CyberTraining:CIU:Computational and Data Science Literacy Curriculum Exchange

国家对具有适当计算和数据科学（CDS）知识的研究人员的需求已经确立。虽然在将CDS能力纳入大学课程方面取得了一些进展，但变化的速度很慢。系界、STEM专业的课程要求和资源限制都导致了STEM学科间CDS课程实施的缓慢步伐。俄亥俄超级计算机中心（OSC）与白求恩库克曼大学（BCU）、克拉克亚特兰大大学（CAU）、摩根州立大学（Morgan）、东南大学研究协会（SURA）、南方大学和a&m学院（SUBR）以及波多黎各大学马亚圭斯分校（UPRM）合作，正在实施一项试点计算和数据科学（CDS）课程交换（C2Exchange），以解决资源有限的机构所面临的挑战，特别是：少数民族服务机构（msi）面临的问题。这个项目符合国家利益，正如NSF的使命所述：通过推进STEM教育和提高我们未来研究人员的计算和数据科学技能，促进科学的进步，为国家的健康、繁荣和福利服务。课程交换方法旨在最大限度地减少教师提供新课程和更新课程所需的准备时间，增加每个机构提供的CDS课程的数量，并通过吸引所有参与机构的学生来提供最初在单个机构可能没有大量注册的课程。该试点项目为CDS课程交换奠定了基础，可以提高资源不足的小型msi以低投资提供本科CDS课程、未成年人课程和证书的能力，并可扩展，供其他资源受限的机构将来参与。这些机构的学生将受益于有机会获得更广泛的计算科学课程选择。这些备受追捧的技能培训旨在增加他们成为STEM劳动力的一部分或继续读研并成为有效研究人员的机会。每个学术机构都在提供和接收课程，如建模与仿真导论、计算化学以及数据可视化，目的是提供一系列CDS课程，这些课程可以成为每个机构证书或辅修课程的一部分。该联盟通过一种混合在线学习模式提供课程，这种模式已经过测试，并证明对技术科目有效。这种模式足够灵活，可以减少当地教师的准备时间，回应学生在材料上的困难，并适应院校不同的时间表。如果成功，这种交换教学模式将扩展到更广泛的机构以及研究生一级的专门教学。该项目探讨了在资源有限的环境中实施共享课程网络所涉及的制度和教学问题。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。

There is a well-established national need for a research workforce with suitable knowledge of computational and data science (CDS). Although, some strides have been made in integrating CDS competencies into the university curriculum, the pace of change has been slow. Department boundaries, course requirements for STEM majors, and resource constraints all contribute to the slow pace of CDS curriculum implementation across STEM disciplines. Ohio Supercomputer Center (OSC) in collaboration with Bethune Cookman University (BCU), Clark Atlanta University (CAU), Morgan State University (Morgan), Southeastern Universities Research Association (SURA), Southern University and A&M College (SUBR), and the University of Puerto Rico at Mayaguez (UPRM) are implementing a pilot Computational and Data Science (CDS) Curriculum Exchange (C2Exchange) to address the challenges experienced by resource constrained institutions and, in particular, those faced by Minority Serving Institutions (MSIs). This project serves the national interest, as stated by NSF's mission: to promote the progress of science and to serve the national health, prosperity, and welfare by advancing STEM education and improving the computational and data science skills of our future research workforce. The curriculum exchange approach is intended to minimize the faculty preparation time required to deliver new and updated courses, increase the number of CDS courses offered at each institution, and allow courses to be offered that may not initially have large enrollments at an individual institution by drawing students from all of the participating institutions. This pilot develops the foundation for a CDS Curriculum Exchange that can increase the capacity of small under-resourced MSIs to deliver undergraduate CDS curriculum, minors, and certificates with low investment and be extensible for future participation by additional resource constrained institutions. Students in these institutions will benefit by having access to a broader selection of computational science courses. Training in these highly sought after skills aims to increase their chances of being part of the STEM workforce or continuing on to graduate school and becoming effective researchers. Each academic institution is contributing and receiving courses, such as Introduction to Modeling and Simulation, Computational Chemistry, as well as Data Visualization, with the goal of providing a sequence of CDS courses that can form part of a certificate or minor program at each institution. The consortium delivers courses through a blended online learning model that has been tested and shown to be effective for technical subjects. This model is flexible enough to reduce preparation time for local instructors, respond to students' difficulties with material, and to accommodate institutions' varied schedules. If successful, this exchange model of instruction will be extensible to a wide range of institutions as well as to specialized instruction at the graduate level. The project explores important insights into both the institutional and pedagogical questions associated with the implementation of shared course networks in resource constrained environments.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.