PFI: AIR-TT: Commercializing a new genre of Intelligent Science Stations for informal and formal learning

这个PFI：空气技术翻译项目旨在建立一个可重复使用的混合现实平台并将其商业化，该平台让儿童参与科学实验，并使用计算机视觉和自动反馈来帮助他们有效地学习科学原理。该项目的重点是翻译产生了第一个智能科学站的先前科学和技术研究，称为EarthShake。EarthShake是一款混合现实的教育游戏，在游戏中，孩子们通过在模拟地震台上进行块塔实验来发现平衡的物理属性。该项目有可能对社会、商业和教育产生重大影响。它的目标是影响数百万在儿童和科学博物馆、图书馆、学校和室内游戏空间度过时间的儿童和家庭。它将把传统的动手展览和游戏空间转变为智能学习环境，培养孩子的好奇心，并以参与和合作的方式改善他们的学习。它还将有助于改变学校的传统教育系统，引入一个互动、引人入胜的混合现实系统，帮助学生理解科学原理的潜在证据，而不仅仅是记忆它们。仅在美国就有270多家儿童和科学博物馆，800多家为儿童提供游戏空间的商场，100家室内游戏/学习空间，4000多家俱乐部和课外项目，119,487家图书馆，36,767所私立和特许小学以及103,460所小学，该项目除了社会和教育效益外，还可以产生商业影响。该系统使用计算机视觉来跟踪儿童的进步，并在预测-观察-解释科学查询过程中提供智能指导。实验表明，K到3年级的孩子从EarthShake中学到的东西比其他相同的平板电脑或笔记本电脑要多得多，在预测、解释和稳定的塔楼测试中，前后的增幅高达5倍。最初的原型将被转化为智能科学站的可重复使用平台，并在可扩展的开发三个游戏--EarthShake、racecars和BalloonScale的多个实例中进行演示。技术挑战是推广VISION算法以在这些游戏中的各种对象和配置中工作，并创建模块化硬件组件，以在开发、分发和新产品中提供规模。该项目吸收了计算机视觉/人工智能、机电一体化、有形界面、物理计算、人/儿童-计算机交互和教育技术方面的技术专长。智能科学站结合了物理世界和虚拟世界的优势，以一种愉快和协作的方式改善儿童的科学和探究学习，并可以在各种环境、室内游戏空间、博物馆、图书馆和学校进行商业化。该项目通过创建一个在物理3D世界中运行的自动化智能教学系统，结合传感器和感知算法来跟踪学习者正在做什么，使用致动器来操纵科学仪器，以及一个智能对话系统来协调互动，从而为一般的机器人挑战做出贡献。它解决了创建通用视觉算法和模块化物理硬件平台的技术挑战，使客户可以在不同的应用程序之间轻松切换。它将创造关于如何开发一个通用的、可重复使用的混合现实平台的新知识，该平台集成了包括机电一体化组件(例如。传感器、执行器、伺服电机、物理实验装置)和智能跟踪系统(包括带有AI视觉算法的硬件和软件组件)。

This PFI: AIR Technology Translation project aims to build and commercialize a reusable mixed-reality platform that engages children in scientific experimentation and uses computer vision and automated feedback to help them effectively learn scientific principles. The project focuses on translating prior science and technology research that produced the first Intelligent Science Station, called EarthShake. EarthShake is a mixed-reality educational game in which children discover physical properties of balance by running experiments with block towers on a simulated earthquake table. This project has the potential to have substantial societal, commercial and educational impacts. It aims to impact millions of children and families that spend time in Children's and Science Museums, libraries, schools, and indoor play spaces. It will transform traditional hands-on exhibits and play spaces into intelligent learning environments that foster children's curiosity and improve their learning in an engaging and collaborative way. It will also help to transform the traditional educational system in schools, introducing an interactive, engaging, mixed-reality system that can help students understand the underlying evidence for scientific principles, not just memorize them. With over 270 Children's and Science Museums in the US alone, over 800 malls with play spaces for children, 100s of indoor play/learning spaces, over 4,000 clubs and after-school programs, 119,487 libraries, 36,767 private and charter elementary schools and 103,460 elementary schools, this project can have a commercial impact in addition to societal and educational benefit.The system uses computer vision to follow children's progress and provide intelligent guidance in a predict-observe-explain scientific inquiry process. Experiments demonstrate that grades K to 3 children learn much more from EarthShake than from an otherwise identical flatscreen tablet or laptop implementation showing as much as a 5 times greater pre to post increase on tests of prediction, explanation, and stable tower building. The initial prototype will be translated into a reusable platform for Intelligent Science Stations and demonstrated in scalable development of multiple instances of three games, EarthShake, RaceCars, and BalloonScale. The technical challenges are to generalize the vision algorithm to work across the variety of objects and configurations in these games and create modular hardware components that provide for scale in development, distribution, and new products. This project draws on technical expertise in computer vision/AI, mechatronics, tangible interfaces, physical computing, human/child-computer interaction, and educational technology.Intelligent Science Stations bridge the advantages of physical and virtual worlds to improve children's science and inquiry learning in an enjoyable and collaborative way and can be commercialized to do so in various settings, indoor play spaces, museums, libraries, and schools. The project contributes to the general robotics challenge by creating an automated intelligent tutoring system operating in the physical 3D world, incorporating sensors and perceptual algorithms to track what learners are doing, actuators to manipulate the scientific apparatus, and an intelligent dialogue system to orchestrate interaction. It addresses technical challenges of creating a generalizable vision algorithm and a modular physical hardware platform that allows customers to easily switch between different applications. It will create new knowledge about how to develop a general and reusable mixed-reality platform that integrates scientific apparatus including mechatronic components (e.g,. sensors, actuators, servo motors, physical experimental set-up) with an intelligent tracking system (including hardware and software components with an AI vision algorithm).