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Learning style is an individual's natural or habitual pattern of acquiring and processing information in learning situations. A core concept is that individuals differ in how they learn. The idea of individualized learning styles originated in the 1970s, and has greatly influenced education.
Proponents of the use of learning styles in education recommend that teachers assess the learning styles of their students and adapt their classroom methods to best fit each student's learning style. Although there is ample evidence for differences in individual thinking and ways of processing various types of information, few studies have reliably tested the validity of using learning styles in education. Critics say there is no evidence that identifying an individual student's learning style produces better outcomes. There is evidence of empirical and pedagogical problems related to the use of learning tasks to "correspond to differences in a one-to-one fashion". Well-designed studies contradict the widespread "meshing hypothesis", that a student will learn best if taught in a method deemed appropriate for the student's learning style.
David A. Kolb's model is based on the Experiential learning Theory, as explained in his book Experiential Learning. The ELT model outlines two related approaches toward grasping experience: Concrete Experience and Abstract Conceptualization, as well as two related approaches toward transforming experience: Reflective Observation and Active Experimentation. According to Kolb's model, the ideal learning process engages all four of these modes in response to situational demands. In order for learning to be effective, all four of these approaches must be incorporated. As individuals attempt to use all four approaches, however, they tend to develop strengths in one experience-grasping approach and one experience-transforming approach. The resulting learning styles are combinations of the individual's preferred approaches. These learning styles are as follows:
David Kolb’s Experiential Learning Model (ELM) 
|Active Experimentation||Reflective Observation|
1. Accommodators: Concrete Experience + Active Experiment
2. Converger: Abstract Conceptualization + Active Experiment
3. Diverger: Concrete Experience + Reflective Observation
4. Assimilator: Abstract Conceptualization + Reflective Observation
Kolb's model gave rise to the Learning Style Inventory, an assessment method used to determine an individual's learning style. An individual may exhibit a preference for one of the four styles—Accommodating, Converging, Diverging and Assimilating—depending on their approach to learning via the experiential learning theory model.
Although Kolb's model is the most widely accepted with substantial empirical support, recent studies suggest the Learning Style Inventory (LSI) is seriously flawed 
"Sensory preferences influence the ways in which students learn ... Perceptual preferences affect more than 70 percent of school-age youngsters" (Dunn, Beaudry, & Klavas, 1989, p. 52). There are three Learning Modalities adapted from Barbe and Swassing(writers of the book, teaching through modality strengths: concept and practices):
3. Tactile (Kinesthetic)
Descriptions of Learning Modalities:
Learning modalities have the ability of occurring independently or in combination, changing over time, and becoming integrated with age.
Two adaptations were made to Kolb's experiential model. Firstly, the stages in the cycle were renamed to accord with managerial experiences of decision making/problem solving. The Honey & Mumford stages are:
Secondly, the styles were directly aligned to the stages in the cycle and named Activist, Reflector, Theorist and Pragmatist. These are assumed to be acquired preferences that are adaptable, either at will or through changed circumstances, rather than being fixed personality characteristics. The Honey & Mumford Learning Styles Questionnaire (LSQ) is a self-development tool and differs from Kolb's Learning Style inventory by inviting managers to complete a checklist of work-related behaviours without directly asking managers how they learn. Having completed the self-assessment, managers are encouraged to focus on strengthening underutilised styles in order to become better equipped to learn from a wide range of everyday experiences.
A MORI survey commissioned by The Campaign for Learning in 1999 found the Honey & Mumford LSQ to be the most widely used system for assessing preferred learning styles in the local government sector in the UK.
Maria Bagby discusses the work of Anthony F. Gregorc and Kathleen A. Butler in her article entitled Learning Style Difference vs Learning Difficulty. Gregorc and Butler worked to organize a model describing different learning styles rooted in the way individuals acquire and process information differently. This model is based on the existence of perceptions—our evaluation of the world by means of an approach that makes sense to us. These perceptions in turn are the foundation of our specific learning strengths, or learning styles.
In this model, there are two perceptual qualities 1) concrete and 2) abstract; and two ordering abilities 1) random and 2) sequential. Concrete perceptions involve registering information through the five senses, while abstract perceptions involve the understanding of ideas, qualities, and concepts which cannot be seen. In regard to the two ordering abilities, sequential involves the organization of information in a linear, logical way and random involves the organization of information in chunks and in no specific order. Both of the perceptual qualities and both of the ordering abilities are present in each individual, but some qualities and ordering abilities are more dominant within certain individuals.
