Abstract
The use of signal detection theory (SDT) in evaluating attentional and decision-making performance in the context of human-computer interaction is reviewed. SDT provides a means for distinguishing between accuracy and criterion setting in decision-making environments. This is useful in evaluating the effectiveness of the decision-making performance of an intelligent machine, a human user, or a human-machine system. SDT is also useful in deciding how best to allocate subtasks and functions in human-computer monitoring systems. Applications of SDT to the evaluation of rule bases in expert systems and the design of computer assistance in human-computer monitoring are discussed.
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