research on learning styles

Center for Teaching

Learning styles, what are learning styles, why are they so popular.

The term  learning styles is widely used to describe how learners gather, sift through, interpret, organize, come to conclusions about, and “store” information for further use.  As spelled out in VARK (one of the most popular learning styles inventories), these styles are often categorized by sensory approaches:   v isual, a ural, verbal [ r eading/writing], and k inesthetic.  Many of the models that don’t resemble the VARK’s sensory focus are reminiscent of Felder and Silverman’s Index of Learning Styles , with a continuum of descriptors for how learners process and organize information:  active-reflective, sensing-intuitive, verbal-visual, and sequential-global.

There are well over 70 different learning styles schemes (Coffield, 2004), most of which are supported by “a thriving industry devoted to publishing learning-styles tests and guidebooks” and “professional development workshops for teachers and educators” (Pashler, et al., 2009, p. 105).

Despite the variation in categories, the fundamental idea behind learning styles is the same: that each of us has a specific learning style (sometimes called a “preference”), and we learn best when information is presented to us in this style.  For example, visual learners would learn any subject matter best if given graphically or through other kinds of visual images, kinesthetic learners would learn more effectively if they could involve bodily movements in the learning process, and so on.  The message thus given to instructors is that “optimal instruction requires diagnosing individuals’ learning style[s] and tailoring instruction accordingly” (Pashler, et al., 2009, p. 105).

Despite the popularity of learning styles and inventories such as the VARK, it’s important to know that there is no evidence to support the idea that matching activities to one’s learning style improves learning .  It’s not simply a matter of “the absence of evidence doesn’t mean the evidence of absence.”  On the contrary, for years researchers have tried to make this connection through hundreds of studies.

In 2009, Psychological Science in the Public Interest commissioned cognitive psychologists Harold Pashler, Mark McDaniel, Doug Rohrer, and Robert Bjork to evaluate the research on learning styles to determine whether there is credible evidence to support using learning styles in instruction.  They came to a startling but clear conclusion:  “Although the literature on learning styles is enormous,” they “found virtually no evidence” supporting the idea that “instruction is best provided in a format that matches the preference of the learner.”  Many of those studies suffered from weak research design, rendering them far from convincing.  Others with an effective experimental design “found results that flatly contradict the popular” assumptions about learning styles (p. 105). In sum,

“The contrast between the enormous popularity of the learning-styles approach within education and the lack of credible evidence for its utility is, in our opinion, striking and disturbing” (p. 117).

Pashler and his colleagues point to some reasons to explain why learning styles have gained—and kept—such traction, aside from the enormous industry that supports the concept.  First, people like to identify themselves and others by “type.” Such categories help order the social environment and offer quick ways of understanding each other.  Also, this approach appeals to the idea that learners should be recognized as “unique individuals”—or, more precisely, that differences among students should be acknowledged —rather than treated as a number in a crowd or a faceless class of students (p. 107). Carried further, teaching to different learning styles suggests that “ all people have the potential to learn effectively and easily if only instruction is tailored to their individual learning styles ” (p. 107).

There may be another reason why this approach to learning styles is so widely accepted. They very loosely resemble the concept of metacognition , or the process of thinking about one’s thinking.  For instance, having your students describe which study strategies and conditions for their last exam worked for them and which didn’t is likely to improve their studying on the next exam (Tanner, 2012).  Integrating such metacognitive activities into the classroom—unlike learning styles—is supported by a wealth of research (e.g., Askell Williams, Lawson, & Murray-Harvey, 2007; Bransford, Brown, & Cocking, 2000; Butler & Winne, 1995; Isaacson & Fujita, 2006; Nelson & Dunlosky, 1991; Tobias & Everson, 2002).

Importantly, metacognition is focused on planning, monitoring, and evaluating any kind of thinking about thinking and does nothing to connect one’s identity or abilities to any singular approach to knowledge.  (For more information about metacognition, see CFT Assistant Director Cynthia Brame’s “ Thinking about Metacognition ” blog post, and stay tuned for a Teaching Guide on metacognition this spring.)

There is, however, something you can take away from these different approaches to learning—not based on the learner, but instead on the content being learned .  To explore the persistence of the belief in learning styles, CFT Assistant Director Nancy Chick interviewed Dr. Bill Cerbin, Professor of Psychology and Director of the Center for Advancing Teaching and Learning at the University of Wisconsin-La Crosse and former Carnegie Scholar with the Carnegie Academy for the Scholarship of Teaching and Learning.  He points out that the differences identified by the labels “visual, auditory, kinesthetic, and reading/writing” are more appropriately connected to the nature of the discipline:

“There may be evidence that indicates that there are some ways to teach some subjects that are just better than others , despite the learning styles of individuals…. If you’re thinking about teaching sculpture, I’m not sure that long tracts of verbal descriptions of statues or of sculptures would be a particularly effective way for individuals to learn about works of art. Naturally, these are physical objects and you need to take a look at them, you might even need to handle them.” (Cerbin, 2011, 7:45-8:30 )

Pashler and his colleagues agree: “An obvious point is that the optimal instructional method is likely to vary across disciplines” (p. 116). In other words, it makes disciplinary sense to include kinesthetic activities in sculpture and anatomy courses, reading/writing activities in literature and history courses, visual activities in geography and engineering courses, and auditory activities in music, foreign language, and speech courses.  Obvious or not, it aligns teaching and learning with the contours of the subject matter, without limiting the potential abilities of the learners.

• Askell-Williams, H., Lawson, M. & Murray, Harvey, R. (2007). ‘ What happens in my university classes that helps me to learn?’: Teacher education students’ instructional metacognitive knowledge. International Journal of the Scholarship of Teaching and Learning , 1. 1-21.
• Bransford, J. D., Brown, A. L. & Cocking, R. R., (Eds.). (2000). How people learn: Brain, mind, experience, and school (Expanded Edition). Washington, D.C.: National Academy Press.
• Butler, D. L., & Winne, P. H. (1995) Feedback and self-regulated learning: A theoretical synthesis . Review of Educational Research , 65, 245-281.
• Cerbin, William. (2011). Understanding learning styles: A conversation with Dr. Bill Cerbin .  Interview with Nancy Chick. UW Colleges Virtual Teaching and Learning Center .
• Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning. A systematic and critical review . London: Learning and Skills Research Centre.
• Isaacson, R. M. & Fujita, F. (2006). Metacognitive knowledge monitoring and self-regulated learning: Academic success and reflections on learning . Journal of the Scholarship of Teaching and Learning , 6, 39-55.
• Nelson, T.O. & Dunlosky, J. (1991). The delayed-JOL effect: When delaying your judgments of learning can improve the accuracy of your metacognitive monitoring. Psychological Science , 2, 267-270.
• Pashler, Harold, McDaniel, M., Rohrer, D., & Bjork, R.  (2008). Learning styles: Concepts and evidence . Psychological Science in the Public Interest . 9.3 103-119.
• Tobias, S., & Everson, H. (2002). Knowing what you know and what you don’t: Further research on metacognitive knowledge monitoring . College Board Report No. 2002-3 . College Board, NY.

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Systematic review article, how common is belief in the learning styles neuromyth, and does it matter a pragmatic systematic review.

• Swansea University Medical School, Swansea University, Swansea, United Kingdom

A commonly cited use of Learning Styles theory is to use information from self-report questionnaires to assign learners into one or more of a handful of supposed styles (e.g., Visual, Auditory, Converger) and then design teaching materials that match the supposed styles of individual students. A number of reviews, going back to 2004, have concluded that there is currently no empirical evidence that this “matching instruction” improves learning, and it could potentially cause harm. Despite this lack of evidence, survey research and media coverage suggest that belief in this use of Learning Styles theory is high amongst educators. However, it is not clear whether this is a global pattern, or whether belief in Learning Styles is declining as a result of the publicity surrounding the lack of evidence to support it. It is also not clear whether this belief translates into action. Here we undertake a systematic review of research into belief in, and use of, Learning Styles amongst educators. We identified 37 studies representing 15,405 educators from 18 countries around the world, spanning 2009 to early 2020. Self-reported belief in matching instruction to Learning Styles was high, with a weighted percentage of 89.1%, ranging from 58 to 97.6%. There was no evidence that this belief has declined in recent years, for example 95.4% of trainee (pre-service) teachers agreed that matching instruction to Learning Styles is effective. Self-reported use, or planned use, of matching instruction to Learning Styles was similarly high. There was evidence of effectiveness for educational interventions aimed at helping educators understand the lack of evidence for matching in learning styles, with self-reported belief dropping by an average of 37% following such interventions. From a pragmatic perspective, the concerning implications of these results are moderated by a number of methodological aspects of the reported studies. Most used convenience sampling with small samples and did not report critical measures of study quality. It was unclear whether participants fully understood that they were specifically being asked about the matching of instruction to Learning Styles, or whether the questions asked could be interpreted as referring to a broader interpretation of the theory. These findings suggest that the concern expressed about belief in Learning Styles may not be fully supported by current evidence, and highlight the need to undertake further research on the objective use of matching instruction to specific Learning Styles.

Introduction

For decades, educators have been advised to match their teaching to the supposed Learning styles of students ( Hyman and Rosoff, 1984 ). There are now over 70 different Learning Styles classification systems ( Coffield et al., 2004 ). They are largely questionnaire-based; students are asked to self-report their preferences for different approaches to learning and other activities and are then assigned one or more Learning Styles. The VARK classification is perhaps the most well-known ( Newton, 2015 ; Papadatou-Pastou et al., 2020 ), which categorizes individuals as one or more of Visual, Auditory, Read-Write and Kinesthetic learners. Other common Learning Styles classifications in the literature include those by Kolb, Honey and Mumford, Felder, and Dunn and Dunn ( Coffield et al., 2004 ; Newton, 2015 ).

In the mid-2000s two substantial reviews of the literature concluded that there was currently no evidence to support the idea that the matching of instructional methods to the supposed Learning Styles of individual students improved their learning ( Coffield et al., 2004 ; Pashler et al., 2008 ). Subsequent reviews have reached the same conclusion ( Cuevas, 2015 ; Aslaksen and Lorås, 2018 ) and there have been numerous, carefully controlled attempts to test this “matching” hypothesis (e.g., ( Krätzig and Arbuthnott, 2006 ; Massa and Mayer, 2006 ; Rogowsky et al., 2015 , 2020 ; Aslaksen and Lorås, 2019 ). The identification of supposed student Learning Style does not appear to influence the way in which students choose to study ( Husmann and O'Loughlin, 2018 ), and does not correlate with their stated preferences for different teaching methods ( Lopa et al., 2015 ).

Despite this lack of evidence, a number of studies suggest that many educators believe that matching instruction to Learning Style(s) is effective. One of the first studies to test this belief was undertaken in 2009 and looked at various statements about the brain and nervous system which are widespread but which are not supported by research evidence, for example the idea what we only use 10% of our brain, or that we are born with all the brain cells that we will ever have. The study described such statements as “neuromyths” and showed that belief in them was high, including belief in matching of instruction to Learning Styles which was reported by 82% of a sample of trainee teachers in the United Kingdom ( Howard-Jones et al., 2009 ). A number of similar studies have been conducted since, and have reached the same conclusion, with belief in Learning Styles reaching as high as 97.6% in a study of preservice teachers in Turkey ( Dündar and Gündüz, 2016 ).

This apparent widespread belief in an ineffective teaching method has caused concern amongst the education community. Part of the concern arises from a perception that the use of Learning Styles is actually harmful ( Pashler et al., 2008 ; Riener and Willingham, 2010 ; Dekker et al., 2012 ; Rohrer and Pashler, 2012 ; Dandy and Bendersky, 2014 ; Willingham et al., 2015 ). The proposed harms include concerns that learners will be pigeonholed or demotivated by being allocated into a Learning Style. For example, a student who is categorized as an “auditory learner” may conclude that there is no point in pursing studies, or a career, in visual subjects such as art, or written subjects such as journalism and so be demotivated during those classes. They might also conclude that they will be more successful in auditory subjects such as music, and thus inappropriately motivated by unrealistic expectations of success and become demotivated if that success does not materalise. It is worth noting however that many advocates of Learning Styles propose that it may be motivating for individual learners to know their supposed style ( Coffield et al., 2004 ). Another concern is that to try and match instruction to Learning Styles risks wasting resources and effort on an ineffective method. Educators are motivated to try and do the best for their learners, and a logical extension of the matching hypothesis is that educators would need to try and generate 4 or more versions of their teaching materials and activities, to match the different styles identified in whatever classification they have used. Additional concerns are that the continued belief in Learning Styles undermines the credibility of educators and education research, and creates unwarranted and unrealistic expectations of educators ( Newton and Miah, 2017 ). These unrealistic expectations could also manifest when students do not achieve the academic grades that they expect, or do not enjoy, or engage with, their learning; if students are not taught in a way that matches their supposed Learning Style, then they may attribute these negative experiences to a lack of matching and be further demotivated for future study. These concerns, and controversy, have also generated publicity in the media, both the mainstream media and in publications focused on educators ( Pullmann, 2017 ; Strauss, 2017 ; Brueck, 2018 ).

The apparent widespread acceptance of a technique that is not supported by evidence is made more striking by the fact that there are many teaching methods which demonstrably promote learning. Many of these methods are simple and easy to learn, for example the use of practice tests, or the spacing of instruction ( Weinstein et al., 2018 ). These methods are based upon an abundance of research which demonstrates how we learn (and how we don't), in particular the limitations of human working memory for the processing of new information in real time, and the use of strategies to account for those limitation (e.g., Young et al., 2014 ). Unfortunately these evidence-based techniques do not appear to be reflected in teacher-training textbooks ( National Council on Teacher Quality, 2016 ).

The lack of evidence to support the matching hypothesis is now acknowledged by some proponents of Learning Styles theory. For example Richard Felder states in a 2020 opinion piece

“ 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 )

“ I now think of learning styles simply as common patterns of student preferences for different approaches to instruction, with certain attributes - behaviors, attitudes, strengths, and weaknesses - being associated with each preference ”. ( Felder, 2020 )

This specific distinction between the matching/meshing hypothesis, and the existence of individual preferences, is at the heart of many studies which have examined belief in the matching hypothesis. Many studies ask about both preferences and matching. These are very different concepts, but the wording of the questions asked about them is very similar. Here for example is the original wording of the questions used in Howard-Jones et al. (2009) , which has been used in many studies since. Participants are asked to rate their agreement with the statements that;

“ Individuals learn better when they receive information in their preferred learning style (e.g., auditory, visual, kinesthetic) ” ( Matching question) .

and, separately ,

“ Individual learners show preferences for the mode in which they receive information (e.g., visual, auditory, kinesthetic)” ( Preferences question) .

The similarities between these statements creates a risk that participants may not fully distinguish between them. This risk is heightened by the existence of similar-sounding but distinct concepts. For example there is evidence that individuals show fairly stable differences in certain cognitive tests, e.g., of visual or verbal ability, sometimes called a “cognitive style” (e.g., Mayer and Massa, 2003 ). There is also evidence that individuals express reasonably stable preferences for the way in which they receive information, although these preferences do not appear to be correlated with abilities ( Massa and Mayer, 2006 ). This literature, and the underlying science, is complex and multi-faceted, but the nomenclature bears a resemblance to the literature on Learning Styles and the science itself may be the genesis of many Learning Styles theories ( Pashler et al., 2008 ).

This potential overlap in concepts is reflected in studies which have examined what educators understand by the term Learning Styles. A 2020 qualitative study investigated this in detail and found a range of different interpretations of the term Learning Styles. Although the VAK/VARK classification system was the most commonly recognized classification, many educators incorrectly conflated it with other theories, such as Howard Gardeners theory of Multiple Intelligences, and learning theories such as cognitivism. There was also a large diversity in the ways in which educators attempted to account for the use of Learning Styles in their teaching practice. Many educators responded by including a diversity of approaches within their teaching, but not necessarily mapped onto specific Learning Styles instrument or with instruction specific to individuals. For example using a wide variety of audiovisual modalities, or a diversity of active approaches to learning ( Papadatou-Pastou et al., 2020 ). An earlier study reported that participants incorrectly used the term “Learning Styles” interchangeably with “Universal Design for Learning,” and other strategies that take into account individual differences (differentiation) ( Ruhaak and Cook, 2018 ). This complexity is reflected in teacher-training textbooks, which commonly refer to Learning Styles but in a variety of ways, including student motivation and preferences for learning ( Wininger et al., 2019 ). There is also a related misunderstanding about Learning Styles theory; the absence of evidence for a matching hypothesis does not mean that students should all be taught the same way, or that they do not have preferences for how they learn. Attempts to refute the matching hypothesis have been incorrectly interpreted in this way ( Newton and Miah, 2017 ).

Thus, one interpretation of the current literature and surrounding media is that, concern has arisen due to widespread belief in the efficacy of an ineffective and potentially harmful teaching technique, but the participants in studies which report on this widespread belief do not clearly understand what they are being asked, or what the intended consequences are if they disagree with what they are asked.

One set of questions to be addressed in this review then is whether the aforementioned concern is fully justified, and whether this potential confusion is reflected in the data. We examine this by using a systematic review approach to take a broader look at trends and patterns in a larger dataset. The evidence showing a lack of evidence for matching instruction to Learning Styles has been available since 2004. It would be reasonable then to expect that belief in this method would have declined since then, particularly if it is harmful. A related question is whether educators actually use Learning Styles; to generate multiple versions of teaching materials and activities would require considerable additional effort for no apparent benefit, which should also hasten the decline of Learning Styles.

With this is mind, we have conducted a Pragmatic Systematic Review. Pragmatism is an approach to research that attempts to identify results that are useful, relevant to practical issues in the real-world, rather than focusing solely on academic questions ( Duram, 2010 ; Feilzer, 2010 ). Pragmatic Evidence-based Education is an approach which combines the most useful education research evidence and relies on judgement to apply it in specific context ( Newton et al., accepted ). Thus, here we have designed research questions to help us develop and discuss findings which are, we hope, useful to the sector rather than solely of academic interest. In addition, we have included many of the usual measures of study quality associated with a systematic review. However, these are included as results as in themselves, rather than as reasons to include/exclude studies from the review. A detailed picture of the quality of studies should be useful for the sector to determine whether the findings justify the aforementioned concern, and whether it needs to be addressed.

Research Questions

1. What percentage of educators believe in the matching of instruction to Learning Styles?

2. What percentage of educators enact, or plan to enact the matching of instruction to Learning Styles?

3. Has belief in matching instruction to Learning Styles decreased over time?

4. Do evidence-based interventions reduce belief in matching instruction to Learning Styles?

5. Do studies present clear evidence that participants understand the difference between (a) matching instruction to Learning Styles and (b) preferences exhibited by learners for the ways in which they receive information?

The review followed the PRISMA guidelines for conducting and reporting a Systematic Review ( Moher et al., 2009 ), with a consideration of measures of quality and reporting for survey-based research, taken from ( Kelley et al., 2003 ; Bennett et al., 2011 ).

Eligibility Criteria, Information Sources, and Search Strategy

Education research is often published in journals that are outside the immediate field of education, but instead are linked to the subject being learned. Therefore, we used EBSCO to search the following databases: CINAHL Plus with Full Text; eBook Collection (EBSCOhost); Library, Information Science & Technology Abstracts; MEDLINE; APA PsycArticles; APA PsycINFO; Regional Business News; SPORTDiscus with Full Text; Teacher Reference Center; MathSciNet via EBSCOhost; MLA Directory of Periodicals; MLA International Bibliography. We also searched PubMed and the Education Research database ERIC.

The following search terms were used: “belief in learning styles”; “believe in learning styles”; “believed in learning styles”; “Individuals learn better when they receive information in their preferred learning style” (this is the survey question used in the original Howard-Jones paper ( Howard-Jones et al., 2009 ). Neuromyth * ; “learning styles” AND myth AND survey or questionnaire. We used advanced search settings for all sources to apply related words and to ensure that the searches looked for the terms within the full text of the articles. No date restriction was applied to the searches and so the results included items up to and including April 2020.

This returned 1,153 items. Exclusion of duplicates left 838 items. These were then screened according to the inclusion criteria (below). Screening articles on the basis of their titles identified 85 eligible items. The abstracts of these were then evaluated which resulted in 46 items for full-text screening. We also used Google Scholar to search for the same terms. Google Scholar provides better inclusion of non-journal research including of gray literature ( Haddaway et al., 2015 ) and unpublished theses that are hosted on servers outside the normal databases ( Jamali and Nabavi, 2015 ). For example, when searching for the specific survey item used in the original Howard-Jones paper ( Howard-Jones et al., 2009 ) and in many studies subsequently; “Individuals learn better when they receive information in their preferred learning style.” This search returned zero results on ERIC and four result on PsychINFO, but returned 107 results on Google Scholar, most of which were relevant. However, all Google Scholar results had to hand screened in real-time since Google Scholar does not have the same functionality as the databases described above; it includes multiple versions of the same papers, and the search interface is limited, making it difficult to accurately quantify and report search results ( Boeker et al., 2013 ).