There are four combinations of perceptual qualities and ordering abilities based on dominance: 1) Concrete Sequential; 2) Abstract Random; 3) Abstract Sequential; 4) Concrete Random. Individuals with different combinations learn in different ways—they have different strengths, different things make sense to them, different things are difficult for them, and they ask different questions throughout the learning process.
Some critics (Mazza) of today's schools, of the concept of learning disabilities, of special education, and of response to intervention, take the position that every child has a different learning style and pace and that each child is unique, not only capable of learning but also capable of succeeding.
Sudbury Model democratic schools in the United States assert that there are many ways to study and learn. They argue that learning is a process you do, not a process that is done to you, and that this is true of everyone; it's basic. The experience of Sudbury model democratic schools shows that there are many ways to learn without the intervention of teaching, that is to say, without the intervention of a teacher being imperative. In the case of reading for instance in the Sudbury model democratic schools, some children learn from being read to, memorizing the stories and then ultimately reading them. Others learn from cereal boxes, others from games instructions, others from street signs. Some teach themselves letter sounds, others syllables, others whole words. Sudbury model democratic schools assert that in their schools no one child has ever been forced, pushed, urged, cajoled, or bribed into learning how to read or write. None of their graduates are real or functional illiterates, and no one who meets their older students could ever guess the age at which they first learned to read or write. In a similar manner, students learn all the subjects, techniques, and skills in these schools.
Describing current instructional methods as homogenization and lockstep standardization, alternative approaches are proposed, such as the Sudbury Model of Democratic Education schools, an alternative approach in which children, by enjoying personal freedom thus encouraged to exercise personal responsibility for their actions, learn at their own pace and style rather than following a compulsory and chronologically-based curriculum. Proponents of unschooling have also claimed that children raised in this method learn at their own pace and style, and do not suffer from learning disabilities.
Gerald Coles asserts that there are partisan agendas behind the educational policy-makers and that the scientific research that they use to support their arguments regarding the teaching of literacy is flawed. These include the idea that there are neurological explanations for learning disabilities.
One of the most common and widely used  categorizations of the various types of learning styles is Fleming's VARK model (sometimes VAK) which expanded upon earlier Neuro-linguistic programming (VARK) models:
Fleming claimed that visual learners have a preference for seeing (think in pictures; visual aids such as overhead slides, diagrams, handouts, etc.). Auditory learners best learn through listening (lectures, discussions, tapes, etc.). Tactile/kinesthetic learners prefer to learn via experience—moving, touching, and doing (active exploration of the world; science projects; experiments, etc.). Its use in instruction allows teachers to prepare classes that address each of these areas. Students can also use the model to identify their preferred learning style and maximize their educational experience by focusing on what benefits them the most.
Anthony Grasha and Sheryl Reichmann, in 1974, formulated the Grasha-Reichmann Learning Style Scale. It was developed to analyze the attitudes of students and how they approach learning. The test was originally designed for college students. Grasha's background is in cognitive processes and coping techniques. The concepts of various learning styles are as follows:
The conclusion of this model was to provide teachers with insight on how to approach instructional plans. 
Aiming to explain why aptitude tests, school grades, and classroom performance often fail to identify real ability, Robert J. Sternberg listed various cognitive dimensions in his book Thinking Styles (1997). Several other models are also often used when researching learning styles. This includes the Myers Briggs Type Indicator (MBTI) and the DISC assessment.
Chris J Jackson's neuropsychological hybrid model of learning in personality argues Sensation Seeking provides a core biological drive of curiosity, learning and exploration. A high drive to explore leads to dysfunctional learning consequences unless cognitions such as goal orientation, conscientiousness, deep learning and emotional intelligence re-express it in more complex ways to achieve functional outcomes such as high work performance. The model aims to explain many forms of functional behaviour (such as entrepreneurial activity, work performance, educational success) as well as dysfunctional behaviour (such as delinquency and anti-social behaviour). The wide applicability of the model and its strong grounding in the academic literature suggests that this evidence based model of learning has much potential. Latest research is summarized here. Evidence for this model is considerable. Siadaty and Taghiyareh (2007) report that training based on Conscientious Achievement increases performance but that training based on Sensation Seeking does not. These results strongly support Jackson's model since the model proposes that Conscientious Achievement will respond to intervention whereas Sensation Seeking (with its biological basis) will not. Jackson's papers can be downloaded here.
Learning style is a gestalt that tells us how a student learns and prefers to learn. Keefe (1979) says that: “Learning styles are characteristic cognitive, affective, and physiological behaviors that serve as relatively stable indicators of how learners perceive, interact with, and respond to the learning environment."
