Empirical Benchmarks of Design Parameters for Group Randomized Trials in Teacher Professional Development Intervention Studies

教师专业发展干预研究中分组随机试验设计参数的实证基准

• 批准号: 1228490
• 负责人: Benjamin Kelcey
• 金额: $ 53.86万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2014-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1228490&HistoricalAwards=false
• 关键词: Empirical; Benchmarks; Design; Parameters; Group

Professional development of teachers is a strong component in the theory of action of improving student outcomes, yet such efforts are rarely rigorously evaluated. One of the problems of robust evaluation of professional development is that these programs are largely conducted with teachers in their school or district settings rather than being randomly assigned individually to different activities. This requires that the evaluation design be developed around group randomized trials, and the field of educational evaluation lacks important knowledge of how to structure such evaluations. This project is developing estimates of the empirical benchmarks of design parameters to be used to structure evaluations of whole school professional development efforts in mathematics. The project uses the large data sets that have been accumulated using the Mathematical Knowledge of Teaching (MKT) measures to develop estimates of the variation in teacher pedagogical content knowledge in mathematics to provide values that can be used to estimate sample size and other design parameters in evaluation design. Researchers from the College of Education at Wayne State University, the Educational Testing Service and Michigan State University are conducting this research.This project leverages the data collected from multiple professional development projects for mathematics teachers that have used the MKT under the auspices of the researchers that have been collected in an online Teacher Knowledge Assessment System from over 10,000 teachers in over 1150 schools. The data from the MKT is combined with data that is available publically in the Common Core of Data about the schools and districts within which the professional development was conducted and additional data that have been collected by the MKT researchers. The researchers use random intercept hierarchical linear models to estimate the design parameters for four different group random trial designs. They examine the impact of several covariate sets of parameters on the variance components and the corresponding estimates of intraclass correlation. The resulting parameters are reported in association with the conditions of the schools and districts in which the data were generated.The findings from this study are reported in the professional literature on research and evaluation design. In addition, professional development workshops disseminate the findings and the processes used to develop them at national educational research and evaluation meetings. In addition, the researchers include their findings in updates of the Optimal Design software that is used by multiple researchers and evaluators to structure the design of their own studies. Too frequently, researchers do not have sufficient knowledge of the potential contextual issues surrounding the schools and districts in which they work to make accurate estimates of the parameters that they should use to determine important characteristics of their research such as sample size. The findings of this study provide more realistic estimates of the design parameters that researchers and evaluators need to conduct their own studies.

教师的专业发展是提高学生成绩的行动理论的重要组成部分，但此类努力很少受到严格评估。对专业发展进行稳健评估的问题之一是，这些计划主要是由教师在学校或学区环境中进行的，而不是随机分配到不同的活动中。这要求评估设计围绕分组随机试验进行，而教育评估领域缺乏如何构建此类评估的重要知识。该项目正在开发设计参数的经验基准的估计，以用于对整个学校数学专业发展工作进行评估。该项目利用通过数学教学知识（MKT）测量积累的大数据集来估计教师数学教学内容知识的变化，以提供可用于估计样本量和其他设计参数的值。评价设计。 来自韦恩州立大学教育学院、教育考试服务中心和密歇根州立大学的研究人员正在进行这项研究。该项目利用了从多个数学教师专业发展项目中收集的数据，这些教师在研究人员的支持下使用了 MKT。在线教师知识评估系统收集了 1150 多所学校的 10,000 多名教师的信息。来自 MKT 的数据与公共核心数据中公开提供的有关进行专业发展的学校和学区的数据以及 MKT 研究人员收集的其他数据相结合。研究人员使用随机截距分层线性模型来估计四个不同组随机试验设计的设计参数。他们检查了几个协变量参数集对方差分量的影响以及相应的类内相关性估计。报告的结果参数与生成数据的学校和学区的条件相关。这项研究的结果报告在有关研究和评估设计的专业文献中。此外，专业发展研讨会在国家教育研究和评估会议上传播研究结果和开发过程。此外，研究人员还将他们的发现纳入了优化设计软件的更新中，多个研究人员和评估人员使用该软件来构建他们自己的研究设计。很多时候，研究人员对他们工作的学校和学区周围的潜在背景问题缺乏足够的了解，无法准确估计他们应该用来确定研究的重要特征（例如样本量）的参数。这项研究的结果为研究人员和评估人员进行自己的研究所需的设计参数提供了更现实的估计。