Signal detection theory and methods for evaluating human performance in decision tasks

Obrien, Kevin; Feldman, Evan M.

Signal Detection Theory (SDT) can be used to assess decision making performance in tasks that are not commonly thought of as perceptual. SDT takes into account both the sensitivity and biases in responding when explaining the detection of external events. In the standard SDT tasks, stimuli are selected in order to reveal the sensory capabilities of the observer. SDT can also be used to describe performance when decisions must be made as to the classification of easily and reliably sensed stimuli. Numbers are stimuli that are minimally affected by sensory processing and can belong to meaningful categories that overlap. Multiple studies have shown that the task of categorizing numbers from overlapping normal distributions produces performance predictable by SDT. These findings are particularly interesting in view of the similarity between the task of the categorizing numbers and that of determining the status of a mechanical system based on numerical values that represent sensor readings. Examples of the use of SDT to evaluate performance in decision tasks are reviewed. The methods and assumptions of SDT are shown to be effective in the measurement, evaluation, and prediction of human performance in such tasks.

Document ID

19940007059

Acquisition Source

Legacy CDMS

Document Type

Conference Paper

Authors

Date Acquired

September 6, 2013

Publication Date

February 1, 1993

Publication Information

Publication: Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992), Volume 2

Subject Category

Accession Number

94N11531

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Public

Work of the US Gov. Public Use Permitted.

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