Number line estimation patterns and their relationship with mathematical performance

Q2 Mathematics
Carola Ruiz, Saskia Kohnen, R. Bull
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Abstract

There is ongoing debate regarding what performance on the number line estimation task represents and its role in mathematics learning. The patterns followed by children’s estimates on the number line task could provide insight into this. This study investigates children’s estimation patterns on the number line task and assesses whether mathematics achievement is associated with these estimation patterns. Singaporean children (n = 324, Age M = 6.2 years, Age SD = 0.3 years) in their second year of kindergarten were assessed on the number line task (0-100) and their mathematical performance (Numerical Operations and Mathematical Reasoning subtests from WIAT II). The results show that most children’s number line estimation patterns can be explained by at least one mathematical model (i.e., linear, logarithmic, unbounded power model, one-cycle power model, two-cycle power model). But the findings also highlight the high percentage of participants for which more than one model shows similar support. Children’s mathematical achievement differed based on the models that best explained children’s estimation patterns. Children whose estimation patterns corresponded to a more advanced model tended to show higher mathematical achievement. Limitations of drawing conclusions regarding what performance on the number line task represents based on models that best explain the estimation patterns are discussed.
数线估计模式及其与数学性能的关系
关于数轴估计任务的表现及其在数学学习中的作用,一直存在争论。孩子们在数轴任务中所遵循的估计模式可以对此提供深入的了解。本研究调查了儿童在数轴任务上的估计模式,并评估了数学成绩是否与这些估计模式有关。对324名新加坡幼儿园二年级儿童(n = 324,年龄M = 6.2岁,年龄SD = 0.3岁)的数线任务(0-100)和数学表现(WIAT II的数值运算和数学推理子测试)进行了评估。结果表明,大多数儿童的数线估计模式可以用至少一种数学模型(即线性、对数、无界幂模型、单周期幂模型、双周期幂模型)来解释。但研究结果也强调了一个以上模型显示出类似支持的参与者比例很高。孩子们的数学成绩取决于最能解释孩子们的估计模式的模型。估计模式符合更高级模型的儿童往往表现出更高的数学成就。讨论了基于最能解释估计模式的模型得出关于数轴任务上的性能所代表的结论的局限性。
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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来源期刊
Journal of Numerical Cognition
Journal of Numerical Cognition Mathematics-Numerical Analysis
CiteScore
3.20
自引率
0.00%
发文量
18
审稿时长
40 weeks
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