Study Selection

To be included in the review a study had to meet the following criteria;

• Survey educators about their belief in the matching of instruction to one or more of the Learning Styles classifications identified in aforementioned reviews ( Coffield et al., 2004 ; Pashler et al., 2008 ) and/or educators use of that matching in their teaching. This included pre-service or trainee teachers (individuals studying toward a teaching qualification).

• Report sufficient data to allow calculation of the number and percentage of respondents stating a belief that individuals learn better when they receive information in their preferred learning style (or use/plan to use Learning Styles theory in this way).

Exclusion criteria included the following

• Surveys of participant groups that were not educators or trainee educators.

• Only survey belief in individual learning preferences (i.e., rather than matching instruction).

• Survey other opinions about Learning Styles, for example whether they explain differences in academic abilities (e.g., Bellert and Graham, 2013 ).

• Survey belief in personalizing learning to suit preferences or other characteristics not included in the Learning Styles literature (e.g., prior educational achievement, “deep, surface or strategic learners.”

Some studies were not explicitly clear that they surveyed belief in matching instruction, but used related non-specific concepts such as the “existence of Learning Styles.” These were excluded unless additional information was available to confirm that the studies specifically surveyed belief in matching instruction to Learning Styles. For example ( Grospietsch and Mayer, 2018 ) reported surveying belief in the existence of Learning Styles. However, the content of this paper discussed knowledge acquisition in the context of matching, and stated that the research instruments was derived from Dekker et al. (2012) , and had been used in an additional paper by the same authors ( Grospietsch and Mayer, 2019 ), while a follow-up paper from the same authors described both these earlier papers as surveying belief in matching instruction to Learning Styles ( Grospietsch and Mayer, 2020 ). These two survey studies were therefore included. Another study ( Canbulat and Kiriktas, 2017 ) was not clear and no additional information was available. Two emails were sent to the corresponding author with a request for clarity, but no response was received.

Application of the inclusion criteria resulted in 33 studies being included, containing a total of 37 samples. We then went back to Google Scholar to search within those articles which cited the 33 included studies. No further studies were identified which met the inclusion criteria.

Data Collection Process

Data were independently extracted from every paper by two authors working separately (PN + AS). Extracted data were then compared and any discrepancies resolved through discussion.

The following metrics were collected where available (all data are shown in Appendix 1 ):

• The year the study was published

• Year that data were collected (where stated, and if different from publication date. If a range was stated, then the year which occupied the majority of the range was taken (e.g., Aug 2014–April 2015 was recorded as 2014).

• Country where the research was undertaken

• Publication type (peer reviewed journal, thesis, gray literature)

• Population type (e.g., academics in HE, teachers, etc.)

• Whether or not funding was received and if so where from

• Whether or not a Conflict of Interest was reported/detected

• Target population size

• Sample size

• “N” (completed returns)

• Average teaching experience of participant group

• Percentage and number of participants who stated agreement with a question regarding belief in the matching of instruction to Learning Styles, and the text of the specific question asked

• Percentage and number of participants who stated agreement with a question regarding belief that learners express preferences for how they receive information, and the text of the specific question asked

• The percentage and number of participants who stated that they did, or would, use matching to instruction in their teaching, and the text of the specific question asked

• The percentage and number of participants who stated agreement with a question regarding belief in the matching of instruction to Learning Styles after any intervention aimed at helping participants understand the lack of evidence for matching instruction to Learning Styles

Summary Measures and Synthesis of Results

Most measures are simple percentages of participants who agreed, or not, with questionnaire statements. Summary measures are then the average of these. In order to account for unequal sample size, simple weighted percentages were calculated; percentages were converted to raw numbers using the stated “N” for an individual sample. The sum of these raw numbers from each study was then divided by the sum of “N” from each study and converted to a percentage. Percentages from individual studies were used as individual data points in groups for subsequent statistical analysis, for example to compare the percentage of participants who believed in matching instruction to the percentage who actually used Learning Styles in this way.

Risk of Bias Within and Across Studies

Bias is defined as anything which leads a review to “over-estimate or under-estimate the true intervention effect” ( Boutron et al., 2019 ). In this case an “intervention effect” would be belief in, or use of, Learning Styles either before or after any intervention, or belief in a preference for receiving information in different ways.

Many concerns regarding bias are unlikely to apply here. For example, publication bias, wherein results are less likely to be reported if they are not statistically significant. Most of the data reported in the studies under consideration here are not subject to tests of significance, so this is less of a concern.

However, a number of other factors affect can generate bias within a questionnaire-type study of the type analyzed here. These factors also affect the external validity of study findings, i.e., how likely is it that study findings can be generalized to other populations. We collected the following information from each study in order to assess the external validity of the studies. These metrics were derived from multiple sources ( Kelley et al., 2003 ; Bennett et al., 2011 ; Boutron et al., 2019 ). Some were calculated from the objective data described above, whereas others were subject to judgement by the authors. In the latter case, each author made an independent judgement and then any queries were resolved through discussion.

• Sampling Method . Each study was classified into one of the following categories. Categories are drawn from the literature ( Kelley et al., 2003 ) and the studies themselves.

◦ Convenience sampling. The survey was distributed to all individuals within a specified population, and data were analyzed from those individuals who voluntarily completed the survey.

◦ Snowball sampling. Participants from a convenience sample were asked to then invite further participants to complete the survey.

◦ Unclassifiable . Insufficient information was provided to allow determination of the sampling method

◦ (no other sampling approaches were used by the included studies)

• Validity Measures

◦ Neutral Invitation . Were participants invited to the study using neutral language. Neutrality in this case was defined as not demonstrating support for, or criticism of, Learning Styles in a way that could influence the response of a participant. An example of a neutral invitation is Dekker et al. (2012) “ The research was presented as a study of how teachers think about the brain and its influence on learning. The term neuromyth was not mentioned in the information for teachers.”

◦ Learning Styles vs. styles of learning . Was sufficient information made available to participants for them to be clear that they were being asked about Learning Styles rather than styles of learning, or preferences ( Papadatou-Pastou et al., 2020 ). For example, was it explained that, in order to identify a Learning Style, a questionnaire needs to be administered which then results in learners being allocated to one or more styles, with named examples (e.g., Newton and Miah, 2017 ).

◦ Matching Instruction . If yes to above, was it also made clear that, according to the matching hypothesis, educators are supposed to tailor instruction to individual learning styles.

Additional Analyses

The following additional analyses were pre-specified in line with our initial research questions.

Has Belief in Matching Instruction to Learning Styles Decreased Over Time?

The lack of evidence to support matching instruction to Learning Styles has been established since the mid-2000s and has been the subject of substantial publicity. We might therefore hypothesize that belief in matching instruction has decreased over time, for example due to the effects of the publicity, and/or from a revision of teacher-training programmes to reflect this evidence. Three different analyses were conducted to test for evidence of a decrease.

1. A Spearman Rank Correlation test was conducted to test for a correlation between the year that the study was undertaken and the percentage of participants who reported a belief in matching instruction to learning styles. A significant negative correlation would indicate a decrease over time.

2. Belief in matching instruction to Learning Styles was compared in trainee teachers vs. practicing teachers. If belief in Learning Styles was declining then we would expect to see lower rates of belief in trainee teachers. Two samples ( Tardif et al., 2015 ; van Dijk and Lane, 2018 ) contained a mix of trainee and qualified teachers and were excluded from this analysis. The samples of teachers in Dekker et al. (2012) and Macdonald et al. (2017) both contained 94% practicing teachers and 6% trainee teachers, and so the samples were counted as practicing teachers for the purpose of this analysis.

3. A Spearman Rank Correlation test was conducted to test for a correlation between the average teaching experience of study participants and the percentage of participants who reported a belief in matching instruction to Learning Styles. If belief in matching instruction to learning styles is decreasing then we might expect to see a negative correlation.

Is There a Difference Between Belief in Learning Styles and Use of Learning Styles

The weighted percentage for each of these was calculated, and the two groups of responses were also compared.

Question Validity Analysis

In many of the studies here, participants were asked about both “preferences for learning” and “matching instruction to Learning Styles.” As described in the introduction, the wording for both questions was similar. If there was confusion about the difference between these two statements, then we would expect the pattern of response to them to be broadly similar. To test for this, we calculated a difference score for each study by subtracting the percentage of participants who believed in matching instruction to Learning Styles from the percentage who agreed that individuals have preferences for how they learn. We then conducted a one-tailed t -test to determine whether the distribution of these scores was significantly different from zero. We also compared both groups of responses.

All datasets were checked for normal distribution before analysis using a Kolmogorov-Smirnov test. Non-parametric tests were used where datasets failed this test. Individual tests are described in the results section.

89.1% of Participants Believe in Matching Instruction to Learning Styles

34/37 samples reported the percentage of participants who stated agreement with an incorrect statement that individuals learn better when they receive information in their preferred learning style. The simple average of these 34 data points is 86.2%. To calculate a weighted percentage, these percentages were converted to raw numbers using the stated “N.” The sum of these raw numbers was then divided by the sum of “N” from the 34 samples to create a percentage. This calculation returned a figure of 89.1%. A distribution of the individual studies is shown in Figure 1 .

Figure 1 . The percentage of participants who stated agreement that individuals learn better when they receive information in their preferred Learning Style. Individual studies are shown with the name of the first author and the year the study was undertaken. Data are plotted as ±95% CI. Bubble size is proportional to the Log10 of the sample size.

No Evidence of a Decrease in Belief Over Time

As described in the methods we undertook three separate analyses to test for evidence that belief in Learning Styles has decreased over time. (1) A Spearman Rank correlation analysis was conducted to test for a relationship between the year a study was conducted and the percentage who reported that they believed in matching instruction to Learning Styles. No significant relationship was found ( r = −0.290, P = 0.102). (2) Belief in matching instruction to Learning Styles was compared in samples of qualified teachers ( N = 16) vs. pre-service teachers ( N = 12) using a Mann-Whitney U test. No significant difference was found ( Figure 2 ). A Mann Whitney U test returned a P value of 0.529 (U = 82). When calculating the weighted percentage from each group, belief in matching was 95.4% for pre-service teachers and 87.8% for qualified teachers. The weighted percentage for participants from Higher Education was 63.6%, although this was not analyzed statistically since these data were calculated from only three studies and these were different to the others in additional ways (see Discussion). (3) A Spearman Rank correlation analysis was conducted to test for a relationship between the mean years of experience reported by a participant group (qualified teachers) and the percentage who reported that the believed in matching instruction to Learning Styles. No significant relationship was found ( r = −0.158, P = 0.642).

Figure 2 . No difference between the percentage of Qualified Teachers vs. Pre-Service Teachers who believe in the efficacy of matching instruction to Learning Styles. The percentage of educators who agreed with each statement was compared by Mann-Whitney U test. P = 0.529.

Effect of Interventions

Four studies utilized some form of training for participants, to explain the lack of current evidence for matching instruction to Learning Styles. A pre-post test analysis was used in these studies to evaluate participants belief in the efficacy of matching instruction to Learning Styles both before and after the training. Calculating a weighted percentage revealed that, in these four studies, belief went from 78.4 to 37.1%. The effect size for this intervention effect was large (Cohens d = 3.6). Comparing these four studies using a paired t -test revealed that the difference between pre and post was significant ( P = 0.012). Results from the individual studies are shown in Figure 3 .

Figure 3 . Interventions which explain the lack of evidence to support the efficacy of matching instruction to Learning Styles are associated with a drop in the percentage of participants who report agreeing that matching is effective. Each of the four studies used a pre-post design to measure self-reported belief. The weighted percentage dropped from 78.4 to 37.1%.

Use of Learning Styles vs. Belief

Seven studies measured self-report of use, or planned use, of matching instruction to Learning Styles. Calculating the weighted average revealed that 79.7% of participants said they used, or intended to use, the matching of instruction to Learning Styles. This was compared to the percentage who reported that they believed in the efficacy of matching instruction. A Mann-Whitney U test was used since four of the seven studies did not measure belief in matching to instruction and so a paired test was not possible. No significant difference was found between the percentage of participants who reported believing that matching instruction to Learning Styles is effective (89.1%), and the percentage who used, or planned to use, it as a teaching method (79.7%) ( P = 0.146, U = 76.5). Data are shown in Figure 4 .

Figure 4 . No difference between the percentage of participants who report believing in the efficacy of matching instruction to Learning Styles, and the percentage who used, or intended to use, Learning Styles in this way. The pooled weighted percentage was 89.1 vs. 79.7%. P = 0.146 by Mann-Whitney U test.

No Difference in Belief in Preferences vs. Belief in Matching Instruction to Learning Styles

As described in the introduction, many studies compared belief in matching instruction to Learning Styles (a “neuromyth”) with a correct statement that individuals show preferences for the mode in which they receive information. Twenty-one studies questioned participants on both their belief in matching instruction to Learning Styles, and their belief that individual learners have preferences for the ways in which they receive information. A Wilcoxon matched-pairs test showed no significant difference between these two datasets ( P = 0.262, W = 57). A difference score was calculated by subtracting the percentage who believe in matching instruction from the percentage who believe that learners show preferences. The mean of these scores was 2.66, with a Standard Deviation of 8.97. A one sample t -test showed that the distribution of these scores was not significantly different from zero ( P = 0.189). The distribution of these scores is shown in Figure 5 and reveals many negative scores, i.e., where belief in matching instruction to Learning Styles is higher than a belief that individuals have preferences for how they receive information.

Figure 5 . No difference between belief in Learning Styles and Learning Preferences. (A) The percentage of participants who report believing that individuals have preferences for how the receive information, and the percentage who report believing that individuals learn better when receiving information in their preferred Learning Style. (B) The difference between these two measures, calculated for individual samples. A negative score means that fewer participants believed that students have preferences for how they received information compared to the percentage who believed that matching instruction to Learning Styles is effective.

Risk of Bias and Validity Measures

A summary table of the individual studies is shown in Table 1 . (The full dataset is available in Appendix 1 ).

Table 1 . Characteristics of included studies.

Of the 34 samples which measured belief in matching instruction to Learning Styles, 30 of them used the same question as used in Howard-Jones et al. (2009 ) (see Introduction). The four which used different questions were “Does Teaching to a Student's Learning Style Enhance Learning?” ( Dandy and Bendersky, 2014 ), “Students learn best when taught in a manner consistent with their learning styles” ( Kilpatrick, 2012 ), “How much do you agree with the thesis that there are different learning styles (e.g., auditory, visual or kinesthetic) that enable more effective learning?” ( Menz et al., 2020 ) and “A pedagogical approach based on such a distinction favors learning” (participants had been previously been asked to rate their agreement with the statement “Some individuals are visual, others are auditory”) ( Tardif et al., 2015 ).

Thirty of the 37 samples included used convenience sampling. Three of the studies used snowballing from convenience sampling, while the remaining 4 were unclassifiable; these were all from one study whose participants were recruited “ at various events related to education (e.g., book fair, pedagogy training sessions, etc.), by word of mouth, and via email invitations to databases of people who had previously enquired about information/courses on neuroscience and education” ( Gleichgerrcht et al., 2015 ). Thus, no studies used a rigorous, representative, random sample and so no further analysis was undertaken on the basis of sampling method. Some studies considered representativeness in their methodology, for example Dekker et al. (2012) reported that the local schools they approached “ could be considered a random selection of schools in the UK and NL” but the participants were then “ Teachers who were interested in this topic and chose to participate.” No information is given about the size of the population or the number of individuals to whom the survey was sent, and no demographic characteristics are given regarding the population.

Response Rate

Only five samples reported the size of the population from which the sample was drawn, and so no meaningful analysis of response rate can be drawn across the 37 samples. In one case ( Betts et al., 2019 ) the inability to calculate a response rate was due to our design rather than the study from which the data were extracted; Betts et al. (2019) reported distributing their survey to a Listserv of 65,780, but the respondents included many non-educators whose data were not relevant for our research question. It is perhaps worth noting however that their total final participant number was 929 and so their total response rate across all participant groups was 1.4%

Neutral Invitation

Nine of the 37 studies presented evidence of using a neutral invitation. None of the remaining studies provided evidence of a biased invitation; the information was simply not provided.

Briefing on Learning Styles and Matching

Two of the 37 studies reported giving participants additional information regarding Learning Styles, sufficient (in our view) for participants to be clear that they were being asked specifically about Learning Styles as defined by Coffield et al., and the matching on instruction to Learning Styles.

We find that 89.1% of 15,045 educators, surveyed from 2009 through to early 2020, self-reported a belief that individuals learn better when they receive information in their preferred Learning Style. In every study analyzed, the majority of educators reported believing in the efficacy of this matching, reaching as high as 97.6% in one study by Dundar and colleagues, which was also the largest study in our analysis, accounting for 19% of the total sample ( Dündar and Gündüz, 2016 ).

Perhaps the most concerning finding from our analysis is that there is no evidence that this belief is decreasing, despite research going back to 2004 which demonstrates that such an approach is ineffective and potentially harmful. We conducted three separate analyses to test for evidence of a decline but found none, in fact the total percentage of pre-service teachers who believe in Learning Styles (95.4%) was higher than the percentage of qualified teachers (87.8%). This finding suggests that belief in matching instruction to Learning Styles is acquired before, or during, teacher training. Tentative evidence in support for this is a preliminary indication that belief in Learning Styles may be lower in educators from Higher Education, where teacher training is less formal and not always compulsory. In addition, Van Dijk and Lane report that overall belief in neuromyths is lower in HE although they do not report this breakdown for their data on Learning Styles ( van Dijk and Lane, 2018 ). However, the studies from Higher Education are small, and two of them are also studies where more information is provided to participants about Learning Styles (see below).

From our pragmatic perspective, there are a number of issues to consider when determining whether these findings should be a cause for alarm, and what to do about them.

The data analyzed here are mostly extracted from studies which assess teacher belief in a range of so-called neuromyths. These all use some version of the questionnaire developed by Howard-Jones and co-workers ( Howard-Jones et al., 2009 ). The value of surveying belief in neuromyths has been questioned, on the basis that, in a small sample of award-winning teachers, there did not appear to be any correlation between belief in neuromyths and receiving a teaching award ( Horvath et al., 2018 ). The Horvath study ultimately proposed that awareness of neuromyths is “irrelevant” to determining teacher effectiveness and played down concerns, expressed elsewhere in the field, that belief in neuromyths might be harmful to learners, or undermine the effectiveness of educators. We have only analyzed one element of the neuromyths questionnaire (Learning Styles), but we share some of the concerns expressed by Horvath and co-workers. The majority (30/34) of the samples analyzed here measured belief in Learning Styles using the original Howard-Jones/Dekker questionnaire. A benefit of having the same questions asked across multiple studies is that there is consistency in what is being measured. However, a problem is that any limitations with that instrument are amplified within the synthesis here. One potential limitation with the Howard-Jones question set is that the “matching” question is asked in many of the same surveys as a “belief” question, as shown in the introduction, potentially leading participants to conflate or confuse the two. Any issues may then be exacerbated by a lack of consistency in what participants understand by “matching instruction to Learning Styles”; this could affect all studies. The potential for multiple interpretations of these questions regarding Learning Styles is acknowledged by some authors (e.g., Morehead et al., 2016 ), and some studies report a lack of clarity regarding the specific meaning of Learning Styles and the matching hypothesis ( Ruhaak and Cook, 2018 ; Papadatou-Pastou et al., 2020 ). This lack of clarity is reflected also in the psychometric properties of Learning Styles instruments themselves, with many failing to meet basic standards of reliability and validity required for psychometric validation ( Coffield et al., 2004 ). In addition, we have previously founds that participants, when advised against matching instruction to Learning Styles, may conclude that this means educators should eliminate any consideration of individual preferences or variety in teaching methods ( Newton and Miah, 2017 ).

Here we found no significant differences between participant responses to the question regarding belief in matching instruction vs. the question about individual preferences, with almost half the studies analyzed actually reporting a higher percentage of participants who believed in matching instruction when compared to belief that individuals have preferences for how they receive information. This is concerning from a basic methodological perspective. The question is normally thus; “ Individual learners show preferences for the mode in which they receive information (e.g., visual, auditory, kinesthetic) .” In any sample of learners, some individuals are going to express preferences. It may not be all learners, and those preferences may not be stable for all learners, and the question does not encompass all preferences, but the question, as asked, cannot be anything other than true.

