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The role of working memory capacity in analytic and multiply-constrained problem-solving in demanding situations

机译:在苛刻的情况下,工作记忆能力在分析和乘以受限的问题解决中的作用

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摘要

Working memory processes are important for analytic problem-solving; however, their role in multiply-constrained problem-solving is currently debated. This study explored individual differences in working memory and successful completion of analytic and multiply-constrained problem-solving by having participants solve algebra and compound remote associate (CRAT) problems of varying difficulty under low and high memory demand conditions. Working memory was predictive of both algebra and multiply-constrained problem-solving. Specifically, participants with high working memory solved more problems than those with low working. Memory load did not differentially affect performance for low and high working memory participants. However, for multiply-constrained problem-solving the effect of item difficulty was more detrimental for high-span participants than low-span participants. Together, these findings suggest that working memory processes are important for both types of problem-solving and that participants with low working memory capacity may need to offload internal memory demands onto the environment to efficiently solve problems.
机译:工作内存过程对于解析解决问题是重要的;但是,目前争论了它们在乘法限制问题解决方面的作用。本研究通过让参与者在低和高记忆需求条件下,通过将参与者求解代数和复合远程助理(CRAT)问题探讨了工作记忆的个人差异和分析和乘以受限制的解决问题。工作存储器预测代数和乘法限制的解决问题。具体而言,具有高工作记忆的参与者可以解决比具有低工作的人的问题。内存负载没有差异地影响低工作内存参与者的性能。然而,对于乘法限制问题解决项目难度对高跨度参与者的效果比低跨度参与者更有害。这些发现表明,工作存储器过程对于两种类型的问题解决是重要的,并且工作存储器容量低的参与者可能需要卸载内部存储器所需的内容,以有效地解决问题。

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