Designing Large-Scale Multisite and Cluster-Randomized Studies of Professional Development
Designing Large-Scale Multisite and Cluster-Randomized Studies of Professional Development
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设计专业发展的大规模多地点和集群随机研究
DOI：
10.1080/00220973.2016.1220911
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Jiaqi Zhang
中科院分区：
文献类型：
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作者：
Ben Kelcey;Jessaca K. Spybrook;Geoffrey Phelps;Nathan D. Jones;Jiaqi Zhang
摘要本研究为教师专业发展研究的设计提供了理论和实证基础。我们建立在以前的工作，（a）开发估计的组内相关系数的教师成果，使用两个和三个层次的数据结构，（B）开发估计的方差解释协变量，和（c）修改传统的最优设计框架，包括差分协变量成本，以捕捉点收集协变量的成本超过它提供的方差减少。我们说明了使用这些估计，以探讨教师专业发展研究中的多水平设计的绝对和相对灵敏度。这些分析的结果旨在指导研究人员在选择研究设计评估专业发展计划的影响时，对所涉及的权衡和考虑因素做出更明智的决定。
ABSTRACT We develop a theoretical and empirical basis for the design of teacher professional development studies. We build on previous work by (a) developing estimates of intraclass correlation coefficients for teacher outcomes using two- and three-level data structures, (b) developing estimates of the variance explained by covariates, and (c) modifying the conventional optimal design framework to include differential covariate costs so as to capture the point at which the cost of collecting a covariate overtakes the reduction in variance it supplies. We illustrate the use of these estimates to explore the absolute and relative sensitivity of multilevel designs in teacher professional development studies. The results from these analyses are intended to guide researchers in making more-informed decisions about the tradeoffs and considerations involved in selecting study designs for assessing the impacts of professional development programs.