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Adventures in Restorative Listening

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Vark Learning Styles Test

The validity of learning styles needs supports of additional objective evidence. The identification of learning styles using subjective evidence from VARK questionnaires (where V is visual, A is auditory, R is read/write, and K is kinesthetic) combined with objective evidence from visual event-related potential (vERP) studies has never been investigated. It is questionable whether picture superiority effects exist in V learners and R learners. Thus, the present study aimed to investigate whether vERP could show the relationship between vERP components and VARK learning styles and to identify the existence of picture superiority effects in V learners and R learners. Thirty medical students (15 V learners and 15 R learners) performed recognition tasks with vERP and an intermediate-term memory (ITM) test. The results of within-group comparisons showed that pictures elicited larger P200 amplitudes than words at the occipital 2 site (P

Vark Learning Styles Test


The concept and existence of learning styles has been fraught with controversy, and recent studies have thrown their existence into doubt. Yet, many students still hold to the conventional wisdom that learning styles are legitimate, and may adapt their outside of class study strategies to match these learning styles. Thus, this study aims to assess if undergraduate anatomy students are more likely to utilize study strategies that align with their hypothetical learning styles (using the VARK analysis from Fleming and Mills, , Improve Acad. 11:137-155) and, if so, does this alignment correlate with their outcome in an anatomy course. Relatedly, this study examines whether students' VARK learning styles are correlated with course outcomes regardless of the students' study strategies, and whether any study strategies are correlated with course outcomes, regardless of student-specific VARK results. A total of 426 anatomy students from the 2015 and 2016 Fall semesters completed a study strategies survey and an online VARK questionnaire. Results demonstrated that most students did not report study strategies that correlated with their VARK assessment, and that student performance in anatomy was not correlated with their score in any VARK categories. Rather, some specific study strategies (irrespective of VARK results), such as use of the virtual microscope, were found to be positively correlated with final class grade. However, the alignment of these study strategies with VARK results had no correlation with anatomy course outcomes. Thus, this research provides further evidence that the conventional wisdom about learning styles should be rejected by educators and students alike. Anat Sci Educ. 2018 American Association of Anatomists.

The influence of sex on learning styles is an area of active research. Previous studies have not yielded any uniform results in that the learning preference of female students has ranged from being predominantly unimodal to predominantly multimodal (3, 13, 14). In our study, most of the female undergraduate medical students (68.3%) preferred more than one modality of learning. Among those with unimodal preferences, female students were predominantly aural (49.3%), whereas an equal number of male students preferred aural and kinesthetic (40%). Unlike a previous study (13) that showed that among students with multimodal learning preferences female students had a more diverse combination of sensory modalities, our study showed diverse sensory modality combinations in both sexes. Hence, in our study sample, sex did not significantly influence the learning style preference. Considering the differing results from various studies, no generalizations can be made regarding the influence of sex.

Our study has limitations. The academic performance data was based on self-reported marks obtained in the various examinations. This could have led to recall bias or inaccurate reporting. Our study does not address whether altering the teaching methods according to student learning styles improves academic performance. It only tells us that differing past academic performance did not significantly influence the learning style preference of students. Although our study showed no influence of sex on learning style preferences, a larger study sample might have shown a statistically significant difference considering that our study sample showed more kinesthetic learners among men, which was not statistically significant (40% vs. 28% for men vs. women, respectively). While collecting data on self-perceived learning style preferences, students were allowed to select multiple preferences. Hence, we were unable to determine the self-perceived dominant learning modality.

Studies further show that teachers cannot assess the learning style of their students accurately.[11] In one study, students were asked to take an inventory on their learning style. After nearly 400 students completed the inventory, 70% didn't use study habits that matched their preferred learning method.[12] This study also indicated that students who used study methods that matched their preferred learning style performed no better on tests than students who did not.[12]

These four learning styles are assumed to be acquired preferences that are adaptable, either at will or through changed circumstances, rather than being fixed personality characteristics. Honey and Mumford's Learning Styles Questionnaire (LSQ)[18] 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 underutilized styles in order to become better equipped to learn from a wide range of everyday experiences.

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

Anthony Gregorc and Kathleen Butler organized a model describing different learning styles rooted in the way individuals acquire and process information differently.[28] This model posits that an individual's perceptual abilities are the foundation of his or her specific learning strengths, or learning styles.[29]

Anthony Grasha and Sheryl Riechmann, in 1974, formulated the Grasha-Reichmann Learning Style Scale.[32] It was developed to analyze the attitudes of students and how they approach learning. The test was originally designed to provide teachers with insight on how to approach instructional plans for college students.[33] Grasha's background was in cognitive processes and coping techniques. Unlike some models of cognitive styles which are relatively nonjudgmental, Grasha and Riechmann distinguish between adaptive and maladaptive styles. The names of Grasha and Riechmann's learning styles are:

Aiming to explain why aptitude tests, school grades, and classroom performance often fail to identify real ability, Robert Sternberg listed various cognitive dimensions in his book Thinking Styles.[34] Several other models are also often used when researching cognitive styles; some of these models are described in books that Sternberg co-edited, such as Perspectives on Thinking, Learning, and Cognitive Styles.[35][36][37]

A completely different Learning Styles Inventory is associated with a binary division of learning styles, developed by Richard Felder and Linda Silverman.[42] In Felder and Silverman's model, learning styles are a balance between pairs of extremes such as: Active/Reflective, Sensing/Intuitive, Verbal/Visual, and Sequential/Global. Students receive four scores describing these balances.[43] 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.[44] The LSP is a diagnostic tool intended as the basis for comprehensive style assessment with students in the sixth to twelfth grades. It was developed by the National Association of Secondary School Principals research department in conjunction with a national task force of learning style experts. The Profile was developed in four phases with initial work undertaken at the University of Vermont (cognitive elements), Ohio State University (affective elements), and St. John's University (physiological/environmental elements). Rigid validation and normative studies were conducted using factor analytic methods to ensure strong construct validity and subscale independence.

Furthermore, knowing a student's learning style does not seem to have any practical value for the student. In 2019, the American Association of Anatomists published a study that investigated whether learning styles had any effect on the final outcomes of an anatomy course. The study found that even when being told they had a specific learning style, the students did not change their study habits, and those students that did use their theoretically dominant learning style had no greater success in the course; specific study strategies, unrelated to learning style, were positively correlated with final course grade.[45] 041b061a72


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