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

来自匹兹堡大学、卡耐基梅隆大学、北卡罗莱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、社会和技术基础设施，以加速计算机学科的教与学研究。该中心将举办社区活动，并为计算教育数据集、工具和通用分析方法提供网络存储库。该中心促进了新工具的创建和采用，以支持计算机教育工作者和学生，以及支持数据收集和数据支持研究的新标准。Hub社区事件帮助来自许多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。该中心提供了一个开创性的基础设施示例，以支持计算机及其他领域的教育数据支持研究。它通过以下方式推进计算机教育研究：(1)建立一个社区和网站，帮助教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、高质量的数据集；(3)利用人工智能、统计和分析方法开发先进的算法，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，以展示大型、持久的、以及对学生成绩的可复制影响。跨学科的科学进展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，该中心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直接的影响。它将减少教育创新的障碍，并支持许多有助于计算机教育研究的科学社区的发现，在这些社区中，许多研究人员和教育工作者目前被隔离在不同的筒仓中。通过社区发展和推广工作，该团队直接与来自服务不足社区的教师和学生合作，设计和使用基础设施。该中心的发现和创新将帮助成千上万的学生在具有重要战略意义的计算机科学领域学习。为了分发与项目相关的信息，我们维护了一个网站http://cssplice.org/，在这个网站上，所有的项目信息，包括标准、最佳实践和资源都将被共享。它告知社区有关活动和贡献的机会。该网站提供了项目出版物、代码、数据和存放在GitHub和DataShop等存档库中的学习内容的链接。该网站将至少维持到2027年。向档案库提供的资源将无限期保留。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.