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Informing Estimates of Program Effects for Studies of Mathematics Professional Development Using Teacher Content Knowledge Outcomes

机译:利用教师内容知识成果告知数学专业发展研究计划效果估计

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Mathematics professional development is widely offered, typically with the goal of improving teachers' content knowledge, the quality of teaching, and ultimately students' achievement. Recently, new assessments focused on mathematical knowledge for teaching (MKT) have been developed to assist in the evaluation and improvement of mathematics professional development. This study presents empirical estimates of average program change in MKT and its variation with the goal of supporting the design of experimental trials that are adequately powered to detect a specified program effect. The study drew on a large database representing five different assessments of MKT and collectively 326 professional development programs and 9,365 teachers. Results from cross-classified hierarchical growth models found that standardized average change estimates across the five assessments ranged from a low of 0.16 standard deviations (SDs) to a high of 0.26 SDs. Power analyses using the estimated pre- and posttest change estimates indicated that hundreds of teachers are needed to detect changes in knowledge at the lower end of the distribution. Even studies powered to detect effects at the higher end of the distribution will require substantial resources to conduct rigorous experimental trials. Empirical benchmarks that describe average program change and its variation provide a useful preliminary resource for interpreting the relative magnitude of effect sizes associated with professional development programs and for designing adequately powered trials.
机译:广泛提供数学专业发展,通常目的是提高教师的内容知识,教学质量以及最终学生的成就。最近,针对数学教学知识(MKT)的新评估方法已经开发出来,以帮助评估和改善数学专业发展。这项研究提出了MKT中平均程序更改及其变化的经验估计,其目的是支持设计有足够能力检测指定程序效果的实验试验的设计。这项研究利用了一个大型数据库,该数据库代表了五种不同的MKT评估,总共326个专业发展计划和9,365名教师。交叉分类的层次增长模型的结果发现,五项评估的标准化平均变化估计值范围从0.16标准差(SD)的低到0.26 SD标准的高。使用估计的测试前和测试后变化估计进行的能力分析表明,需要数百名教师来检测分布较低端的知识变化。即使是旨在检测分布较高端影响的研究,也将需要大量资源来进行严格的试验。描述平均程序变更及其变化的经验基准为解释与专业发展计划相关的效应量的相对大小以及设计足够有力的试验提供了有用的初步资源。

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