There are three broad categories of learning style characteristics:
•Cognitive styles are preferred ways of perception, organization and retention.
•Affective styles represent the motivational dimensions of the learning personality; each learner has a personal motivational approach.
•Physiological styles are traits deriving from a person's gender, health and nutrition, and reaction to school physical surroundings, such as preferences for levels of light, sound, and temperature.
Styles are hypothetical constructs that help to explain the learning (and teaching) process. Because learning is an internal process, we know that it has taken place only when we observe a relatively stable change in learner behavior resulting from what has been experienced” (Keefe, 1979). Similarly, learning style reflects underlying learning behavior. We can recognize the learning style of an individual student only by observing his or her behavior.
The Learning Style Inventory (LSI) is connected with Kolb's model and is used to determine a student's learning style. The LSI assesses an individual's preferences and needs regarding the learning process. It does the following:
1. Allows students to designate how they like to learn and indicates how consistent their responses are
2. Provides computerized results which show the student's preferred learning style
3. Provides a foundation upon which teachers can build in interacting with students
4. Provides possible strategies for accommodating learning styles
5. Provides for student involvement in the learning process
6. Provides a class summary so students with similar learning styles can be grouped together.
A completely different Learning Styles Inventory is associated with a binary division of learning styles, developed by Felder and Silverman. In this model, learning styles are a balance between four pairs of extremes: Active/Reflective, Sensing/Intuitive, Verbal/Visual and Sequential/Global. Students receive four scores describing these balances. Like the LSI mentioned above, this inventory provides overviews and synopses for teachers.
The NASSP Learning Style Profile (LSP) is a second-generation instrument for the diagnosis of student cognitive styles, perceptual responses, and study and instructional preferences. The Profile was developed by the NASSP research department (Keefe and Monk, 1986) in conjunction with a national task force of learning style experts. The task force spent almost a year reviewing the available literature and instrumentation before deciding to develop a new instrument. The Profile was developed in four phases with initial work undertaken at the University of Vermont (cognitive elements), Ohio State University (affective elements), and St. John's University (physiological/environmental elements). Rigid validation and normative studies were conducted using factor analytic methods to ensure strong construct validity and subscale independence. The Learning Style Profile contains 24 scales representing four higher order factors: cognitive styles, perceptual responses, study preferences and instructional preferences (the affective and physiological elements). The LSP scales are as follows: • Analytic Skill • Spatial Skill • Discrimination Skill • Categorizing Skill • Sequential Processing Skill • Simultaneous Processing Skill • Memory Skill • Perceptual Response: Visual • Perceptual Response: Auditory • Perceptual Response: Emotive • Persistence Orientation • Verbal Risk Orientation; • Verbal-Spatial Preference • Manipulative Preference • Study Time Preference: Early Morning • Study Time Preference: Late Morning • Study Time Preference: Afternoon • Study Time Preference: Evening • Grouping Preference • Posture Preference • Mobility Preference • Sound Preference • Lighting Preference • Temperature Preference
The LSP is a first-level diagnostic tool intended as the basis for comprehensive style assessment. Extensive readability checks, reliability and validity studies, and factor analyses of` the instrument, combined with the supervisory efforts of the task force, ensure valid use of the instrument with students in the sixth to twelfth grades. Computer scoring is available.*
Other methods (usually questionnaires) used to identify learning styles include Fleming's VARK Learning Style Test, Jackson's Learning Styles Profiler (LSP), and the NLP meta programs based iWAM questionnaire. Many other tests have gathered popularity and various levels of credibility among students and teachers.
Ilene Thiel introduced LLL as a preferred method of learning style otherwise known as Lifelong Love of Learning.
Learning style theories have been criticized by many scholars and researchers. Some psychologists and neuroscientists have questioned the scientific basis for and the theories on which they are based. According to Susan Greenfield the practice is "nonsense" from a neuroscientific point of view: "Humans have evolved to build a picture of the world through our senses working in unison, exploiting the immense interconnectivity that exists in the brain."
Many educational psychologists believe that there is little evidence for the efficacy of most learning style models, and furthermore, that the models often rest on dubious theoretical grounds. According to Stahl, there has been an "utter failure to find that assessing children's learning styles and matching to instructional methods has any effect on their learning." Guy Claxton has questioned the extent that learning styles such as VARK are helpful, particularly as they can have a tendency to label children and therefore restrict learning.
