Teaching with style: computer aided instruction, personality and design education

Durling, David (1996). Teaching with style: computer aided instruction, personality and design education. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.0000e11b


The investigation reported in this thesis concerns the possibility of automatically matching the learning styles of design students with appropriate styles of computer aided instruction (CAl).

Individual adult learners exhibit preferences for the way information is presented and for the ways in which they are taught. These preferences arise from characteristics known as cognitive styles which are associated with personality. Cognitive dissonance occurs when there is a mismatch between styles of teaching and styles of learning. Under these conditions some students will be discouraged. A survey of students on typical design courses showed them to have particular learning preferences. In this respect they are differentiated from tutors who may prefer to teach in a different style.

CAl systems also exhibit styles. These are manifest in features such as the computer's control of learning interactions and the form of information which the system delivers. Computer-based training has often been of a sequential, drill-andpractice kind which encourages rote learning. This style has met with limited success, and it is shown to be unsuitable for most design students.

The Myers-Briggs Type Indicator (MBTI) is used to classify the psychological types of design students. Evidence of learning preferences from the MBTI and from related sources is given. From a theoretical description of learning episodes, a computer-based model is developed that provides CAl treatments matched to sixteen learning styles.

It is concluded that CAl-based teaching of technological information to design students can be more optimally matched. The principles established have wider implications for communications between designers and others.

Viewing alternatives

Download history


Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions