Abstract

Experimental research in education and training programs typically involves administering treatment to whole groups of individuals. As such, researchers rely on the estimation of design parameter values to conduct power analyses to efficiently plan their studies to detect desired effects. In this study, we present design parameter estimates from a compilation of 11 studies involving teacher-level outcomes. These results expand upon what little is known about the clustering of variance among teacher-level outcomes. The findings inform the design of intervention studies which nest teachers within schools and aim to improve teacher mathematics and science content knowledge or instructional practices. The results show large differences in unconditional intraclass correlation coefficients across studies as well as within outcomes. They also quantify the relative importance of having a pretest measure to promote efficiency. This study highlights a need for improved reporting of this information in the literature to facilitate better experimental designs of interventions involving teacher-level outcomes.

摘要

教育和培训计划中的实验研究通常涉及对整个个体群体进行治疗。因此，研究人员依靠设计参数值的估计来进行功率分析，以有效地计划他们的研究以检测所需的效果。在这项研究中，我们从11项涉及教师水平结果的研究的汇编中给出了设计参数估计。这些结果扩展了关于教师水平结果之间方差聚类的鲜为人知的知识。这些发现为干预研究的设计提供了参考，这些研究使教师在学校中排位，并旨在改善教师的数学和科学知识或教学实践。结果表明，跨研究以及结果中无条件的类内相关系数存在很大差异。他们还量化了采取预测试措施来提高效率的相对重要性。这项研究强调需要改进文献中有关此信息的报告，以促进对涉及教师水平结果的干预措施进行更好的实验设计。