发表机构
University of Minnesota; Michigan Tech Hitech Kids（明尼苏达大学; 密歇根理工大学高科技创新儿童项目）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文介绍低成本开源ROV平台Jar Jar ROV，通过百余名学生参与水质监测，验证了将机器人技术融入K-12环境教育的可扩展模型，并指出学生参与度差距及改进方向。
AI 中文摘要
让K-12学生参与真实的科学研究仍然是一个重大挑战，尤其是在环境科学与机器人技术的交叉领域。我们介绍了Jar Jar ROV，一个专为中学生基于公民科学的水质监测而设计的低成本、开源遥控潜水器（ROV）平台。本文介绍了该平台的设计以及在美国一个州内超过100名学生参与的大规模部署结果，这些学生建造、编程并在当地湖泊中部署了ROV。该教育框架在动手活动中获得了学生的高度参与，ROV建造环节获得了导师们的满分平均分。在科学方面，该项目建立了一个基层监测网络，生成了近一万一千个经过验证的温度、pH值、溶解氧和浊度测量数据。然而，我们的评估发现了一个关键的“参与度差距”，即学生在电子组装和数据上传等更复杂的任务中兴趣急剧下降。本文既贡献了一个经过验证的、可扩展的将机器人技术融入环境教育的模型，也为未来改进提供了一条数据驱动的路线图。这些改进侧重于降低技术门槛，并在数据收集与科学发现之间建立更直观的联系，以应对赋能下一代公民科学家这一关键挑战。
英文摘要
Engaging K-12 students in authentic scientific research remains a significant challenge, particularly at the intersection of environmental science and robotics. We introduce the Jar Jar ROV, a low-cost, open-source Remotely Operated Vehicle (ROV) platform designed for citizen science-based water quality monitoring by middle school students. This paper presents the design of the platform and the results of a large-scale deployment with over 100 students across a US state who built, programmed, and deployed the ROVs in local lakes. The educational framework yielded high student engagement in hands-on activities, with ROV construction earning a perfect average score from mentors. Scientifically, the program established a grassroots monitoring network, generating nearly eleven thousand validated measurements of temperature, pH, dissolved oxygen, and turbidity. However, our evaluation identified a critical "engagement gap," with student interest declining sharply during more complex tasks such as electronics assembly and data uploading. This paper contributes both a validated, scalable model for integrating robotics into environmental education and a data-driven roadmap for future improvements. These enhancements focus on lowering technical barriers and creating a more intuitive link between data collection and scientific discovery, addressing a key challenge in empowering the next generation of citizen scientists.
CommentsAccepted to ICRA 2026
Journal ref2026 IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria, 2026, pp. 4643-4650
DOI：10.1109/ICRA57385.2026.11696593