More relevant for our research questions is the apparent evidence of a lack of clarity within the research instrument; it may not be clear to study participants what the matching hypothesis is and so it is difficult to conclude that the results truly represent belief in matching instruction to Learning Styles. This finding is tentatively supported by our analysis which shows that, in the two studies which give participants additional instructions and guidance to help them understand the matching hypothesis, belief in matching instruction to Learning Styles is much lower, a weighted average of 63.5% ( Dandy and Bendersky, 2014 ; Newton and Miah, 2017 ). However, these are both small studies, and both are conducted in Higher Education rather than school teaching, so the difference may be explained by other factors, for example the amount and nature of teacher-training given to educators in Higher Education when compared to school-teaching. It would be informative to conduct further studies in which more detail was provided to participants about Learning Styles, before they are asked whether or not they believed matching instruction to Learning Styles is effective.

However, even if we conclude that the findings represent, in part, a lack of clarity over the specific meaning of “matching instruction to Learning Styles,” this might itself still be a cause for concern. The theory is very common in teacher training and academic literature ( Newton, 2015 ; National Council on Teacher Quality, 2016 ; Wininger et al., 2019 ) and so we might hope that the meaning and use of it is clear to a majority of educators. An additional potential limitation is that the Howard-Jones question cites VARK as an example of Learning Styles, when there are over 70 different classifications. Thus we have almost no information about belief in other common classifications, such as those devised by Kolb, Honey and Mumford, Dunn and Dunn etc. ( Coffield et al., 2004 ).

79.7% of participants reported that they used, or planned to use, the approach of matching instruction to Learning Styles. This high percentage was surprising since our earlier work ( Newton and Miah, 2017 ) showed that only 33% of participants had used Learning Styles in the previous year. If Learning Styles are ineffective, wasteful of resources and even harmful, then we might predict that far fewer educators would actually use them. There are a number of caveats to the current results. There are only seven studies which report on this and all are small, accounting for <10% of the total sample. Most are not paired, i.e., they do not explicitly ask about belief in the efficacy of Learning Styles and then compare it to use of Learning Styles. The questions are often vague, broad and do not specifically represent an example of matching instruction to individual student Learning Styles as organized into one of the recognized classifications. For example “do you teach to accommodate those differences” (Learning Styles). Agreement with statements like these might reflect a belief that educators feel like they have to say they use them in order to respect any/all individual differences, rather than Learning Styles specifically. In addition this is still a self-report of a behavior, or planned behavior. It would be useful, in further work, to measure actual behavior; how many educators have actually designed distinct versions of educational resources, aligned to multiple specific individual student Learning Styles? This would appear to be a critical question when determining the impact of the Learning Styles neuromyth.

The studies give us little insight into why belief in Learning Styles persists. The theory is consistently promoted in teacher-training textbooks ( National Council on Teacher Quality, 2016 ) although there is some evidence that this is in decline ( Wininger et al., 2019 ). If educators are themselves screened using Learning Styles instruments as students at school, then it seems reasonable that they would then enter teacher-training with a view that the use of Learning Styles is a good thing, and so the cycle of belief would be self-perpetuating.

We have previously shown that the research literature generally paints a positive picture of the use of Learning Styles; a majority of papers which are “about” Learning Styles have been undertaken on the basis that matching instruction to Learning Styles is a good thing to do, regardless of the evidence ( Newton, 2015 ). Thus an educator who was unaware of, or skeptical of, the evidence might be influenced by this. Other areas of the literature reflect this idea. A 2005 meta-analysis published in the Journal of Educational Research attempted to test the effect of matching instruction to the Dunn and Dunn Learning Styles Model. The results were supposedly clear;

“ results overwhelmingly supported the position that matching students' learning-style preferences with complementary instruction improved academic achievement ” ( Lovelace, 2005 ).

A subsequent publication in the same journal in 2007 ( Kavale and LeFever, 2007 ) discredited the 2005 meta-analysis. A number of technical and conceptual problems were identified with the 2005 meta-analysis, including a concern that the vast majority of the included studies were dissertations supervised by Dunn and Dunn themselves, undertaken at the St. John's University Center for the Study of Learning and Teaching Styles, run by Dunn and Dunn. At the time of writing (August 2020), the 2005 meta-analysis has been cited 292 times according to Google Scholar, whereas the rebuttal has been cited 38 times. A similar pattern played out a decade earlier, when an earlier meta-analysis by R Dunn, claiming to validate the Dunn and Dunn Learning Styles model, was published in 1995 ( Dunn et al., 1995 ). This meta-analysis has been cited 610 times, whereas a rebuttal in 1998 ( Kavale et al., 1998 ), has been cited 60 times.

An early attempt by Dunn and Dunn to promote the use of their Learning Styles classification was made on the basis that teachers would be less likely to be the subject of malpractice lawsuits if they could demonstrate that they had made every effort to identify the learning styles of their students ( Dunn et al., 1977 ). This is perhaps an extreme example, but reflective of a general sense that, by identifying a supposed learning style, educators may feel they are doing something useful to help their students.

A particular issue to consider from a pragmatic perspective is that of study quality. Many of the studies did not include key indicators of the quality of survey responses ( Kelley et al., 2003 ; Bennett et al., 2011 ). For example, none of the studies use a defined, representative sample, and very few include sufficient information to allow the calculation of a response rate. From a traditional research perspective, the absence of these indicators undermines confidence in the generalizability of the findings reported here. Pragmatic research defines itself as identifying useful answers to research questions ( Newton et al., accepted ). From this perspective then, we considered it useful to still proceed with an analysis of these studies, and consider the findings holistically. It is useful for the research community to be aware of the limitations of these studies, and we report on these measures of study quality in Appendix 1 . We also think it is useful to report on the evidence, within our findings, of a lack of clarity regarding what is actually meant by the term “Learning Styles.” Taken all together these analyses could prompt further research, using a large representative sample with a high response rate, using a neutral invitation, with a clear explanation of the difference between Learning Styles and styles of Learning. Perhaps most importantly this research should focus on whether educators act on their belief, as described above.

Some of these limitations, in particular those regarding representative sampling, are tempered by the number of studies and a consistency in the findings between studies, and the overall very high rates of self-reported belief in Learning Styles. Thirty-four samples report on this question, and in all studies, the majority of participants agree with the key question. In 25 of the 34 samples, the rate of agreement is over 80%. Even if some samples were not representative, it would seem unlikely to affect the qualitative account of the main finding (although this may be undermined by the other limitations described above).

A summary conclusion from our findings then is that belief in matching instruction to Learning Styles is high and has not declined, even though there is currently no evidence to support such an approach. There are a number of methodological issues which might affect that conclusion, but when taken all together these are insufficient to completely alleviate the concerns which arise from the conclusion; a substantial majority of educators state belief in a technique for which the lack of evidence was established in 2004. In the final section of the discussion here we then consider, from a pragmatic perspective, what are the useful things that we might do with these findings, and consider what could be done to address the concerns which arise from them.

Our findings present some limited evidence that training has some effect on belief in matching instruction to Learning Styles. Only four studies looked at training, but in those studies the percentage who reported that belief in the efficacy of matching instruction to individual Learning Styles dropped from 78.4 to 37.1%. It seems reasonable to conclude that there is a risk of social desirability bias in these studies; if participants have been given training which explains the lack of evidence to support Learning Styles, then they might be reasonably expected to disagree with a statement which supports matching. Even then, for 37.1% of participants to still report that they believe this approach is effective is potentially concerning; it still represents a substantial number of educators. Perhaps more importantly these findings are, like many others discussed here, a self-report of a belief, rather than a measure of actual behavior.

There is already a substantial body of literature which identifies Learning Styles as a neuromyth, or an “urban legend.” A 2018 study analyzed the discourse used in a sample of this literature and concluded that the language used reflected a power imbalance wherein “experts” told practitioners what was true or not. A conclusion was that this language may not be helpful if we truly want to address this widespread belief in a method that is ineffective ( Smets and Struyven, 2018 ). We have previously proposed that a “debunking” approach is unlikely to be effective ( Newton and Miah, 2017 ). It takes time and effort to identify student learning styles, and much more effort to then try and design instruction to match those styles. The sorts of instructors who go to that sort of effort are likely to be motivated by a desire to help their students, and so to be told that they have been propagating a “myth” seems unlikely to be news that it is well received.

Considering these limitations from a pragmatic perspective, it does not seem that training, or debunking, is a useful approach to addressing widespread belief in Learning Styles. It is also difficult to determine whether training has been effective when we have limited data regarding the actual use of Learning Styles theory. It may be better to focus on the promotion of techniques that are demonstrably effective, such as retrieval practice and other simple techniques as described in the introduction. There is evidence that these are currently lacking from teacher training ( National Council on Teacher Quality, 2016 ). Many evidence-based techniques are simple to implement, for example the use of practice tests, the spacing of instruction, and the use of worked examples ( Young et al., 2014 ; Weinstein et al., 2018 ). Concerns exist about the generalizability of education research findings to specific contexts, but these concerns might be addressed by the use of a pragmatic approach ( Newton et al., accepted ).

In summary then, we find a substantial majority of educators, almost 90%, from samples all over the world in all types of education, report that they believe in the efficacy of a teaching technique that is demonstrably not effective and potentially harmful. There is no sign that this is declining, despite many years of work, in the academic literature and popular press, highlighting this lack of evidence. To understand this fully, future work should focus on the objective behavior of educators. How many of us actually match instruction to the individual Learning Styles of students, and what are the consequences when we do? Does it matter? Should we instead focus on promoting effective approaches rather than debunking myths?

Data Availability Statement

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

Author Contributions

PN conceived and designed the study, undertook searches, extracted data, undertook analysis, drafted manuscript, and finalized manuscript. AS re-extracted data and provided critical comments on the manuscript. AS and PN undertook PRIMSA quality analyses.

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.

Acknowledgments

The authors would like to acknowledge the assistance of Gabriella Santiago and Michael Chau who undertook partial preliminary data extraction on a subset of papers identified in an initial search. We would also like to thank Prof Greg Fegan and Dr. Owen Bodger for advice and reassurance with the analysis.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2020.602451/full#supplementary-material

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Keywords: evidence-based education, pragmatism, neuromyth, differentiation, VARK, Kolb, Honey and Mumford

Citation: Newton PM and Salvi A (2020) How Common Is Belief in the Learning Styles Neuromyth, and Does It Matter? A Pragmatic Systematic Review. Front. Educ. 5:602451. doi: 10.3389/feduc.2020.602451

Received: 12 September 2020; Accepted: 25 November 2020; Published: 14 December 2020.

Reviewed by:

Copyright © 2020 Newton and Salvi. 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: Philip M. Newton, p.newton@swansea.ac.uk

This article is part of the Research Topic

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Evidence-Based Higher Education – Is the Learning Styles ‘Myth’ Important?

Associated data.

The basic idea behind the use of ‘Learning Styles’ is that learners can be categorized into one or more ‘styles’ (e.g., Visual, Auditory, Converger) and that teaching students according to their style will result in improved learning. This idea has been repeatedly tested and there is currently no evidence to support it. Despite this, belief in the use of Learning Styles appears to be widespread amongst schoolteachers and persists in the research literature. This mismatch between evidence and practice has provoked controversy, and some have labeled Learning Styles a ‘myth.’ In this study, we used a survey of academics in UK Higher Education ( n = 114) to try and go beyond the controversy by quantifying belief and, crucially, actual use of Learning Styles. We also attempted to understand how academics view the potential harms associated with the use of Learning Styles. We found that general belief in the use of Learning Styles was high (58%), but lower than in similar previous studies, continuing an overall downward trend in recent years. Critically the percentage of respondents who reported actually using Learning Styles (33%) was much lower than those who reported believing in their use. Far more reported using a number of techniques that are demonstrably evidence-based. Academics agreed with all the posited weaknesses and harms of Learning Styles theory, agreeing most strongly that the basic theory of Learning Styles is conceptually flawed. However, a substantial number of participants (32%) stated that they would continue to use Learning Styles despite being presented with the lack of an evidence base to support them, suggesting that ‘debunking’ Learning Styles may not be effective. We argue that the interests of all may be better served by promoting evidence-based approaches to Higher Education.

Introduction

The use of so-called ‘Learning Styles’ in education has caused controversy. The basis for the use of Learning Styles is that individual difference between learners can supposedly be captured by diagnostic instruments which classify learners into ‘styles’ such as ‘visual,’ ‘kinaesthetic,’ ‘assimilator,’ etc. According to many, but not all, interpretations of Learning Styles theory, to teach individuals using methods which are matched to their ‘Learning Style’ will result in improved learning ( Pashler et al., 2008 ). This interpretation is fairly straightforward to test, and, although there are over 70 different instruments for classifying Learning Styles ( Coffield et al., 2004 ) the current status of the literature is that there is no evidence to support the use of Learning Styles in this way ( Pashler et al., 2008 ; Rohrer and Pashler, 2012 ). This has lead to Learning Styles being widely classified as a ‘myth’ ( Geake, 2008 ; Riener and Willingham, 2010 ; Lilienfeld et al., 2011 ; Dekker et al., 2012 ; Pasquinelli, 2012 ; Rato et al., 2013 ; Howard-Jones, 2014 ).

Despite this lack of evidence, it appears that belief in the use of Learning Styles is common amongst schoolteachers – A 2012 study demonstrated that 93% of schoolteachers in the UK agree with the statement “Individuals learn better when they receive information in their preferred Learning Style (e.g., auditory, visual, kinaesthetic) ( Dekker et al., 2012 ).” A 2014 survey reported that 76% of UK schoolteachers ‘used Learning Styles’ and most stated that to do so benefited their pupils in some way ( Simmonds, 2014 ). A study of Higher Education faculty in the USA showed that 64% agreed with the statement “Does teaching to a student’s learning style enhance learning?” ( Dandy and Bendersky, 2014 ). A recent study demonstrated that current research papers ‘about’ Learning Styles, in the higher education research literature, overwhelmingly endorsed their use despite the lack of evidence described above ( Newton, 2015 ). Most of this endorsement was implicit and most of the research did not actually test Learning Styles, rather proceeded on the assumption that their use was a ‘good thing.’ For example, researchers would ask a group of students to complete a Learning Styles questionnaire, and then make recommendations for curriculum reform based upon the results.

This mismatch between the empirical evidence and belief in Learning Styles, alongside the persistence of Learning Styles in the wider literature, has lead to tension and controversy. There have been numerous publications in the mainstream media attempting to explain the limitations of Learning Styles (e.g., Singal, 2015 ; Goldhill, 2016 ) and rebuttals from practitioners who believe that the theory of Learning Styles continues to offer something useful and/or that criticism of them is invalid (e.g., Black, 2016 ). Some of the original proponents of the concept have self-published their own defense of Learning Styles, e.g., ( Felder, 2010 ; Fleming, 2012 ).

The continued use of Learning Styles is, in theory, associated with a number of harms ( Pashler et al., 2008 ; Riener and Willingham, 2010 ; Dekker et al., 2012 ; Rohrer and Pashler, 2012 ; Dandy and Bendersky, 2014 ; Willingham et al., 2015 ). These include a ‘pigeonholing’ of learners according to invalid criteria, for example a ‘visual learner’ may be dissuaded from pursuing subjects which do not appear to match their diagnosed Learning Style (e.g., learning music), and/or may become overconfident in their ability to master subjects perceived as matching their Learning Style. Other proposed harms include wasting resources on an ineffective method, undermining the credibility of education research/practice and the creation of unrealistic expectations of teachers by students.

This study aimed at asking first whether academics in UK Higher Education also believe in Learning Styles. We then attempted to go beyond the controversy and ask whether academics actually use Learning Styles, and how seriously they rate the proposed harms associated with the use of Learning Styles, with the aim of understanding how best to address the persistence of Learning Styles in education. In addition, we compared belief in/use of Learning Styles to some educational techniques whose use is supported by good research evidence, to put the use of, and belief in, Learning Styles into context.

We found that belief in the use of Learning Styles was high (58% of participants), but that actual use of Learning Styles was much lower (33%) and lower than other techniques which are demonstrably effective. The most compelling weakness/harm associated with Learning Styles was a simple theoretical weakness; 90% of participants agreed that Learning Styles are conceptually flawed.

Materials and Methods

Data were collected using an online questionnaire distributed to Higher Education institutions in the UK. Ethical approval for the study was given by the local Research Ethics Committee at Swansea University with informed consent from all subjects.

Participants

The survey was distributed via email. Distribution was undertaken indirectly; emails were sent to individuals at eight different Higher Education institutions across the UK. Those persons were known to the corresponding author as colleagues in Higher Education but not through work related to Learning Styles. Those individuals were asked to send the survey on to internal email distribution lists of academics involved in Higher Education using the following invitation text (approved by the ethics committee) “You are invited to participate in a short anonymous survey about teaching methods in Higher Education. It will take approximately 10–15 min to complete. It is aimed at academics in Higher Education,” followed by a link to the survey which was entitled “Teaching Methods in Higher Education.” Thus the survey was not directly distributed by the authors and did not contain the phrase ‘Learning Styles’ anywhere in the title or introductory text. These strategies of indirect distribution, voluntary completion and deliberately not using the term ‘Learning Styles’ in the title were based upon similar strategies used in similar studies ( Dekker et al., 2012 ; Dandy and Bendersky, 2014 ) and were aimed at avoiding biasing and/or polarizing the participant pool, given the aforementioned controversy associated with the literature on Learning Styles. Although this inevitably results in a convenience sample (we do not know how many people the survey as sent to or how many responded), this was preferable to distributing a survey that was expressly about Learning Styles (which may have put off those who are already familiar with the concept). The survey remained open for 2 months (which included the end-of-year holiday period) and was closed once we had over 100 participants who had fully completed the survey, to ensure a sample size equivalent to similar studies ( Dekker et al., 2012 ; Dandy and Bendersky, 2014 ).

One hundred sixty-one participants started the survey, with 114 completing the survey up to the final (optional) question about demographics. This meant that 29% of participants did not complete, which is slightly better than the average dropout rate of 30% for online surveys ( Galesic, 2006 ). Question-by-question analysis revealed that the majority of these non-completers (79%) did not progress beyond the very first ranking question (ranking the effectiveness of teaching methods) and thus did not complete the majority of the survey, including answering those questions about Learning Styles. Participants had been teaching in Higher Education for an average of 11 years ( SD = 9.8). Participants were asked to self-report their academic discipline. Simple coding of these revealed that participants came from a wide variety of disciplines, including Life and Physical Sciences (26%), Arts, humanities and languages (24%), Healthcare professions (medicine, nursing, pharmacy, etc.) (16%), Social Sciences (10%), Business and Law (5%).

Materials and Procedure

The lack of an evidence base for Learning Styles has been described numerous times in the literature, and these papers have suggested that there may be harms associated with the use of Learning Styles ( Pashler et al., 2008 ; Riener and Willingham, 2010 ; Dekker et al., 2012 ; Rohrer and Pashler, 2012 ; Dandy and Bendersky, 2014 ; Willingham et al., 2015 ). We reviewed these publications to identify commonly posited harms. We then constructed a questionnaire using LimeSurvey TM . All the survey questions are available via the Supplementary Material. Key aspects of the structure and design are described below. The survey was piloted by five academics from Medical and Life Sciences, all of whom were aware of the lack of evidence regarding Learning Styles. They were asked to comment on general clarity and were specifically asked to comment on the section regarding the evidence for the use of Learning Styles and whether it would disengage participants (see below). Key concepts in the survey were addressed twice, from different approaches, so as to ensure the quality of data obtained.

Participants were first asked to confirm that they were academics in Higher Education. They were then asked about their use of five teaching methods, four of which are supported by research evidence [Worked Examples, Feedback, Microteaching and Peer Teaching ( Hattie, 2009 )] and Learning Styles. They were then asked to rank these methods by efficacy.

We then asked participants about their use of Learning Styles, both generally and the use of specific classifications (VARK, Kolb, Felder, Honey and Mumford). For each of these individual Learning Styles classifications we identified, in our question, the individual styles that result (e.g., active/reflective, etc., from Felder). Thus participants were fully oriented to what was meant by ‘Learning Styles’ before we went on to ask them about the efficacy of Learning Styles. To allow comparisons with existing literature, we used the same question as Dekker et al. (2012) “Rate your agreement with this statement ‘Individuals learn better when they receive information in their preferred Learning Style (e.g., auditory, visual, kinaesthetic).”’

