Embodied Explanatory Expressions for Facilitating Science Reasoning and Enhancing Interactive Simulations

该项目将研究学生的身体运动如何支持他们对涉及隐藏结构或不可观察的机制的科学概念的推理和理解。学生和科学家的描述和解释往往涉及具体的表达，例如用于表示或象征性地操纵科学系统的组成部分的身体动作(例如，将手转向物体的旋转，倾斜上半身以显示某种类型的不平衡，等等)。探索科学推理的具体基础也是及时的，因为人机界面的最新进展允许人们使用富有表现力的自然动作与计算机交互，而不是击键和鼠标点击。该项目最初将研究哪些类型的身体运动支持对可观察现象的因果解释，这些现象被称为具体化解释表达(EEES)。在这项研究的基础上，该项目将探索是否可以利用新推出的运动感应输入设备(例如Microsoft Kinect、Leap Motion)将识别出的EEE集成到在线模拟的控制结构中。研究结果将丰富我们对科学学习的基本认识，并对课程设计和新学习技术的开发具有实际意义。该项目将通过记录和分析学生在解释这些科学概念时的手势和身体动作来研究这些手势和身体动作，不仅识别这些知识的体现，而且根据这些动作设计干预和模拟，以促进学习。使用访谈、可用的运动感应输入设备和其他方法，该项目将验证该方法，调查学生如何使用身体运动进行推理，以及他们的表情如何随着干预而变化。该项目将确定在涉及不可观测机制的三个关键科学领域中支持科学推理的核心因素：分子相互作用、热传递和地球系统。该项目将专门关注支持学生构建解释的具体化互动的类型，并探索这些身体动作是否可以整合到新一代在线学习模拟的设计中，以提高使用它们的学生展示的科学推理水平。

The project will research how student body movements support their reasoning and understanding about scientific concepts that involve hidden structures or unobservable mechanisms. Student and scientist descriptions and explanations often involve embodied expressions, such as body movements used to represent or symbolically manipulate components of scientific systems (e.g., turning the hands to an object's rotation, tilting the upper torso to demonstrate some type of imbalance, etc.). Exploring the embodied foundations of science reasoning is also timely because of recent advances in human-computer interfaces that allow people to interact with computers using expressive, natural movements as opposed to keystrokes and mouse-clicks. The project will initially research what types of body motion that support causal explanations for observable phenomena, which are called Embodied Explanatory Expressions (EEEs). Building on the research, the project will then explore whether identified EEEs can be integrated into the control structures of online simulations utilizing newly available motion sensing input devices (e.g., Microsoft Kinect, Leap Motion). The research findings will enrich our basic understanding of science learning and have practical implications in curriculum design and in the development of new learning technologies.The project will research student gestures and body motion during explanation of such scientific concepts by recording and analyzed these gestures and motion not only to identify the embodiment of such knowledge, but also to design interventions and simulations based on such motions that could facilitate learning. Using interviews, available motion sensing input devices, and other methods, the project will validate the approach, investigate how students reason using body movements, and how their expressions change with interventions. This project will identify core EEEs for supporting scientific reasoning in three critical areas of science involving unobservable mechanisms: Molecular Interactions, Heat Transfer, and Earth Systems. The project will focus specifically on the types of embodied interactions that support students' construction of explanations, and explore whether these body movements can be integrated into the design of a new generation of online learning simulations that elevates the level of science reasoning exhibited by students who use them.