可视化动态系统:体积和全息显示

M. M. Haghanikar
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引用次数: 2

摘要

本书旨在帮助教学设计师,科学游戏设计师,科学教师,实验室设计师和内容开发人员设计使用新兴技术和网络学习的互动学习体验。建议的解决方案适用于本科生和研究生的科学交流、工程课程、科研交流和劳动力培训。回顾科学教育文献揭示了科学概念可视化中未解决的挑战或无能的各个方面。视觉空间思维是学习科学的基础部分;然而,促进空间思维在教育系统中并没有得到足够的重视(Hegarty, 2014)。认知科学家区分了空间能力的多个方面,并强调不同的问题或学科需要不同类型的空间技能。例如,可视化解剖截面的空间能力与心理旋转技能显著相关。对于经常处理空间表示的物理问题也是如此。然而,大多数物理问题都具有动态性,而动态性的可视化是通过系统中不同参与组件的集成来推断的。因此,学习动态性所需要的是将静态情节的心理动画可视化。这本书是一个飞跃到设计框架使用混合现实(XR)技术和网络学习交流先进的科学概念。目的是充实复杂系统的认知基础设施和视觉空间需求,并在不同的环境和学科中比较它们。新兴技术的实际实现可以通过预测每种XR技术的功能,并将其映射到正在开发的内容的认知基础设施和视觉空间需求来实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualizing Dynamic Systems: Volumetric and Holographic Display
This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training. Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014)1. Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes. This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology’s affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.
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