We then explained to participants about the lack of an evidence base for the use of Learning Styles, including the work of Coffield et al. (2004) , Pashler et al. (2008) , Rohrer and Pashler (2012) , Willingham et al. (2015) . We explained the difference between learning preferences and Learning Style, and made it clear that there was specifically no evidence to support the ‘matching’ of teaching methods to individual Learning Styles. We explained that this fact may be surprising, and that participants would be free to enter any comments they had at the end of the survey. Those academics who piloted the initial survey were specifically asked to comment on this aspect of the survey to ensure that it was neutral and objective.

We then asked participants to rate their agreement with some of the proposed harms associated with the use of Learning Styles. Mixed into the questions about harms were some proposed reasons to use Learning Styles, regardless of the evidence. These questions were interspersed so as to avoid ‘acquiescence bias’ ( Sax et al., 2003 ). Agreement was measured on a 5-point Likert scale.

Finally, participants were asked for some basic demographic information and then offered the opportunity to provide free-text comments on the content of the survey.

Quantitative data were analyzed by non-parametric methods; specific tests are described in the results. Percentages of participants agreeing, or disagreeing, with a particular statement were calculated by collapsing the two relevant statements within the Likert scale (e.g., ‘Strongly Agree and Agree’ were collapsed into a single value). Qualitative data (free-text comments) were analyzed using a simple ground-up thematic analysis ( Braun and Clarke, 2006 ) to identify common themes. Both authors independently read and re-read the comments to identify their own common themes. The authors then met and discussed these, arriving at agreed common themes and quantifying the numbers of participants who had raised comments for each theme. Many participant comments were pertinent to more than one theme.

Belief vs. Use; Do Teachers in Higher Education Actually Use Learning Styles?

We addressed this question from two perspectives. Academics were asked to identify which teaching methods, from a list of 5, they had used in the last 12 months. Results are shown in Figure ​ Figure1 1 . Thirty-three percent of participants reported having used Learning Styles in the last 12 months, but this was lower than the evidence-based techniques of formative assessment, worked examples, and peer teaching. Participants were then asked “have you ever administered a Learning Styles questionnaire to your students” and were given four specific examples along with the ‘styles’ identified by those examples. The examples chosen were those most commonly found in a recent study of the literature on Learning Styles ( Newton, 2015 ). Participants were also given the option to check ‘other’ and identify any other types of Learning Styles questionnaire that they might have used. 33.1% of participants had given their students any sort of Learning Styles Questionnaire, with the response for individual classifications being 18.5% (Honey and Mumford), 14.5% (Kolb), 12.9% (VARK), and 1.6% (Felder).

Use of various teaching methods in the last 12 months. Academics were asked which of the methods they had used in the last 12 months. Four of the methods were accompanied by a brief description: Formative Assessment (practice tests), Peer Teaching (students teaching each other), Learning Styles (matching teaching to student Learning Styles). Microteaching (peer review by educators using recorded teaching).

We subsequently asked two, more general, questions about Learning Styles. The first of these was the same as that used by Dekker et al. “Individuals learn better when they receive information in their preferred Learning Style (e.g., auditory, visual, kinaesthetic),” with which 58% agreed. The second was “I try to organize my teaching to accommodate different student Learning Styles (e.g., visual, kinaesthetic, assimilator/converger),” with which 64% of participants agreed. These data show a contrast between a general belief in the use of Learning Styles, which is much higher than actual use ( Figure ​ Figure2 2 ).

Belief in use of Learning Styles. At different points throughout the survey, participants were asked to rate their agreement with the statements regarding their belief in, and their actual use of, Learning Styles. These questions were asked prior to informing participants about the lack of evidence for the use of Learning Styles. When asked if they believed in the use of Learning Styles 1,2 , approximately two thirds of participants agreed, whereas when asked specifically about actual use 3,4 , agreement dropped to one-third.

1 Rate your agreement with this statement: Individuals learn better when they receive information in their preferred Learning Style (Individuals learn better LS) .

2 Rate your agreement with the statement: I try to organize my teaching to accommodate different Learning Styles (Accomodate LS) .

3 Have you ever administered a Learning Styles questionnaire to your students? If so, please state which one (Given students a LSQ) .

4 Which of these teaching methods have you used in the last 12 months? (Used LS in year) .

Possible Harms Associated with the Use of Learning Styles

There was significant agreement with all the proposed difficulties associated with the use of Learning Styles, as shown in Figure ​ Figure3 3 . However, compared to the other proposed harms, participants showed stronger agreement with the statement “The theory of Learning Styles is conceptually flawed” – it does not account for the complexity of ‘understanding.’ It is not possible to teach complex concepts such as mathematics or languages by presenting them in only one style. In addition, some information cannot be presented in a single style (e.g., teaching medical students to recognize heart sounds would be impossible using visual methods, whereas teaching them to recognize different skin rashes would be impossible using sounds). In this section of the survey we also included two questions that were not about proposed harms. Forty-six percent of participants agreed with the statement “Even though there is no ‘evidence base’ to support the use of Learning Styles, it is my experience that their use in my teaching benefits student learning,” while 70% agreed that “In my experience, students believe, rightly or wrongly, that they have a particular Learning Style.”

Participants were asked to rate their agreement with various difficulties that have been proposed to result from the use of Learning Styles. Participants agreed with all the proposed harms but there was a stronger agreement (compared to other options) with the idea that the use of Learning Styles is conceptually flawed. ∗ , significantly different from median of ‘3’ (1-sample Wilcoxon Signed Rank test). #, different from other statements (Kruskal–Wallis test).

Ranking of Proposed Harms

Having asked participants to rate their agreement (or not) with the various harms associated with the use of Learning Styles, we then asked participants to “Rank the aforementioned factors in terms of how compelling they are as reasons not to use Learning Styles” (1, most compelling, 6, least compelling) and to “only rank those factors which you agree with.” There is not universal agreement on the analysis of ranking data and so we analyzed these data in two simple, descriptive ways. The first was to determine how frequently each harm appeared as the top ranked reason. The second was to calculate a ranking score, such that the top ranked harm was scored 6, and the lowest ranked scored 1, and then to sum these across the participants. Both are shown in Table ​ Table1 1 . Results from both methods were similar and agreed with the prior analysis ( Figure ​ Figure3 3 ), with participants most concerned about the basic conceptual flaws associated with the use of Learning Styles, alongside a potential pigeonholing of learners into a particular style.

Ranking of proposed harms as compelling reasons not to use Learning Styles.

Continued Use of Learning Styles?

Toward the end of the questionnaire, we asked participants two question to determine whether the completion of the questionnaire had made any difference to their understanding of the evidence base for the use of Learning Styles. Participants were first asked to rate their agreement with the statement “Completing this questionnaire has helped me understand the lack of any evidence base to support the use of Learning Styles.” The 64% agreed while 9% disagreed and 27% neither agreed or disagreed.

Participants were then asked “In light of the information presented, rate your agreement with the following statement – ‘I plan to try and account for individual student Learning Styles in my teaching.”’ 31.6% agreed, 43.9% disagreed, and 23.6% neither agreed or disagreed. The results from this question were compared to those obtained before the evidence was presented, when participants were asked to rate their level of agreement with this statement “I try to organize my teaching to accommodate different student Learning Styles (e.g., visual, kinaesthetic, assimilator/converger).” The results, shown in Figure ​ Figure4 4 , show a statistically significant difference in the two sets of responses suggesting that completion of the questionnaire improved participants understanding of the lack of an evidence base for the use of Learning Styles and thus they were unlikely to continue using them. However, almost one-third of participants still agreed with the statement; they intended to continue using Learning Styles.

The completion of the survey instrument associated with a change of participants views of Learning Styles. At the beginning of the study, participants were asked to rate their agreement with the statement “I try to organize my teaching to accommodate different student Learning Styles (e.g., visual, kinaesthetic, assimilator/converger),” and 64% agreed. At the end of the study, participants were asked “In light of the information presented, rate your agreement with the following statement – ‘I plan to try and account for individual student Learning Styles in my teaching,”’ and 32% agreed. ∗ , a Wilcoxon signed rank test revealed a statistically significant difference in the pattern of response ( P < 0.0001, W = -1977).

This then raised a series of interesting questions about why participants would persist in using Learning Styles despite having been presented with all the evidence showing that they are not effective (although participants were not specifically asked whether they would persist in the matching of instructional design to student Learning Style). The sample size here, although equivalent to previous studies, is modest and obviously the 32% are only a portion of that. Thus we were reluctant to undertake extensive post hoc analysis to identify relationships within the sample. However, in response to a reviewer’s suggestion we undertook a simple descriptive analysis of the profile of the 31.6% of participants who indicated that they would continue to account for Learning Styles and compare them to the 43.9% who said that they would not. When splitting the data into these two groups, we observed that almost all (94.4%) of those who said they would still use Learning Styles at the end of the survey had originally agreed with the question “I try to organize my teaching to accommodate different student Learning Styles (e.g., visual, kinaesthetic, assimilator/converger),” and no participants from that group had disagreed. In contrast, agreement was only 40% for the group that eventually said they would not use Learning Styles, while disagreement was 46%. A similar split was found for the question “Even though there is no ‘evidence base’ to support the use of Learning Styles, it is my experience that their use in my teaching benefits student learning”; for the group that would go on to say that they will still use Learning Styles, 89% agreed, while agreement was only 18% from the group that would go on to say they will not continue to use Learning Styles.

Educational Research Literature

Finally we asked participants to rate their agreement with the statement “my educational practice is informed by the education research literature.” Forty-eight percent of participants agreed with the statement. A Spearman Rank Correlation test revealed no correlation between responses on that question and on the ‘Dekker’ question “Individuals learn better when they receive information in their preferred Learning Style (e.g., auditory, visual, kinaesthetic)” r = 0.07508, P = 0.4.

Qualitative Comments

Forty-eight participants left free-text comments. The dominant common theme, raised by 23 participants was the need to use a variety of teaching methods in order to (for example) keep students engaged or to promote reflection. This theme was often stated in the context of ‘despite the evidence again showing a lack of effectiveness of Learning Styles.’ A related theme (13 participants) was that participants had a looser interpretation of ‘Learning Styles,’ for example that they referred simply to ‘styles of learning,’ while a second related theme from nine participants was they would still, despite the evidence, use Learning Styles and/or found them useful. Eight participants commented that they were aware of the lack of evidence base for the use of Learning Styles and eight participants also gave their own examples of why Learning Styles were conceptually flawed. Despite the careful piloting described above, a small number of participants (four) commented that the survey was biased against Learning Styles, while eight participants perceived some of the questions to be ‘leading.’ No specific ‘leading’ questions were identified but there was a substantial overlap between these two themes, with three of the comments about the survey being ‘biased against Learning Styles’ coming alongside, or as part of, a comment about questions being ‘leading,’ with an implied relationship between the two. An additional theme, from five participants, was thanks; for raising the issue and/or interesting content.

The first aim of this study was to determine how widespread belief in, and use of, Learning Styles is by academics in UK Higher Education. In a 2012 study, 93% of a sample of 137 UK school teachers agreed with the statement “Individuals learn better when they receive information in their preferred learning style (e.g., auditory, visual, kinesthetic).” In our sample of academics in UK Higher Education, 58% agreed with that same statement while 64% agreed with the similar, subsequent statement “I try to organize my teaching to accommodate different Learning Styles.” Thus a majority of academics in UK HE ‘believe’ in the use of Learning Styles although the figures are lower than in the 2012 study of schoolteachers. However, prior to asking these questions we asked some more direct questions about the actual use of Learning Styles instruments. Here the figures were much lower, with 33% of participants answering ‘yes’ to the statement “Have you ever administered a Learning Styles questionnaire to your students” and the same number stating that they had used ‘Learning Styles’ as a method in the last 12 months, where the method was defined as “matching teaching to individual student Learning Styles.” This value was lower than for a number of teaching methods that are evidence-based. Interestingly the most commonly used Learning Styles instrument was the Kolb Learning Styles Inventory; this is the Learning Styles classification that has been most frequently tested for evidence of such a ‘matching effect’ and where no evidence has been found ( Pashler et al., 2008 ).

The empirical evidence is clear that there is currently no evidence to support the use of Learning Styles instruments in this way ( Coffield et al., 2004 ; Pashler et al., 2008 ) and thus the fact that actual use of Learning Styles is lower than the use of demonstrably evidence-based methods could be considered reassuring, as could our finding that actual use is lower than ‘belief’ in the efficacy of Learning Styles. In addition, although we find that a majority of UK academics in Higher Education believe in the use of Learning Styles, the actual numbers observed are the lowest of any similar study. Studies examining belief in the use of Learning Styles have been carried out over the last few years in a number of different populations, and the overall trend is down, from 93% of UK schoolteachers in 2012 (Dekker), to 76% of UK schoolteachers in 2014 (Simmonds), 64% of HE academics in the US in 2014 (Dandy and Bendersky) to 58% here. There are obviously a number of caveats to consider before concluding that belief in the use of Learning Styles is declining; these studies have been conducted in different countries (US and UK), using teachers in different disciplines (school teachers and higher education). A follow-up, longitudinal study across different populations/contexts would be informative to address whether belief in the use of Learning Styles is truly declining, and to further understand whether actual use of Learning Styles is lower than ‘belief,’ as we have found here.

However, a more pessimistic interpretation of the data would be to focus on our finding that one-third of academics in UK higher education have, in the last year, used a method that was shown to be ineffective more than a decade earlier. The free-text comments give us some insight into the broader issue and perhaps a further hypothesis as to why the ‘myth’ of Learning Styles persists. The dominant theme was a stated need to use a diverse range of teaching methods. This is a separate issue to the use of Learning Styles and there was no suggestion in the survey that to not use Learning Styles was to advocate for all students to be taught the same way, and/or to use only one method of teaching. Neither of these approaches are advocated by the wider literature which seeks to ‘debunk’ Learning Styles, but it is clear from the abundance of comments on this theme that these two issues were related in the view of many of the participants. This is supported by the emergence of the related theme of ‘styles of learning rather than Learning Styles’; many participants had a looser definition of ‘Learning Styles’ than those introduced early in the survey. This finding leads us to urge caution and clarity in the continued ‘debunking’ of the ‘myth’ of Learning Styles. Learners obviously have preferences for how they learn. In addition, there is an obvious appeal to using a variety of teaching methods and in asking students to reflect on the ways in which they learn. However, these three concepts are unrelated to the (unsupported) idea that there is a benefit to learners from diagnosing their ‘Learning Style’ using one of the specific classifications ( Coffield et al., 2004 ) and attempting to match teaching to those styles. However, these concepts were clearly linked in the mind of many of our participants.

Participants agreed with many of the statements describing proposed harms or weaknesses of Learning Styles. Part of our intention here was to understand which are the most compelling of these; all have, at least, a face validity if not empirical evidence to support them. As we attempt to ‘spread the word’ about Learning Styles and promote alternate, evidence-based approaches, it is useful to know where perceived weaknesses are with Learning Styles. Thus our aim was not so much to observe absolute rates of agreement with individual harms/weaknesses (we would expect to see agreement, given that participants had just been told of the lack of evidence for Learning Styles), but to identify any differences in rates of agreement between the individual statements. There was strongest agreement with the conceptual weaknesses associated with Learning Style theory; that it is not possible to teach ‘understanding’ using a particular style, or to capture certain types of learning in all styles. Weakest agreement was with the statement that “The continued promotion of Learning Styles as a product is exploiting students and their teachers, for the financial gain of those companies which sell access to, and training in, the various Learning Style questionnaires.” The difference between the ‘conceptual weakness’ and other weaknesses/harms was statistically significant, suggesting that, where efforts are being made to ‘debunk’ the ‘myth’ of Learning Styles, then an appeal to the simple conceptual problems may be the most compelling approach. This would also seem to fit with the data described above re: ‘belief vs. use’; although it is tempting to believe that individual students have a Learning Style than can be utilized to benefit their education, the conceptual flaws inherent in the theory mean that actually putting them into practice may prove challenging.

Completion of the questionnaire, which highlighted all of the problems associated with the use of Learning Styles, was clearly associated with a group-shift in the stated likelihood that the participant group would use Learning Styles, although we must also consider that, having been presented with all the evidence that Learning Styles are not effective, it seems reasonable to assume that some participants may succumb to some form of social desirability bias, wherein participants respond in the way that they perceive the researchers desire or expect ( Nederhof, 1985 ). However, despite being presented with all the aforementioned evidence, approximately one-third of participants still agreed with the statement “In light of the information presented……‘I plan to try and account for individual student Learning Styles in my teaching.’” As described in the section “Introduction” there is an ongoing controversy, often played out via blogs and social media, about the use of Learning Styles, with some continuing to advocate for their use despite presentation of all the aforementioned evidence. It is even possible that to persist with a ‘myth debunking’ approach to Learning Styles may be counter-productive; the so-called ‘backfire effect’ describes a phenomenon wherein attempts to counter myths and misconceptions can result in a strengthening of belief in those myths. For example, 43% of the US population believe that the flu vaccine causes flu, and amongst that group are some who are very worried about the side effects of vaccines. Correcting the misconception that the vaccine causes flu is effective in reducing belief in the myth, yet reduces the likelihood that those who are concerned about vaccines will get vaccinated ( Nyhan and Reifler, 2015 ). We observed that almost all those who said they would still use Learning Styles after completing the survey had originally said that they try to account for Learning Styles in their teaching. An interesting question for further study may be to ask, of those who are currently using Learning Styles, whether being presented with the (lack of) evidence regarding their use makes it more likely that those academics will continue to use them? In addition, it may be informative to use an in-depth qualitative approach that would allow us to understand, in detail, what it is about Learning Styles that continues to appeal.

Instead of focusing on Learning Styles, it may be more productive for all, most importantly for students, to focus on the use of teaching and development activities which are demonstrably effective. For example, the use of microteaching, a simple, multi-peer review activity, the effectiveness of which has been repeatedly demonstrated in teacher-training settings ( Yeany and Padilla, 1986 ). Only 12% of survey participants here stated that they had used microteaching within the last 12 months, yet to do so would be relatively straightforward; it is little more than the application of a few more peers to an episode of peer-observation; something that is routinely undertaken by academics in UK Higher Education. This finding may be confounded by participants simply not being aware that ‘microteaching’ means, basically, ‘multi-peer observation and feedback,’ although this was explained twice in the survey itself.

Further support for an approach focused on raising awareness comes from our finding ( Figure ​ Figure1 1 ) that, as a group, participants stated use of different teaching methods mapped directly on to their perceived usefulness (e.g., the most commonly used technique was formative assessment which was also perceived as the most effective). It seems reasonable to infer a causative relationship between these two observations, i.e., that participants use techniques which they consider to be effective, and thus if we can raise awareness of techniques which are demonstrably effective, then their use will increase.

There are some limitations to our study. A review of factors associated with dropouts from online surveys ( Galesic, 2006 ) observed that the average dropout rate amongst general-invitation online surveys (such as this one) is ∼30%, and so our dropout rate is entirely within expectations, although upon reflection we could perhaps have designed the instrument in a way that reduced dropout. A number of factors are associated with higher dropout rates, including the participant’s level of interest in the topic and the presence of ‘matrix questions.’ As described in the methods, we deliberately avoid entitling the survey as being about ‘Learning Styles’ to avoid biasing the responses, and a detailed analysis of the participation rate for each question revealed that the majority of dropouts occurred very early in the survey, after being asked to rank the effectiveness of the five teaching methods; a question potentially requiring higher effort than the others. An additional point reviewed by Galesic (2006) is the evidence that the quality of responses tails off for the items preceding the actual dropout point, thus the fact that participation rate remained steady after this early dropout is reassuring. It would also have been helpful to have a larger sample size. Although ours was equivalent to that in similar studies ( Dekker et al., 2012 ; Dandy and Bendersky, 2014 ) we may have been able to tease out more detail from the responses with a larger sample size, for example to determine whether ‘belief’ in Learning Styles was associated with any of the demographics factors (e.g., subject discipline, or age) to get a deeper understanding of why and where Learning Styles persist.

In summary, we found that 58% of academics in UK Higher Education believe that Learning Styles are effective, but only about a third actually use them, a lower percentage than use other, demonstrably evidence-based techniques. Ninety percent of academics agreed that there is a basic conceptual flaw with Learning Styles Theory. These data suggest that, although there is an ongoing controversy about Learning Styles, their actual use may be low, and further attempts to educate colleagues about this limitation might best focus on the fundamental conceptual limitations of Learning Styles theory. However, approximately one-third of academics stated that they would continue to use Learning Styles despite being presented with all the evidence. Thus it may be better still to focus on the promotion of techniques that are demonstrably effective.

