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// Workers AI · dad joke modeWhat did visual learning say to the eye? "You see things my way.

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Visual learning is one of the learning styles in which information is primarily received and understood when presented in a visual format. Visual learners can use graphs, charts, maps, diagrams, and other visual material to interpret information. A learning style is best treated as a matter of individual preference rather than an educational need.[1][2][3] Students generally learn best from mixed-modality presentations, such as combining a spoken lecture (an auditory approach) with a visual aid.[4]

Visual learning is one component of Neil Fleming's VARK model.[5]

Techniques

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Famous people showing their inventions

A review study concluded that using graphic organizers improves student performance in the following areas:[6]

Retention
Students remember and recall information better when it is learned both visually and verbally.[6]
Reading comprehension
Graphic organizers help improve reading comprehension.[6]
Student achievement
Students with and without learning disabilities improve performance across content areas and grade levels.[6]
Thinking and learning skills
Developing and using a graphic organizer enhances higher-order and critical thinking skills.[6]

Areas of the brain affected

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Multiple regions of the brain work together to produce and process the images seen by the eyes, centered on the visual cortex in the occipital lobe. When acquiring new visual information, the brain first recognizes it, a task involving the inferior temporal cortex, the superior parietal cortex, and the cerebellum, with recognition aided by neural plasticity.[7] It then categorizes the information, drawing on the orbitofrontal cortex and two dorsolateral prefrontal regions to sort new material and relate it to existing knowledge.[8]

Once recognized and categorized, information enters the encoding process that leads to learning, involving areas such as the frontal lobe, the extrastriate cortex, and the neocortex; the limbic–diencephalic region is essential for transforming perceptions into memories.[9] Schemas make encoding easier by relating new images to what is already known, enhancing visual memory and learning.[10]

Infancy

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Between the fetal stage and 18 months, an infant undergoes rapid growth of gray matter, the tissue responsible for processing sensory information in regions such as the primary visual cortex.[citation needed] Located in the occipital lobe, the primary visual cortex processes visual information, including static and moving objects and pattern recognition.

Within the primary visual cortex, four pathways support the development of visual attention in the first months of life: the superior colliculus (SC), middle temporal (MT), frontal eye fields (FEF), and inhibitory pathways. The SC pathway generates eye movements toward simple stimuli, the MT pathway enables smooth tracking of objects, and the FEF pathway helps the infant control eye movements and attention, while the inhibitory pathway regulates activity in the superior colliculus and underlies later obligatory attention.

Infants show visual learning early. Haith, Hazan, and Goodman (1988) found that babies as young as 3.5 months form short-term expectations, tested by tracking eye movements in response to predictable versus irregular slide sequences.[11] Johnson, Posner, and Rothbart (1991) reported that by 4 months infants develop expectations, shown through anticipatory looks and disengagement from stimuli.[12] David Roberts (2016) found that appropriate use of images can reduce the cognitive load of excessive text and make better use of visual processing capacity.[13]

In early childhood

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From roughly ages 3–8, visual learning develops in new forms. Toddlers (3–5) combine newly developed sensory-motor skills with improving vision to explore their surroundings, often bringing objects of interest close to their eyes and faces. Because their experience is dominated by objects directly in front of them, proximal (close-up) vision is their primary perspective, unlike adults, whose larger bodies and greater viewing distance let them scan a whole scene rather than focus on a single object.[14]

Integrating visual learning with motor experience enhances perceptual and cognitive development.[15] In children aged 4–11, intellect is positively related to auditory–visual integrative proficiency, which develops most between ages 5 and 7. As this integration matures, visual learning extends from physical objects to reading, and rising reading ability supports broader learning.[16]

In middle childhood

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In middle childhood (roughly ages 9–14), vision is sharp and learning processes are well established. Studies generally find that visual approaches improve students' overall learning experience, in part by increasing engagement: graphics, animation, and video raise interest and attention to lesson material.

Students who learn visually tend to organize and process information more thoroughly, understand it better, and remember it longer.[17] Teachers using visual methods with middle-school students report more positive student attitudes, higher test performance and achievement scores, greater use of higher-order thinking, and more engagement; one study found that presenting emotional topics such as the Holocaust with visual aids increased children's empathy.[18]

In adolescence

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Gray matter generates the nerve impulses that process information, while white matter transmits them between regions; transmission is sped by myelin, which sheathes white-matter fibers but not gray matter. Because the myelin sheath is not fully formed until roughly ages 24–26, adolescents and young adults often rely on visual aids to help them grasp difficult material.[19]

Learning preferences vary widely, including between people who prefer text-based instructions and those who prefer graphics. When college students were assessed on learning preference and spatial ability, their self-ratings proved reasonably accurate, suggesting that such self-assessments can indicate how well a person learns visually.[20]

Gender differences

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One study of adolescents identified a range of preferred learning modes, from reading and teacher explanation to manipulative activity and various forms of visual and social stimulation.[21] It reported that young males tended to prefer hands-on activities they could manipulate, while young females tended to prefer learning through reading and teacher explanation.

Evidence for and against

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Although learning styles have "enormous popularity", educational psychologists regard them as urban legends.[1] While both children and adults express personal preferences, there is no evidence that identifying a student's learning style produces better outcomes.[2][3] There is significant evidence against the widely touted "meshing hypothesis" (that a student will learn best if taught in a method deemed appropriate for that student's learning style).[22] Well-designed studies "flatly contradict the popular meshing hypothesis",[22] and some suggest that students perform better when not taught with their preferred learning style.[23][24] Rather than targeting instruction to a preferred learning style, students appear to benefit most from mixed-modality presentations, for instance using both auditory and visual techniques for all students.[4]

The picture superiority effect is the observed phenomenon that pictures and images are more likely to be remembered than words,[25] evidence that visual information can aid memorization and learning.

