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Set size influences the relationship between ANS acuity and math performance: a result of different strategies?

机译:设定大小会影响敏锐度和数学绩效之间的关系:不同策略的结果?

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Previous research has proposed that the approximate number system (ANS) constitutes a building block for later mathematical abilities. Therefore, numerous studies investigated the relationship between ANS acuity and mathematical performance, but results are inconsistent. Properties of the experimental design have been discussed as a potential explanation of these inconsistencies. In the present study, we investigated the influence of set size and presentation duration on the association between non-symbolic magnitude comparison and math performance. Moreover, we focused on strategies reported as an explanation for these inconsistencies. In particular, we employed a non-symbolic magnitude comparison task and asked participants how they solved the task. We observed that set size was a significant moderator of the relationship between non-symbolic magnitude comparison and math performance, whereas presentation duration of the stimuli did not moderate this relationship. This supports the notion that specific design characteristics contribute to the inconsistent results. Moreover, participants reported different strategies including numerosity-based, visual, counting, calculation-based, and subitizing strategies. Frequencies of these strategies differed between different set sizes and presentation durations. However, we found no specific strategy, which alone predicted arithmetic performance, but when considering the frequency of all reported strategies, arithmetic performance could be predicted. Visual strategies made the largest contribution to this prediction. To conclude, the present findings suggest that different design characteristics contribute to the inconsistent findings regarding the relationship between non-symbolic magnitude comparison and mathematical performance by inducing different strategies and additional processes.
机译:以前的研究提出,近似数字系统(ANS)构成了稍后数学能力的构建块。因此,众多研究调查了敏锐度和数学性能之间的关系,但结果不一致。已经讨论了实验设计的性质作为这些不一致的潜在解释。在本研究中,我们调查了集大小和呈现持续时间对非符号幅度比较和数学性能之间的关联的影响。此外,我们专注于报告的策略作为对这些不一致的解释。特别是,我们雇用了非符号幅度比较任务,并要求参与者如何解决任务。我们观察到,设定的大小是非符号幅度比较和数学性能之间的关系的重要主持人,而刺激的呈现持续时间没有适度的这种关系。这支持特定设计特征有助于不一致结果的概念。此外,参与者报告了不同的策略,包括基于数值,视觉,计数,基于计算的和副化策略。这些策略的频率不同于不同的设定尺寸和呈现持续时间。但是,我们发现没有特定的策略,单独预测的算术性能,但是在考虑所有报告的策略的频率时,可以预测算术性能。视觉策略对这一预测的贡献提供了最大的贡献。为了得出结论,目前的研究结果表明,通过诱导不同的策略和附加过程,不同的设计特征有助于非符号幅度比较和数学绩效之间的关系的不一致结果。

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