Author Contributions

PN conceived the study, PN and MM designed the questionnaire, PN piloted and distributed the questionnaire, PN and MM analyzed the data, PN wrote the manuscript.

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.

Acknowledgments

The authors would like to thank those colleagues who distributed the survey at their institutions, and Helen Davies from the Swansea Academy of Learning and Teaching for support with Limesurvey TM .

Supplementary Material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00444/full#supplementary-material

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What are Learning Styles and How did They Get Started?

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Learning styles have been around for several years, becoming most popular beginning in the 1970s. Several inventories have been developed to measure learning styles. Although students may indeed have preferences concerning the modality in which they prefer to receive instruction, there is no evidence that students have a certain learning style that is beyond their control. Despite this lack of evidence, the notion of learning styles is alive and well at most institutions of higher education—including the most prominent. Similar to the Myers-Briggs Type Indicator and Multiple Intelligences, learning styles hold appeal for higher education because they provide an explanation for academic struggles outside one’s locus of control. Such a false attribution is not helpful and the learning styles snake oil should be exposed and exterminated.

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Robinson, D.H. (2022). What are Learning Styles and How did They Get Started?. In: Robinson, D.H., Yan, V.X., Kim, J.A. (eds) Learning Styles, Classroom Instruction, and Student Achievement. Monographs in the Psychology of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-90792-1_2

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Learning Styles: Concepts and Evidence

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• 1 University of California, San Diego [email protected].
• 2 Washington University in St. Louis.
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• 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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Learning Styles

The models, myths and misconceptions – and what they mean for your learning.

By the Mind Tools Content Team

It's tempting to try to pin down one "perfect" way of learning. But it can also be dangerous.

Everyone's approach to learning is based on a complex mix of strengths and preferences. And we absorb and apply new concepts, skills and information in different ways at different times.

So, however helpful it would be to find out how each of us does it "best," there are many reasons why even asking the question is far from straightforward.

After all, how we learn depends a great deal on what we're learning. And our preferred learning techniques might not, in fact, be the most useful. Despite this, many scientists, psychologists and education experts have tried to identify distinct, innate "learning styles."

But serious doubts have arisen about some of the most popular models – especially the ways in which they have been applied. There are even concerns that the "labels" they produce might actually limit people's learning.

In this article, we look at how the key learning styles theories were developed, and explore their intentions and limitations. We also show why it's still valuable to understand your personal approach to learning – even if there's no single, "magic bullet" solution for any of us.

What Are Learning Styles?

The notion that everyone has their own learning style became popular in the 1970s. It's an attractive thought: if each of us could identify one, "ideal" approach to learning, we'd be able to focus on it – and be consistently successful.

What's more, by understanding other people's needs, we'd know how best to support them to learn. It could revolutionize education, training and L&D, and help all of us to reach our full potential as learners.

Before we explain why many experts now have little faith in learning styles, let's explore how some of the original ideas came about.

Learn more about the theories behind learning styles – and their drawbacks and limitations.

Different Learning Styles: 6 Influential Models and Theories

1. david kolb and experiential learning.

David Kolb's model of "experiential learning" stated that we learn continually, and, in the process, build particular strengths. Those strengths were said to give rise to personal preferences, which Kolb described in terms of four learning styles: Accommodating , Converging , Diverging , and Assimilating .

As Kolb saw it, Accommodators were "hands-on" types, keen to learn from real experience.

Convergers were supposed to deal better with abstract ideas, but still liked to end up with concrete results. They understood theories, but wanted to test them out in practice.

Divergers tended to use personal experiences and practical ideas to formulate theories that they could apply more widely.

And Assimilators , according to Kolb, were most comfortable working with abstract concepts. They extended their understanding by developing new theories of their own.

Kolb said that it was beneficial to know which type of learner you were, in order to "play to your strengths." He also believed that educators and trainers could tailor their teaching methods to different people's learning styles.

2. Honey and Mumford's Learning Styles

Peter Honey and Alan Mumford developed Kolb's model by focusing on how learning is used in practice, particularly at work. They identified four new learning styles: Activist , Pragmatist , Reflector , and Theorist – using terms that we might naturally pick to describe ourselves and our colleagues.

To find out more about Kolb's model, and about Honey and Mumford's Learning Styles, see our article on the 4MAT approach to learning.

3. Anthony Gregorc's Mind Styles

Anthony Gregorc and Kathleen Butler went into more detail about how we think, and how this might affect the way we learn.

This theory put us all on a spectrum between concrete and abstract thinking, and between sequential and random ordering of our thoughts.

• Concrete perceptions happen through the senses, while abstract perceptions deal with ideas.
• Sequential thinking arranges information in a logical, linear way, while a random approach is multidirectional and unpredictable.

In Gregorc's model, our strengths and weaknesses in each of these areas determined our individual learning style.

4. 4 Learning Styles (VARK)

Educational psychologist Walter Burke Barbe and his colleagues proposed three "modalities" of learning: Visual , Auditory , and Kinesthetic (movement and touch). These were often referred to simply as VAK.

A variation on the acronym, developed by New Zealand-based teacher Neil D. Fleming, is VARK® , or visual, auditory, reading/writing, and kinesthetic. You can find out more about both VAK and VARK in our article, VAK Learning Styles .

Visual Learning Style

A visually-dominant learner absorbs and retains information better when it is presented in, for example, pictures, diagrams and charts.

Auditory Learning Style

An auditory-dominant learner prefers listening to what is being presented. They respond best to voices, for example, in a lecture or group discussion. Hearing their own voice repeating something back to a tutor or trainer is also helpful.

Reading/Writing Learning Style

People with a dominant reading-and-writing learning style take in new information best when they read it as words and text. They're often good at summarizing information in written notes.

Kinesthetic Learning Style

A kinesthetic-dominant learner prefers a physical experience. They like a "hands-on" approach and respond well to being able to touch or feel an object or learning prop.

Barbe was clear that everyone had strengths, weaknesses and preferences in each of the VAK modalities. The most effective learning, he said, utilized all three in combination. He said that the mix we achieved depended on many factors, and would likely change over time.

The VAK model was popular and widely applied. But, like some of the earlier models, it became associated with a fixed outlook on learning. Many people took it to mean that learners could be classified by a single modality – as a "visual learner," for example – with little room for maneuver. And there was confusion over whether the VAK definition referred to someone's innate abilities, their personal preferences, or both.

5. The Learning Styles Task Force

In the 1980s, American educationalists were still trying to find out as much as they could about learning styles, to help classroom teachers to achieve the best possible results.

The National Association of Secondary School Principals (NASSP) formed a research "task force," and proposed additional factors that might affect someone's ability to learn. These included the way study was organized, levels of motivation, and even the time of day when learning took place.

They divided learning styles into three categories: Cognitive , Affective and Physiological .

• Cognitive: how we think, how we organize and retain information, and how we learn from our experiences.
• Affective: our attitudes and motivations, and how they impact our approach to learning.
• Physiological: a variety of factors based on our health, well-being, and the environment in which we learn.

6. The Index of Learning Styles™

Various related questionnaires and tests quickly came into use, aimed at helping people to identify their personal learning style. One of the most popular was based on The Index of Learning Styles™ , developed by Dr Richard Felder and Barbara Soloman in the late 1980s.

The questionnaire considered four dimensions: Sensory/Intuitive , Visual/Verbal , Active/Reflective , and Sequential/Global . The theory was that we're all somewhere on a "continuum" for each of them. Neither extreme was said to be "good" or "bad." Instead, we'd do best by drawing on both ends of the spectrum.

Questionnaires like this promised to define anyone's learning style, so that they could address any "imbalances," and learn in the ways that would benefit them most.

Criticisms of Learning Styles

These and other theories about learning styles have become extremely popular and widespread. However, a growing body of research has challenged many of their claims.

Let's look at the four key criticisms that have been leveled against them:

1. The Science Isn't Strong Enough

We may express our preferences about how we learn, but they're not necessarily an accurate reflection of how our brains work. According to neuroscientist Susan Greenfield , the idea that we can be defined as purely visual, auditory or kinesthetic learners is "nonsense." That's because, she says, "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."

A study by Massa and Mayer also found little difference in learning outcomes when they matched their test subjects' preferences (visual or verbal) to the learning materials they were given.

2. Learning Styles Change

Attempts to "diagnose" someone's learning style once and for all will likely fail. As Eileen Carnell and Caroline Lodge explain in their book " Effective Learning ," an individual's learning method will be different in different situations, and likely change over time.

3. Strengths and Preferences Are Not the Same

An influential piece of research published in the Journal of Educational Psychology revealed big differences between people's assessed strengths, and how they actually tackled learning tasks in practice. For example, someone who scores better in tests after hearing the information might still choose to learn by reading – simply because they enjoy that style of learning more.

4. Teaching to Particular Learning Styles Doesn't Work

For psychologist Scott Lilienfeld, the idea that "students learn best when teaching styles are matched to their learning styles" is one of the " 50 Great Myths of Popular Psychology ." This, he says, "encourages teachers to teach to students' intellectual strengths rather than their weaknesses," limiting their learning as a result.

Using Learning Styles to Improve Learning

Despite the criticisms we've outlined, some of the ideas that underpin learning styles theories still have value – especially the emphasis on metacognition: "thinking about thinking."

One influential collection of research cast doubt on specific learning styles models, but was still positive about metacognition. And metacognition has been shown to improve educational outcomes – leading the Education Endowment Foundation to recommend it as a key teaching and learning tool.

Analyzing our thinking can help us to plan learning strategies that work for us. It can support us to become more organized in our studies, to use prior knowledge as the foundation for new learning, and to choose effective methods for different learning tasks.

Plus, by examining our strengths and weaknesses, we can make the most of any aspects of learning that "come naturally" and that we enjoy, while also working on the areas that might be holding us back.

If you're eager to improve your personal approach to learning, here are three key steps to take:

1. See the Big Picture

Do everything you can to gain a rounded picture of your learning. Look at all the different reasons why you tend to tackle learning the way you do.

And, when you're in the process of learning, ask yourself why you're doing it a particular way. Is it because it's the most effective for you, or simply because it's what you've always done?

Be wary of definitive judgments. Instead, consider different scenarios, and try to differentiate between how you like to learn, and how you learn best – in a variety of learning situations.

2. Identify Your Strengths

Highlight the types of learning that work best for you, and the conditions for learning that support them. For instance, you might be more of an active learner, who operates best in groups.

Keep doing the things that give the best results, to keep your learning fast and effective – and look for ways to improve them even more.

But also leave room to practice and strengthen any learning behaviors that you find more difficult.

3. Work on Your Weaknesses

You can often improve areas of your learning that are letting you down simply by using them more.

If you feel that you're not confident learning visually, for example, get into the habit of reading the charts and diagrams in an article before grappling with the ideas in the text.

Or, if you're an independent learner by nature, make a point of involving others in your problem-solving from time to time.

Also, actively look for opportunities to try out new ways to learn. You might be surprised about what works – and about the new elements of learning that you enjoy.

How to Help Other People to Learn

Becoming more aware of your own strengths and preferences helps you to appreciate and cater for the diverse ways in which others learn, too.

For example, when you're giving a presentation, chairing a meeting, or leading a training session, avoid leaning too heavily on the approach that you would enjoy yourself.

Remember that some learners will benefit from visual aids, while others will rely on listening to what you say, or on watching your body language. Back up abstract theories with real-life examples. Spend time discussing small details as well as outlining large-scale ideas.

You can't always cater for everyone, but you can better engage your audience by allowing for different approaches to learning. If nothing else, your varied approach will keep people energized and alert!

Frequently Asked Questions

What is the kinesthetic learning style.

A learner with a preference for the kinesthetic learning style prefers a physical experience. They like a "hands-on" approach and respond well to being able to touch or feel an object or learning prop.

Can you have two learning styles?

Yes. Or more than two. Very few people, if any, are completely reliant on one learning style. They may favor, say, visual learning, but still be able to learn by reading and writing.

• "Learning Styles" theories attempted to define people by how they learn – based on individual strengths, personal preferences, and other factors such as motivation and favored learning environment.
• Many different Learning Styles models were developed, but even the most popular ones have now been called into question. The main criticisms are that they are unscientific, inflexible, and ineffective in practice.
• However, it's still worth using metacognition – "thinking about thinking" – to work out what does help you to learn. That way, you can play to your strengths, develop any weaker areas, and create the best conditions for learning.
• This level of awareness can also help you to communicate with greater impact, and to support other people to learn.

Butler, K. A. (1988). ' It's All In Your Mind ,' Columbia, CT: Learner's Dimension.

Carnell, E. and Lodge, C. (2002). ' Supporting Effective Learning ,' London: Paul Chapman Publishing.

Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning Styles and Pedagogy in Post-16 Learning: a Systematic and Critical Review. LSRC Reference, Learning & Skills Research Center, London. Available here .

Education Endowment Foundation (2018). Metacognition and Self-Regulation [online]. Available here . [Accessed November 13, 2019.]

Felder & Soloman. Index of Learning Styles Questionnaire [online]. Available here . [Accessed November 1, 2019.]

Henry, J. (2007). Professor Pans "Learning Style" Teaching Method [online]. Available here . [Accessed November 1, 2019.]

Honey, P., & Mumford, A. (1982). ' The Manual of Learning Styles .' Maidenhead: Peter Honey.

Keefe, J. W. (1985). 'Assessment of Learning Style Variables: the NASSP Task Force Model,' Theory into Practice , 24(2), 138-144. Available here .

Kolb, David A. (2015). ‘ Experiential Learning ' (2nd ed.), Upper Saddle River, NJ: Pearson Education.

Krätzig, G. P. and Arbuthnott, K. D. (2006). 'Perceptual learning style and learning proficiency: a test of the hypothesis,' Journal of Educational Psychology , 98(1), 238-246. Available here .

Lilienfeld, S. O., Lynn, S. J., Ruscio, J., & Beyerstein, B. L. (2010). ' 50 Great Myths of Popular Psychology ,' Chichester, UK: Wiley-Blackwell.

Massa, L. J., & Mayer, R. E. (2006). 'Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style?' Learning and Individual Differences , 16(4), 321-335. Available here .

Pashler, H. et al. (2008). ‘Learning Styles: Concepts and Evidence,’ Psychological Science in the Public Interest , 9(3), 105-19. Available here .

VARK is a registered trademark of Vark Learn Ltd., see www.vark-learn.com .

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Learning Styles Debunked: There is No Evidence Supporting Auditory and Visual Learning, Psychologists Say

• Auditory Perception
• Child Development
• Cognitive Psychology
• Learning Styles
• Methodology
• Psychological Science in the Public Interest
• Visual Perception

Are you a verbal learner or a visual learner? Chances are, you’ve pegged yourself or your children as either one or the other and rely on study techniques that suit your individual learning needs. And you’re not alone— for more than 30 years, the notion that teaching methods should match a student’s particular learning style has exerted a powerful influence on education. The long-standing popularity of the learning styles movement has in turn created a thriving commercial market amongst researchers, educators, and the general public.

The wide appeal of the idea that some students will learn better when material is presented visually and that others will learn better when the material is presented verbally, or even in some other way, is evident in the vast number of learning-style tests and teaching guides available for purchase and used in schools. But does scientific research really support the existence of different learning styles, or the hypothesis that people learn better when taught in a way that matches their own unique style?

Unfortunately, the answer is no, according to a major report published in Psychological Science in the Public Interest , a journal of the Association for Psychological Science. The report, authored by a team of eminent researchers in the psychology of learning—Hal Pashler (University of San Diego), Mark McDaniel (Washington University in St. Louis), Doug Rohrer (University of South Florida), and Robert Bjork (University of California, Los Angeles)—reviews the existing literature on learning styles and finds that although numerous studies have purported to show the existence of different kinds of learners (such as “auditory learners” and “visual learners”), those studies have not used the type of randomized research designs  that would make their findings credible.

Nearly all of the studies that purport to provide evidence for learning styles fail to satisfy key criteria for scientific validity. Any experiment designed to test the learning-styles hypothesis would need to classify learners into categories and then randomly assign the learners to use one of several different learning methods, and the participants would need to take the same test at the end of the experiment. If there is truth to the idea that learning styles and teaching styles should mesh, then learners with a given style, say visual-spatial, should learn better with instruction that meshes with that style. The authors found that of the very large number of studies claiming to support the learning-styles hypothesis, very few used this type of research design.  Of those that did, some provided evidence flatly contradictory to this meshing hypothesis, and the few findings in line with the meshing idea did not assess popular learning-style schemes.

No less than 71 different models of learning styles have been proposed over the years. Most have no doubt been created with students’ best interests in mind, and to create more suitable environments for learning. But psychological research has not found that people learn differently, at least not in the ways learning-styles proponents claim. Given the lack of scientific evidence, the authors argue that the currently widespread use of learning-style tests and teaching tools is a wasteful use of limited educational resources.

Could you please direct me to the source material for this? Thank you.

I found the study here: https://www.psychologicalscience.org/journals/pspi/PSPI_9_3.pdf

The study is here: http://www.psychologicalscience.org/journals/pspi/PSPI_9_3.pdf

I doubt a valid study could be created. There are too many variables. I expect we learn by a combination of all inputs. How could a study overcome the issues of quality of the teachers’ presentation, quality of visuals used compared to quality of auditory materials?

Larry, speaking as a statistics student, I’ll propose an answer to the issue of how a “valid study” can be designed. Feel free to call me out if there is an inherent flaw with my proposal.

I will be referring to American students specifically since this is an issue debated for the American school system. I assume the author is talking about the same thing, but I’ll admit I don’t know if this teaching idea is prevalent in other countries. For the sake of this argument, it really doesn’t matter anyways as this variable is easily changed.

The sample is the most difficult part here, I expect there to be a lot of chosen students who’s parents do not wish their children to be a part of the study for some reason or another. It would also have to be conducted locally, or over a short period of time, though doing it locally would have a greater chance of acceptance among chosen participants. The greatest effort should be made to account for demographics, but, again, this would be difficult. (^Not a great way to start, apologies, but I’m sure a seasoned statistician could come up with the solution that I’m afraid I can’t)

Now, you have your grouping of students, say 1,500 for a reasonable number that would provide relatively a relatively small margin of error. Split each of these students into groups of 500, and assign them to a 25 student-per-teacher classroom that each taught only through auditory, visual, or “hands-on” learning. The students are specifically instructed not to take notes. For this example, let’s say they are learning the properties of liquids. The visual classes are taught through packets that each student is given. The “hands-on” class is given a sheet instructing them how to perform a lab and giving them blanks to fill in. Obviously, for this one, a teacher will tell them how to properly handle equipment and said equipment will be protected against the children hurting themselves inadvertently.(ie, no bunsen burners, but maybe a low-heat burner with students only able to turn it on/off and not touch the hot surface) The hearing group will be given a lecture on the subject, with questions being allowed afterward. After a few days learning this way, every student in every class would be given the same test. Then they would all switch, this time learning about the properties of a solid through the same methods, before being tested on it. Lastly, they would switch to learning and testing on the properties of a gas. As a control, through the same selection process, 500 students could be selected to be taught using all three of the described methods in the same timeframe. That is, instead of a packet, a lecture, or a lab, they could receive a lecture while being shown a powerpoint, followed by a lab.

To prevent previous learning bias, I would suggest all students in the sampling population be the same age, while having not received formal education prior. Also, every student should be taught to use the equipment before the experiment so that the “hands-on” group wouldn’t be at an initial disadvantage.

I’m not a teacher, a psychologist, or a professional statistician. This is just my proposal using my current knowledge of statistics. Take it with a grain of salt and form your own opinions, this is simply being put forth in the effort to show that such an experiment seems to be viable given the proper infrastructure and coordination.

Of course, your method makes sense, but it borders on unethical because it is wrong to teach a child anything in a way that they will not understand. I’m not saying you are unethical, but that any scheme that teaches inappropriately (“don’t take notes”) for more than 5 minutes is unethical.

What a bunch of arrogant people to think that they know if there exists one learning style…!? The only learning style we know is the one in our head. How can you say that there is no other creative ways of learning? What about Autistic people? What about Blind people? What about Deaf people? And Bipolar people? And what about Dyslexic people? And people who have a part of verbal speech comprehensions damages in their brain???? Why give so much importance to a little psychology paper? Any body can do a 3 year psychology degree and then write a paper claiming blabla bla

That’s not what they’re saying at all. They’re saying that there are no categories, or boxes, that people can be put in based on their learning style. They’re not saying there is just one way to learn. No need to get so worked up. People with damage to specific parts of their brains or sensory organs are obviously the outlier. Obviously they are going to be radically different.

