NRT-DESE LUCID: A project-focused cross-disciplinary graduate training program for data-enabled research in human and machine learning and teaching

学习、理解、认知、智能和数据科学在现代生活中，有许多情况需要人们与计算机互动，要么是为了让他们从机器那里学习，要么是为了让机器可以从他们那里学习。在教育、工业、卫生、机器人和国家安全方面的应用表明，研究促进人和计算机学习的技术将产生巨大的社会和经济效益。然而，这种潜力很难实现，因为这样的研究需要在完全不同的研究领域拥有专业知识的科学家。虽然计算机科学家接受了复杂计算思想和方法的培训，但他们对人们如何学习和行为知之甚少。这项授予威斯康星大学麦迪逊分校的国家科学基金会研究培训(NRT)奖将为受训者提供数据支持的科学和工程培训，使他们同时了解计算理论和方法、支持人类学习和行为的机制，以及这些机制在复杂的现实世界中的行为方式。通过一个新的侧重于学习、理解、认知、智能和数据科学的培训计划，该培训计划预计将为四十(40)名博士生提供必要的技能和专业知识，以促进我们对人类和机器学习和教学的理解。该项目将培训来自计算机科学、工程学、认知心理学和教育科学的博士生，目标是促进一个共同的知识库，使这些科学家能够跨越传统边界，在基础研究问题和实际、现实世界问题上进行富有成效的工作。培训项目将包括几项研究生培训创新：(1)以项目为重点的“教授-同行”辅导系统，科学家在该系统中以跨学科团队合作解决共同的研究问题；(2)工业、政府和非营利部门的合作伙伴密切参与，以开发具有现实世界应用的研究问题；(3)信息外展努力，培训科学家通过传统和新媒体与公众、行业和政策制定者沟通；(4)灵活的发展计划，允许每个受训人员获得推进特定研究重点所需的跨学科专业知识。以及(5)在STEM研究中招募和留住代表性不足群体的新机制。这种培训将使美国科学家做好准备，在21世纪知识经济的增长领域，在全球最高级别的科学、工业和政府职位上展开竞争。NSF研究培训(NRT)计划旨在鼓励开发和实施大胆的、新的、潜在的变革性和可扩展的STEM研究生教育培训模式。Traineesship Track致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求保持一致的综合培训模式，在高度优先的跨学科研究领域对STEM研究生进行有效培训。该奖项部分得到了EHR核心研究(ECR)计划的支持，特别是ECR特别关注的残疾教育研究(RDE)领域。ECR强调能够产生该领域基础知识的STEM基础教育研究。在基本、广泛和持久的关键领域进行投资：STEM学习和STEM学习环境，扩大STEM的参与，以及STEM劳动力发展。

NRT DESE: Learning, understanding, cognition, intelligence, and data science (LUCID)In modern life there are many situations requiring people to interact with computers, either so that they may learn from the machine or so that the machine may learn from them. The applications in education, industry, health, robotics, and national security hint at the enormous societal and economic benefits arising from research into the technologies that promote learning in both people and computers. Yet the potential has been difficult to realize because such research requires scientists with expertise in quite different fields of study. While computer scientists receive training in complex computational ideas and methods, they know little about how people learn and behave. This National Science Foundation Research Traineeship (NRT) award to the University of Wisconsin-Madison will prepare trainees with data-enabled science and engineering training to simultaneously understand computational theory and methods, the mechanisms that support human learning and behavior, and the ways these mechanisms behave in complex real-world situations. The traineeship anticipates equipping forty (40) doctoral students with the skills and expertise necessary to advance our understanding of human and machine learning and teaching, through a new training program that focuses on learning, understanding, cognition, intelligence, and data science.This project will train doctoral students from computer science, engineering, cognitive psychology, and education sciences, with the goal of promoting a common knowledge base that allows these scientists to work productively across traditional boundaries on both basic research questions and practical, real-world problems. The traineeship will include several graduate training innovations: (1) a project-focused "prof-and-peer" mentoring system where scientists work in cross-disciplinary teams to address a shared research problem, (2) close involvement of partners in industry, government, and non-profit sectors to develop research problems with real-world application, (3) an information outreach effort that trains scientists to communicate with the public, industry, and policy-makers through traditional and new media outlets, (4) a flexible development plan that allows each trainee to garner the cross-disciplinary expertise needed to advance a particular research focus, and (5) new mechanisms for recruiting and retaining under-represented groups in STEM research. This training will prepare US scientists to compete globally at the highest levels for positions in science, industry, and government, in a growth sector of the 21st century knowledge economy. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.This award is supported, in part, by the EHR Core Research (ECR) program, specifically the ECR Research in Disabilities Education (RDE) area of special interest. ECR emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development.