffield et al.
A 2004 non-peer-reviewed literature review by authors from the University of Newcastle upon Tyne criticized most of the main instruments used to identify an individual's learning style. In conducting the review, Frank Coffield and his colleagues selected 13 of the most influential models of the 71 models they identified,:8–9 including most of the models cited on this page. 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.
One of the most widely known theories assessed by Coffield's team was the learning styles model of Dunn and Dunn. This model is widely used in schools in the United States, and 177 articles have been published in peer-reviewed journals referring to this model.:20 The conclusion of 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.":35
Coffield's team claimed that another model, Anthony Gregorc's Gregorc Style Delineator, was "theoretically and psychometrically flawed" and "not suitable for the assessment of individuals".:20
Critique of Kolb's model
Mark K. Smith compiled and reviewed some critiques of Kolb's model in his article, "David A. Kolb on Experiential Learning". According to Smith's research, there are six key issues regarding the model:
- 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.
It should be noted, however, that the most recent work by Kolb that Smith cites is from 2005, and he does not address the changes in the 2015 edition of Kolb's book Experiential Learning.
Coffield and his colleagues and Mark Smith are not alone in their judgements. 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".: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: "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."
The work of Daniel T. Willingham also holds true to the idea that there is not enough evidence to support a theory describing the differences in learning styles amongst students. In his book Why Don't Students Like School, he claims 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."[page needed] That being said, he concludes 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 are unable to "find them".[page needed]
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. 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. Examples of such negative findings include the research of Laura J. Massa and Richard E. Mayer, as well as more recent research since the 2009 review.
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.).: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.":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." This charge was also discussed by Science, which reported that Pashler said, "Just so... most of [the evidence] is 'weak'."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."
- ^ abcdefghijklCoffield, Frank; Moseley, David; Hall, Elaine; Ecclestone, Kathryn (2004). Learning styles and pedagogy in post-16 learning: a systematic and critical review(PDF). London: Learning and Skills Research Centre. ISBN 1853389188. OCLC 505325671. Archived from the original on 2016-03-04.
- ^ abcdeWillingham, Daniel T.; Hughes, Elizabeth M.; Dobolyi, David G. (July 2015). "The scientific status of learning styles theories". Teaching of Psychology. 42 (3): 266–271. doi:10.1177/0098628315589505.
- ^In one extensive list of learning-styles instruments and theories (Coffield et al. 2004, pp. 166–169), the authors listed three works on learning styles before the 1950s, four from the 1950s, seven from the 1960s, 21 from the 1970s, 22 from the 1980s, and 17 from the 1990s.
- ^ abcdefghiPashler, Harold; McDaniel, Mark; Rohrer, Doug; Bjork, Robert A. (December 2008). "Learning styles: concepts and evidence"(PDF). Psychological Science in the Public Interest. 9 (3): 105–119. doi:10.1111/j.1539-6053.2009.01038.x.
- ^Pritchard, Alan (2014) . "Learning styles". Ways of learning: learning theories and learning styles in the classroom (3rd ed.). Milton Park, Abingdon, Oxon; New York: Routledge. pp. 46–65. ISBN 9780415834926. OCLC 853494423.
- ^ abVasquez, Kris (2009). "Learning styles as self-fulfilling prophecies". In Gurung, Regan A. R.; Prieto, Loreto R. Getting culture: incorporating diversity across the curriculum. Sterling, VA: Stylus. pp. 53–63. ISBN 9781579222796. OCLC 228374299.
- ^Klein, Perry D. (January 2003). "Rethinking the multiplicity of cognitive resources and curricular representations: alternatives to 'learning styles' and 'multiple intelligences'". Journal of Curriculum Studies. 35 (1): 45–81. doi:10.1080/00220270210141891.
- ^ abcdeKolb, David A. (2015) . Experiential learning: experience as the source of learning and development (2nd ed.). Upper Saddle River, NJ: Pearson Education. ISBN 9780133892406. OCLC 909815841.
