Visualizing spatial material is a cornerstone of human problem solving, but human visualization capacity is sharply limited. To investigate the sources of this limit, we developed a new task to measure visualization accuracy for verbally-described spatial paths (similar to street directions), and implemented a computational process model to perform it. In this model, developed within the Adaptive Control of Thought-Rational (ACT-R) architecture, visualization capacity is limited by three mechanisms. Two of these (associative interference and decay) are longstanding characteristics of ACT-R's declarative memory. A third (spatial interference) is a new mechanism motivated by spatial proximity effects in our data. We tested the model in two experiments, one with parameter-value fitting, and a replication without further fitting. Correspondence between model and data was close in both experiments, suggesting that the model may be useful for understanding why visualizing new, complex spatial material is so difficult.

中文翻译：

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空间可视化能力的计算模型

将空间材料可视化是人类解决问题的基石，但人类的可视化能力却非常有限。为了调查此限制的来源，我们开发了一项新任务来测量口头描述的空间路径（类似于街道方向）的可视化准确性，并实施了一个计算过程模型来执行它。在这个模型中，在思想理性的自适应控制 (ACT-R) 架构内开发，可视化能力受到三个机制的限制。其中两个（联想干扰和衰减）是 ACT-R 陈述性记忆的长期特征。第三种（空间干扰）是由我们数据中的空间邻近效应激发的一种新机制。我们在两个实验中测试了模型，一个是参数值拟合，另一个是没有进一步拟合的复制。