And publishing a paper in an esteemed journal takes a _little_ bit more than a 3 year BSc in psychology. It’s that comment that really reveales the depth of your ignorance.

As someone diagnosed with high-functioning autism and currently in a concurrent education course, it is much more dangerous to tell someone they should be okay with only learning in one way rather than teaching them to be flexible and learn to absorb information from all sorts of mediums. So I’m gonna assume you’re blind, dyslexic, and autistic because you’ve assumed you can speak for all of them, yes? Your example of someone being blind also helps to further disprove learning theory — which implies nature over nurture — because clearly the ‘visual’ learners who are rendered blind must learn to learn in a different way (which statistically is shown to affect their learning no differently).

…SOMEBODY doesn’t at all understand the scientific method, reasoning or science in general.

I hope that we can finally move past these always dubious “sensory” learning styles. They’re really “modes,” different ways of learning. I’ve long argued that anyone who feels weak at using any of them needs to practice using that mode more, not less. But another old branch of learning styles based on differing neurotransmitter biases seemed to have better prospects, even if I’ve seen little done with it for decades now. I hope we don’t toss out the entire learning style baby with the dirty “sensory style” bathwater. With our updated technology, we could probably go much farther with it. For background, see dated and rather poorly written but better reasoned explanatory work by Jane Gear.

“I’ve long argued that anyone who feels weak at using any of them needs to practice using that mode more, not less.” As a kid already struggling through school with learning disabilities and the resulting long term stress and exhaustion the last thing I needed was to make things more difficult.

Allow me to state categorically that there are learning styles of which to speak specific to learners. To get the issue on hand, the methods proposed by these researchers as a way to disregard the widespread validity or to invalidate the validity of learning proclivities as a concept is not only inapposite, but also akin to saying that every learner approaches the universe of learning in the exact same way. If that is the measure of what we are to agree on as what constitutes scientific efficacy on any issue, then all forms of research are mitigatable and a suspect in the sense of their nature, methods, outcomes, and overall usefulness.

Such a view to research pieces is clearly misguided, ill-informed and half-scientific … even from a commonsense perspective. It serves no social and scientific utility, but for the interest of the investigators.

Mind you, we are not referring to the efficacy of styles presumptive of or correlative to bettering grade acquisition; rather that it should be argued that there are humane, less torturous, comfortable, less arduous and even naturalistic way of teaching students by emphasizing their uniquely preferred styles, wherever determinable.

Even where indeterminable, instructors are to be encouraged to vary their teaching methods to accommodate the learning needs of their captive audience, in this case, their students, and especially not to think that students learn essentially in the very same way as, for example, their instructors.

To think that all learners learn the same way whether in styles or approaches and to even suppose that instruction is a form of a “straight-jacket” and should work with all “body sizes” is in itself a form of miseducation, misrepresentation and,or a type of stiff recalcitrance that should not ever conduce to the mind of an educator, much less a group of psychologists.

Conbach and Snow’s [in the 60’s] work on learning differences, along with findings affecting Trait/Factor analysis are some of few materials that may well serve as enviable pivots for the current exchange.

When it comes to research concerning learning styles…the human dynamics of learning is so complex that attempting to isolate independent variables that may affect learning is like trying to determine the direction of an automobile by studying petroleum chemistry.

The big problem of understanding this is that people don’t focus on the clear and precise language being used, and don’t understand how experimental science works.

What is being said is that “learning styles” theories which denote specific “auditory” and “visual” learning styles do not have any scientific evidence for them. Those who are evaluated to be predominantly “auditory” in terms of a “learning style” do not in fact perform better or differently when taught “visually” and vice versa.

This is important, because while it seems intuitively true that some people might learn better with a specific medium, there is no evidence for it. What there is evidence for is the superiority of multi-modal or multi-media instruction, in terms of learning outcomes.

The main point is don’t waste time on something that has no evidence to support it. See a ranking of effect size on educational reforms to see what is most important, and what is least: https://visible-learning.org/hattie-ranking-influences-effect-sizes-learning-achievement/

I am currently studying to be an ESL teacher and have come across these “learning styles” with in the course. I do have a rather concerning view about them.

I can see that many minds are put behind how we are going to teach and get the “message” across to learners, but sadly i feel like there is an overdose of ego on “who has the better way to teach”. I know that’s a pretty heavy assumption but i can’t conclude much else except maybe there is a fear that the future generation may not learn correctly, which if this is the case, this manifests into over thinking techniques and deviding the way how individuals learn. I do however believe that segregating ways in which people learn is crazy and an over analysed attempt.

As i was studying this i couldn’t help but scrunch my nose in confusion when alot of the individual “learning styles” were something that i have as a “whole” and as an “individual”. I strongly believe that everything works hand in hand.

If i was to simply hold up a picture of someone playing golf and not attach a word or action to it, they would simply know what it looks like but not know what to call it or how it works. Auditory and kinaesthetic would be eliminated and the student will be deprived. But what concerns me is, that i would be compelled to put action to something like this(in a teachers mind) and tell them what we call it (golf). So to be segregating “learning styles” you must be going against a law within your conscience as to how we ALL “learn” this seriously is a no brainer for me.

I must say though not everything is based on science, simply using your brain can solve many of complications. I say that encouragingly not as a rivalry. Hope this was helpful.

Teaching golf would integrate all 4 learning styles. Why not use kinesthetic methods to complement visual, auditory, and logical when appropriate?

Howdy folks! I’d like to understand this a little better. So these guys invalidated all of the studies because they didn’t meet their standard and for that reason they declare that everyone has the same learning style? Is that what they are saying? I don’t see that they setup and carried out a scientific study that meets their own criteria to prove their hypothesis that we all the same learning style. Did I miss something there? Let’s just say the science wasn’t good enough as they say, then that only means that the science hasn’t proved anything. If the science isn’t good enough to prove it right…. then I’m thinking that it doesn’t prove it wrong either. Wouldn’t that just mean that the hypothesis just remains unproven? I wonder too if someone can explain what learning style I’m using when I’m learning how to play my drums? So I’m trying to learn a double stroke roll and feeling the stick bounce and snapping my fingers and wrist at the right moment… it’s all about the feel. To me that’s my kinesthetic learning channel. I’m programming my “muscle memory” is yet another frame for explaining it. Does their conclusion invalidate this learning channel? When it comes to learning songs, I listen by sound. I listen and repeat. I have friends who can only play along with sheet music. They read and play. I didn’t carry out a study to figure this out. I just talk to other drummers and there’s clearly 2 sets of learning styles right there. Many drummers can only sight read. I can’t. I ask then… how is this possible if we all have the same learning style? And the argument is that we should stop wasting money trying to make education better? Really? I think I’ll disengage my gullible learning style and turn on my critical thinking style. …or does that not exist either?

You have to learn to read sheet music , just like reading a book. but it takes effort and once you learn it is good. learning by ear is more natural and maybe you will be more creative because music is audio. The Beatles could not read music. They seem to be saying it has not been determined if audio or visual leaning styles exist. Not whether one is better than the other and if we don’t know if they exist then why spend money behind them. You could invent many other plausible teaching methods and theories and spend a lot of money but maybe the best money spent is on things we know make a difference.

I dont what most people in here are even talking about. Scientific research? In the end it comes down to enjoyment.

The individual is as diverse from one another both in appearance and behaviours. It is not been proven that learning styles are debunked, only that on review by some eminent scientists, a shadow of doubt challenges the premise. Thus if we are diverse creatures it follows we will take in the world in diverse ways, some of us will have more developed auditory facilities, some hardwiring may mean visuals are easier – this is not a study but a fact. We as humans do everything differently than others, perhaps the universal categories should not be bandied about carelessly. But in education in particular, we certainly do take our world in in many and varied forms, construct how we see it and enact a life we see fit, all embedded in our social environment

I was encouraged that the psychologists got put in their place by those of us(teachers) who understand that all children learn differently. Why would you want to frustrate any child with visual learning material that leads to nothing but failure, when the same child can find success with teaching methods that match the child’s learning style?

Byron Thorne author of Toward A Failure-Proof Methodology for Learning To Read.

I love the article and the follow up debate. As a long time educator and student of education it is positive to see all the different perspectives. How to make things manageable for learners? Multi-modal presentations with options for showing one’s understanding and learning. Any teaching can be presented in various ways concurrently as long as we give the students what they need to have access to. My question would be more about how to best engage students so they would be engaged and self-motivated. Love the conversation.

I don’t agree or believe you! I am a visual and auditory learner. It works for me! I was a teacher and everyone has preferred learning styles. Some people do better with a snack. Some are tactile. Your study may be flawed but your conclusions are wrong.c Nance

They can say what they like, but I have seen very different foci in various individuals, with the same-system adherants failing miserably, more often than not, relative to more flexible instructors. I myself cannot grasp complex ideas without first having, or mentally generating, a visual reference.

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Learning Styles Debunked

By Med Kharbach, PhD | Last Update: May 9, 2024

Every time I broach the topic of learning styles theory here, I receive a flurry of negative feedback from teachers. Many label the theory as obsolete and thoroughly debunked. Prompted by this reaction, I decided to delve deeper into what the research actually says. It turns out that while there’s a growing body of research that cautions against the uncritical application of learning styles theory, it’s not completely dismissed as irrelevant. To shed more light on this, I’ve taken the time to synthesize some of the main research critiques for you.

For a refresher of what the learning styles theory is all about, check out the full overview in Learning Styles Theory: Strengths and Weaknesses!

For convenience, I divided it into into three main parts:

1. Quick Scan : For those who prefer a brief glance, this section summarizes the key points of various papers in just a few sentences.

3. Detailed Summaries: If you’re interested in a more comprehensive understanding, section two offers a detailed summary of each critique.

1. My Take : If you’re looking for a quick overview of my findings in the research, check out this section. I’ve distilled the essence of the research into an easily digestible format.

I hope this structure helps you navigate through the information efficiently and gain a clearer understanding of the current stance on learning styles theory.

I. Quick Scan of the Research Debunking Learning Styles Theory

Here is a quick overview of the main points covered in each featured research paper:

An & Carr (2017):

• Critique of the lack of a clear explanatory framework in learning styles theory.
• Problems with measurement and linking learning styles to academic achievement.
• Suggestion to focus on cognitive and developmental psychology for understanding individual learning differences.

Kirschner (2017):

• Argument against tailoring education to preferred learning styles like visual, auditory, or kinesthetic.
• Emphasis on the difference between preferred learning methods and effective learning.
• Lack of scientific validity and support for learning styles theory.

Knoll et al. (2017):

• Investigation of the impact of learning styles on learning performance and Judgments of Learning (JOLs).
• Finding that learning styles may influence subjective perceptions but not objective learning outcomes.

Newton & Miah (2017):

• Challenge to the effectiveness of learning styles in education.
• Highlighting the lack of empirical evidence supporting the theory.
• Discussion on the potential negative impacts of adhering to learning styles theory.

Pashler (2009):

• Critical review of the idea that tailored teaching improves educational outcomes.
• Lack of substantial scientific evidence supporting learning-styles-based instruction.
• Recommendation against incorporating learning styles assessments in education.

Riener & Willingham (2010):

• Assertion that there is no credible evidence for the existence of learning styles.
• Suggestion to understand and apply knowledge about student differences in classroom.
• Attribution of the popularity of learning styles theory to confirmation bias and “common knowledge.”

Rohrer & Pashler (2012):

• Critique of the widespread acceptance of learning styles without empirical scrutiny.
• Questioning the practicality and legitimacy of style-based instruction.
• Conclusion on the lack of empirical justification for tailoring instruction to different learning styles.

Scott (2010):

• Discussion on how the search for individual differences in education led to the popularization of learning styles.
• Argument that learning styles theory continues due to cultural alignment, not effectiveness.
• Emphasis on the opportunity costs of adhering to the learning styles myth.

Williamson & Watson (2007):

• Exploration of the significance of learning styles in education.
• Focus on how a student’s personality correlates with their preferred learning style.
• Caution against using learning style theories to judge students’ intelligence or abilities.

Willingham et al. (2015):

• Examination of the scientific status of learning styles theories.
• Pointing out the lack of belief in the accuracy of learning styles theories due to absent scientific support.
• Highlighting the difficulty in proving a theory definitively wrong but emphasizing the need for evidence to support classroom application.

II. Summary of the Research Criticizing Learning Styles Theory

Here are summaries of each of some of featured research papers critiquing learning styles theory:

1. An, D., & Carr, M. (2017). Learning Styles Theory Fails to Explain Learning and Achievement: Recommendations for Alternative Approaches. The paper “Learning Styles Theory Fails” critiques the traditional concept of learning styles by highlighting its three major flaws: the lack of a clear explanatory framework, problems with measurement, and the failure to link learning styles to actual academic achievement. The authors propose alternative approaches to understanding individual differences in learning, suggesting a focus on factors such as verbal and visual skills, domain knowledge, self-regulation, and perfectionism. These alternative approaches, rooted in cognitive and developmental psychology, aim to provide a more effective framework for predicting and explaining individual learning differences.

The paper argues that learning styles theories are ineffective in explaining the causes of individual differences in student learning and that teaching based on these styles does not result in improved learning. In fact, it often leads to hindered development and poor achievement, as this approach fails to address the learners’ weaknesses.

The authors suggest that a better understanding of individual learning differences can be achieved through cognitive and developmental theories, as well as temperament and personality theories. They recommend that educators focus on these theories, rather than on learning styles, to better cater to the individual differences they observe in their classrooms.

2. Kirschner, P. A. (2017). Stop propagating the learning styles myth In this article, Kirschner argues against the common belief that educational approaches should be tailored to students’ preferred learning styles, such as visual, auditory, or kinesthetic. He highlights major issues with this notion, emphasizing that there’s a significant difference between someone’s preferred way of learning and what actually leads to effective learning. According to the author, the concept of learning styles, often based on categorizing people into distinct groups, lacks support from objective studies and fails to meet key criteria for scientific validity.

The author also urges educators and researchers to stop endorsing the learning styles myth, as it is not grounded in solid evidence. Kirschner concludes that the premise of different learning styles requiring different instructional methods is more of a belief than a proven fact, with little to no scientific backing.

The author further explains that there are fundamental problems with measuring learning styles, and the theoretical basis for the interaction between learning styles and instructional methods is weak. Furthermore, significant empirical evidence supporting the learning-styles hypothesis is almost nonexistent. The concept of learning styles, as the paper confirms, is so vaguely defined that it becomes ineffective for instructional purposes, leading some to adhere to it merely for convenience rather than educational efficacy.

3. Knoll, A. R., Otani, H., Skeel, R. L., & Van Horn, K. R. (2017). Learning style, judgements of learning, and learning of verbal and visual information. This study investigates the impact of learning styles on learning performance, focusing on the relationship between learning styles and Judgments of Learning (JOLs). Participants were assessed for their preference for verbal or visual information and then studied and recalled word and picture pairs while making JOLs.

The results indicated that while preferences for certain types of information were linked to higher immediate JOLs, there was no significant correlation between these preferences and actual recall performance or JOL accuracy, suggesting that learning styles might influence subjective perceptions of learning but not the objective outcomes.

Further analysis in the study explored immediate, delayed, and global JOLs in relation to learning styles. Immediate JOLs were influenced by learning style preferences, reflecting the processing fluency hypothesis (ease of processing influences JOLs) and the beliefs hypothesis (beliefs about learning effectiveness guide JOLs).

However, learning styles showed no significant relation to delayed or global JOLs, which are more reflective of actual learning performance. The paper concludes while learning styles may affect initial perceptions about learning, they do not significantly impact the deeper aspects of learning and memory retrieval.

4. Newton, P. M., & Miah, M. (2017). Evidence-Based Higher Education – Is the Learning Styles ‘Myth’ Important? This pape challenges the effectiveness of learning styles in education. It points out a recurring theme in the critique of learning styles theory which is lack of empirical evidence supporting the idea that matching teaching methods to students’ learning styles enhances learning outcomes. Despite its popularity among educators, the concept, as the authors stated, is labeled a “myth” due to its failure in empirical validation.

Additionally, the paper discusses the potential negative impacts of adhering to the learning styles theory. These include limiting students to specific learning categories, misusing educational resources, and damaging the credibility of educational research. The authors’ survey of UK academics revealed a significant belief in learning styles, but also an acknowledgment of its theoretical flaws. This , as the authors contend, highlights the challenge in changing educational practices based on deeply entrenched beliefs, despite contrary evidence.

5. Pashler. (2009). Learning Styles: Concepts and Evidence The paper “Learning Styles: Concepts and Evidence” critically reviews the idea that educational outcomes improve when teaching is tailored to individual learning styles, such as visual or verbal preferences. Despite the popularity of this concept in education, the authors find no substantial scientific evidence to support the effectiveness of learning-styles-based instruction. They argue that credible validation would require specific experimental findings demonstrating that students learn better when taught according to their preferred learning style.

Their literature review reveals very few studies that meet the necessary criteria to test this theory, and those that do, including a notable study by Sternberg et al., show methodological weaknesses and inconclusive results. Other studies with appropriate designs contradict the popular hypothesis that teaching methods should match individual learning styles.

Consequently, the authors recommend against incorporating learning styles assessments into general educational practice, advising a focus on other educational practices with a stronger evidence base.

6. Riener, C., & Willingham, D. (2010). The Myth of Learning Styles. In the “The Myth of Learning Styles”, Reiner and Willingham assert that there is no credible evidence supporting the existence of learning styles. While acknowledging that learners are indeed different from each other and these differences affect their performance, the authors further explain that these variations do not validate the concept of learning styles. Instead, it suggests that understanding and applying knowledge about student differences in the classroom can improve education. The authors also emphasize that a belief in learning styles is unnecessary for incorporating effective teaching strategies.

According to the authors, the widespread acceptance of learning styles theory is attributed to it becoming “common knowledge,” reinforced by confirmation bias—where people seek information that supports their beliefs while ignoring contrary evidence. This cognitive phenomenon leads to misconceptions about learning preferences and their impact on education.

The article also highlights the opportunity costs of adhering to the learning styles myth, suggesting that educators should instead focus on research in cognitive science and education that offers insights into effective learning strategies. The authors caution that focusing on learning styles, for which there is no solid evidence, may cause educators to overlook scientifically supported research on learning.

7. Rohrer, D., & Pashler, H. (2012). Learning styles: where’s the evidence? The paper “Learning Styles: Where’s the Evidence?” by Doug Rohrer and Harold Pashler critically examines the widespread acceptance of learning styles in educational practices. The authors argue that, unlike evidence-based treatments in modern medicine, most instructional techniques, including learning styles, have not undergone thorough empirical scrutiny. Despite the popularity and profitability of tailoring instruction to students’ supposed learning styles, such as visual or verbal preferences, the authors assert that a comprehensive review of existing data does not support the efficacy of style-based instruction.

The paper highlights that only a few studies have employed the appropriate design to test the effectiveness of style-based instruction, and most of these have resulted in negative findings. The authors question the practicality of style-based instruction, considering its logistical demands and costs, and suggest that the perceived legitimacy of this concept may be more illusory, based on superficial similarities to true observations that do not logically support style-based instruction.

Ultimately, the paper concludes that there is no empirical justification for tailoring instruction to different learning styles and advises educators to focus on developing more effective and cohesive methods of presenting content.

8. Scott, C. (2010). The Enduring Appeal of “Learning Styles.” The paper “The Enduring Appeal of ‘Learning Styles'” discusses how the search for individual differences in education, driven by Western individualism, has led to the popularization of learning styles. Despite extensive research over four decades, there’s no evidence that learning styles can guide effective teaching practices. The theory, according to the author, continues to thrive, not because of its effectiveness, but due to its alignment with cultural values, even though it may perpetuate harmful stereotypes and ineffective teaching methods.

As the Scot states, the interest in individual differences for pedagogical decision-making dates back to the 1960s, but research has consistently failed to support the effectiveness of personalizing teaching based on these differences. While research has identified effective general principles of teaching and learning, these evidence-based practices lack the appeal and simplicity of the learning styles theory.

The paper argues that the continuous promotion of learning styles theory wastes valuable teaching time, promotes damaging stereotypes, and hinders the adoption of evidence-based teaching practices. It emphasizes that learning styles have no place in education if it aims to be scientifically grounded.

9. Williamson, M. F., & Watson, R. L. (2007). Learning Styles Research: Understanding how Teaching Should be Impacted by the Way Learners Learn Part III: Understanding how Learners’ Personality Styles Impact Learning. This paper explores the significance of learning styles in education from the perspectives of both instructors and students. It particularly focuses on how a student’s personality correlates with their preferred learning style, discussing the implications for Christian education contexts.

