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Time-based expectancy in multitasking: From cognitive psychology to movement science

Time-based expectancy in multitasking: From cognitive psychology to movement science
多任务处理中基于时间的期望:从认知心理学到运动科学
批准号:
274870665
负责人:
Professor Dr. Roland Thomaschke
金额:
$0.0万
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
2015
资助国家:
德国
项目状态:
已结题
起止时间:
2014-12-31 至 2022-12-31

项目摘要

项目成果

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中文摘要
翻译
该项目调查了时间作为信息源如何支持多任务处理。在第一个资助期,实验集中在任务转换情景中的基于角色时间的可预测性,因为它们在认知心理学关于多任务处理的基础研究中很常见。当在任务转换中,空准备间隔的持续时间预测下一项任务的类型时,参与者在行为上适应了这种规律,而没有意识到这一点。第一个资助期的结果表明,这一适应相对独立于可预测性程度,它涉及时间的相对表示(例如短与长),而不是绝对时间(例如500毫秒与1500毫秒)。此外,对基于时间的可预测性的适应在其他基本认知心理学范式中也可以观察到,例如双重任务或效果监控。然而,在优先项目中,认知心理学和运动科学之间的强烈互动导致了初步的实验证据,即基于时间的可预测性也可能在多任务处理中发挥更基本的作用。除了在任务切换中宣布下一步要做哪项任务外,当可预测性嵌入到两个连续的并发任务之一时,基于时间的可预测性也可能有助于多任务处理。具有连续并发任务的范例在运动学中占主导地位。在优先计划内与运动科学家合作,开发了一个连续的并发多任务范例,其中基于时间的可预测性嵌入到其中一个任务中。一个简单的手动选择任务(按下振动按钮)以不同步的方式与心算任务相结合。两个按钮振动之间的短间隔的持续时间预测下一个按钮将振动。初步研究的结果表明,这种可预测性支持多任务处理。当人工选择任务在时间上是可预测的时,算术任务的表现比在时间上不可预测的时候更好。本文提出的实验将系统地研究基于时间的可预测性对并发任务绩效的影响机制。假设是从优先计划中多个项目关于可预测性的汇聚理论中得出的。第一组实验将调查两个任务中的表现是如何相互关联的,以及哪些间隔时间主要驱动了这种影响。第二组实验致力于研究这些效应的领域特异性。一项任务中基于时间的可预测性是否特别支持与时间相关的第二项任务?最后一组实验将处理在适应效应中加工的时间的认知表征。它是否涉及相对表征,例如对任务预测的适应?或者它采用的是绝对表征,就像一些相关的移动计时任务的典型表现一样?
英文摘要
The project investigates how time as a source of information supports multitasking. During the first funding period, experiments focused on the role time-based predictability in task switching scenarios, as they are common in cognitive psychology basic research on multitasking. When in task switching the duration of an empty preparatory interval predicts the type of the next task, participants behaviorally adapt to such regularity without getting aware of it. Results from the first funding period showed that this adaptation is relatively independent of the degree of predictability, and that it involves relative (e.g. short vs. long) instead of absolute (e.g. 500 ms vs. 1500 ms) representations of time. Further, adaptation to time-based predictability is also observable in other basic cognitive psychology paradigms, such as dual-tasking, or effect monitoring. However, the intense interaction between cognitive psychology and movement science in the priority program lead to preliminary experimental evidence that time-based predictability might also play a more fundamental role in multitasking. In addition to announcing which task to do next in task switching, time-based predictabilities might also assist multitasking when the predictability is embedded in one of two continuous concurrent tasks. Paradigms with continuous concurrent tasks, are predominant in the movement sciences. In collaboration with movement scientists within the priority program, a continuous concurrent multitasking paradigm has been developed, where time-based predictability is embedded in one of the tasks. A simple manual choice task (pressing on vibrating buttons) is combined, in an unsynchronized manner, with a mental arithmetic task. The duration of the short interval between two button vibrations predicts which button will vibrate next. Results from a preliminary study show that this predictability supports multitasking. Performance on the arithmetic task is better when the manual choice task is temporally predictable, relative to when it is not. The experiments proposed here will systematically investigate the mechanism underlying the effect from time-based predictability in one task on performance in a concurrent task. Hypotheses are derived from converging theorizing about predictability by multiple projects in the priority program. A first set of experiments will investigate how performance in both tasks is related to each other, and which interval durations primarily drive the effect. A second set of experiments is devoted to the domain specificity of the effects. Does time-based predictability in one task support timing related second tasks in particular? A last set of experiments will be deal with the cognitive representations of time processed in the adaptation effect. Does it involve relative representations, such as adaptation to task prediction? Or does it employ absolute representation, as typical for some related movement timing tasks?
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