A non-peer-reviewed literature review by authors from the University of Newcastle upon Tyne identified 71 different theories of learning style. This report, published in 2004, criticized most of the main instruments used to identify an individual's learning style. In conducting the review, Coffield and his colleagues selected 13 of the most influential models for closer study, including most of the models cited on this page. They examined the theoretical origins and terms of each model, and the instrument that purported to assess individuals against the learning styles defined by the model. They analyzed the claims made by the author(s), external studies of these claims, and independent empirical evidence of the relationship between the learning style identified by the instrument and students' actual learning. Coffield's team found that none of the most popular learning style theories had been adequately validated through independent research, leading to the conclusion that the idea of a learning cycle, the consistency of visual, auditory and kinesthetic preferences and the value of matching teaching and learning styles were all "highly questionable."
One of the most widely known theories assessed by Coffield's team was the learning styles model of Dunn and Dunn, a VAK model. This model is widely used in schools in the United States, and 177 articles have been published in peer-reviewed journals referring to this model. The conclusion of Coffield et al. was as follows:
Despite a large and evolving research programme, forceful claims made for impact are questionable because of limitations in many of the supporting studies and the lack of independent research on the model.
Coffield's team claimed that another model, Gregorc's Style Delineator (GSD), was "theoretically and psychometrically flawed" and "not suitable for the assessment of individuals."
Mark K. Smith compiled and reviewed some critiques of Kolb's model in his article, "David A. Kolb on Experiential Learning". According to Smith's research, there are six key issues regarding the model. They are as follows:
Coffield and his colleagues and Mark Smith are not alone in their judgements. Demos, a UK think tank, published a report on learning styles prepared by a group chaired by David Hargreaves that included Usha Goswami from Cambridge University and David Wood from the University of Nottingham. The Demos report said that the evidence for learning styles was "highly variable", and that practitioners were "not by any means frank about the evidence for their work." 
Cautioning against interpreting neuropsychological research as supporting the applicability of learning style theory, John Geake, Professor of Education at the UK's Oxford Brookes University, and a research collaborator with Oxford University's Centre for Functional Magnetic Resonance Imaging of the Brain, commented that
We need to take extreme care when moving from the lab to the classroom. We do remember things visually and aurally, but information isn't defined by how it was received.
In late 2009, the journal Psychological Science in the Public Interest of the Association for Psychological Science (APS) published a report on the scientific validity of learning styles practices (Pashler et al., 2009). The panel was chaired by Hal Pashler (University of California, San Diego); the other members were Mark McDaniel (Washington University), Doug Rohrer (University of South Florida), and Robert Bjork (University of California, Los Angeles). The panel concluded that an adequate evaluation of the learning styles hypothesis—the idea that optimal learning demands that students receive instruction tailored to their learning styles—requires a particular kind of study. Specifically, students should be grouped into the learning style categories that are being evaluated (e.g., visual learners vs. verbal learners), and then students in each group must be randomly assigned to one of the learning methods (e.g., visual learning or verbal learning), so that some students will be "matched" and others will be "mismatched". At the end of the experiment, all students must sit for the same test. If the learning style hypothesis is correct, then, for example, visual learners should learn better with the visual method, whereas auditory learners should learn better with auditory method. Notably, other authors have reached the same conclusion (e.g., Massa & Mayer, 2006).
As disclosed in the report, the panel found that studies utilizing this essential research design were virtually absent from the learning styles literature. In fact, the panel was able to find only a few studies with this research design, and all but one of these studies were negative findings—that is, they found that the same learning method was superior for all kinds of students (e.g., Massa & Mayer, 2006).
Furthermore, the panel noted that, even if the requisite finding were obtained, the benefits would need to be large, and not just statistically significant, before learning style interventions could be recommended as cost-effective. That is, the cost of evaluating and classifying students by their learning style, and then providing customized instruction would need to be more beneficial than other interventions (e.g., one-on-one tutoring, after school remediation programs, etc.).
As a consequence, the panel concluded, "at present, there is no adequate evidence base to justify incorporating learning styles assessments into general educational practice. Thus, limited education resources would better be devoted to adopting other educational practices that have strong evidence base, of which there are an increasing number."
The article incited critical comments from some defenders of learning styles. The Chronicle of Higher Education reported that Robert Sternberg from Tufts University spoke out against the paper: "Several of the most-cited researchers on learning styles, Mr. Sternberg points out, do not appear in the paper's bibliography." This charge was also discussed by Science, which reported that Pashler said, "Just so…most of [the evidence] is 'weak.'"
