CI-TEAM Demonstration Project: TRENDS: Training the next generation workforce in Real-time Data and Simulation Technologies

传感器和通信技术的进步以及网络连通性的增强使人们能够获得大量不同的数据集。这种访问是交互式的，因为人们可以控制收集什么，采样的频率以及收集的粒度。这种网络化的基础设施有望彻底改变物理世界的监测和现场实验的方式-自动化，远程，实时数据收集和反馈取代传统的手动和耗时的方法。虽然网络可访问的信息被用于我们的日常决策，并使令人兴奋的新的研究可能性，它是非常利用在学习和课堂环境。仅仅培训下一代劳动力查看或利用在线数据是不够的，他们必须能够通过利用各种网络基础设施支持的数据源，综合新的解决方案来应对新出现的挑战。这项工作的前提是，培训这样一个网络基础设施识字的公民必须从K-12水平开始。该项目的重点是增加K-12教师和学生群体对传感器网络和基于模拟的网络基础设施工具的接触。研究表明，实验和实践活动是课程的重要组成部分，因为它们可以加强课本知识，并导致更好的保留。目前，这些活动往往局限于课堂实验，受可用空间（教室），仪器和资源，并在有限的时间（一个类的跨度）。使用点数据（例如，在实验期间保持温度为固定值）而不是时变输入（其更好地模拟真实世界系统）。此外，对于新兴的科学和技术领域，学生往往不得不依赖于教科书中的阅读。例如，一项新的堪萨斯农业教育标准要求学生学习可持续农业实践、全球定位系统/地理信息系统的使用以及肥料/杀虫剂对产量的影响。但由于缺乏资源，学生主要依靠从教科书上阅读有关可持续农业的内容。拟议项目的智力优势包括开发用于现场实验的传感器基础设施，模拟软件以及K-12教育的课程和培训材料。（a）为基于传感器网络的数据收集技术开发软件和培训模块：其目标是，教师最终将能够在任何科学和技术课上用“实时数据”取代“课堂观察”，并包括涉及对实时输入的反应的互动方面，（B）开发一个“智能农场”模拟包，学生将在其中管理虚拟农场的日常运作，并将其与包括实时数据在内的各种数据源联系起来，（c）通过根据实地实验和模拟软件制定课程计划，促进基于探究的教育，将其纳入课程，并根据这些课程计划培训教师/学生。该项目更广泛的影响包括接触各种各样的学生，以扩大参与。该项目建立在由NSF RET（教师研究经验）和NSF CRCD（联合研究课程开发）计划以及NSF GK-12 STEM研究员计划资助的实时嵌入式传感器系统设计的过去成功项目的基础上。这些都导致了与农村和城市堪萨斯学校的牢固关系。该项目利用这些联系来训练多样化的人群。该项目正在向堪萨斯服务不足的农村学区和西班牙裔人口众多的地区伸出援手。通过智能农场模拟对农业应用的关注使该项目能够覆盖历史上服务不足的学生群体。通过使软件可在网上访问，该项目正在努力缩小那些在家中拥有宽带接入和最先进计算硬件的学生与那些拥有过时或没有设备的学生之间的“技术差距”。该团队继续与堪萨斯州立大学现有的项目合作，如GROW和EXCITE，将初中和高中女生带到校园，并与Kan-Ed项目合作，其目的是在堪萨斯的教育机构之间提供全州范围的合作和信息交流机会。

Advances in sensor and communication technologies and increased cyber-connectivity are enabling access to a vast amount of varied datasets. This access is interactive in that one can control what is being collected, how often it is sampled and the granularity at which it is being collected. Such cyber-enabled infrastructures are poised to revolutionize the way the physical world is monitored and field experiments are performed -- with automated, remote, real-time data collection and feedback replacing traditional manual, and time-consuming methods. Although web accessible information is being used in our daily decision making and has enabled exciting new research possibilities, it is very under-utilized in learning and classroom environments. It is not enough for the next generation workforce to be simply trained to view or utilize online data, rather they must be able to synthesize new solutions to emerging challenges by leveraging diverse cyber-infrastructure enabled data sources. The premise of this work is that training such a cyber-infrastructure literate citizen must start at the K-12 level. The focus of this project is to increase the exposure of K-12 teachers and student populations to sensor network and simulation based cyber-infrastructure tools. Research has shown that experiments and hands-on activities are an important part of the curriculum as they re-enforce textbook knowledge and lead to better retention. Currently, these activities often are restricted to in-class experiments subject to the available space (the classroom), instruments and resources, and are of limited duration (the span of a single class). Point data is used (e.g., holding temperature to a fixed value for the duration of the experiment) rather than time-varying input (which better models real-world systems). Further, for new, emerging areas of science and technology, students often have to rely on reading in textbooks. For example, a new Kansas Standards for Agricultural Education requires students to learn about sustainable agriculture practices, use of GPS/GIS, and the impact of fertilizers/pesticides on yield. However, due to lack of resources, students mainly rely on reading about sustainable agriculture from textbooks. The intellectual merits of the proposed project include developing sensor infrastructure for field experiments, simulation software, and curriculum and training material for K-12 education. These efforts include the following: (a) Developing software and training modules for sensor network based data collection technologies: The aim is that teachers will eventually be able to replace "in-class observing" with "real-time data" for experiments in any of their science and technology classes, and include interactive aspects involving reactions to real-time input, (b) Developing a "smart farm" simulation package in which students will manage the day-to-day operations of a virtual farm, and link it to diverse data sources including real-time data, (c) Promoting inquiry based education by developing lesson plans based on field experiments and simulation software, integrating them into curriculum and training teachers/students based on these lesson plans. The broader impacts of the project include reaching out to a diverse pool of students to broaden participation. The project builds upon past successful projects in real-time embedded sensor systems design funded by NSF RET (Research Experience for Teachers) and NSF CRCD (Combined Research-Curriculum Development) programs, and the NSF GK-12 STEM Fellows program. These have resulted in strong relationships with both rural and urban Kansas schools. This project leverages these connections to train a diverse population set. The project is reaching out to rural under-served school districts in Kansas and those with significant Hispanic population. The focus on agricultural applications via Smart Farm simulations enables the project to reach student populations that have historically been underserved. By making the software web-accessible, the project is working to minimize the "Technology Gap" between those students who have broadband access and state-of-the-art computing hardware in their homes, and those who have outdated or no equipment. The team is continuing to work with existing programs at Kansas State University such as GROW and EXCITE which bring middle and high school girls to campus, and with the Kan-Ed program whose purpose is to provide state-wide collaboration and information exchange opportunities among educational institutions in Kansas.