The Sleep of Reason Produces Monsters: How and When Biased Input Shapes Mathematics Learning

R. Siegler, Soo-hyun Im, Lauren K. Schiller, Jing Tian, David W. Braithwaite
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引用次数: 8

Abstract

Children's failure to reason often leads to their mathematical performance being shaped by spurious associations from problem input and overgeneralization of inapplicable procedures rather than by whether answers and procedures make sense. In particular, imbalanced distributions of problems, particularly in textbooks, lead children to create spurious associations between arithmetic operations and the numbers they combine; when conceptual knowledge is absent, these spurious associations contribute to the implausible answers, flawed strategies, and violations of principles characteristic of children's mathematics in many areas. To illustrate mechanisms that create flawed strategies in some areas but not others, we contrast computer simulations of fraction and whole number arithmetic. Most of their mechanisms are similar, but the model of fraction arithmetic lacks conceptual knowledge that precludes strategies that violate basic mathematical principles. Presentingbalanced problem distributions and inculcating conceptual knowledge for distinguishing flawed from legitimate strategies are promising means for improving children's learning.
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理性的睡眠产生怪物:有偏见的输入如何以及何时影响数学学习
孩子们的推理能力不足往往导致他们的数学成绩受到问题输入和对不适用程序的过度概括的虚假联想的影响,而不是答案和程序是否有意义。特别是,问题的不平衡分布,特别是在教科书中,导致孩子们在算术运算和它们组合的数字之间建立虚假的联系;当概念性知识缺失时,这些虚假的关联会导致难以置信的答案,有缺陷的策略,以及在许多领域违反儿童数学特征的原则。为了说明在某些领域而不是其他领域产生有缺陷策略的机制,我们对比了分数和整数算法的计算机模拟。它们的大多数机制是相似的,但分数算术模型缺乏概念性知识,无法排除违反基本数学原理的策略。提出平衡的问题分布和灌输区分错误和合法策略的概念知识是提高儿童学习的有希望的手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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