Collaborative Research: CI-Team Diff: The Virtual Learning Commons: STEM Research Communities Learning about Data Management, Geospatial Informatics, and Scientific Visualization

通过网络基础设施（CI）实现21世纪科学的预期国家转型，取决于在许多科学、技术、工程和数学（STEM）领域采用新的CI方法。对于不熟悉CI但准备充分的STEM教师和研究人员来说，采用新技术的学习曲线是陡峭的，工具不成熟且难以使用。关键问题是需要1)有效的流程和机制，通过这些流程和机制，STEM专业人员可以学习将CI整合到他们的工作中，以及2)在研究环境中发展基于经验的CI创新扩散理论，以便设计和实施有效的流程和机制。该项目正在开发一个协同环境，使STEM研究社区，包括研究生，教师和研究人员，能够终身参与新兴CI的学习。该项目的目标是：创建一个专注于数据和信息获取、管理、管理、分析、可视化、来源和发现技术的虚拟学习环境；让地方、区域、国家和国际STEM研究和教育界参与面对面和虚拟环境；并继续发展和扩展我们对跨学科研究环境中CI创新的技术采用和传播的理解、理论、概念和模型。该项目通过四项活动来实现其目标：1)协作开发虚拟学习共享（VLC）；2)使用视讯会议技术和VLC的虚拟工作坊，3)面对面的工作会议，以及4)博士后研究员和研究生辅导。所有活动都将研究与教育结合起来，通过以问题为基础的体验式学习，通过实践社区在解决实际问题的背景下进行。知识价值。该项目将提供有关CI的虚拟协作学习的新知识，并通过CI开发新的CI支持学习系统。它将产生新的支持ci的专业STEM研究人员社区，特别是那些在数据管理、地理空间信息学和可视化领域工作的研究人员。它将对全球STEM研究界现有和新兴CI创新的传播产生新的理解，以及CI研究人员和所有专业水平的STEM研究人员之间跨学科，分布式合作的新模式-研究生到经验丰富的研究人员。该项目将更好地理解虚拟学习环境、实践社区和研究人员终身学习之间的相互作用。该项目涉及来自德克萨斯大学埃尔帕索分校（UTEP）、堪萨斯大学（KU）和新墨西哥大学（UNM）的经验丰富的CI研究人员团队，他们与新墨西哥大学、洛斯阿拉莫斯国家实验室（LANL）以及国家和国际长期生态研究网络的科学和工程教育、地理流行病学和信息管理研究团体合作。该项目建立在我们之前的ci团队演示和实施项目中产生的协作学习模型的基础上，以实现目标。更广泛的影响。该项目将对传统上在高端科学计算中代表性不足的多个STEM社区产生广泛影响，并涉及两个西班牙裔服务机构中代表性不足的少数族裔。该项目将确保UTEP STEM学科的西班牙裔学生获得知识和技能，使他们成为CI支持的STEM研究的领导者，通过指导UTEP的科学和工程教育工作者，因为他们在VLC中学习和使用CI-教育教育工作者。该项目为将社区转移到基于ci的方法提供了一个模型，可以在任何STEM社区中复制。它将为广泛的STEM研究界提供学习数据管理的资源，而数据管理现在是所有NSF项目的要求。它还将产生一个新的虚拟空间，在其中，从事CI劳动力开发的新兴实践社区可能开始共享资源和协作。

The expected national transformation of 21st Century science through cyberinfrastructure (CI) depends on adoption of new CI approaches across many science, technology, engineering and mathematics (STEM) domains. For STEM faculty and researchers who are unfamiliar with CI but are otherwise well prepared, the learning curve to adopt new technology is steep and tools are immature and difficult to use. Key issues are the need for 1) effective processes and mechanisms by which STEM professionals can learn to integrate CI into their work, and 2) development of empirically based theories about the diffusion of CI innovation in research settings so that effective processes and mechanisms can be designed and enacted. This project is developing a synergistic environment that will enable the STEM research community, including graduate students, faculty, and researchers, to engage in life-long, life-wide learning about emerging CI. The goals of the project are to: create a virtual learning environment focused on techniques for data and information acquisition, management, curation, analysis, visualization, provenance, and discovery; engage local, regional, national and international STEM research and education communities in face-to-face and virtual settings; and continue to develop and extend our understanding, theories, concepts, and models of technology adoption and diffusion of CI innovation in interdisciplinary research settings. The project uses four activities to accomplish its goals: 1) collaborative development of a Virtual Learning Commons (VLC); 2) virtual workshops using videoconference technology and the VLC, 3) face-to-face working meetings, and 4) postdoctoral researcher and graduate student mentoring. All activities integrate research with education through problem-based, experiential learning by communities of practice in the context of real problem solving. Intellectual Merit. This project will contribute new knowledge about virtual, collaborative learning about CI and through CI, developing a new, CI-enabled learning system. It will generate new communities of CI-enabled professional STEM researchers, in particular those working in the areas of data management, geospatial informatics, and visualization. It will generate new understanding of diffusion of existing and emerging CI innovations in the global STEM research community and new models of interdisciplinary, distributed collaboration between CI researchers and STEM researchers at all professional levels - graduate student to highly experienced. The project will provide a better understanding of interactions between virtual learning environments, communities of practice, and life-long, life-wide learning by researchers. The project involves an experienced team of CI researchers from the University of Texas at El Paso (UTEP), University of Kansas (KU), and University of New Mexico (UNM) who are partnering with research communities in science and engineering education, geo-epidemiology, and information management at UNM, Los Alamos National Laboratory (LANL), and the National and International Long Term Ecological Research (LTER) Network. The project builds on models of collaborative learning generated from our previous CI-Team Demonstration and Implementation Projects to accomplish the objectives. Broader Impacts. This project will have broad impacts within multiple STEM communities traditionally underrepresented in high-end scientific computing, as well as involving underrepresented minorities at two Hispanic Serving Institutions. The project will ensure that Hispanic students in STEM disciplines at UTEP receive the knowledge and skills that enable them to become leaders in CI-enabled STEM research, through mentoring Science and Engineering Educators at UTEP as they learn about and use CI within the VLC -- educating the educators. The project provides a model for moving communities to CI-based approaches that can be replicated in any STEM community. It will generate resources for the broad STEM research community to learn about data management - now a requirement for all NSF programs. It will also generate a new virtual space within which an emerging community of practice engaged in CI Workforce Development may begin to share resources and collaborate.