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Eileen B. Entin

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Publications by Eileen B. Entin (bibliography)

1995

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Entin, Eileen B., Serfaty, Daniel and MacMillan, Jean (1995): The Effect of Time Pressure on Visual Information Utilization in Machine-Aided Target Recognition. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. p. 950.

“In machine-aided target detection, human operators work with an aided target recognition (ATR) system to locate targets in cluttered and degraded imagery. A tradeoff exists when time is short between the use of fine-grained information that may offer more information to a human decision maker but may require more processing time, and the use of coarser-grained information that offers less information but may be processed more quickly. We investigated operators' preferences and the sensitivity of their performance to time pressure under varying levels of information granularity. Three levels of granularity of ATR information were presented: binary (coarse granularity), discrete (moderate granularity), and continuous (fine granularity). The display methods for the ATR's judgments were selected to be most appropriate and natural for each level of granularity. The binary and discrete levels were presented graphically while the continuous information was presented numerically. Subjects' performance (measured as missed-detection and false-alarm rates) and their preferences were analyzed. The results showed that coarse and moderate levels of granularity for presentation of ATR information are robust to varying degrees of time pressure. The presentation of fine-grained ATR information, while slightly improving performance when a comfortable amount of time was available, decremented performance in the high time-pressure situation. The discrete level of information, which was presented in this study in a color-coded display format, was preferred by subjects over the binary and continuous levels. Subsequent studies will investigate different modes of presentation of discrete information to assist operators in their detection task, especially under high time-pressure conditions. The results of this work will be used in designing human-machine interfaces for ATR systems.”

1994

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MacMillan, Jean, Entin, Eileen B. and Serfaty, Daniel (1994): Operator Reliance on Automated Support for Target Recognition. In: Proceedings of the Human Factors and Ergonomics Society 38th Annual Meeting 1994. pp. 1285-1289.

“In machine-aided target recognition, human operators work with an automatic target recognition (ATR) system to locate targets in cluttered and degraded imagery. The operator must integrate his or her own visual judgment concerning whether a target is present in the image with the ATR's judgment, which is typically expressed numerically. We conducted a series of experiments in which subjects attempted to locate target shapes among non-targets based only on visual images and based on both visual images and supplementary numeric information such as an ATR might provide. Image quality was controlled as an independent variable through the use of distortion rates that randomly altered pixel values to degrade the image. We found that subjects maintained a constant false alarm rate as image distortion increased, at the expense of a lower hit rate. This result was found consistently in experiments where the subjects' task was to distinguish single targets from a blank background, to distinguish single targets from single non-targets, and to locate multiple targets in a multiple-object display. We also found a bias toward over reliance on image versus numeric information. As image distortion increased, subjects failed to make optimal use of supplementary numeric information and showed an unnecessary decrease in performance. The results suggest that operators may experience difficulty in working with an ATR that has a high false alarm rate, even if the ATR's hit rate is also high, and that numeric expressions of ATR judgment may be undervalued by operators in locating targets.”

1993

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MacMillan, Jean, Entin, Eileen B. and Serfaty, Daniel (1993): Evaluating Expertise in a Complex Domain -- Measures Based on Theory. In: Proceedings of the Human Factors and Ergonomics Society 37th Annual Meeting 1993. pp. 1152-1155.

“Human factors practitioners are often concerned with defining and evaluating expertise in complex domains where there may be no agreed-upon expertise levels, no single right answers to problems, and where the observation and measurement of real-world expert performance is difficult. This paper reports the results of an experiment in which expertise was assessed in an extremely complex and demanding domain -- military command decision making in tactical warfare. The hypotheses of the experiment were: 1) command decision-making expertise can be recognized in practice by domain experts; 2) differences in the command decision-making expertise of individuals can be identified even under conditions that do not fully replicate the real world; and 3) observers who are not domain experts can recognize the expert behaviors predicted by a mental-model theory about the nature of expertise. In the experiment, the expertise of military officers in developing tactical plans was assessed independently by three "super-expert" judges, and these expertise-level ratings were correlated with independent theory-based measures used by observers who were not domain experts. The results suggest that experts in a domain have a shared underlying concept of expertise in that domain even if they cannot articulate that concept, that this expertise can be elicited and measured in situations that do not completely mimic the real world, and that expertise measures based on a mental-model theory can be used effectively by observers who are not experts in the domain.”

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