Abstract
Learning styles and courseware design
Highlights
As the use of technology to support teaching and learning becomes more widespread, the need to make learning with computers more effective becomes more important
In this paper we outlined a number of ways of classifying learners according to preferred learning style, and raised a number of issues regarding the feasibility of tailoring learning to accommodate learning styles
We presented two solutions that illustrate how courseware design can take into account individual preference for learning in a particular way
Summary
As the use of technology to support teaching and learning becomes more widespread, the need to make learning with computers more effective becomes more important. Many learner attributes that can affect performance on a learning task have been identified (see Goodyear et al, 1991). They include: intelligence, prior knowledge of the subject matter or skill, motivation, level of anxiety, estimation of learning ability (the learner's self-concept), the amount of learner control offered, and preferred cognitive or learning style (these terms are often used interchangeably). If pedagogical activities accommodate different learning styles, it is argued that motivation will increase and that learning will be more enjoyable, effective and efficient. A learner may fall part of the way along the deep-surface spectrum, rather than being either wholly a deep learner or wholly a surface learner
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