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How spatial information structuring in an interactive technological environment affects decision performance under working memory load

机译:在交互式技术环境中的空间信息如何影响工作内存负荷下的决策性能

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摘要

In situations (over-)taxing working memory (WM), offloading cognitive burdens and operations onto an interactive technological device could be key to success. Technological support allowing external storage and manipulation of information like in WM could offer even greater benefits in these demanding situations, where reducing WM burdens is essential for task performance, than in less demanding situations. However, the relationship between technological offloading support and WM load has not been systematically examined. This study (N = 138) therefore investigated the effectiveness of self-directed structuring functions allowing the manipulation of information on a multi-touch table to support complex decision-making under induced low and high WM load (contrasted with no self-structuring support). Individuals equipped with self-structuring demonstrated deeper information processing irrespective of load. Measures for updating of mental representations showed partially higher effectiveness of self-structuring support under high load. Descriptive statistics for correct decisions could show self-structuring helping to maintain or even improve performance especially under high WM load, while corresponding inference statistics could not. Thus, results for correct decisions were inconclusive. Detailed process analyses showed that specific structuring strategies rather than overall structuring amount were related to better decisions and point out possibilities to increase self-structuring effectiveness.
机译:在举行的情况(过度)征税工作记忆(WM)中,将认知负担和操作卸载到交互式技术设备上可能是成功的关键。技术支持允许外部存储和操纵WM中的信息可以在这些苛刻的情况下提供更大的好处,其中减少WM负担对于任务性能至关重要,而不是在较小的苛刻情况下。然而,技术卸载支持与WM负载之间的关系尚未得到系统检查。因此,本研究(n = 138)研究了自定导结构功能的有效性,允许在多点触摸表上操纵信息以支持诱导低和高WM负载下的复杂决策(与无自动构造支持对比) 。具有自我结构的个体,无论负载如何都证明了更深的信息处理。更新心理表现的措施表明,在高负荷下自我结构性支持的效力部分更高。正确决策的描述性统计数据可以显示自身结构,帮助维护甚至改善性能,尤其是在高WM负载下,而相应的推断统计可能不会。因此,正确决策的结果不确定。详细的过程分析表明,具体的结构性策略而不是整体结构化量与更好的决策有关,并指出增加自我结构性效果的可能性。

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