The paper emphasizes that learning style theory can be instrumental in enhancing the educational process, aiding students to become effective learners and lifelong learners. It suggests that these theories can help educators identify their strengths and weaknesses and align their teaching methods with the diverse learning styles of students.

However, the paper cautions against using learning style theory to judge students’ intelligence or abilities or to label learners, as this could lead to predetermined expectations about student success. Instead, it advises educators to choose and apply the learning style theory that resonates most with them, continually adapting and improving their teaching methods to cater to different types of learners.

10. Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The Scientific Status of Learning Styles Theories. “The Scientific Status of Learning Styles Theories” critically examines the concept of learning styles, which suggests that individuals have specific preferences for processing information that affect their learning. The paper points out that while many believe in the accuracy of learning styles theories, scientific support for these theories is notably absent. The authors argue that educators would be better served by focusing their time and energy on other theories that have a more solid foundation in aiding instruction.

According to the authors, decades of literature reviews have consistently found no viable evidence to support the theory of learning styles. These reviews have highlighted the unreliability of most instruments used to identify learners’ styles. The paper underscores the difficulty in proving a negative—that a theory is definitively wrong—but emphasizes that for a theory to influence classroom practice, it must be supported by evidence. In the case of learning styles, as the authors contend, there needs to be evidence not only of their existence but also that teaching to these styles benefits students in some way.

III. My Take

Reflecting on the critiques of learning styles theory, it’s clear that the concept, although popular, lacks empirical support and practical effectiveness. you can tell from reading the summaries that a recurring theme across almost all of these studies is the lack of empirical evidence to support the effectiveness of learning styles theory.

As a former teacher and current educational researcher, I’ve always been intrigued by the different ways students learn. However, these studies, spanning several decades, consistently highlight the absence of solid scientific evidence supporting the effectiveness of tailoring teaching to specific learning styles, like visual or auditory preferences. The idea that individual preferences in learning translate into more effective educational outcomes has not been substantiated by credible research.

What’s particularly striking is the emphasis on the difference between preferred learning methods and those that actually lead to effective learning. These critiques suggest that while students may have preferences, these do not necessarily correlate with better learning outcomes.

In fact, focusing too much on these supposed learning styles can lead to stereotyping and ineffective teaching strategies, which ultimately hinder the learning process. It’s also noteworthy how learning styles has become embedded in educational discourse, more because of its intuitive appeal and alignment with cultural values, rather than its empirical validity.

Given this, I believe that as educators, we should shift our focus towards more evidence-based teaching practices that consider the diverse needs and capabilities of learners without confining them to rigid categories. Understanding individual differences in abilities and intelligences, and how these can be leveraged in a learning environment, seems to be a more fruitful approach than adhering to the unproven learning styles theory. This shift not only aligns with the scientific evidence but also supports a more inclusive and effective educational practice.

In conclusion, the dive into the research on learning styles theory reveals a nuanced picture. While there’s substantial criticism and evidence challenging the efficacy and scientific basis of this theory, it’s not wholly discarded in educational discourse. The key takeaway is that educators should approach the concept of learning styles with a critical eye and avoid relying on it as the sole framework for designing educational experiences. Instead, it’s advisable to integrate a variety of evidence-based teaching strategies that acknowledge the diverse needs and abilities of students. This balanced approach can lead to more inclusive and effective educational practices, moving beyond the confines of a single, possibly outdated theory. As educators, our goal should always be to adapt and evolve our methods in line with the best available evidence to provide the highest quality education to our students

• An, D., & Carr, M. (2017). Learning styles theory fails to explain learning and achievement: Recommendations for alternative approaches. Personality and Individual Differences, 116, 410–416. https://doi.org/10.1016/j.paid.2017.04.050
• Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers and Education, 106, 166–171. https://doi.org/10.1016/j.compedu.2016.12.006
• Knoll, A. R., Otani, H., Skeel, R. L., & Van Horn, K. R. (2017). Learning style, judgements of learning, and learning of verbal and visual information. The British Journal of Psychology, 108(3), 544–563. https://doi.org/10.1111/bjop.12214
• Newton, P. M., & Miah, M. (2017). Evidence-Based Higher Education – Is the Learning Styles ‘Myth’ Important? Frontiers in Psychology, 8, 444–444. https://doi.org/10.3389/fpsyg.2017.00444
• Pashler. (2009). Learning Styles: Concepts and Evidence. Geological Society of America Bulletin, 9(3), 105–119. https://doi.org/info:doi/
• RIENER, C., & WILLINGHAM, D. (2010). THE MYTH OF LEARNING STYLES. Change, 42(5), 32–35. http://www.jstor.org/stable/25742629
• Rohrer, D., & Pashler, H. (2012). Learning styles: where’s the evidence? Medical Education, 46(7), 634–635. https://doi.org/10.1111/j.1365-2923.2012.04273.x
• Scott, C. (2010). The enduring appeal of “learning styles.” The Australian Journal of Education, 54(1), 5–17. https://doi.org/10.1177/000494411005400102
• Williamson, M. F., & Watson, R. L. (2007). Learning Styles Research: Understanding how Teaching Should be Impacted by the Way Learners Learn Part III: Understanding how Learners’ Personality Styles Impact Learning. Christian Education Journal, 4(1), 62–77. https://doi.org/10.1177/073989130700400105
• Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The Scientific Status of Learning Styles Theories. Teaching of Psychology, 42(3), 266–271. https://doi.org/10.1177/0098628315589505

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Dr. Med Kharbach is an influential voice in the global educational technology landscape, with an extensive background in educational studies and a decade-long experience as a K-12 teacher. Holding a Ph.D. from Mount Saint Vincent University in Halifax, Canada, he brings a unique perspective to the educational world by integrating his profound academic knowledge with his hands-on teaching experience. Dr. Kharbach's academic pursuits encompass curriculum studies, discourse analysis, language learning/teaching, language and identity, emerging literacies, educational technology, and research methodologies. His work has been presented at numerous national and international conferences and published in various esteemed academic journals.

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• Open access
• Published: 11 May 2024

Nursing students’ stressors and coping strategies during their first clinical training: a qualitative study in the United Arab Emirates

• Jacqueline Maria Dias 1 ,
• Muhammad Arsyad Subu 1 ,
• Nabeel Al-Yateem 1 ,
• Fatma Refaat Ahmed 1 ,
• Syed Azizur Rahman 1 , 2 ,
• Mini Sara Abraham 1 ,
• Sareh Mirza Forootan 1 ,
• Farzaneh Ahmad Sarkhosh 1 &
• Fatemeh Javanbakh 1  

BMC Nursing volume  23 , Article number:  322 ( 2024 ) Cite this article

202 Accesses

Metrics details

Understanding the stressors and coping strategies of nursing students in their first clinical training is important for improving student performance, helping students develop a professional identity and problem-solving skills, and improving the clinical teaching aspects of the curriculum in nursing programmes. While previous research have examined nurses’ sources of stress and coping styles in the Arab region, there is limited understanding of these stressors and coping strategies of nursing students within the UAE context thereby, highlighting the novelty and significance of the study.

A qualitative study was conducted using semi-structured interviews. Overall 30 students who were undergoing their first clinical placement in Year 2 at the University of Sharjah between May and June 2022 were recruited. All interviews were recorded and transcribed verbatim and analyzed for themes.

During their first clinical training, nursing students are exposed to stress from different sources, including the clinical environment, unfriendly clinical tutors, feelings of disconnection, multiple expectations of clinical staff and patients, and gaps between the curriculum of theory classes and labatories skills and students’ clinical experiences. We extracted three main themes that described students’ stress and use of coping strategies during clinical training: (1) managing expectations; (2) theory-practice gap; and (3) learning to cope. Learning to cope, included two subthemes: positive coping strategies and negative coping strategies.

Conclusions

This qualitative study sheds light from the students viewpoint about the intricate interplay between managing expectations, theory practice gap and learning to cope. Therefore, it is imperative for nursing faculty, clinical agencies and curriculum planners to ensure maximum learning in the clinical by recognizing the significance of the stressors encountered and help students develop positive coping strategies to manage the clinical stressors encountered. Further research is required look at the perspective of clinical stressors from clinical tutors who supervise students during their first clinical practicum.

Peer Review reports

Nursing education programmes aim to provide students with high-quality clinical learning experiences to ensure that nurses can provide safe, direct care to patients [ 1 ]. The nursing baccalaureate programme at the University of Sharjah is a four year program with 137 credits. The programmes has both theoretical and clinical components withs nine clinical courses spread over the four years The first clinical practicum which forms the basis of the study takes place in year 2 semester 2.

Clinical practice experience is an indispensable component of nursing education and links what students learn in the classroom and in skills laboratories to real-life clinical settings [ 2 , 3 , 4 ]. However, a gap exists between theory and practice as the curriculum in the classroom differs from nursing students’ experiences in the clinical nursing practicum [ 5 ]. Clinical nursing training places (or practicums, as they are commonly referred to), provide students with the necessary experiences to ensure that they become proficient in the delivery of patient care [ 6 ]. The clinical practicum takes place in an environment that combines numerous structural, psychological, emotional and organizational elements that influence student learning [ 7 ] and may affect the development of professional nursing competencies, such as compassion, communication and professional identity [ 8 ]. While clinical training is a major component of nursing education curricula, stress related to clinical training is common among students [ 9 ]. Furthermore, the nursing literature indicates that the first exposure to clinical learning is one of the most stressful experiences during undergraduate studies [ 8 , 10 ]. Thus, the clinical component of nursing education is considered more stressful than the theoretical component. Students often view clinical learning, where most learning takes place, as an unsupportive environment [ 11 ]. In addition, they note strained relationships between themselves and clinical preceptors and perceive that the negative attitudes of clinical staff produce stress [ 12 ].

The effects of stress on nursing students often involve a sense of uncertainty, uneasiness, or anxiety. The literature is replete with evidence that nursing students experience a variety of stressors during their clinical practicum, beginning with the first clinical rotation. Nursing is a complex profession that requires continuous interaction with a variety of individuals in a high-stress environment. Stress during clinical learning can have multiple negative consequences, including low academic achievement, elevated levels of burnout, and diminished personal well-being [ 13 , 14 ]. In addition, both theoretical and practical research has demonstrated that increased, continual exposure to stress leads to cognitive deficits, inability to concentrate, lack of memory or recall, misinterpretation of speech, and decreased learning capacity [ 15 ]. Furthermore, stress has been identified as a cause of attrition among nursing students [ 16 ].

Most sources of stress have been categorized as academic, clinical or personal. Each person copes with stress differently [ 17 ], and utilizes deliberate, planned, and psychological efforts to manage stressful demands [ 18 ]. Coping mechanisms are commonly termed adaptation strategies or coping skills. Labrague et al. [ 19 ] noted that students used critical coping strategies to handle stress and suggested that problem solving was the most common coping or adaptation mechanism used by nursing students. Nursing students’ coping strategies affect their physical and psychological well-being and the quality of nursing care they offer. Therefore, identifying the coping strategies that students use to manage stressors is important for early intervention [ 20 ].

Studies on nursing students’ coping strategies have been conducted in various countries. For example, Israeli nursing students were found to adopt a range of coping mechanisms, including talking to friends, engaging in sports, avoiding stress and sadness/misery, and consuming alcohol [ 21 ]. Other studies have examined stress levels among medical students in the Arab region. Chaabane et al. [ 15 ], conducted a systematic review of sudies in Arab countries, including Saudi Arabia, Egypt, Jordan, Iraq, Pakistan, Oman, Palestine and Bahrain, and reported that stress during clinical practicums was prevalent, although it could not be determined whether this was limited to the initial clinical course or occurred throughout clinical training. Stressors highlighted during the clinical period in the systematic review included assignments and workload during clinical practice, a feeling that the requirements of clinical practice exceeded students’ physical and emotional endurance and that their involvement in patient care was limited due to lack of experience. Furthermore, stress can have a direct effect on clinical performance, leading to mental disorders. Tung et al. [ 22 ], reported that the prevalence of depression among nursing students in Arab countries is 28%, which is almost six times greater than the rest of the world [ 22 ]. On the other hand, Saifan et al. [ 5 ], explored the theory-practice gap in the United Arab Emirates and found that clinical stressors could be decreased by preparing students better for clinical education with qualified clinical faculty and supportive preceptors.

The purpose of this study was to identify the stressors experienced by undergraduate nursing students in the United Arab Emirates during their first clinical training and the basic adaptation approaches or coping strategies they used. Recognizing or understanding different coping processes can inform the implementation of corrective measures when students experience clinical stress. The findings of this study may provide valuable information for nursing programmes, nurse educators, and clinical administrators to establish adaptive strategies to reduce stress among students going clinical practicums, particularly stressors from their first clinical training in different healthcare settings.

A qualitative approach was adopted to understand clinical stressors and coping strategies from the perspective of nurses’ lived experience. Qualitative content analysis was employed to obtain rich and detailed information from our qualitative data. Qualitative approaches seek to understand the phenomenon under study from the perspectives of individuals with lived experience [ 23 ]. Qualitative content analysis is an interpretive technique that examines the similarities and differences between and within different areas of text while focusing on the subject [ 24 ]. It is used to examine communication patterns in a repeatable and systematic way [ 25 ] and yields rich and detailed information on the topic under investigation [ 23 ]. It is a method of systematically coding and categorizing information and comprises a process of comprehending, interpreting, and conceptualizing the key meanings from qualitative data [ 26 ].

Setting and participants

This study was conducted after the clinical rotations ended in April 2022, between May and June in the nursing programme at the College of Health Sciences, University of Sharjah, in the United Arab Emirates. The study population comprised undergraduate nursing students who were undergoing their first clinical training and were recruited using purposive sampling. The inclusion criteria for this study were second-year nursing students in the first semester of clinical training who could speak English, were willing to participate in this research, and had no previous clinical work experience. The final sample consisted of 30 students.

Research instrument

The research instrument was a semi structured interview guide. The interview questions were based on an in-depth review of related literature. An intensive search included key words in Google Scholar, PubMed like the terms “nursing clinical stressors”, “nursing students”, and “coping mechanisms”. Once the questions were created, they were validated by two other faculty members who had relevant experience in mental health. A pilot test was conducted with five students and based on their feedback the following research questions, which were addressed in the study.

How would you describe your clinical experiences during your first clinical rotations?

In what ways did you find the first clinical rotation to be stressful?

What factors hindered your clinical training?

How did you cope with the stressors you encountered in clinical training?

Which strategies helped you cope with the clinical stressors you encountered?

Data collection

Semi-structured interviews were chosen as the method for data collection. Semi structured interviews are a well-established approach for gathering data in qualitative research and allow participants to discuss their views, experiences, attitudes, and beliefs in a positive environment [ 27 ]. This approach allows for flexibility in questioning thereby ensuring that key topics related to clinical learning stressors and coping strategies would be explored. Participants were given the opportunity to express their views, experiences, attitudes, and beliefs in a positive environment, encouraging open communication. These semi structured interviews were conducted by one member of the research team (MAS) who had a mental health background, and another member of the research team who attended the interviews as an observer (JMD). Neither of these researchers were involved in teaching the students during their clinical practicum, which helped to minimize bias. The interviews took place at the University of Sharjah, specifically in building M23, providing a familiar and comfortable environment for the participant. Before the interviews were all students who agreed to participate were provided with an explanation of the study’s purpose. The time and location of each interview were arranged. Before the interviews were conducted, all students who provided consent to participate received an explanation of the purpose of the study, and the time and place of each interview were arranged to accommodate the participants’ schedules and preferences. The interviews were conducted after the clinical rotation had ended in April, and after the final grades had been submitted to the coordinator. The timings of the interviews included the month of May and June which ensured that participants have completed their practicum experience and could reflect on the stressors more comprehensively. The interviews were audio-recorded with the participants’ consent, and each interview lasted 25–40 min. The data were collected until saturation was reached for 30 students. Memos and field notes were also recorded as part of the data collection process. These additional data allowed for triangulation to improve the credibility of the interpretations of the data [ 28 ]. Memos included the interviewers’ thoughts and interpretations about the interviews, the research process (including questions and gaps), and the analytic progress used for the research. Field notes were used to record the interviewers’ observations and reflections on the data. These additional data collection methods were important to guide the researchers in the interpretation of the data on the participants’ feelings, perspectives, experiences, attitudes, and beliefs. Finally, member checking was performed to ensure conformability.

Data analysis

The study used the content analysis method proposed by Graneheim and Lundman [ 24 ]. According to Graneheim and Lundman [ 24 ], content analysis is an interpretive technique that examines the similarities and differences between distinct parts of a text. This method allows researchers to determine exact theoretical and operational definitions of words, phrases, and symbols by elucidating their constituent properties [ 29 ]. First, we read the interview transcripts several times to reach an overall understanding of the data. All verbatim transcripts were read several times and discussed among all authors. We merged and used line-by-line coding of words, sentences, and paragraphs relevant to each other in terms of both the content and context of stressors and coping mechanisms. Next, we used data reduction to assess the relationships among themes using tables and diagrams to indicate conceptual patterns. Content related to stress encountered by students was extracted from the transcripts. In a separate document, we integrated and categorized all words and sentences that were related to each other in terms of both content and context. We analyzed all codes and units of meaning and compared them for similarities and differences in the context of this study. Furthermore, the emerging findings were discussed with other members of the researcher team. The final abstractions of meaningful subthemes into themes were discussed and agreed upon by the entire research team. This process resulted in the extraction of three main themes in addition to two subthemes related to stress and coping strategies.

Ethical considerations

The University of Sharjah Research Ethics Committee provided approval to conduct this study (Reference Number: REC 19-12-03-01-S). Before each interview, the goal and study procedures were explained to each participant, and written informed consent was obtained. The participants were informed that participation in the study was voluntary and that they could withdraw from the study at any time. In the event they wanted to withdraw from the study, all information related to the participant would be removed. No participant withdrew from the study. Furthermore, they were informed that their clinical practicum grade would not be affected by their participation in this study. We chose interview locations in Building M23that were private and quiet to ensure that the participants felt at ease and confident in verbalizing their opinions. No participant was paid directly for involvement in this study. In addition, participants were assured that their data would remain anonymous and confidential. Confidentiality means that the information provided by participants was kept private with restrictions on how and when data can be shared with others. The participants were informed that their information would not be duplicated or disseminated without their permission. Anonymity refers to the act of keeping people anonymous with respect to their participation in a research endeavor. No personal identifiers were used in this study, and each participant was assigned a random alpha-numeric code (e.g., P1 for participant 1). All digitally recorded interviews were downloaded to a secure computer protected by the principal investigator with a password. The researchers were the only people with access to the interview material (recordings and transcripts). All sensitive information and materials were kept secure in the principal researcher’s office at the University of Sharjah. The data will be maintained for five years after the study is completed, after which the material will be destroyed (the transcripts will be shredded, and the tapes will be demagnetized).

In total, 30 nursing students who were enrolled in the nursing programme at the Department of Nursing, College of Health Sciences, University of Sharjah, and who were undergoing their first clinical practicum participated in the study. Demographically, 80% ( n  = 24) were females and 20% ( n  = 6) were male participants. The majority (83%) of study participants ranged in age from 18 to 22 years. 20% ( n  = 6) were UAE nationals, 53% ( n  = 16) were from Gulf Cooperation Council countries, while 20% ( n  = 6) hailed from Africa and 7% ( n  = 2) were of South Asian descent. 67% of the respondents lived with their families while 33% lived in the hostel. (Table  1 )

Following the content analysis, we identified three main themes: (1) managing expectations, (2) theory-practice gap and 3)learning to cope. Learning to cope had two subthemes: positive coping strategies and negative coping strategies. An account of each theme is presented along with supporting excerpts for the identified themes. The identified themes provide valuable insight into the stressors encountered by students during their first clinical practicum. These themes will lead to targeted interventions and supportive mechanisms that can be built into the clinical training curriculum to support students during clinical practice.

Theme 1: managing expectations

In our examination of the stressors experienced by nursing students during their first clinical practicum and the coping strategies they employed, we identified the first theme as managing expectations.

The students encountered expectations from various parties, such as clinical staff, patients and patients’ relatives which they had to navigate. They attempted to fulfil their expectations as they progressed through training, which presented a source of stress. The students noted that the hospital staff and patients expected them to know how to perform a variety of tasks upon request, which made the students feel stressed and out of place if they did not know how to perform these tasks. Some participants noted that other nurses in the clinical unit did not allow them to participate in nursing procedures, which was considered an enormous impediment to clinical learning, as noted in the excerpt below:

“…Sometimes the nurses… They will not allow us to do some procedures or things during clinical. And sometimes the patients themselves don’t allow us to do procedures” (P5).

