Creating a High-Performance Computing Virtual Environment for Artificial Intelligence Education

该项目旨在开发学习人工智能（AI）的虚拟环境，为国家利益服务。人工智能的进步正在改变各行各业、政府和学术界的研发。学习人工智能的一个关键挑战是，它的解决方案不如模仿人类高级推理的传统算法解决方案透明。人工智能解决方案通常是一个黑盒子，缺乏可解释性，这使得很难获得洞察力，理解并最终开发人工智能知识。该项目将开发一种实时互动工具，以促进来自所有学科背景的学习者的人工智能知识和实践的发展。这种工具将为学习干预的设计提供信息，使抽象和复杂的主题更容易理解。该项目的成果将根据具身认知理论的原则，在交互式可视化的框架下支持人工智能的学习。设想中的工具将从头开始设计，通过交互式可视化来最好地支持人工智能教育，这种可视化要么是沉浸式的，使用虚拟现实耳机，要么是非沉浸式的，在传统的显示器上。该项目将专注于人工智能的基础主题，并将为人工智能教育的学科教育研究做出贡献。这些发现将产生关于学生对人工智能结构的概念性理解和对人工智能实践的程序性理解的新知识。可视化环境的学习效果将首先在试点阶段进行迭代验证，然后在实验阶段进行验证，由来自普渡大学跨学科社区的250名学习者组成的不同小组进行验证。NSF IUSE: EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。通过其参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by developing a virtual environment for learning Artificial Intelligence (AI). Advances in AI are transforming research and development across industries, government, and academia. A key challenge in learning AI is that its solutions are less transparent than traditional algorithmic solutions that mimic high-level human reasoning. AI solutions are often a black box, lacking interpretability, which makes it hard to gain insights, understand, and ultimately develop knowledge in AI. This project will develop a real-time interactive tool that will promote the development of AI knowledge and practices of learners from all disciplinary backgrounds. Such a tool will inform the design of learning interventions that will make abstract and complex topics more accessible. The outcomes of this project will support learning in AI with the scaffolding of interactive visualization, according to tenets of embodied cognition theories. The envisioned tool will be designed from the ground up to best support AI education through interactive visualization that is either immersive, using virtual reality headsets, or non-immersive, on conventional displays. The project will focus on foundational topics in AI and will contribute to discipline-based education research in AI education. The findings will generate new knowledge about students’ conceptual understanding of AI constructs and procedural understanding of AI practices. The visualization environment’s learning effectiveness will be validated iteratively first in a pilot and then in an experimental stage, with a diverse group of 250 learners from an interdisciplinary community at Purdue University. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.