See also

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References

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  1. 1 2 Kirschner, Paul A.; van Merriënboer, Jeroen J.G. (July 2013). "Do Learners Really Know Best? Urban Legends in Education". Educational Psychologist. 48 (3): 169–183. doi:10.1080/00461520.2013.804395.
  2. 1 2 Alley, Stephanie; Plotnikoff, Ronald C; Duncan, Mitch J; Short, Camille E; Mummery, Kerry; To, Quyen G; Schoeppe, Stephanie; Rebar, Amanda; Vandelanotte, Corneel (September 2023). "Does matching a personally tailored physical activity intervention to participants' learning style improve intervention effectiveness and engagement?". Journal of Health Psychology. 28 (10): 889–899. doi:10.1177/13591053221137184.
  3. 1 2 Cuevas, Joshua (November 2015). "Is learning styles-based instruction effective? A comprehensive analysis of recent research on learning styles". Theory and Research in Education. 13 (3): 308–333. doi:10.1177/1477878515606621.
  4. 1 2 Coffield, F., Moseley, D., Hall, E., Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning. A systematic and critical review Archived 2008-12-05 at the Wayback Machine. London: Learning and Skills Research Centre.
  5. ↑ Leite, Walter L.; Svinicki, Marilla; and Shi, Yuying, Attempted Validation of the Scores of the VARK: Learning Styles Inventory With Multitrait–Multimethod Confirmatory Factor Analysis Models, p. 2. Sage Publications, 2009.
  6. 1 2 3 4 5 "Graphic Organizers: A Review of Scientifically Based Research, The Institute for the Advancement of Research in Education at AEL" (PDF).
  7. ↑ Poldrack, R., Desmond, J., Glover, G., & Gabrieli, J. "The Neural Basis of Visual Skill Learning: An fMRI Study of Mirror Reading". Cerebral Cortex. Jan/Feb 1998.
  8. ↑ Vogel, R., Sary, G., Dupont, P., Orban, G. Human Brain Regions Involved in Visual Categorization. Elsevier Science (US) 2002.
  9. ↑ Squire, L. "Declarative and Nondeclarative Memory: Multiple Brain Systems Supporting Learning and Memory". 1992 Massachusetts Institute of Technology. Journal of Cognitive Neuroscience 4.3.
  10. ↑ Lord, C., "Schemas and Images as Memory Aids: Two Modes of Processing Social Information". Stanford University. 1980. American Psychological Association.
  11. ↑ Haith, M. M., Hazan, C., & Goodman, G. S. (1988). "Expectation and Anticipation of Dynamic Visual Events by 3.5 Month Old Babies". Child Development, 59, 467–479.
  12. ↑ Johnson, M. H., Posner, M. I., & Rothbart, M. K. (1991). "Components of Visual Orienting in Early Infancy: Contingency Learning, Anticipatory Looking, and Disengaing". Journal of Cognitive Neuroscience, 335–344
  13. ↑ "David Roberts Academic Consulting". vl.catalystitsolutions.co.uk. Retrieved 2017-01-04.
  14. ↑ Smith, L.B., Yu, C., & Pereira, A. F. (2011). "Not your mother's view: The dynamics of toddler visual experience". Developmental science, 14(1), 9–17.
  15. ↑ Bertenthal, B. I., Campos, J. J., & Kermoian, R. (1994). "An epigenetic perspective on the development of self-produced locomotion and its consequences". Current Directions in Psychological Science, 3(5), 140–145.
  16. ↑ Birch, H. G., & Belmont, L. (1965). "Auditory-visual integration, intelligence and reading ability in school children". Perceptual and Motor Skills, 20(1), 295–305.
  17. ↑ Beeland, W. "Student Engagement, Visual Learning, and Technology: Can Interactive Whiteboards Help?" (2001). Theses and Dissertations from Valdosta State University Graduate School.
  18. ↑ Farkas, R. "Effects of Traditional Versus Learning-Styles Instructional Methods on Middle School Students" The Journal of Educational Research. Vol. 97, No. 1 (Sep. – Oct., 2003), pp. 42–51.
  19. ↑ Wolfe, Pat. (2001). "Brain Matters: Translating the Research to Classroom Practice". ASCD: 1–207
  20. ↑ Mayer, R. E., & Massa, L. J. (2003). "Three Facets of Visual and Verbal Learners: Cognitive Ability, Cognitive Style, and Learning Preference". Journal of Educational Psychology, 95(4), 833.
  21. ↑ Eiszler, C. F. (1982). "Perceptual Preferences as an Aspect of Adolescent Learning Styles".
  22. 1 2 Pashler, Harold; McDaniel, Mark; Rohrer, Doug; Bjork, Robert (December 2008). "Learning Styles: Concepts and Evidence". Psychological Science in the Public Interest. 9 (3): 105–119. doi:10.1111/j.1539-6053.2009.01038.x.
  23. ↑ Rogowsky, Beth A.; Calhoun, Barbara M.; Tallal, Paula (14 February 2020). "Providing Instruction Based on Students' Learning Style Preferences Does Not Improve Learning". Frontiers in Psychology. 11. doi:10.3389/fpsyg.2020.00164. PMC 7033468.
  24. ↑ Krätzig, Gregory P.; Arbuthnott, Katherine D. (February 2006). "Perceptual learning style and learning proficiency: A test of the hypothesis". Journal of Educational Psychology. 98 (1): 238–246. doi:10.1037/0022-0663.98.1.238.
  25. ↑ Shepard, Roger N. (1967-02-01). "Recognition memory for words, sentences, and pictures". Journal of Verbal Learning and Verbal Behavior. 6 (1): 156–163. doi:10.1016/S0022-5371(67)80067-7. ISSN 0022-5371.
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