BCC: Community and Capacity for Educational Discourse Research

BCC：教育话语研究的社区和能力

• 批准号: 1439520
• 负责人: Christopher Brooks
• 金额: $ 25.34万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1439520&HistoricalAwards=false
• 关键词: BCC; Community; Capacity; Educational; Discourse

Online learning environments are rapidly expanding the nature of the data that can be collected about student opportunity to learn and the details of the learning process. As high schools, community colleges and universities enroll more students in blended or online courses, the volume of data about what students are doing surpasses typical educational research methodologies. Borrowing from multiple traditions, analysis of educational discourse data addresses multiple persistent problems in education, including the development of ways to better predict student success during a course and to design interventions to provide support. The researchers in this proposal will build a community to address three important areas: ethics in data sharing; technical issues in data sharing; and, plans for an infrastructure to support and develop capabilities in both of these. The community built in this effort will collaboratively create the necessary metadata and standards for data sets and tools, templates for appropriate approval to use online discourse data, and de-identification algorithms that can be shared across data platforms. The research will be conducted through two interrelated workshops parsed by planning meetings with an expert advisory board. An initial workshop will focus on educational discourse and the undergraduate experience to identify the issues around the infrastructure necessary to support collaborative education discourse research. The second workshop will focus on the specific infrastructure needs for working with discourse data from massive open online courses (MOOCs). A white paper will be constructed and disseminated that addresses ethical and technical issues and solutions, as well as infrastructure needs to facilitate collaborative educational discourse research.

在线学习环境正在迅速扩大可以收集的关于学生学习机会和学习过程细节的数据的性质。随着高中、社区学院和大学招收更多的学生参加混合或在线课程，关于学生正在做什么的数据量超过了典型的教育研究方法。借鉴多种传统，教育话语数据的分析解决了教育中的多个长期存在的问题，包括制定更好地预测学生在课程中的成功的方法，并设计干预措施以提供支持。该提案中的研究人员将建立一个社区来解决三个重要领域：数据共享中的道德问题;数据共享中的技术问题;以及支持和发展这两方面能力的基础设施计划。在这一努力中建立的社区将合作创建必要的元数据和数据集和工具标准，用于适当批准使用在线话语数据的模板，以及可以在数据平台上共享的去识别算法。研究将通过两个相互关联的讲习班进行，讲习班由与专家咨询委员会举行的规划会议进行分析。最初的研讨会将重点关注教育话语和本科生体验，以确定支持协作教育话语研究所需的基础设施周围的问题。第二个研讨会将重点关注处理来自大规模开放式在线课程（MOOC）的话语数据的具体基础设施需求。将编写和分发一份白色文件，阐述伦理和技术问题及解决办法，以及促进合作教育话语研究的基础设施需求。