Stability of early number sense competencies for predicting mathematics difficulties

IF 9 1区 心理学 Q1 PSYCHOLOGY, EDUCATIONAL Learning and Individual Differences Pub Date : 2025-02-01 DOI:10.1016/j.lindif.2025.102633
Amber Beliakoff , Nancy Jordan , Alice Klein , Brianna Devlin , Chun-Wei Huang
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Abstract

Significant individual differences in children's number competencies exist in early childhood, and these competencies can have long-term implications for academic and economic success (National Research Council, 2009). The present study assessed the classification accuracy of the Screener for Early Number Sense (SENS), a screening tool grounded in an evidence-informed conceptual model of number sense that is designed for children in pre-kindergarten (pre-K), kindergarten, and first grade. A cohort of 450 children was assessed on the SENS, followed by a standardized mathematics achievement measure one year later. Receiver operating characteristic (ROC) curve analyses indicated that the SENS effectively differentiated children who went on to show math difficulties (MD) from those without MD. Accuracy rate was acceptable for pre-K, kindergarten, and first grade. An analysis of SENS performance over time categorized by MD risk status revealed differing patterns of growth across the pre-K vs. kindergarten year. These collective findings underscore the importance of math screening as early as pre-K.

Educational relevance

Educators need reliable and valid tools to identify young children who may be at risk for mathematics learning difficulties. The present study presents a number sense screener that accurately predicts pre-kindergarten, kindergarten, and first grade students' later mathematical difficulties. The study demonstrates how screener results and prevalence rates can be used to identify individual-level student risk and to make subsequent instructional decisions across varying schools or districts.
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预测数学困难的早期数感能力的稳定性
儿童早期的数字能力存在显著的个体差异,这些能力可能对学术和经济成功产生长期影响(国家研究委员会,2009年)。本研究评估了早期数字感觉筛选器(SENS)的分类准确性,SENS是一种基于证据知情的数字感觉概念模型的筛选工具,专为学前班(pre-K),幼儿园和一年级的儿童设计。研究人员对450名儿童进行了SENS测试,一年后对他们进行了标准化的数学成绩测试。受试者工作特征(ROC)曲线分析表明,SENS可以有效地区分出出现数学困难(MD)的儿童和没有数学困难(MD)的儿童。正确率在学前班、幼儿园和一年级都是可以接受的。根据MD风险状态分类的SENS表现随时间的分析揭示了学前班与幼儿园的不同增长模式。这些集体发现强调了早在学前班就进行数学筛选的重要性。教育相关性教育工作者需要可靠和有效的工具来识别可能有数学学习困难风险的幼儿。本研究提出一种数字感觉筛选器,可准确预测学前班、幼稚园及一年级学生日后的数学困难。该研究展示了如何使用筛查结果和患病率来识别个人层面的学生风险,并在不同的学校或地区做出后续的教学决策。
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来源期刊
Learning and Individual Differences
Learning and Individual Differences PSYCHOLOGY, EDUCATIONAL-
CiteScore
6.60
自引率
2.80%
发文量
86
期刊介绍: Learning and Individual Differences is a research journal devoted to publishing articles of individual differences as they relate to learning within an educational context. The Journal focuses on original empirical studies of high theoretical and methodological rigor that that make a substantial scientific contribution. Learning and Individual Differences publishes original research. Manuscripts should be no longer than 7500 words of primary text (not including tables, figures, references).
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