The idea that each of us has a preferred way of learning is a long-established concept. This “learning style” approach, rooted in psychological type theory, suggests that individuals process and understand information most effectively in different ways: a common distinction being between those who learn best through visual, auditory or kinesthetic means. More complex models identify several dimensions that can be used in combination to describe an individual’s learning style, for example:  sensory/intuitive, visual/verbal, active/reflective, sequential/global (index of learning styles developed by Felder and Silverman in the late-80s, revised by Felder 2002); concrete experience/abstract conceptualization, active experimentation/reflective observation (Kolb’s learning styles model).

The concept of ‘learning styles’ has been applied in a wide variety of settings, from kindergarten through adult education, with countless educational and training programs designed to take the preferred learning style/s of the target audience into account – the other side of the learning styles coin being of course matching teaching styles.  

An alternative view was explored in a recent New York Times article which looked at the factors that can best contribute to effective learning (studying)  – a topic clearly of great interest to the NYT Science Section reading public according to the ‘most-popular ’ article ratings that week!

 The article describes the environmental and cognitive variables that may best support learning and suggests ideas to improve study skills; for example, alternating study environments, mixing content and types of practice, spacing study sessions, self-testing (e-learning and project-based learning anyone?), and discusses their impact on retention.  Interestingly, the article references a review of the research on learning styles published in the journal “Psychological Science in The Public Interest”, which concluded there is a lack of ‘methodologically sound studies’ of the learning styles approach despite its popularity.

So, although the article focuses on how to improve traditional study habits, there are useful connections with instructional design in its broader application. In particular, self-directed e-learning programs can allow for the variety of experiences that the article suggests help learning and retention of information. For example:

–          Being able to study in different environments (e.g. at home in a quiet room, at a busy café). The researchers suggest that concentrating on the same material in different locations aids retention and ‘slows down forgetting’.

–          Mixing the type of task or problem covered in one sitting, rather than repeating the same type of exercise over and over, and only then moving on to a different type.  Working through a mixed set of practices means that each task requires new processing and encourages deeper learning.

–          Varying the modes of presentation, so the learner can interact with the material in different forms.

–          Incorporating frequent self-testing opportunities throughout a program. The suggestion is that rather than simply being a method of assessment, the very act of testing can enhance learning in that it forces the brain to retrieve ideas that subsequently become more accessible.

As e-learning becomes more widely used for a range of purposes – higher education, workplace training, professional development – integrating such findings from cognitive science research into the instructional design can move it away from the old ‘page-turning online’ experience into a truly rich learning experience.