| ©1990, 1995 | section list | 2: Literature | overview | General Contents |
| Section 2.1 | 2.2 Classification subsections | Section 2.3 | ||
Part of the disarray of the literature is caused by different authors meaning different things when they write about models, and by these meanings not being entirely clear and explicit. The literature shows that people have been aware of a variety of meanings for many years, and there are several papers which offer classifications of the meaning or usage of the terms. We shall start this section by looking at the distinctions between owners of models and between objects of models. Then, looking at the purpose of models, we find that there is a reasonable correspondence between purposes and the categories given in the previous section. This suggests that the purpose of a model is a important factor in classifying a mental modelling approach.
Distinguishing the owner and object of a mental model is important, particularly for readers who may gain a wrong impression by writings that do not make this clear. To start clarifying this, let us imagine a situation where we have a user using a system (often complex) which has been designed by someone else (a designer), and the interaction is being studied by another person, a scientist.
An author often quoted or cited for distinguishing the owner and object of a model is Norman [94]. He distinguishes the target system t, the scientist's conceptual model of that system C(t), the user's mental model of that system M(t), and the scientist's conceptual model of the user's mental model C(M(t)). This brings out the importance of whose model it is, in that M(t) is not assumed to be identical with C(t). Equally well, C(t) is not the same as C(M(t)), even though it may be the same scientist who is doing the conceptualising. Great potential confusion may arise, because C(M(t)) is intended to be like M(t). Other authors sometimes talk loosely as if C(M(t)) actually was M(t).
Now if the user could reliably describe his or her mental model M(t) explicitly, the scientist could presumably accept this, and there would be no need for a separate C(M(t)). But most often, much of M(t) is implicit and tacit. Remembering this should help to reinforce the distinction.
Streitz [133], elaborating Norman, introduces the needs of a designer into his ``mental model `zoo' ''. The models of the target belonging to the system designer Cd(t) and to the psychologist Cp(t) may differ, as may their models of the user's mental model, Cd(M(t)) and Cp(M(t)). He also makes the distinction between the `content problem' (the problem to be solved, itself) and the `interaction problem' (how to solve the problem with the tools in hand). The user's mental model of the content domain is referred to as M(c). We may follow Streitz in suggesting a different `target' for each of the different ways in which someone may be treating a system. Clearly there are many such distinctions which could be made in the spirit of the original ones put forward by Norman.
Whitefield [140] gives a classification based on these same two dimensions of `whose' and `what of'. He claims that this classification is of use to systems designers, so it is worth a closer look. He has
There is also the question of what a model is for. As we shall see, the categories revealed by this question map much more closely onto the apparent groups outlined in §2.1, suggesting that the purpose of a model is an important feature for its classification. Although the purpose of a model is often ill-defined in many authors' works, it seems that without the dimension of purpose, there is little order or sense to be made from the literature on models.
Norman [94] makes passing reference to the purpose of a model without considering purposes as centrally important. In his view, the purpose of a mental model is to allow the person who owns it to understand and to anticipate the behaviour of a system, whereas conceptual models are devised as tools for the understanding or teaching of systems. (Norman talks of physical systems here, but we can easily extend the idea to cover human or social systems.) In this way, Norman recognises the question of what the model is for, without considering it as contentious. In particular, he does not discuss the possibility that a user may have a number of separate models of a particular system, used for different purposes, nor the possibility that a scientist may have various models of the user's mental model of a particular system. Norman describes models as tools, and we may reflect that, for a tool, the purpose is at least as significant a determining factor in its nature, as the identities of the tool's user and the object on which the tool is used.
Other authors make more of the importance of purposes of models in general. Murray [88] posits that ``a statement of a model's purpose is an additional necessary constituent of any taxonomy which is to be used to specify the boundaries of different classes of models''. Benyon [13] asks ``what is the purpose of the User Model? Is it to assist designers? to assist the user? to provide an adaptive capability for the system? to assess the knowledge of the user? to develop and refine other models? to assist research into human cognition?'' Wahlström [138] distinguishes the following possible purposes of models:
There is a general approach to the concept of mental models, which aims not to describe particular users' mental models of a system, but rather to describe general issues for the designer to consider when thinking about the needs of the user. These issues may include general principles of human cognition, and its limitations; general observations about the way people deal with complex systems; factors which affect human tendency to error; and so on. These considerations may aid systems designers simply by getting them to think along appropriate lines. These approaches fall largely into the class described in §2.1.9 above.
