成年人可以自动处理和翻译数字表示吗?
Iro Xenidou-Dervou1, Caroline Appleton1, Serena Rossi1
1Centre for Mathematical Cognition, Department of Mathematics Education, Loughborough University, Loughborough, UK.
Royal Society open science
|July 29, 2025
概括
处理数字,无论是象征性的还是非象征性的,都需要工作内存 (WM). 视觉空间WM对于象征性和跨模式任务至关重要,令人惊的是,执行挑战在象征性比较中提高了性能.
科学领域:
- 认知心理学 认知心理学
- 神经科学是一个神经科学.
- 数学教育教育 数学教育
背景情况:
- 数字认知包括理解和操纵数字.
- 数字可以象征性地表示 (例如数字),也可以非象征性地表示 (例如点).
- 工作记忆 (WM) 在数值处理和相互表示协会中的作用得到了讨论.
研究的目的:
- 调查是否需要自动流程或工作内存 (WM) 资源来进行不同数值表示的大小比较.
- 确定涉及象征性,非象征性和跨模态数值任务的特定类型的WM (声学与视觉空间).
主要方法:
- 采用双任务模式,81名成年人执行点,数字和跨模态大小比较任务.
- 介绍了声学 (PL) 和视觉空间 (VSSP) 工作记忆干扰条件.
- 在独立任务和双任务条件下比较性能.
主要成果:
- 所有规模的比较任务 (象征性,非象征性,跨模式) 都需要WM资源.
- 符号比较特别依赖VSSP WM,在WM干扰下准确性得到改善.
- 非象征性比较涉及VSSP和PL WM,而交叉模式比较需要VSSP WM.
结论:
- 工作记忆对于处理数值表示和它们之间的翻译至关重要.
- 视觉空间处理在数值认知中起着至关重要的作用.
- 执行职能挑战可以提高熟悉的数值任务的性能.
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