DIP: Developing Crosscutting Concepts in STEM with Simulation and Embodied Learning

网络学习和未来学习技术计划资助的努力将有助于设想下一代学习技术，并推进我们对人们如何在技术丰富的环境中学习的了解。开发和实施（DIP）项目建立在概念验证工作的基础上，展示了拟议的新型学习技术的可能性，项目团队建立并完善了他们拟议创新的最低可行性示例，使他们能够理解未来应该如何设计和使用这种技术，并使他们能够回答有关人们如何学习，如何促进或评估学习，and/or how to design设计for learning学习.该提案使用了多模态沉浸式界面的进步，例如允许运动检测的传感器（如Microsoft Kinect），以检查学习者如何用他们的身体思考的问题，因为他们理解科学概念，如“规模”或“变化率”。该项目将帮助创建“体现学习的模拟剧院”，或具有沉浸式技术的房间，允许学生与科学模拟互动，同时通过移动身体表达想法。研究将检查学生使用的手势是否从一个科学学科转移到下一个学科，以及这种类型的互动是否有助于他们将他们在一个科学领域中所知道的知识转移到其他领域。在项目结束时，我们应该有1。一个技术平台，可以用来帮助研究学生如何使用手势来理解科学概念，2。关于该工具如何支持跨学科学习的信息，以及3.关于人们如何用身体思考的新颖心理学研究。2该项目旨在扩展和完善体现学习和体现设计的新兴理论。交互式互动已经显示出增加特定STEM概念学习的希望，但关于身体运动和手势如何促进理解抽象和横切思想，可能有助于学习迁移，则知之甚少。这个项目明确地研究了计算机模拟的体现性交互的持久方案是否使学习者更容易参与，并从新的STEM主题的新模拟中学习。该项目还将在计算手势识别和处理方面取得智力进步，例如通过单实例机器学习算法，实时训练和paraterized手势建模来捕获全身手势，以创建一个高度灵活的手势学习环境，该环境将使训练基于单个主题，而不必建立大型手势数据库以实现可靠的识别。通过开发（1）一个易于使用，低成本和高度可重构的系统，用于识别学习手势和（2）一套集成的学习模拟，依赖于具体的互动，使用一致的界面方案来研究广泛的STEM主题，该项目将能够研究如何使用手势一致性来支持学习者对STEM学科的概念。研究将在最初阶段使用12-15名中学生来帮助识别跨学科手势隐喻的候选手势。之后的三次迭代将使用每次迭代约50名学生，以检查与系统的交互是否可以参与支持从STEM模拟域到其他域的学习转移的体现隐喻，包括评估转移的工具的开发。

The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Development and Implementation (DIP) Projects build on proof-of-concept work that showed the possibilities of the proposed new type of learning technology, and project teams build and refine a minimally-viable example of their proposed innovation that allows them to understand how such technology should be designed and used in the future and that allows them to answer questions about how people learn, how to foster or assess learning, and/or how to design for learning. This proposal uses advances in multimodal immersive interfaces, such as sensors that allow motion detection (like the Microsoft Kinect) to examine questions about how learners think with their bodies as they make sense of science concepts like 'scale' or 'rates of change'. The project will help create "simulation theatres for embodied learning," or rooms with immersive technology that allow students to interact with science simulations and simultaneously express ideas by moving their bodies. Research studies will examine whether gestures students use carry over from one science discipline to the next, and whether this type of interaction helps them transfer what they know in one science domain to others. At the end of the project, we should have 1. a technology platform that can be used to help research how students use gesture to understand science concepts, 2. information about how well this tool supports learning across disciplines, and 3. novel psychology research about how people think with their bodies.This project seeks to extend and refine emerging theories of embodied learning and embodied design. Embodied interactions have shown promise for increasing learning in specific STEM concepts, but there is less known about how body movement and gesture promote understanding abstract and crosscutting ideas that may facilitate learning transfer. This project examines explicitly whether persistent schemes of embodied interactions with computer simulations make it easier for learners to engage with, and learn from, new simulations of novel STEM topics. This project will also make intellectual advances in computational gesture recognition and processing, for instance through single-instance machine learning algorithms, real-time training, and modeling of paraterized gestures to capture full-body gestures to create a highly flexible gesture-learning environment that will enable training based on individual subjects without having to build a large database of gestures in order to achieve reliable recognition. By developing (1) an easy to use, low cost, and highly reconfigurable system for recognizing learning gestures and (2) an integrated set of learning simulations that rely on embodied interactions to investigate a broad range of STEM topics using consistent interface schemes, the project will be able to investigate how gestural congruency can be used to support learners' conceptions of STEM disciplines. Research studies will use 12-15 middle-school students in the initial phases to help identify candidate gestures for cross-disciplinary gestural metaphors. Three later iterations will use approximately 50 students per iteration to examine whether interacting with the system can engage embodied metaphors that support transfer of learning from the domain of a STEM simulation to other domains, including development of instruments for assessing transfer.