HUMAN-COMPUTER INTERACTION
SECOND EDITION
HUMAN-COMPUTER INTERACTION
SECOND EDITION
The ultimate test of a product's usability is based on measurements of users' experience with it. Therefore, since a user's direct experience with an interactive system is at the physical interface, focus on the actual user interface is understandable. The danger with this limited focus is that much of the work that is accomplished in interaction involves more than just the surface features of the systems used to perform that work. In reality, the whole functional architecture of the system and the cognitive capacity of the users should be observed in order to arrive at meaningful measures. But it is not at all simple to derive measurements of activity beyond the physical actions in the world, and so usability engineering is limited in its application.
In this chapter we will look at two types of model. First we will consider the capture of user requirements within its social and organizational context. After this we will look at cognitive models which address aspects of users' perceptual and mental processes. Both types of model are highly user centred. The first looks outwards at the larger human context, the second is focused inwards at the individual user.
Another useful distinction between these models is whether they address the acquisition or formulation of a plan of activity or the execution of that plan. Referring back to the interaction framework presented in Chapter 3, this classification would mean that some models are concerned with understanding the User and his associated task language while others are concerned with the articulation translation between that task language and the Input language. The presentation of the cognitive models in this chapter follows this classification scheme, divided into the following categories:
Architectural assumptions about the user are needed in any of the cognitive models discussed here. Some of the more basic architectural assumptions were covered in Chapter 1, such as the distinction between long- and short-term memory. After discussing models in the three categories above, we will describe two additional cognitive architectures and how they are relevant for analyzing inter-active system design.
Many of these nominally cognitive models have a rather computational flavour. This reflects the way that computational analogies are currently used in cognitive psychology. The similarity between the language describing the user and that describing the computer has some advantages and some dangers. On the positive side it makes communication and analysis of the combined human--computer system easier. For instance, cognitive complexity theory (described later) produces models of both user goals and the system grammar, and can reason about their interaction. On the other hand, there is a danger that this will encourage a mechanistic view of the user.
Another important issue has to do with the treatment of error. Users are not perfect. A goal hierarchy may show how the perfect user would achieve a goal, but what can it say about difficulties the user may have along the way? In general, prediction of error behaviour is poor amongst these hierarchical modelling techniques, though some (cognitive complexity theory (CCT), for example) can represent error behaviour.
The original GOMS model has served as the basis for much of the cognitive modelling research in HCI. It was good for describing how experts perform routine tasks. Coupled with the physical device models discussed later, it can be used to predict the performance of these users in terms of execution times. It was never intended to provide the kind of information about the user's knowledge that could be compared across different tasks in order to predict things like training or transfer times.
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