Data‐based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple single‐subject design was used to measure effects of a 2‐year training, in which entire school teams learned how to implement and sustain DBDM, in 39 elementary schools. In a multilevel modeling approach, student achievement in mathematics and spelling was analyzed to broaden our understanding of the effects of DBDM interventions. Student achievement data covering the period from August 2010 to July 2014 were retrieved from schools’ student monitoring systems. Student performance on standardized tests was scored on a vertical ability scale per subject for Grades 1 to 6. To investigate intervention effects, linear mixed effect analysis was conducted. Findings revealed a positive intervention effect for both mathematics and spelling. Furthermore, low‐SES students and low‐SES schools benefitted most from the intervention for mathematics.

中文翻译：

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评估和验证基于数据的决策干预对学生数学和拼写成长的影响

假定基于数据的决策（DBDM）可以提高所有学科的小学学生表现。评估DBDM效果的大多数研究都集中在数学上。分层的多个单主题设计用于衡量为期2年的培训的效果，整个培训团队在39所小学中学习了如何实施和维护DBDM。在多层次建模方法中，对学生在数学和拼写方面的成绩进行了分析，以加深我们对DBDM干预效果的理解。从学校的学生监控系统中检索了2010年8月至2014年7月期间的学生成绩数据。在1至6年级，按照每个科目的垂直能力等级对学生在标准化考试中的表现进行评分。要调查干预效果，进行线性混合效应分析。调查结果显示，数学和拼写均具有积极的干预作用。此外，低SES学生和低SES学校从数学干预中受益最大。