Data Connections: Developing a Coherent Picture of Mathematics Teaching and Learning

本研究的目的是建立统计模型，以建立一个连贯的数学教师专业发展对学生学习影响的模型。该项目与美国国家科学基金会数学与科学伙伴关系（MSP）计划的两个伙伴关系密切合作，即中学数学研究所伙伴关系和内布拉斯加州数学研究所，以及林肯公立学校。利用通过这些MSP伙伴关系收集的数据，该研究建立了新开发的模型，以帮助这些和其他MSP伙伴关系及其评估人员以统计上富有成效和有意义的方式解释学生和教师的数据。具体而言，该项目侧重于评估教师效果的分层增值模型，以及如何调整这些模型以适用于杂乱的数据，例如，当不同年级在一年中的不同时间进行不同的考试时。该项目正在研究使用z分数、并行处理和分位数分组来解决现有学生成绩数据中出现的问题。项目研究的范围包括：1)评估学生成绩轨迹的方法；2)将这些轨迹与教学质量的衡量标准最佳地联系起来的方法；3)将学生态度和教师态度的测量相互联系起来，并将学生成绩和教学质量的测量联系起来；4)评估MSP干预措施对上述所有方面的影响。MSP项目、学区和各州都在努力解决如何评估教师专业发展项目对学生学习的影响。很少有研究涉及如何使用增值模型来分析不属于单一发展尺度的成就数据，讨论如何在一年内使用不同尺度的多种工具的信息的研究就更少了。除了这项工作之外，研究成果将通过在国家会议上的演讲、在同行评议期刊上发表的文章以及针对MSP项目和评估人员的传播会议进行广泛传播。利用增值模型增加了在高需求学校提供高质量教师影响证据的潜力。通过帮助MSP伙伴使用本研究中开发的方法，该项目正在建立他们的能力，以告知国家他们的MSP如何影响教学和学习。

The purpose of this study is to develop statistical models to create a coherent model of the effects of teacher professional development in mathematics on student learning. The project works closely with two partnerships of the NSF Math and Science Partnership (MSP) program, the Math in the Middle Institute Partnership and NebraskaMATH, and with the Lincoln Public Schools. Utilizing data already collected through these MSP partnerships, the study builds newly developed models to help these and other MSP partnerships and their evaluators interpret student and teacher data in statistically productive and meaningful ways. Specifically, the project focuses on layered value-added models to estimate teacher effects, and how those models can be adapted for use with messy data, for example when different tests are administered in different grade levels at different times of year. The project is investigating the use of Z-scores, parallel processing, and binning by quantile to address issues arising with available student achievement data. The scope of the project research includes: 1) methods to estimate student achievement trajectories over time; 2) methods for best connecting these trajectories to measures of teaching quality; 3) connecting measures of student and teacher attitudes to each other and to measures of student achievement and teaching quality; and 4) estimating the impact of MSP interventions on all of the above.MSP projects, school districts and States are grappling with how to evaluate the effects of their professional development programs for teachers on student learning. Few studies have addressed how to use value-added models to analyze achievement data that are not on a single developmental scale, and even fewer have discussed how to use information from multiple instruments in a single year that are on different scales. In addition to this work, the research findings will be disseminated widely, through presentations at national conferences, articles published in peer-reviewed journals, and a dissemination conference targeting MSP project and evaluation personnel. Utilizing value-added models increases the potential to provide evidence of high quality teacher impact in high-need schools. By helping MSP partnerships use the methods developed in this study, the project is building build their capacity to inform the nation of how their MSPs impact teaching and learning.