The brain is made up of two sides, or hemispheres, connected by an intricate network of nerve fibres called the corpus callosum. Although each hemisphere is almost identical in terms of structure, each side operates in an entirely different way and is associated with very different activities. This is referred to as specialisation of lateralisation.

In general terms, learning style is thought to be connected with an individual’s dominant brain hemisphere and dominant mode of processing new information. This can be split into auditory, tactile or visual learning. At times we all use both hemispheres either alternatively or simultaneously, with one usually acting as the primary, and for this reason it is useful for an individual to know which side is dominant and to recognise which learning style is preferred.

Classical education usually involves lectures in which facts are presented one after the other without an initial overview, followed by timed tests that assess how well students have memorised the information and check how quickly and accurately they can retrieve it on demand. This tends to fit the left-brained auditory learner most effectively. Hands-on workshops may be a good fit for a right-brained tactile learner who learns best by actively testing information. Auditory-tactile learning may need a combination of vocal and tactile stimulation in the classroom in order to learn new information. Lastly, right-brained visual learners tend to prefer a top down view of the whole picture before learning the details, with far more images and diagrams. Some learn most effectively from a combination of auditory, visual and tactile multimedia input (video clips and the internet are often helpful in this case).

When faced with a classroom of thirty plus individuals, teachers are faced with the mammoth task of accommodating the various learning styles in the short amount of time available. Even the most dedicated teacher can struggle with this, and some subjects seem to be least compatible with those students who prefer to learn primarily by seeing and visualising. The same subjects that we are told are most important to the future progress of our civilisation: science, technology, engineering and mathematics (STEM subjects). To solve the issues facing us in the twenty first century, we need a workforce that can think creatively about scientific and technological issues. Yet the most creative students are the ones faced with a difficult barrier when it comes to education in the above subjects.

The vast majority of teaching is currently done using words. The teacher speaks to the class, the students read a textbook or digital document, and they are expected to respond to tasks in a mostly written format. Not only does this have a negative impact on visual learners, but it also causes difficulties for students for whom English is a second or third language (an increasing factor in today’s multicultural society), or for those students with dyslexia. Data-heavy subjects such as maths and science compound the problem by adding numbers to the words, making it near impossible for both visual learners and those with additional issues such as dyscalculia to navigate the information.

So how can we more effectively encourage visual learners to engage with traditionally non-visual subjects? One famous individual who is often used as an example of the potential synthesis between images and mathematical thinking is Albert Einstein. In M. Wertheimer’s “Productive Thinking” (1959) he explains, “I rarely think in words at all. A thought comes, and I may try to express in words afterwards.” For Einstein, words and other symbols (mathematical or scientific) were a secondary stage of the thought process, only employed after the initial formulation of ideas with images and feelings. In his autobiographical notes, he states that “I have no doubt that our thinking goes on for the most part without the use of symbols, and, furthermore, largely unconsciously” (Schilpp, 1979, pp.8-9).

Imagining the universe. Photo: NASA

Imagination and the ability to see a problem as a whole were hugely important components of scientific thinking for Einstein, and, he believed, the basis for all great achievements. In fact he argued that for creative work in science, imagination was even more important than knowledge: “when I examine myself and my methods of thought, I come close to the conclusion that the gift of imagination has meant more to me than any talent for absorbing absolute knowledge” (Calaprice, 2000, 22, 287, 10).

If the use of imagery can play such an important role in the development of scientific work, then surely we need to make better use of visual information in education, even so far as treating the transition between imagery and words or mathematical symbols just like the translation of one language to another.

There have been some recent endeavours in this area. IT is one field that has seen a modern trend towards teaching in a graphical format. This year, England is set to become the first country in the world in which computer programming will be mandatory from primary school onwards. Children will begin writing basic code at the age of five and develop their skills at least until GCSE level. In order to teach programming at such a young age, a variety of new software has been developed, such as the Alice interface (an interactive 3D environment that teaches object-oriented programming through the creation and manipulation of a virtual world), Merlin Kids (a simple program that teaches sequential programming through the direction of 3D characters), and RoboMind (software that teaches logic, computer science and robotics by programming a small robot through a series of challenges), to name but a few.

The above examples are certainly encouraging and hopefully the start of a new movement towards a more visual approach to teaching methods. Understanding and utilising an individual’s learning styles is a big step towards maximising potential and overcoming learning differences, and an essential task when considering the wider implications for scientific and technological advances in the future.

References

• Calaprice, Alice. (Ed.). (2000). The Expanded Quotable Einstein. Princeton, N. J.: Princeton University Press.
• Schilpp, P. (Ed.), (1979), Albert Einstein: Autobiographical Notes. La Salle, III: Open Court.
• Wertheimer, Max. (1959). Productive Thinking. Enlarged edition. New York: Harper and Brothers.