Human cognition and the expert system interface: mental models and inference explanations
Human cognition and the expert system interface: mental models and inference explanations
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人类认知与专家系统接口：心智模型与推理解释
DOI：
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发表时间：
1993
期刊：
影响因子：
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通讯作者：
M. Donnell
中科院分区：
文献类型：
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作者：
F. Rook;M. Donnell
对影响用户/专家系统交互的变量进行了经验评估，并讨论了人类认知和智能机器使用之间的关系的理论发展。假设一个好的心理模型将导致用户/计算机交互和性能的提高，图形推理解释将导致比文本解释更高的性能。对这些假设的检验，以及它们背后的认知过程，直接有助于专家系统界面设计原则，以及心理模型在理解和使用动态复杂系统中的作用的理论发展。基于Newell和Simon(1972)的问题解决理论和发生在问题空间中的概念，量化了人与专家系统的交互，确定了相关的搜索策略和方向，并发展了复杂动态系统的心理模型理论。基本结论是，用户必须对专家系统的推理过程有很好的理解(即良好的心理模型)，并且用户必须有效地理解专家系统的推理解释中存在的信息。>；
Variables affecting user/expert system interaction are evaluated empirically, and theoretical development of the relationship between human cognition and the use of intelligent machines is addressed. The hypotheses are that a good mental model will lead to increased user/computer interaction and performance and that graphic inference explanations will lead to higher performance than textual explanation. The examination of these hypotheses, as well as the cognitive processing underlying them, contributes directly to expert system interface design principles, as well as to theoretical development of the role of mental models in the understanding and use of dynamic, complex systems. Based on Newell and Simon's (1972) theory of problem solving and the concept occurring in a problem space, human interaction with expert systems is quantified, relevant search strategies and directions are identified, and a theory of mental models of complex, dynamic systems is developed. The basic findings are that the user must have a good understanding (i.e., good mental model) of the expert system's reasoning process, and that the user must effectively understand the information present in the expert system's inference explanations. >