Synthesis and design workshop: Designing Scalable Advanced Learning Ecosystems

美国目前正处于高等教育的十字路口，高质量的高等教育是进入中产阶级的先决条件，但负担得起这样的教育的能力正变得越来越有限。佐治亚理工学院提出了可扩展的高级学习生态系统来解决这一不匹配问题。佐治亚理工学院在成功的在线教育项目的基础上，提供了计算机科学和分析硕士S学位，并为高等教育管理人员和研究人员举办了一次研讨会，以建立可扩展的高级学习生态系统的组件，该生态系统可应用于高校。可扩展高级学习生态系统的目标是创建可根据不断增长的学生群体进行扩展的教育体验，同时提供个性化的关注，而这通常是不可扩展的个人面对面教学和建议的领域。技术描述佐治亚理工学院假设，随着对高等教育的需求不断增长，但满足这种需求的教授、顾问和预算有限，可扩展高级学习生态系统可用于为大量学生提供个性化和定制。人类的活动和专业知识被用来指导这个生态系统的创新创造，但日常操作是机器驱动的。这些创新包括：个性化学习系统，使用人工智能和机器学习为每个学生制定定制的教育计划；智能辅导系统，根据学生的表现修改材料的呈现和顺序；数据挖掘和学习分析，提取有用和可操作的信息，以了解学生对学习资源和结果的使用；可扩展的在线环境，提供高质量、高参与度的学习体验；以及沉浸式学习环境，模拟现实或想象世界中的物理存在，覆盖这些世界上的内容，并融合现实和虚拟世界以创造新的学习机会。研讨会于2018年11月29日和30日在亚特兰大市中心佐治亚理工学院园区的全球学习中心举行，参与机构是根据提交的建议书选出的，这些建议书描述了每个机构？S对可扩展的高级学习生态系统的兴趣和该机构？S致力于采取行动改善教育机会。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智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The U.S. is currently at a crossroads in higher education where access to quality post-secondary education is a prerequisite for entry into the middle class but the ability to afford such an education is becoming increasingly limited. Georgia Tech proposes the Scalable Advanced Learning Ecosystem to address this mismatch. Building on successful online education programs that have offered Master?s degrees in computer science and analytics, Georgia Tech hosts a workshop for higher education administrators and researchers to establish components of Scalable Advanced Learning Ecosystems that can be applied across colleges and universities. The goal of Scalable Advanced Learning Ecosystems is to create educational experiences that can be scaled to growing populations of students while providing the personalized attention that has typically been the domain of unscalable individual, face-to-face teaching and advising.Technical descriptionGeorgia Tech hypothesizes that with growing demand for higher education, but with a limited supply of professors, advisors, and budgets to meet such demand, Scalable Advanced Learning Ecosystems can be used to provide personalization and customization for large populations of students. Human activity and expertise are used to guide the creation of this ecosystem's innovations, but day-to-day operations are machine-driven. The innovations include: Personalized Learning Systems that use artificial intelligence and machine learning to establish customized educational plans for each student; Intelligent Tutoring Systems that modify the presentation and sequence of materials in response to student performance; Data Mining and Learning Analytics that extract useful and actionable information to understand student uses of learning resources and outcomes; Scalable Online Environments that deliver high-quality, high-engagement learning experiences; and Immersive Learning Environments that simulate a physical presence in real or imagined worlds, overlay content on those worlds, and merge real and virtual worlds to produce new learning opportunities. The workshop is held on November 29 and 30, 2018 at the Global Learning Center on the Georgia Tech campus in Midtown Atlanta, and participating institutions are selected by proposals submitted that describe each institution?s interest in Scalable Advanced Learning Ecosystems and the institution?s commitment to action to improve educational access.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.