Previous study has shown that an understanding of expert performance expressed as a cognitive model represents a valuable training asset, with uses ranging from improving training design to informing feedback in intelligent tutoring systems. This paper presents performance data from an expert landmine detection operator, and a general cognitive model of frequency-based decision-making applied to the specific task of making mine-vs-clutter decisions based on sequences of discrete stimuli. The functional capabilities of the model are studied in a general testbed, then its performance is directly compared to that of the expert. Further extensions and applications of the cognitive model are discussed.
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