If the purpose of a model is communication of an idea (outside the training context), there is not much we can deduce in principle about the form of the model. The way in which a researcher may attempt to communicate important ideas to a systems designer could be expected to vary greatly depending on the individual researcher and his or her appreciation of, and rapport with, the intended audience, which is typically seen to be both academic and professional.
Three surveys of opinions or practice of professional designers [11, 51, 131] give no positive evidence that designers are influenced by this kind of model. Designers seem to have many other more pressing things in mind: consistency and structure in the software; commercial pressure and deadlines; compatibility, convention and current design practice are among these.
Of course, these ideas continue to circulate among HCI researchers. More discussion on this topic would say no more than could be said of ideas within scientific enquiry in general.
A possible purpose for a mental model is to aid understanding of human cognition. Researchers need to develop their understanding of the field to continue to generate further useful facts for designers, whereas one would expect designers to be more interested in the applicable facts. Models of user's mental structures and processes could help researchers' understanding by giving extra ways of looking at cognition, whether by metaphor, analogy or other means. It is the kind of knowledge that requires further digestion and synthesis by cognitive scientists and HCI researchers before it is directly useful.
Some authors see mental models primarily in this way. For example, Young [150] suggests that what he calls a ``User's Conceptual Model'' (even though this sometimes refers, as here, to a model possessed by a psychologist) should help to explain aspects of the user's performance, learning and reasoning about a system, as well as providing guidelines for good design. Similarly, Carroll [21] says, ``Mental models are structures and processes imputed to a person's mind in order to account for that person's behavior and experience'', thereby characterising models as psychological theories. There is much overlap between the class of models described here and those described in §2.1.5 above.
Viewing mental models as aids to understanding does not imply much about the form of such models, except perhaps that they should be comprehensible by the people for whom they are intended, i.e., researchers in HCI. It would be shortsighted of HCI practitioners to underrate the importance of this kind of model just because they are not immediately useful. It is from here that future developments may arise.
A designer may wish to know something about the potential or actual performance of a human-machine system, while wishing to avoid the need to do experiments involving people, which could be time-consuming and expensive. This could be in the context of choice between possible designs.
The formalisable models mentioned in §2.1.3 explicitly aim to predict either human performance or competence in terms of their analysis of the task. For any model to be a useful predictive tool, it must be able to take values of things which are assumed to be known, and produce values for the quantities which are to be predicted. This, of course, depends on what quantities are assumed to be known, or taken as known. One view of the essence of a model could be to predict whatever the modeller was interested in, from the things the modeller knows.
There is an important distinction within this class of models between models to be communicated and ones for private use. If the model is made to be communicated it would of course have to be explicit; but the models that we spontaneously generate, for the prediction and control of the things that we deal with in everyday life, are not normally available for direct inspection, either by others or even (often) by the owner of the model, and therefore if we wish to know about these models, their contents have to be inferred.
The formality of explicit models enables much more detailed discussion of particular approaches to modelling, which will be done in §2.3.1 shortly below.
Operator, or engineering, models also provide predictions, particularly about human performance and mental workload; and hence possible errors, and suggested task allocation between human and computer. For reasons given above (§2.1.4), no discussion of these models is given here.
As has been explained above (§2.1.6), these models form a separate category, which is recognised here, but will not be discussed. From the user's point of view, the purpose of these models is to aid understanding and using the system, while at the same time the trainer is treating them as something to be communicated, to assist the training process by supporting ``direct and simple inference of the exact steps required to operate the device'' [67]. The form of these models is an issue to be dealt with by theoretical and empirical study within the discipline of the psychology of learning, which is outside the present study.
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