technology based on digital computers for the

design of man-machine interface systems has led to

a requirement for consistent models of human

performance in routine task environments and

during unfamiliar task conditions. A discussion is

presented of the requirement for different types of

models for representing performance at the skill-,

rule-, and knowledge-based levels, together with a

review of the different ways in which information is

perceived at these different levels in terms of

signals signs, and symbols. Particular attention is

paid to the different possible ways of representing

system properties which underlie knowledge-based

performance and which can b characterized at

several levels of abstraction—from the

representation of physical form, through functional

representation, to representation in terms of

intention or purpose. Furthermore, the role of

qualitative and quantitative models in the design

and evaluation of interface systems is mentioned,

and the need to consider such distinctions carefully

is discussed