Using structural descriptions of interfaces to automate the modelling of user cognition (original) (raw)
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This paper is a theoretical contribution, elaborating the concept of models as used in Cognitive Ergonomics. A number of formal modelling techniques in humancomputer interaction will be reviewed and discussed. The analysis focusses on different related concepts of formal modelling techniques in humancomputer interaction. The label "model" is used in various ways to represent the knowledge users needs to operate interactive computer systems, to represent user relevant aspects in the design of interactive systems, and to refer to methods that generate evaluative and predictive statements about usability aspects of such systems. The reasons underlying the use of formal models will be discussed. A review is presented of the most important modelling approaches, which include External Internal Task Mapping Analysis; Action Language; TaskAction Grammar; the Goals, Operators, Methods and Selection model; Command Language Grammar and Extended TaskAction Grammar. The problems associated with applying the present formal modelling techniques are reviewed, and possibilities to solve these problems are presented. Finally, we conclude with a discussion of the future work that needs to be done, i.e., the development of a general design approach for usable systems, and the need to focus attention on the practice of applying formal modelling techniques in design.
Causal Functionally Models For Graphical User Interfaces
International Journal of Modelling and Simulation, 1990
When building user interfaces to AI applications for a complex system, there is an often-overlooked knowledge engineering effort to capture an expert's view of the system, and to detennine the abstraction of data that will be presented to users. This knowledge is generally mixed into the interface or graphics code, and is subsequently lost when other applications are developed for the same complex system, or in the event of porting the application to another platform. Few methods exist for representing the underlying structure of an expert's view of a system that originally indicated the content to be presented by an interface. It is desirable to capture and explicitly represent this knowledge, so that it can be used by a vuriety of interface processes and accessed in different ways to provide appropriate views of the system for new application. We present a technique for using a causal model to represent expert knowledge about system functionality and behavior. Our approach extends previous work in causal reasoning by mapping the behavior of a system at the usual structural level to higher-level functional descriptions of what the system is actually doing. In this paper, we discuss the causal-modeling approach to user interfaces and demonstrate the applicability of the approach with an example system. Practical implementation trade-offs and considerations are discussed.
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Since the early 1980's, intelligent and adaptive systems have appeared and have been written about in a variety of guises. Although there are many differences between such systems as adaptive user interfaces, intelligent help systems and explanation systems, there are many similarities as well. The most notable of these is that they all require user models to be maintained and exploited as part of their designs. Furthermore, they share the same high level architecture. This paper discusses the use of user models in humancomputer interaction design and offers a common architecture for these adaptive systems. A methodology for the development of these systems is presented.
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