BCC: Developing a comprehensive regional approach to data set integration to support data-intensive research in education in Silicon Valley

BCC：制定全面的区域数据集集成方法，以支持硅谷教育领域的数据密集型研究

• 批准号: 1338411
• 负责人: Rodney Ogawa
• 金额: $ 35.65万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1338411&HistoricalAwards=false
• 关键词: BCC; Developing; comprehensive; regional; approach

The PIs of this proposal are developing a collaborative community to support data-intensive research in education regionally in the Silicon Valley, California. A team of researchers in education, the social sciences and engineering from the University of California, Santa Cruz have engaged in a partnership with researchers from the National Laboratory for Educational Transformation, a private non-profit organization. The collaborative team is structuring a network of other regional agencies to expand capacity around four challenges: cultural, legal and regulatory issues that prevent sharing data across institutions, analytical approaches, technical infrastructure issues to integrate and manage the data set, and ethical issues including data security and privacy. Regional stakeholders from public agencies and the private sector are coming together with the researchers in five meetings over the course of the year to expand the scope of research that can be addressed with the multiple datasets that are being integrated.As the states develop more sophisticated longitudinal data systems, the need to increased collaboration and interoperability becomes more important. This project develops a model of such collaboration from a regional perspective to expand on data available from the state longitudinal data systems and to incorporate local data from a number of agencies. This collaboration also addresses more than just the coordination of data and identification of research agendas with an additional emphasis on analytical approaches. The work in this project expands the efforts on the part of the Directorate for Education and Human Resources to strengthen the relationship between STEM education researchers and the state, regional, and local longitudinal data system. The project connects to multiple national efforts that support the use of data in education with the work of the Regional Education Laboratories. It also connects to other state and national efforts.

该提案的PI正在开发一个协作社区，以支持加州硅谷地区的数据密集型教育研究。来自圣克鲁斯的加州大学的一个教育、社会科学和工程学研究小组与一个私人非营利组织国家教育改革实验室的研究人员建立了伙伴关系。该协作小组正在构建一个由其他区域机构组成的网络，以围绕四个挑战扩大能力：阻碍机构间共享数据的文化、法律的和监管问题;分析方法;整合和管理数据集的技术基础设施问题;以及包括数据安全和隐私在内的道德问题。来自公共机构和私营部门的区域利益相关者与研究人员一起参加了今年的五次会议，以扩大可以通过正在整合的多个数据集解决的研究范围。随着各州开发更复杂的纵向数据系统，加强合作和互操作性的需求变得更加重要。该项目从区域角度开发了一个这种合作的模式，以扩大国家纵向数据系统提供的数据，并纳入一些机构提供的当地数据。这种合作不仅涉及数据的协调和研究议程的确定，还特别强调分析方法。该项目的工作扩大了教育和人力资源局的努力，以加强STEM教育研究人员与州，地区和地方纵向数据系统之间的关系。该项目与支持在教育中使用数据的多个国家努力以及区域教育实验室的工作相联系。它还与其他国家和国家的努力相联系。