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Monica C. Zubritzky

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Publications by Monica C. Zubritzky (bibliography)

1989

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Zubritzky, Monica C., Zachary, Wayne and Ryder, Joan M. (1989): Constructing and Applying Cognitive Models to Mission Management Problems in Air Anti-Submarine Warfare. In: Proceedings of the Human Factors Society 33rd Annual Meeting 1989. pp. 129-133.

“The ever-increasing capabilities of computers have resulted in a new generation of man-machine systems in which the machine acts in an intelligent manner to enhance the operator's decision-making capabilities in real-time multi-tasking (RTMT) situations. In such situations, the operator's information needs constantly change as he/she must attend to several events simultaneously and often switch from one decision-making task to another. The ability of the intelligent systems to aid humans in a flexible interactive fashion depends on the capability of the machine to predict these switches and the resulting changes in the human's information needs at a given time. These systems must therefore incorporate a model of the human operator's tasks based on information about the individual tasks and the dynamic relationships between the tasks and the occurrence of outside events. This paper focuses on the construction of such a model in the context of mission management problems of airborne Tactical Coordinators (TACCOs) in anti-submarine warfare (ASW). The model is built as a Cognitive Network of Tasks (COGNET) and is based on the integration of GOMS notation and the Blackboard architecture and is now being used to develop an adaptive intelligent interface for TACCOs.”

1988

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Zachary, Wayne, Zubritzky, Monica C. and Glenn, Floyd A. (1988): The Development of the Air Anti-Submarine Warfare Mission Testbed as a Tool for the Development of Operator Models. In: Proceedings of the Human Factors Society 32nd Annual Meeting 1988. pp. 1073-1077.

“The central concern of human factors engineering (HFE) is facilitating a productive relationship between man and machine. A new generation of man-machine systems has arisen in which the machine acts in a relatively intelligent manner to enhance the operator's decision-making capabilities in real-time multi-tasking situations. These systems have been termed "distributed intelligence systems" (DIS) because intelligence is distributed among all system entities, whether they are human or computer. The ability of these systems to aid humans in a flexible, interactive fashion depends on the capability of the machine to predict the human's information needs in a given decision-making situation. Thus, the DIS must incorporate a model that reflects the operator's information processing requirements for the tasks necessary to operate the system. Of construct this model, it is necessary to develop a DIS testbed where experimental investigations can occur. The mission environment chosen for simulation is the Naval Air Anti-Submarine Warfare (ASW) mission, whose objectives to search for, find, and attack the enemy submarine involve complex tactical decisions in a real-time multi-tasking environment. In the Air ASW mission, most significant tactical decisions are made by the Tactical Coordinator (TACCO), the main operator of the system. The aspects of the testbed discussed in this paper include those elements of the simulation and responsibilities of the TACCO needed to illustrate the types of information processing tasks involved in the ASW mission. Also, the data collection capabilities of the testbed and how this data will be applied to operator model development will be discussed.”

1987

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Zubritzky, Monica C. and Coury, Bruce G. (1987): Multidimensional Scaling as a Method for Probing the Conceptual Structure of State Categories: An Individual Differences Analysis. In: Proceedings of the Human Factors Society 31st Annual Meeting 1987. pp. 107-111.

“Identifying the underlying decision criteria used by operators to classify system state, and revealing the way in which that information is internally represented in one of the challenges facing designers of control systems. This paper describes the use of multidimensional scaling (MDS) to probe the structure and composition of the internal conceptual models used by operators to identify system state. Specifically, the issue of individual differences in mental model is addressed, as well as the impact of these differences on individual performance in a classification task. Twenty subjects were trained as operators to classify instances of system data into one of four system state categories. After training, subjects were asked to rate the similarity between instances of system state. Results showed that the dominant dimensions used by an individual are related to his/her performance on the classification task.”

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