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访问大量不同的数据集。这种访问是交互的，因为用户可以控制正在收集的内容、采样频率以及收集的粒度。这种由网络支持的基础设施将彻底改变监测物理世界和进行现场实验的方式--自动化、远程、实时的数据收集和反馈将取代传统的手动和耗时的方法。尽管网络可访问信息正被用于我们的日常决策，并使令人兴奋的新研究成为可能，但它在学习和课堂环境中的利用率很低。对于下一代劳动力来说，仅仅接受查看或利用在线数据的培训是不够的，他们必须能够通过利用各种支持网络基础设施的数据源来合成新的解决方案，以应对新出现的挑战。这项工作的前提是，培训这样一名懂网络基础设施的公民必须从K-12级别开始。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，实验和动手活动是课程的重要组成部分，因为它们强化了课本知识，并有助于更好地记忆。目前，这些活动往往仅限于课堂实验，受可用空间(教室)、仪器和资源的限制，而且持续时间有限(一节课的时间跨度)。使用点数据(例如，在实验期间将温度保持在固定值)，而不是时变输入(这更好地模拟真实世界的系统)。此外，对于新兴的科学技术领域，学生们往往不得不依赖教科书上的阅读。例如，新的堪萨斯州农业教育标准要求学生学习可持续农业实践、GPS/GIS的使用以及化肥/杀虫剂对产量的影响。然而，由于缺乏资源，学生主要依靠阅读教科书中关于可持续农业的知识。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、模拟软件以及用于K-12教育的课程和培训材料。这些努力包括：(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：目的是教师最终将能够在其任何一节科学和技术课上用“实时数据”代替“课堂上的观察”进行实验，并包括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不同数据来源联系起来；(C)通过在实地实验和模拟软件的基础上开发教案来促进基于探究的教育。将它们整合到课程中，并根据这些教案对教师/学生进行培训。该项目的更广泛影响包括接触到不同的学生群体，以扩大参与。该项目建立在过去由NSF RET(教师研究体验)和NSF CRCD(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成功项目的基础上。这些都与堪萨斯州的乡村和城市学校建立了牢固的关系。该项目利用这些联系来培训不同的人群。该项目正在向堪萨斯州服务不足的农村学区和拥有大量拉美裔人口的地区伸出援手。通过智能农场模拟将重点放在农业应用上，使该项目能够接触到历史上服务不足的学生群体。通过使该软件可在网络上访问，该项目致力于将家里有宽带接入和最先进的计算硬件的学生与那些设备过时或没有设备的学生之间的“技术差距”降至最低。该团队继续与堪萨斯州立大学现有的项目合作，如将初中和高中女孩带到校园的Growth和Extreme项目，以及旨在提供堪萨斯州教育机构之间全州合作和信息交流机会的Kan-Ed项目。

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.