- ^ abSmith, Donna M.; Kolb, David A. (1996) . User's guide for the learning-style inventory: a manual for teachers and trainers. Boston: McBer. OCLC 38505355.
- ^ abManolis, Chris; Burns, David J.; Assudani, Rashmi; Chinta, Ravi (February 2013). "Assessing experiential learning styles: a methodological reconstruction and validation of the Kolb Learning Style Inventory"(PDF). Learning and Individual Differences. 23: 44–52. doi:10.1016/j.lindif.2012.10.009.
- ^ abMumford, Alan (1997). "Putting learning styles to work". Action learning at work. Aldershot, Hampshire; Brookfield, VT: Gower. pp. 121–135. ISBN 0566078902. OCLC 35777384.
- ^Honey, Peter; Mumford, Alan (2006). Learning styles questionnaire: 80-item version. London: Maidenhead. ISBN 1902899296. OCLC 889619009.
- ^ abBarbe, Walter Burke; Swassing, Raymond H.; Milone, Michael N. (1979). Teaching through modality strengths: concepts practices. Columbus, Ohio: Zaner-Bloser. ISBN 0883091003. OCLC 5990906.
- ^ abcBarbe, Walter Burke; Milone, Michael N. (February 1981). "What we know about modality strengths"(PDF). Educational Leadership. Association for Supervision and Curriculum Development: 378–380.
- ^Krätzig, Gregory P.; Arbuthnott, Katherine D. (February 2006). "Perceptual learning style and learning proficiency: a test of the hypothesis". Journal of Educational Psychology. 98 (1): 238–246. doi:10.1037/0022-06126.96.36.199.
- ^Sharp, John G.; Bowker, Rob; Byrne, Jenny (September 2008). "VAK or VAK-uous?: towards the trivialisation of learning and the death of scholarship". Research Papers in Education. 23 (3): 293–314. doi:10.1080/02671520701755416.
- ^Franklin, Shirley (March 2006). "VAKing out learning styles—why the notion of 'learning styles' is unhelpful to teachers". Education 3–13: International Journal of Primary, Elementary and Early Years Education. 34 (1): 81–87. doi:10.1080/03004270500507644.
- ^ abLilienfeld, Scott O.; Lynn, Steven Jay; Ruscio, John; Beyerstein, Barry L. (2010). "Myth #18: Students learn best when teaching styles are matched to their learning styles". 50 great myths of popular psychology: shattering widespread misconceptions about human behavior. Chichester, UK; Malden, MA: Wiley-Blackwell. pp. 92–99. ISBN 9781405131117. OCLC 396172891.
- ^ abLeite, Walter L.; Svinicki, Marilla; Shi, Yuying (April 2010). "Attempted validation of the scores of the VARK: learning styles inventory with multitrait–multimethod confirmatory factor analysis models". Educational and Psychological Measurement. 70 (2): 323–339. doi:10.1177/0013164409344507.
- ^Fleming, Neil D. (July 1995). "I'm different; not dumb: modes of presentation (VARK) in the tertiary classroom"(PDF). In Zelmer, A. C. Lynn; Zelmer, Amy Elliott. Higher education: blending tradition and technology: proceedings of the 1995 Annual Conference of the Higher Education and Research Development Society of Australasia (HERDSA). Research and development in higher education. 18. Rockhampton: Professional Education Centre, Faculty of Health Science, Central Queensland University. pp. 308–313. OCLC 154135362.
- ^ abFleming, Neil D. (2014). "The VARK modalities". vark-learn.com. Archived from the original on 14 March 2015. Retrieved 9 August 2015.
- ^Kraemer, David J. M.; Rosenberg, Lauren M.; Thompson-Schill, Sharon L. (March 2009). "The neural correlates of visual and verbal cognitive styles". The Journal of Neuroscience. 29 (12): 3792–3798. doi:10.1523/JNEUROSCI.4635-08.2009. PMC 2697032. PMID 19321775.