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

来自匹兹堡大学、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支持计算机科学教育中心，这是一个社会和技术基础设施，以加快对计算学科教学和学习的研究。该中心将主办社区活动，并为计算教育数据集、工具和常见分析方法提供网络存储库。该中心促进创建和采用新工具来支持计算教育工作者和学生，以及新标准来支持数据收集和数据启用的研究。Hub社区活动帮助来自多个学习环境的研究人员和教育工作者开发和改进计算教育资源。该中心提供了一个先锋基础设施的例子，以支持基于数据的计算教育及其他领域的研究。它通过以下方式推动计算教育研究：(1)建立社区和网站，帮助教师采用循证实践和创新的学习技术；(2)创建数据标准和大型、高质量的数据集；(3)使用人工智能、统计和分析方法开发高级算法，利用数据优化学生的学习效果、效率和参与度；(4)开发严格的评估方法，以展示对学生成绩的巨大、持久和可复制的影响。跨学科的科学进步通过Hub基础设施社区和科学出版物传播。在项目阶段及以后，Hub将对数百名研究人员和教育工作者以及数万名学生产生直接和即时的影响。它将减少教育创新的障碍，并支持许多为计算教育研究做出贡献的科学社区的发现，在这些社区，许多研究人员和教育工作者目前被隔离在不同的竖井中。通过社区发展和外展工作，该团队直接与来自服务不足社区的教师和学生接触基础设施的设计和使用。该中心的发现和创新将帮助数以万计的学生在具有战略重要性的计算机科学领域。为了分发与项目相关的信息，http://cssplice.org/网站将得到维护，所有项目信息，包括标准、最佳实践和资源，都将在这里共享。它向社区通报活动和作出贡献的机会。该站点提供指向GitHub和DataShop等档案存储库中托管的项目出版物、代码、数据和学习内容的链接。该网站将至少维持到2027年。贡献给档案库的资源将无限期保留。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.