FW-HTF-RL: Cultivating Capacities and Confidence in Open Access Technologies through Anticipatory Workforce Development for the Future of Digital Agriculture

FW-HTF-RL：通过面向数字农业未来的预期劳动力发展培养开放获取技术的能力和信心

• 批准号: 1928582
• 负责人: Sudhagar Mani
• 金额: $ 199.65万
• 依托单位: University of Georgia Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928582&HistoricalAwards=false
• 关键词: FW; HTF; RL; Cultivating; Capacities

This project aims to advance the science informing anticipatory workforce development programs in American agriculture. The program has the potential to increase rural adult learners' confidence in digital technologies. It also has the potential to cultivate capacities and skills for developing, using, and re-using Open Access Digital Agriculture technologies. Digital technologies have become a vital element of the successful operation of farms. Open systems enable agriculturalists to adapt digital systems to their specific operational requirements, business configurations, and the environment. This project addresses the desire of farmers and farm managers to take ownership of the software and hardware systems they operate daily. Through convergent research between engineering, the social sciences, and the learning sciences, this project explores three questions. First, what viable configurations of open access agricultural systems can be deployed at different scales of farming? Second, can hands-on informal learning delivered to agriculturalists at their place of work increase comfort with using digital agricultural technologies? Third, by creating immersive learning opportunities to pair students with agriculturalists through partnerships with Cooperative Extension, can we reduce barriers to underrepresented students in STEM curricula? This project will investigate the theories, methods, and tools for understanding how convergent research fields develop, are negotiated, and ultimately create new domains of inquiry.This project will investigate new configurations of open access sensors, standards, systems, and methods of data collection analysis. These will be informed by practicing agriculturalists' understanding of digital technologies. Agriculturalist experiential data will be collected via a series of interviews with small/micro, medium, and large growers. This data will be supplemented by existing data sources on technology trends in agriculture throughout Georgia. These agriculturalists will play a critical role in developing an online curriculum for digital agriculture skills. The design of the curriculum will be scalable and deployable via the Cooperative Extension system. Undergraduate students will work with agriculturalists across the State of Georgia to develop these modules. Augmented and virtual reality technologies will be deployed to enhance the approachability and ultimately the comfort of agriculturalists with digital agriculture technologies. These educational opportunities will be supported by the development and deployment of a mobile performance computing and makerspace facility. This will enable agriculturalists to engage with digital agriculture technologies and data science within the context of their working environments and real-life problems. This is an essential modality for highly effective adult education programming. The mobile facilities will be deployed throughout the State of Georgia. They will deliver on-site programming and adapt programming to meet the needs of specific agricultural operations and co-designing open access sensor networks. They will incorporate the prototyping of parts via 3-D printing, as well as machine learning, artificial intelligence, and other needs that emerge during the project. The results of this study will leverage information gleaned from the open-source digital agriculture problem area as a model for understanding the emergence of convergent research fields and future knowledge domains.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.

该项目旨在推进美国农业中预期劳动力发展计划的科学信息。该计划有可能提高农村成人学习者对数字技术的信心。它还具有培养开发、使用和再利用开放获取数字农业技术的能力和技能的潜力。数字技术已成为农场成功运营的重要因素。开放系统使农业学家能够根据其特定的操作要求、业务配置和环境调整数字系统。该项目满足了农民和农场管理人员对他们日常操作的软件和硬件系统的所有权的愿望。通过工程，社会科学和学习科学之间的融合研究，该项目探讨了三个问题。第一，在不同规模的农业生产中，可以采用哪些可行的开放式农业系统配置？第二，在农业工作者的工作场所向他们提供的非正式实践学习是否能提高他们使用数字农业技术的舒适度？第三，通过与Cooperative Extension合作，创造沉浸式学习机会，让学生与农学家配对，我们能否减少STEM课程中代表性不足的学生面临的障碍？本项目将研究的理论，方法和工具，了解如何融合研究领域的发展，协商，并最终创建新的调查领域。本项目将研究开放获取传感器，标准，系统和数据收集分析方法的新配置。这些将通过实践农业家对数字技术的理解来了解。将通过对小型/微型、中型和大型种植者的一系列访谈收集农业学家的经验数据。这一数据将得到有关整个格鲁吉亚农业技术趋势的现有数据来源的补充。这些农学家将在开发数字农业技能在线课程方面发挥关键作用。课程的设计将是可扩展的，并通过合作推广系统部署。本科生将与整个格鲁吉亚州的农学家合作开发这些模块。 将部署增强和虚拟现实技术，以提高数字农业技术的可接近性，并最终提高农业家的舒适度。这些教育机会将得到移动的性能计算和创客空间设施的开发和部署的支持。这将使农学家能够在其工作环境和现实生活问题的背景下参与数字农业技术和数据科学。这是一个非常有效的成人教育规划的基本模式。这些移动的设施将部署在格鲁吉亚全州各地。他们将提供现场编程并调整编程以满足特定农业运营的需求，并共同设计开放接入传感器网络。他们将通过3D打印，以及机器学习，人工智能和项目期间出现的其他需求来整合零件的原型。该研究的结果将利用从开源数字农业问题领域收集的信息，作为理解融合研究领域和未来知识领域出现的模型。该奖项反映了NSF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。