12岁儿童的简单加法问题的解决时间模式与检索模型不兼容:对Andras和Macizo (2025) 的反驳 (2025)
Catherine Thevenot1, Jérôme Prado2
1Institut de Psychologie, Université de Lausanne, Switzerland.
Journal of experimental child psychology
|January 17, 2026
概括
对算术学习的认知模型进行了辩论. 新的分析表明,除此之外,与之前的说法相反,问题大小效应支持自动计数理论,而不是检索干扰.
科学领域:
- 认知心理学 认知心理学
- 教育心理学教育心理学
- 神经科学是一个神经科学.
背景情况:
- 讨论了算术学习的认知基础,特别是简单的加法.
- 传统模型表明,从计数策略到直接检索的发展转变.
- 自动计数理论提出了快速,无意识的计数,用于专家在小的加法上的表现.
研究的目的:
- 在简单的加法中重新评估问题大小效应的解释.
- 确定哪种认知模型 (检索与自动计数) 最好解释观察到的模式.
- 批判性地检查挑战现有理论的最新发现.
主要方法:
- 对不同大小的加法问题解决时间的现有数据进行分析.
- 观察到的问题大小效应与检索和自动计数模型的预测进行比较.
- 重新检查Andras和Macizo (2025) 关于六年级学生算术表现的数据.
主要成果:
- 最近的发现表明,问题大小效应在超过7的总和中消失,这挑战了检索干扰模型.
- 安德拉斯和马奇佐 (2025) 报告了解决方案时间的单调增加,支持检索账户.
- 对Andras和Macizo (2025) 数据的重新分析显示了一个非单调的模式,对于总和>7.没有问题大小效应.
结论:
- 观察到的非单调的问题大小效应与基于检索的干扰模型不一致.
- 这些发现与自动化计数理论一致,表明自动化出现了断点.
- 之前支持基于数据重新分析的基于检索的账户的结论没有经验支持.
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