QuEST: Revolutionizing Repository Cross-referencing to Transform Discovery of Teaching Materials

QuEST：彻底改变存储库交叉引用以转变教材的发现

• 批准号: 1043647
• 负责人: Min Song
• 金额: $ 15万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1043647&HistoricalAwards=false
• 关键词: QuEST; Revolutionizing; Repository; Cross; referencing

An emerging activity of digital educational repositories is the cross-referencing of resources with national and state standards. The goal of QuEST (Quality Estimate Scoring Technique) is to provide a cross-referencing support system to greatly increase the productivity of the expert human cross-referencer so vastly more resources can be matched with higher accuracy. This mechanism uses information found in NSDL's Strand Maps for both characterization and discrimination analysis to support the scoring of a resource to a particular Strand Map benchmark. QuEST is providing a working cross-referencing support system that can be plugged into any partner digital repository. It is transforming the cross-referencing task from a strictly concept matching effort to a truly representative comparison of what is important to educators. This is reducing the burden on teachers by providing a better filtered set of resources that have been selected based on quality markers used by teachers.By cross-referencing useful content more quickly and effectively, teachers are able to find and select more appropriate content which in turn is helping them deliver high quality education to their students and achieve higher personal satisfaction. This is also leading to greater utilization of the repository. QuEST also supports the NSDL mission by functioning as a learning environment for its project participants, including undergraduate and graduate students, teachers, and librarians. Through their exposure to the larger evaluation and software development components of QuEST, project participants gain increased understanding of the overall digital repository research process.

数字教育存储库的一项新兴活动是资源与国家和州标准的交叉引用。 QuEST（质量评估评分技术）的目标是提供一个交叉引用支持系统，以大大提高人类交叉引用专家的生产力，从而可以以更高的精度匹配更多的资源。该机制使用 NSDL 的 Strand Map 中的信息进行表征和区分分析，以支持根据特定 Strand Map 基准对资源进行评分。 QuEST 提供了一个有效的交叉引用支持系统，可以插入任何合作伙伴的数字存储库。它将交叉引用任务从严格的概念匹配工作转变为对教育工作者重要的内容进行真正具有代表性的比较。通过提供根据教师使用的质量标记选择的更好过滤的资源集，减轻了教师的负担。通过更快、更有效地交叉引用有用的内容，教师能够找到并选择更合适的内容，反过来，帮助他们为学生提供高质量的教育并实现更高的个人满意度。这也导致了存储库的更大利用率。 QuEST 还通过为项目参与者（包括本科生和研究生、教师和图书馆员）提供学习环境来支持 NSDL 的使命。通过接触 QuEST 的更大评估和软件开发组件，项目参与者可以更好地了解整个数字存储库研究过程。