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Active and Passive Spatial Learning in Human Navigation: Acquisition of Graph Knowledge

机译:人类导航中的主动和被动空间学习:图知识的获得

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摘要

It is known that active exploration of a new environment leads to better spatial learning than does passive visual exposure. We ask whether specific components of active learning differentially contribute to particular forms of spatial knowledge-the exploration-specific learning hypothesis. Previously, we found that idiothetic information during walking is the primary active contributor to metric survey knowledge (Chrastil & Warren, 2013). In this study, we test the contributions of 3 components to topological graph and route knowledge: visual information, idiothetic information, and cognitive decision making. Four groups of participants learned the locations of 8 objects in a virtual hedge maze by (a) walking or (b) watching a video, crossed with (1) either making decisions about their path or (2) being guided through the maze. Route and graph knowledge were assessed by walking in the maze corridors from a starting object to the remembered location of a test object, with frequent detours. Decision making during exploration significantly contributed to subsequent route finding in the walking condition, whereas idiothetic information did not. Participants took novel routes and the metrically shortest routes on the majority of both direct and barrier trials, indicating that labeled graph knowledge-not merely route knowledge-was acquired. We conclude that, consistent with the exploration-specific learning hypothesis, decision making is the primary component of active learning for the acquisition of topological graph knowledge, whereas idiothetic information is the primary component for metric survey knowledge.
机译:众所周知,与被动视觉曝光相比,主动探索新环境可以带来更好的空间学习。我们询问主动学习的特定组成部分是否对空间知识的特定形式(探索特定的学习假设)有不同的贡献。以前,我们发现步行过程中的惯常信息是度量调查知识的主要积极贡献者(Chrastil&Warren,2013)。在这项研究中,我们测试了三个组成部分对拓扑图和路线知识的贡献:视觉信息,惯常信息和认知决策。四组参与者通过(a)步行或(b)观看视频来了解虚拟树篱迷宫中8个对象的位置,并与(1)做出关于其路径的决策或(2)通过迷宫进行引导。通过在迷宫走廊中从起始对象走到被记住的测试对象位置(经常走弯路)来评估路线和图形知识。勘探过程中的决策显着有助于步行条件下的后续路线寻找,而惯性信息则没有。在大多数直接试验和障碍试验中,参与者都采用了新颖的路线和距离最短的路线,这表明获得了带标签的图知识,而不仅仅是路线知识。我们得出的结论是,与探索特定的学习假设一致,决策是获取拓扑图知识的主动学习的主要组成部分,而惯常信息是度量调查知识的主要组成部分。

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