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5.3. INTERFACE DESIGN AND PROVISION STRATEGIES

The design features of the interface used to provide explanations, as well as the strategies used for providing explanations, will also influence the patterns of ES explanation use. Specific aspects of the interface design include the following. First, the amount of effort required for users to access the explanations, i.e., the accessibility of the explanations, will influence their use. Two possible classes of strategies for accessing explanations can be identified. These include an active strategy where the ES presents explanations without the user having to request them, and a range of passive strategies that require the user to make varying levels of explicit physical effort to access the explanations. Such effort can range from clicking on specialized explanation icons presented on the screen to hitting predesignated function keys for accessing and scanning the explanations. Generally, an active strategy has the system interrupt the dialog to provide explanations or makes them available continuously as part of every screen of the ES. In the design of ES explanation facilities, it is important that interface designers consider the amount of effort required for users to request and access the explanations. The results of studies on cost-benefit models of the effort involved in utilizing computerized decision aids suggest that the accessibility of explanations, i.e., the cost of accessing them, will exert a salient influence on the use of explanations. Second, the communication mode used for presenting the explanations, e.g., audio and/or visual modes, will also influence the use of explanations. Third, the presentation format utilized for the explanations is also a factor, e.g., text explanations in contrast to image-based explanations that use graphical, iconic, and animation formats.

Considering that the primary reason for the provision of ES explanations is to improve users' understanding of the ES and its domain, the feedforward and feedback explanation provision strategies presented earlier will also influence the use of explanations. The importance of these explanation provision strategies becomes obvious if one considers the analogy of a child engaged in a learning process to improve his or her understanding. While "an explanation machine," in the form of a child's parents, may be continuously available to provide explanations about some phenomenon that is the target of the learning, the child will only seek, attend to, and benefit from explanations provided at particular stages of the learning process. At different stages of the process, different types of explanations will be sought, and it can be expected that children at varying stages of cognitive development will seek different amounts and types of explanations. As well, it is also likely that explanations provided automatically without being requested, will at times impede rather than encourage the learning that takes place. This analogy therefore suggests that any evaluation of the influence of the explanation provision strategies must therefore take into consideration the other design factors.

5.4. USER CHARACTERISTICS

Three distinct categories of user characteristics that will impact the use of explanations can be identified: user expertise, individual differences, and the level of user agreement with the ES. Of these, user expertise is potentially the most significant to the design and use of ES explanations. Various theories of skill acquisition support this belief. As well, the empirical studies discussed in the last section, have also found significant effects for this factor. All these studies employed users' knowledge of the task domain to operationalize user expertise. The human-computer interface literature reveals another aspect of user expertise that can be considered as being just as relevant. This is the level of users' expertise or familiarity with expert systems themselves. This is termed systems expertise.

Various types of cognitive and personality-based individual differences can also be identified, primarily from the literature on decision support systems, as potentially influencing the use of ES explanations. However, while much is known of their influence on human cognitive functioning, they suffer from the lack of an adequate and coherent theoretical basis. Additionally, as is now recognized in the study of decision support systems, there is only a small likelihood that an individual differences approach to the design of decision aids will yield practical and cost-beneficial design requirements.

The final category of user characteristics that can be identified is the level of user agreement with the ES. Studies found that the use of explanations increased the level of user agreement with ES conclusions. Together with the finding that experts were more likely to agree with an ES's conclusions than novices, this suggests that there could potentially be a reverse effect as well. The level of initial user agreement with ES conclusions would influence, to some extent, the amount of explanations used. As the differences in the level of domain expertise can result in different levels of agreement with an ES's conclusions, this suggests that the level of user agreement potentially moderates the influence of user expertise on the use of explanations.


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