2.5 Where does the literature point to?

2.5.1 What do authors consider desirable?

A number of authors have expressed what they think would make a good mental model, though for obvious reasons they cannot say exactly how this would be achieved, or indeed whether it is in principle possible.

Green, Schiele & Payne [45] give six tentative criteria (here abbreviated) that they think a formalisable model should meet in order to be directly applicable by systems designers.

1. It must include all major relevant psychological phenomena.
2. It must separate the representations of the human and of the design.
3. It must represent external semantics.
4. It must be usable by, and appealing to, the designer.
5. It must be executable, or otherwise verifiable.
6. It must yield quantitative evaluations, which must have been confirmed empirically in the kind of setting intended for its use.

Models that would be currently appropriate, according to Hollnagel [57], would be those that describe intentions, goals, plans, strategies and the human ways of thinking about these.

Sheridan & Hennessy [125] suggest both qualitative and quantitative models of the various parts of the human-machine system, which would then give to the systems designer the goal of harmonising these various models.

In giving these desiderata, these authors either state or imply that no model currently comes up to all of these standards at once, and also they imply that they do not see any model coming up to those standards in the near future. This points towards the need to develop theories, that are currently still in the realm of speculative psychology, into formal implemented models; to broaden current formal theories to take into account more of the realities of human cognition; and to package them into a form that matches the needs of their users, the designers.

A model of a human operator which could be combined with a task description, and from that predict what information the operator would need, at what time, would make the task of the designer much easier. For whereas in the simplest systems it is possible to present all relevant information all the time, in a complex system this is not practical, and thus the designer needs to know about the operator's information needs. In order for the designer to know how to prioritise information for the operator, the model of the operator needs to tell the designer much about the presumed mental processes in progress in the operator. Such a model would at least have to cover the operator's representations both of the task, and of the tools by which he or she is going to perform that task; and the operator's ways of combining together and processing that information.

2.5.2 Needs

Needs are perhaps only the converse of desires, but the points that can be made about the general deficiencies in mental models differ somewhat from the desiderata.

Woods [145] states that the problem in designing decision support systems is ``the lack of an adequate language to describe cognitive activities in particular domains''. The formalisms reviewed above are too idealised for this task, as they rely on unsubstantiated assumptions. In the opinion of Hollnagel & Woods [59], ``practically every attempt to make a formal description of a part of human activity'' fails to recognise that one cannot formalise human activity on the same basis as the logical models of the physical world.

The models of cognition are off target, dealing with cognition at the wrong level. Suchman [134, p.178] characterises the research strategy in cognitive science as first representing mental constructs, then stipulating the procedures by which those constructs might determine action: this is seen as relying on an explicit enumeration of the conditions under which certain actions are appropriate. Suchman wishes to ``explore the relation of knowledge and action to the particular circumstances in which knowing an acting invariably occur.'' Suchman goes on to say that the way each person interprets and uses particular circumstances depends on the particular situation. Her views tally with the recognition that skilled behaviour does not have the explicit nature of problem-solving tasks, such as the involvement of detailed stable plans. The AI view of planning is also regarded as inadequate for characterising human cognition in HCI by Young & Simon [152]. They suggest an approach based on partial, rather than complete, plans.

The literature seems to be saying that neither formal nor more general mental models are able to deal with the particularities of real complex tasks. Further, if we are to model an operator in a situation where there are a number of concurrent tasks, this would obviously compound the modelling problem with the need to model the tasks separately, and it may also introduce the added need to model the way in which the operator allocates attention and effort between the various tasks. All this underlines what may be regarded as the central message from the literature, that there are currently no experimentally derived and tested models of human performance in complex control tasks.