二维图形的人工处理:图形任务匹配锚定框架中的信息量概念和效果

Joseph K. Tan
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引用次数: 9

摘要

本报告讨论了三个相关实验的结果,这些实验是关于文献中报道的图任务拟合锚定框架中信息量的影响。信息量在操作上被定义为数据矩阵(SDM)的大小,即图形显示中的点总数。锚定框架指定一个提取任务具有高或低的x值锚定,这取决于该x组件是否在问题中表示(作为给定值或未知值)。采用全受试者重复测量实验设计来检验SDM对数据提取速度和准确性的影响。这些实验还整合了不同的框架来关联信息量效应。结果表明,SDM的增加只会对数据提取时间产生不利影响,而不会影响准确性。通过信息量交互作用观察到显著的图形格式;训练确实降低了感知信息的复杂性,特别是对于高数据量的显示。此外,……
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Human processing of two-dimensional graphics: Information-volume concepts and effects in graph-task fit anchoring frameworks
This report discusses the findings from three related experiments on the effects of information volume in graph‐task fit anchoring frameworks reported in the literature. Information volume is operationally defined as the size of a data matrix (SDM), that is, the total number of points in a graphical display. The anchoring frameworks specify that an extraction task has high or low x‐value anchoring depending on whether or not the x‐component is represented in the question (as a given or unknown value). A total within‐subject repeated measure experimental design was used to test the effects of SDM on speed and accuracy of data extraction. These experiments also integrated different frameworks to relate the information‐volume effects. Results indicated that increased SDM adversely affected only data extraction time, not accuracy. A significant graph format by information volume interaction was observed; and training did reduce perceived information complexity, especially for high data volume displays. Also, ...
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