Browsing by Author "Lin, DYM"

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The effect of time pressure on expert system based training for emergency management
(1998-07-01)
Lin, DYM
;
Su, YL
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
In many emergency situations, human operators are required to derive countermeasures based on contingency rules whilst under time pressure. In order to contribute to the human success in playing such a role, the present study intends to examine the effectiveness of using expert systems to train for the time-constrained decision domain. Emergency management of chemical spills was selected to exemplify the rule-based decision task. An Expert System in this domain was developed to serve as the training tool. Forty subjects participated in an experiment in which a computerized information board was used to capture subjects' rule-based performance under the manipulation of time pressure and training. The experiment results indicate that people adapt to time pressure by accelerating their processing of rules where the heuristic of cognitive availability was employed. The simplifying strategy was found to be the source of human error that resulted in undesired decision performance. The results also show that the decision behaviour of individuals who undergo the expert system training is directed to a normative and expeditious pattern, which leads to an improved level of decision accuracy. Implications of these findings are examined in the present study.
The impact of expert-system-based training on calibration of decision confidence in emergency management
(1998-01-01)
Su, YL
;
Lin, DYM
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
In many emergency incidents, human operators need to derive countermeasures based an contingency rules under time pressure. Since people tend to be overconfident regarding their performance levels, it ir necessary that the operators be well trained to calibrate proper decision confidence in the safety-related domain. This paper examines the effectiveness of using expert systems to train for the desired calibration. Emergency management of chemical spills was selected to exemplify the rule-based decision task. An expert system in the domain was developed to serve as the training tool. A total of 40 student subjects participated in an experiment in which they were asked to resolve spill scenarios under the manipulation of training and deadline conditions. The experiment results indicate that people tend to overestimate their performance capabilities when reasoning with a rule-based knowledge set, especially with the presence of time constraints. The results also show that the manifestation of overconfidence can be reduced for individuals who undergo the expert-system calibration training. The implications of the findings are examined in this paper. (C) 1997 Elsevier Science Ltd.