Various researchers have attempted to hypothesize ways in which learning style theory can be used in the classroom. Two such scholars are Dr. Rita Dunn and Dr. Kenneth Dunn, who follow a VARK approach.
Although learning styles will inevitably differ among students in the classroom, Dunn and Dunn say that teachers should try to make changes in their classroom that will be beneficial to every learning style. Some of these changes include room redesign, the development of small-group techniques, and the development of Contract Activity Packages. Redesigning the classroom involves locating dividers that can be used to arrange the room creatively (such as having different learning stations and instructional areas), clearing the floor area, and incorporating student thoughts and ideas into the design of the classroom.
Their so-called "Contract Activity Packages" are educational plans that use: 1) a clear statement of the learning need; 2) multisensory resources (auditory, visual, tactile, kinesthetic); 3) activities through which the newly mastered information can be used creatively; 4) the sharing of creative projects within small groups; 5) at least three small-group techniques; 6) a pre-test, a self-test, and a post-test.
Another scholar who believes that learning styles should have an effect on the classroom is Marilee Sprenger in Differentiation through Learning Styles and Memory. Sprenger bases her work on three premises: 1) Teachers can be learners, and learners teachers. We are all both. 2) Everyone can learn under the right circumstances. 3) Learning is fun! Make it appealing. She details various ways of teaching, visual, auditory, or tactile/kinesthetic. Methods for visual learners include ensuring that students can see words written, using pictures, and drawing time lines for events. Methods for auditory learners include repeating words aloud, small-group discussion, debates, listening to books on tape, oral reports, and oral interpretation. Methods for tactile/kinesthetic learners include hands-on activities (experiments, etc.), projects, frequent breaks to allow movement, visual aids, role play, and field trips. By using a variety of teaching methods from each of these categories, teachers cater to different learning styles at once, and improve learning by challenging students to learn in different ways.
James W. Keefe and John M. Jenkins (2000; 2008) have incorporated learning style assessment as a basic component in their "Personalized Instruction" model of schooling. Six basic elements constitute the culture and context of personalized instruction. The cultural components - - teacher role, student learning characteristics, and collegial relationships - -establish the foundation of personalization and ensure that the school prizes a caring and collaborative environment. The contextual factors—interactivity, flexible scheduling, and authentic assessment—establish the structure of personalization. These six elements constitute the state of the art in personalized instruction. Cognitive and learning style aanlysis have a special role in the process of personalizing instruction. Style elements are relatively persistent qualities in the behavior of individual learners. They reflect genetic coding, personality, development, motivation, and environmental adaptation. Second only to the more flexible teacher role, the assessment of student learning style, more than any other element, establishes the foundation for a personalized approach to schooling: for student advisement and placement, for appropriate retraining of student cognitive skills, for adaptive instructional strategy, and for the authentic evaluation of learning. Some learners respond best in instructional environments based on an analysis of their perceptual and environmental style preferences. Most individualized and personalized teaching methods reflect this point of view. Other learners, however, need help to function successfully in any learning environment. If a youngster cannot cope under conventional instruction, enhancing his cognitive skills may make successful achievement possible. Many of the student learning problems that learning style diagnosis attempts to solve relate directly to elements of the human information processing system. Processes such as attention, perception and memory, and operations such as integration and retrieval of information are internal to the system. Any hope for improving student learning necessarily involves an understanding and application of information processing theory. Learning style assessment is an important window to understanding and managing this process.
Some research evaluating teaching styles and learning styles, however, has found that congruent groups have no significant differences in achievement from incongruent groups (Spoon & Schell, 1998). Furthermore, learning style in this study varied by demography, specifically by age, suggesting a change in learning style as one gets older and acquires more experience. While significant age differences did occur, as well as no experimental manipulation of classroom assignment, the findings do call into question the aim of congruent teaching-learning styles in the classroom.
Spoon J.C., & Schell, J.W. (1998). Aligning student learning styles with instructor teaching styles. Journal of Industrial Teacher Education, 35, 41-56. Keefe, J. W. (1979). Learning style: An overview. In Student learning styles — Diagnosing and prescribing programs. Reston, VA: National Association of Secondary School Principals. Keefe, J. W., & Jenkins, J. M. (1997). Instruction and the learning environment. Larchmont, NY: Eye on Education. Keefe J. W., & Jenkins, J. M. (2000). Personalized instruction: Changing classroom practice. Larchmont, NY: Eye on Education. Keefe, J. W. & Jenkins, J. M. (2008). Personalized instruction: The key to student achievement. 2nd edition. Lanham, MD: Rowman & Littlefield Education.