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The relational integration task explains fluid reasoning above and beyond other working memory tasks

机译:关系集成任务比其他工作记忆任务更能说明流体推理

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摘要

This study aimed to evaluate how well fluid reasoning can be predicted by a task that involves the monitoring of patterns of stimuli. This task is believed to measure the effectiveness of relational integration-the process that binds mental representations into more complex relational structures. In Experiments 1 and 2, the task was indeed validated as a proper measure of relational integration, since participants' performance depended on the number of bindings that had to be constructed in the diverse conditions of the task, whereas neither the number of objects to be bound nor the amount of elicited interference could affect this performance. In Experiment 3, by means of structural equation modeling and variance partitioning, the relation integration task was found to be the strongest predictor of fluid reasoning, explaining variance above and beyond the amounts accounted for by four other kinds of well-established working memory tasks.
机译:这项研究旨在评估通过涉及刺激模式监测的任务可以预测流体推理的水平。人们认为,这项任务可以衡量关系整合的有效性,这一过程将精神表征绑定到更复杂的关系结构中。在实验1和2中,由于参与者的表现取决于在任务的不同条件下必须构造的绑定数,而没有将对象数作为对象,因此确实将任务验证为关系整合的适当方法。限制也不会引起干扰的数量会影响此性能。在实验3中,通过结构方程建模和方差划分,发现关系积分任务是流体推理的最强预测因子,解释了超出其他四种公认的工作记忆任务的数量的方差。

著录项

  • 作者

    Chuderski Adam;

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  • 年度 2014
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  • 原文格式 PDF
  • 正文语种 eng
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