课题基金 / 基金详情

Building Community and Capacity for Data-Intensive Evidence-Based Decision Making in Schools and Districts

Building Community and Capacity for Data-Intensive Evidence-Based Decision Making in Schools and Districts
在学校和学区建设数据密集型循证决策的社区和能力
批准号:
1560720
负责人:
Alex Bowers
金额:
$49.96万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-05-15 至 2021-04-30

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中文摘要
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英文摘要
Evidence-based decision making in schools and districts is a growing area of research and practice, in which teachers and administrators come together around their students' data to build capacity and inform instructional decision making. The goal of this project is to build a researcher-practitioner community around data-intensive evidence-based decision making through bringing together large and diverse school district datasets and then applying recent innovations from the data sciences to pilot and test data analytics with teachers and administrators. This will provide a test-bed and exemplars which will be used to spur capacity building between and among researchers and current school leaders around the data currently in use in their schools.This study will inform current research and practice around data analytics and evidence-based practice in schools using the data that districts already collect. Research from this project will extend beyond a single discipline, helping to inform a diverse set of research domains, including data science, statistics, education data mining, improvement science, design-based research, education research and social services. Furthermore, this project will bring together researchers and school leaders to build community and capacity around intensive data analytics for educational decision making. The project will publish and release the open source R code. Publishing the code as open access will provide a means to help structure school district education data cycles, as the R code will provide an incentive for districts to store and structure their data in such a way so that they can implement the analytics and visualizations immediately from the code that will be generated in this project.
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BIGDATA: EAGER: Using Big Data to Investigate Longitudinal Education Outcomes through Visual Analytics
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