Some of the students noted that they felt they did not belong and felt like foreigners in the clinical unit. Excerpts from the students are presented in the following quotes;

“The clinical environment is so stressful. I don’t feel like I belong. There is too little time to build a rapport with hospital staff or the patient” (P22).

“… you ask the hospital staff for some guidance or the location of equipment, and they tell us to ask our clinical tutor …but she is not around … what should I do? It appears like we do not belong, and the sooner the shift is over, the better” (P18).

“The staff are unfriendly and expect too much from us students… I feel like I don’t belong, or I am wasting their (the hospital staff’s) time. I want to ask questions, but they have loads to do” (P26).

Other students were concerned about potential failure when working with patients during clinical training, which impacted their confidence. They were particularly afraid of failure when performing any clinical procedures.

“At the beginning, I was afraid to do procedures. I thought that maybe the patient would be hurt and that I would not be successful in doing it. I have low self-confidence in doing procedures” (P13).

The call bell rings, and I am told to answer Room No. XXX. The patient wants help to go to the toilet, but she has two IV lines. I don’t know how to transport the patient… should I take her on the wheelchair? My eyes glance around the room for a wheelchair. I am so confused …I tell the patient I will inform the sister at the nursing station. The relative in the room glares at me angrily … “you better hurry up”…Oh, I feel like I don’t belong, as I am not able to help the patient… how will I face the same patient again?” (P12).

Another major stressor mentioned in the narratives was related to communication and interactions with patients who spoke another language, so it was difficult to communicate.

“There was a challenge with my communication with the patients. Sometimes I have communication barriers because they (the patients) are of other nationalities. I had an experience with a patient [who was] Indian, and he couldn’t speak my language. I did not understand his language” (P9).

Thus, a variety of expectations from patients, relatives, hospital staff, and preceptors acted as sources of stress for students during their clinical training.

Theme 2: theory-practice gap

Theory-practice gaps have been identified in previous studies. In our study, there was complete dissonance between theory and actual clinical practice. The clinical procedures or practices nursing students were expected to perform differed from the theory they had covered in their university classes and skills lab. This was described as a theory–practice gap and often resulted in stress and confusion.

“For example …the procedures in the hospital are different. They are different from what we learned or from theory on campus. Or… the preceptors have different techniques than what we learned on campus. So, I was stress[ed] and confused about it” (P11).

Furthermore, some students reported that they did not feel that they received adequate briefing before going to clinical training. A related source of stress was overload because of the volume of clinical coursework and assignments in addition to clinical expectations. Additionally, the students reported that a lack of time and time management were major sources of stress in their first clinical training and impacted their ability to complete the required paperwork and assignments:

“…There is not enough time…also, time management at the hospital…for example, we start at seven a.m., and the handover takes 1 hour to finish. They (the nurses at the hospital) are very slow…They start with bed making and morning care like at 9.45 a.m. Then, we must fill [out] our assessment tool and the NCP (nursing care plan) at 10 a.m. So, 15 only minutes before going to our break. We (the students) cannot manage this time. This condition makes me and my friends very stressed out. -I cannot do my paperwork or assignments; no time, right?” (P10).

“Stressful. There is a lot of work to do in clinical. My experiences are not really good with this course. We have a lot of things to do, so many assignments and clinical procedures to complete” (P16).

The participants noted that the amount of required coursework and number of assignments also presented a challenge during their first clinical training and especially affected their opportunity to learn.

“I need to read the file, know about my patient’s condition and pathophysiology and the rationale for the medications the patient is receiving…These are big stressors for my learning. I think about assignments often. Like, we are just focusing on so many assignments and papers. We need to submit assessments and care plans for clinical cases. We focus our time to complete and finish the papers rather than doing the real clinical procedures, so we lose [the] chance to learn” (P25).

Another participant commented in a similar vein that there was not enough time to perform tasks related to clinical requirements during clinical placement.

“…there is a challenge because we do not have enough time. Always no time for us to submit papers, to complete assessment tools, and some nurses, they don’t help us. I think we need more time to get more experiences and do more procedures, reduce the paperwork that we have to submit. These are challenges …” (P14).

There were expectations that the students should be able to carry out their nursing duties without becoming ill or adversely affected. In addition, many students reported that the clinical environment was completely different from the skills laboratory at the college. Exposure to the clinical setting added to the theory-practice gap, and in some instances, the students fell ill.

One student made the following comment:

“I was assisting a doctor with a dressing, and the sight and smell from the oozing wound was too much for me. I was nauseated. As soon as the dressing was done, I ran to the bathroom and threw up. I asked myself… how will I survive the next 3 years of nursing?” (P14).

Theme 3: learning to cope

The study participants indicated that they used coping mechanisms (both positive and negative) to adapt to and manage the stressors in their first clinical practicum. Important strategies that were reportedly used to cope with stress were time management, good preparation for clinical practice, and positive thinking as well as engaging in physical activity and self-motivation.

“Time management. Yes, it is important. I was encouraging myself. I used time management and prepared myself before going to the clinical site. Also, eating good food like cereal…it helps me very much in the clinic” (P28).

“Oh yeah, for sure positive thinking. In the hospital, I always think positively. Then, after coming home, I get [to] rest and think about positive things that I can do. So, I will think something good [about] these things, and then I will be relieved of stress” (P21).

Other strategies commonly reported by the participants were managing their breathing (e.g., taking deep breaths, breathing slowly), taking breaks to relax, and talking with friends about the problems they encountered.

“I prefer to take deep breaths and breathe slowly and to have a cup of coffee and to talk to my friends about the case or the clinical preceptor and what made me sad so I will feel more relaxed” (P16).

“Maybe I will take my break so I feel relaxed and feel better. After clinical training, I go directly home and take a long shower, going over the day. I will not think about anything bad that happened that day. I just try to think about good things so that I forget the stress” (P27).

“Yes, my first clinical training was not easy. It was difficult and made me stressed out…. I felt that it was a very difficult time for me. I thought about leaving nursing” (P7).

I was not able to offer my prayers. For me, this was distressing because as a Muslim, I pray regularly. Now, my prayer time is pushed to the end of the shift” (P11).

“When I feel stress, I talk to my friends about the case and what made me stressed. Then I will feel more relaxed” (P26).

Self-support or self-motivation through positive self-talk was also used by the students to cope with stress.

“Yes, it is difficult in the first clinical training. When I am stress[ed], I go to the bathroom and stand in the front of the mirror; I talk to myself, and I say, “You can do it,” “you are a great student.” I motivate myself: “You can do it”… Then, I just take breaths slowly several times. This is better than shouting or crying because it makes me tired” (P11).

Other participants used physical activity to manage their stress.

“How do I cope with my stress? Actually, when I get stressed, I will go for a walk on campus” (P4).

“At home, I will go to my room and close the door and start doing my exercises. After that, I feel the negative energy goes out, then I start to calm down… and begin my clinical assignments” (P21).

Both positive and negative coping strategies were utilized by the students. Some participants described using negative coping strategies when they encountered stress during their clinical practice. These negative coping strategies included becoming irritable and angry, eating too much food, drinking too much coffee, and smoking cigarettes.

“…Negative adaptation? Maybe coping. If I am stressed, I get so angry easily. I am irritable all day also…It is negative energy, right? Then, at home, I am also angry. After that, it is good to be alone to think about my problems” (P12).

“Yeah, if I…feel stress or depressed, I will eat a lot of food. Yeah, ineffective, like I will be eating a lot, drinking coffee. Like I said, effective, like I will prepare myself and do breathing, ineffective, I will eat a lot of snacks in between my free time. This is the bad side” (P16).

“…During the first clinical practice? Yes, it was a difficult experience for us…not only me. When stressed, during a break at the hospital, I will drink two or three cups of coffee… Also, I smoke cigarettes… A lot. I can drink six cups [of coffee] a day when I am stressed. After drinking coffee, I feel more relaxed, I finish everything (food) in the refrigerator or whatever I have in the pantry, like chocolates, chips, etc” (P23).

These supporting excerpts for each theme and the analysis offers valuable insights into the specific stressors faced by nursing students during their first clinical practicum. These insights will form the basis for the development of targeted interventions and supportive mechanisms within the clinical training curriculum to better support students’ adjustment and well-being during clinical practice.

Our study identified the stressors students encounter in their first clinical practicum and the coping strategies, both positive and negative, that they employed. Although this study emphasizes the importance of clinical training to prepare nursing students to practice as nurses, it also demonstrates the correlation between stressors and coping strategies.The content analysis of the first theme, managing expectations, paves the way for clinical agencies to realize that the students of today will be the nurses of tomorrow. It is important to provide a welcoming environment where students can develop their identities and learn effectively. Additionally, clinical staff should foster an environment of individualized learning while also assisting students in gaining confidence and competence in their repertoire of nursing skills, including critical thinking, problem solving and communication skills [ 8 , 15 , 19 , 30 ]. Another challenge encountered by the students in our study was that they were prevented from participating in clinical procedures by some nurses or patients. This finding is consistent with previous studies reporting that key challenges for students in clinical learning include a lack of clinical support and poor attitudes among clinical staff and instructors [ 31 ]. Clinical staff with positive attitudes have a positive impact on students’ learning in clinical settings [ 32 ]. The presence, supervision, and guidance of clinical instructors and the assistance of clinical staff are essential motivating components in the clinical learning process and offer positive reinforcement [ 30 , 33 , 34 ]. Conversely, an unsupportive learning environment combined with unwelcoming clinical staff and a lack of sense of belonging negatively impact students’ clinical learning [ 35 ].

The sources of stress identified in this study were consistent with common sources of stress in clinical training reported in previous studies, including the attitudes of some staff, students’ status in their clinical placement and educational factors. Nursing students’ inexperience in the clinical setting and lack of social and emotional experience also resulted in stress and psychological difficulties [ 36 ]. Bhurtun et al. [ 33 ] noted that nursing staff are a major source of stress for students because the students feel like they are constantly being watched and evaluated.

We also found that students were concerned about potential failure when working with patients during their clinical training. Their fear of failure when performing clinical procedures may be attributable to low self-confidence. Previous studies have noted that students were concerned about injuring patients, being blamed or chastised, and failing examinations [ 37 , 38 ]. This was described as feeling “powerless” in a previous study [ 7 , 12 ]. In addition, patients’ attitudes towards “rejecting” nursing students or patients’ refusal of their help were sources of stress among the students in our study and affected their self-confidence. Self-confidence and a sense of belonging are important for nurses’ personal and professional identity, and low self-confidence is a problem for nursing students in clinical learning [ 8 , 39 , 40 ]. Our findings are consistent with a previous study that reported that a lack of self-confidence was a primary source of worry and anxiety for nursing students and affected their communication and intention to leave nursing [ 41 ].

In the second theme, our study suggests that students encounter a theory-practice gap in clinical settings, which creates confusion and presents an additional stressors. Theoretical and clinical training are complementary elements of nursing education [ 40 ], and this combination enables students to gain the knowledge, skills, and attitudes necessary to provide nursing care. This is consistent with the findings of a previous study that reported that inconsistencies between theoretical knowledge and practical experience presented a primary obstacle to the learning process in the clinical context [ 42 ], causing students to lose confidence and become anxious [ 43 ]. Additionally, the second theme, the theory-practice gap, authenticates Safian et al.’s [ 5 ] study of the theory-practice gap that exists United Arab Emirates among nursing students as well as the need for more supportive clinical faculty and the extension of clinical hours. The need for better time availability and time management to complete clinical tasks were also reported by the students in the study. Students indicated that they had insufficient time to complete clinical activities because of the volume of coursework and assignments. Our findings support those of Chaabane et al. [ 15 ]. A study conducted in Saudi Arabia [ 44 ] found that assignments and workload were among the greatest sources of stress for students in clinical settings. Effective time management skills have been linked to academic achievement, stress reduction, increased creativity [ 45 ], and student satisfaction [ 46 ]. Our findings are also consistent with previous studies that reported that a common source of stress among first-year students was the increased classroom workload [ 19 , 47 ]. As clinical assignments and workloads are major stressors for nursing students, it is important to promote activities to help them manage these assignments [ 48 ].

Another major challenge reported by the participants was related to communicating and interacting with other nurses and patients. The UAE nursing workforce and population are largely expatriate and diverse and have different cultural and linguistic backgrounds. Therefore, student nurses encounter difficulty in communication [ 49 ]. This cultural diversity that students encounter in communication with patients during clinical training needs to be addressed by curriculum planners through the offering of language courses and courses on cultural diversity [ 50 ].

Regarding the third and final theme, nursing students in clinical training are unable to avoid stressors and must learn to cope with or adapt to them. Previous research has reported a link between stressors and the coping mechanisms used by nursing students [ 51 , 52 , 53 ]. In particular, the inability to manage stress influences nurses’ performance, physical and mental health, attitude, and role satisfaction [ 54 ]. One such study suggested that nursing students commonly use problem-focused (dealing with the problem), emotion-focused (regulating emotion), and dysfunctional (e.g., venting emotions) stress coping mechanisms to alleviate stress during clinical training [ 15 ]. Labrague et al. [ 51 ] highlighted that nursing students use both active and passive coping techniques to manage stress. The pattern of clinical stress has been observed in several countries worldwide. The current study found that first-year students experienced stress during their first clinical training [ 35 , 41 , 55 ]. The stressors they encountered impacted their overall health and disrupted their clinical learning. Chaabane et al. [ 15 ] reported moderate and high stress levels among nursing students in Bahrain, Egypt, Iraq, Jordan, Oman, Pakistan, Palestine, Saudi Arabia, and Sudan. Another study from Bahrain reported that all nursing students experienced moderate to severe stress in their first clinical placement [ 56 ]. Similarly, nursing students in Spain experienced a moderate level of stress, and this stress was significantly correlated with anxiety [ 30 ]. Therefore, it is imperative that pastoral systems at the university address students’ stress and mental health so that it does not affect their clinical performance. Faculty need to utilize evidence-based interventions to support students so that anxiety-producing situations and attrition are minimized.

In our study, students reported a variety of positive and negative coping mechanisms and strategies they used when they experienced stress during their clinical practice. Positive coping strategies included time management, positive thinking, self-support/motivation, breathing, taking breaks, talking with friends, and physical activity. These findings are consistent with those of a previous study in which healthy coping mechanisms used by students included effective time management, social support, positive reappraisal, and participation in leisure activities [ 57 ]. Our study found that relaxing and talking with friends were stress management strategies commonly used by students. Communication with friends to cope with stress may be considered social support. A previous study also reported that people seek social support to cope with stress [ 58 ]. Some students in our study used physical activity to cope with stress, consistent with the findings of previous research. Stretching exercises can be used to counteract the poor posture and positioning associated with stress and to assist in reducing physical tension. Promoting such exercise among nursing students may assist them in coping with stress in their clinical training [ 59 ].

Our study also showed that when students felt stressed, some adopted negative coping strategies, such as showing anger/irritability, engaging in unhealthy eating habits (e.g., consumption of too much food or coffee), or smoking cigarettes. Previous studies have reported that high levels of perceived stress affect eating habits [ 60 ] and are linked to poor diet quality, increased snacking, and low fruit intake [ 61 ]. Stress in clinical settings has also been linked to sleep problems, substance misuse, and high-risk behaviors’ and plays a major role in student’s decision to continue in their programme.

Implications of the study

The implications of the study results can be grouped at multiple levels including; clinical, educational, and organizational level. A comprehensive approach to addressing the stressors encountered by nursing students during their clinical practicum can be overcome by offering some practical strategies to address the stressors faced by nursing students during their clinical practicum. By integrating study findings into curriculum planning, mentorship programs, and organizational support structures, a supportive and nurturing environment that enhances students’ learning, resilience, and overall success can be envisioned.

Clinical level

Introducing simulation in the skills lab with standardized patients and the use of moulage to demonstrate wounds, ostomies, and purulent dressings enhances students’ practical skills and prepares them for real-world clinical scenarios. Organizing orientation days at clinical facilities helps familiarize students with the clinical environment, identify potential stressors, and introduce interventions to enhance professionalism, social skills, and coping abilities Furthermore, creating a WhatsApp group facilitates communication and collaboration among hospital staff, clinical tutors, nursing faculty, and students, enabling immediate support and problem-solving for clinical situations as they arise, Moreover, involving chief nursing officers of clinical facilities in the Nursing Advisory Group at the Department of Nursing promotes collaboration between academia and clinical practice, ensuring alignment between educational objectives and the needs of the clinical setting [ 62 ].

Educational level

Sharing study findings at conferences (we presented the results of this study at Sigma Theta Tau International in July 2023 in Abu Dhabi, UAE) and journal clubs disseminates knowledge and best practices among educators and clinicians, promoting awareness and implementation of measures to improve students’ learning experiences. Additionally we hold mentorship training sessions annually in January and so we shared with the clinical mentors and preceptors the findings of this study so that they proactively they are equipped with strategies to support students’ coping with stressors during clinical placements.

Organizational level

At the organizational we relooked at the available student support structures, including counseling, faculty advising, and career advice, throughout the nursing program emphasizing the importance of holistic support for students’ well-being and academic success as well as retention in the nursing program. Also, offering language courses as electives recognizes the value of communication skills in nursing practice and provides opportunities for personal and professional development.

For first-year nursing students, clinical stressors are inevitable and must be given proper attention. Recognizing nursing students’ perspectives on the challenges and stressors experienced in clinical training is the first step in overcoming these challenges. In nursing schools, providing an optimal clinical environment as well as increasing supervision and evaluation of students’ practices should be emphasized. Our findings demonstrate that first-year nursing students are exposed to a variety of different stressors. Identifying the stressors, pressures, and obstacles that first-year students encounter in the clinical setting can assist nursing educators in resolving these issues and can contribute to students’ professional development and survival to allow them to remain in the profession. To overcome stressors, students frequently employ problem-solving approaches or coping mechanisms. The majority of nursing students report stress at different levels and use a variety of positive and negative coping techniques to manage stress.

The present results may not be generalizable to other nursing institutions because this study used a purposive sample along with a qualitative approach and was limited to one university in the Middle East. Furthermore, the students self-reported their stress and its causes, which may have introduced reporting bias. The students may also have over or underreported stress or coping mechanisms because of fear of repercussions or personal reasons, even though the confidentiality of their data was ensured. Further studies are needed to evaluate student stressors and coping now that measures have been introduced to support students. Time will tell if these strategies are being used effectively by both students and clinical personnel or if they need to be readdressed. Finally, we need to explore the perceptions of clinical faculty towards supervising students in their first clinical practicum so that clinical stressors can be handled effectively.

Data availability

The data sets are available with the corresponding author upon reasonable request.

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Acknowledgements

The authors are grateful to all second year nursing students who voluntarily participated in the study.

No funding was received. Not applicable.

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Department of Nursing, College of Health Sciences, University of Sharjah, POBox, Sharjah, 272272, UAE

Jacqueline Maria Dias, Muhammad Arsyad Subu, Nabeel Al-Yateem, Fatma Refaat Ahmed, Syed Azizur Rahman, Mini Sara Abraham, Sareh Mirza Forootan, Farzaneh Ahmad Sarkhosh & Fatemeh Javanbakh

Health Care Management, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates

Syed Azizur Rahman

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Contributions

JMD conceptualized the idea and designed the methodology, formal analysis, writing original draft and project supervision and mentoring. MAS prepared the methodology and conducted the qualitative interviews and analyzed the methodology and writing of original draft and project supervision. NY, FRA, SAR, MSA writing review and revising the draft. SMF, FAS, FJ worked with MAS on the formal analysis and prepared the first draft.All authors reviewed the final manuscipt of the article.

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Correspondence to Jacqueline Maria Dias .

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The Research Ethics Committee (REC) under) the Office of the Vice Chancellor for Research and Graduate Studies UOS approved this study (REC 19-12-03-01-S). Additionally, a written consent was obtained from all participants and the process followed the recommended policies and guidelines of the Declaration of Helsinki.

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Dr Fatma Refaat Ahmed is an editorial board member in BMC Nursing. Other authors do not have any conflict of interest

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Dias, J.M., Subu, M.A., Al-Yateem, N. et al. Nursing students’ stressors and coping strategies during their first clinical training: a qualitative study in the United Arab Emirates. BMC Nurs 23 , 322 (2024). https://doi.org/10.1186/s12912-024-01962-5

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Received : 06 January 2024

Accepted : 22 April 2024

Published : 11 May 2024

DOI : https://doi.org/10.1186/s12912-024-01962-5

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