Collaborative Research: CCRI: New: An Infrastructure for Sustainable Innovation and Research in Computer Science Education

合作研究：CCRI：新：计算机科学教育可持续创新和研究的基础设施

• 批准号: 2213789
• 负责人: Peter Brusilovsky
• 金额: $ 65.88万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213789&HistoricalAwards=false
• 关键词: Collaborative; Research; CCRI; New; Infrastructure

Researchers from the University of Pittsburgh, Carnegie Mellon University, North Carolina State University, and Virginia Tech collaborate to support the Computer Science Education Hub, social and technical infrastructure to accelerate research on teaching and learning of computing disciplines. The Hub will host community events and provide a web repository for computing education datasets, tools, and common analysis methods. The Hub facilitates creation and adoption of new tools to support computing educators and students, and new standards to support data collection and data-enabled research. Hub community events help researchers and educators from many learning contexts to develop and improve computing education resources. The Hub provides a pioneering example of infrastructure to support data-enabled research on education in Computing and beyond. It advances Computing Education Research through: (1) building a community and website that helps instructors adopt evidence-based practices and innovative learning technologies, (2) creating data standards and large, high-quality datasets, (3) developing advanced algorithms using artificial intelligence, statistics, and analytics methods that leverage data to optimize student learning effectiveness, efficiency, and engagement, (4) developing rigorous evaluation methods to demonstrate large, lasting, and replicable impacts on student achievement. Cross-disciplinary scientific advances are disseminated through the Hub infrastructure community and through scientific publications.The Hub will have a direct and immediate impact on hundreds of researchers and educators, and tens of thousands of students, during the project phase and beyond. It will reduce barriers to educational innovation and support discoveries in the many scientific communities that contribute to computing education research, where many researchers and educators are currently isolated into separate silos. Through community development and outreach efforts, this team directly engages with instructors and students from underserved communities in the design and use of the infrastructure. Discoveries and innovations enabled by the Hub will help tens of thousands of students in the strategically important field of computer science.To distribute project-related information, the website at http://cssplice.org/ is maintained, where all project information including standards, best practices, and resources will be shared. It informs the community about events and opportunities to contribute. The site provides links to project publications, code, data, and learning content hosted in archival repositories such as GitHub and DataShop. The website will be maintained at least through 2027. The resources contributed to archival repositories will be maintained indefinitely.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

匹兹堡大学，卡内基·梅隆大学，北卡罗来纳州立大学和弗吉尼亚理工大学的研究人员合作，以支持计算机科学教育枢纽，社会和技术基础设施，以加快计算学科的教学研究。该枢纽将举办社区活动，并提供用于计算教育数据集，工具和常见分析方法的网络存储库。枢纽有助于创建和采用新工具来支持计算教育者和学生，以及支持数据收集和支持数据的研究的新标准。枢纽社区活动可帮助许多学习环境的研究人员和教育者开发和改善计算教育资源。该枢纽提供了一个开创性的基础架构示例，以支持有关计算及其他方面的教育研究。它通过：（1）建立一个社区和网站来推进计算教育研究，该社区和网站可以帮助讲师采用基于证据的实践和创新的学习技术，（2）创建数据标准和大型高质量数据集，（3）使用人工智能，统计学和分析方法来开发先进的算法，以利用大量的学生进行研究，以优化学生的学习效率和效率，（4）效率，效率，（4）（4）（4）（4）（4）（4）（4）（4）（4）（4），（4）（4）（4）（4）（4），（4）效率，（4）的效率，（4）。对学生成就的可复制影响。跨学科的科学进步通过枢纽基础设施社区和科学出版物传播。在项目阶段及以后，该枢纽将对数百名研究人员和教育工作者以及成千上万的学生产生直接和直接的影响。它将减少许多有助于计算教育研究的科学社区中教育创新和支持发现的障碍，目前，许多研究人员和教育工作者都被隔离为单独的孤岛。通过社区发展和宣传工作，该团队直接与来自服务不足社区的讲师和学生在基础设施的设计和使用方面接触。枢纽启用的发现和创新将帮助计算机科学的战略重要领域中成千上万的学生。分发与项目相关的信息，网站http://cssplice.org/均维护，其中所有项目信息都将共享，包括标准，最佳实践和资源在内的所有项目信息。它告知社区有关贡献的事件和机会。该网站提供了指向项目出版物，代码，数据和学习内容的链接，该内容托管了Github和DataShop等档案存储库中的链接。该网站将至少至2027年维护。将无限期地维护档案存储库的资源。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子和更广泛的影响评估标准，认为值得通过评估来获得支持。

项目成果

Analysis of an Explainable Student Performance Prediction Model in an Introductory Programming Course

• 发表时间: 2023
• 期刊: Environmental Research Letters
• 影响因子: 6.7
• 作者: Muntasir Hoq;Peter Brusilovsky;Bita Akram