Collaborative Research: Adaptable Game-based, Interactive Learning Environments for STEM Education (AGILE STEM)

协作研究：适用于 STEM 教育的适应性强、基于游戏的交互式学习环境 (AGILE STEM)

• 批准号: 2302815
• 负责人: Christian Lopez Bencosme
• 金额: $ 15万
• 依托单位: Lafayette College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2302815&HistoricalAwards=false
• 关键词: Collaborative; Research; Adaptable; Game; based

Learners of all ages are expected to be prepared to interact with emerging and technology-driven work environments. In addition, the growing reliance on online learning and its unprecedented and unexpected acceleration due to the COVID-19 pandemic are expected to change the education landscape forever. Thus, there is a need to grow the development of digital platforms for teaching and learning. Emerging technologies such as machine learning and high fidelity simulated environments have the potential to create customized and adaptable learning environments to support STEM learning outcomes. This project serves the national interest by advancing the knowledge about designing and creating adaptable game-based, interactive learning environments for STEM. The inclusion of underrepresented minority and female learners in the design stages of these learning environments, their portability, as well as the capability of these environments to be customized and adaptive have the potential to enhance education equality, engagement, and learning outcomes, and broaden their usability to several STEM domains. Moreover, the narratives and simulation models are inspired by real-world systems. Therefore, the learning environments are expected to enhance the learner’s understanding of complex system concepts that are challenging to understand using traditional teaching approaches and will help build the much-needed skills for the U.S. future STEM workforce. The proposed emerging technologies do not necessarily need access to specialized equipment, which eliminates barriers to scalability and border implementation and use. The primary goals of this project are to automatically customize and adapt three-dimensional (3D) simulated game-based learning environments to improve engagement, and provide a deeper understanding of their design, development, and deployment, impact on learning and self-regulated learning (SRL) skills, and knowledge transferability from the learning environments to real-life applications. The project addresses the lack of scientific evidence and/or work in the following thrust areas: 1) the potential of reducing the barriers to content generation of 3D simulated game-based learning environments using emerging and advanced machine-learning methods; 2) creating customized content and adaptive 3D simulated game-based learning environments that improve and maintain learners motivation and engagement, enhance learning via instructional assistive content scaffolding, and increase knowledge transferability from game to real-life applications; 3) assessing the effectiveness of the learning environments for all learner groups in online and residential settings; and 4) exploring how learner decision-making and behavior data in the simulated game-based learning environments, and eye-tracking, facial expressions, bio-signals, and usage data, enhance knowledge about the relationships between decision-making/usage and SRL skills development.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.

所有年龄段的学习者都应做好与新兴和技术驱动的工作环境互动的准备。此外，对在线学习的日益依赖以及由于 COVID-19 大流行而导致的前所未有的、意想不到的加速预计将永远改变教育格局。因此，需要发展机器学习和高保真模拟环境等新兴技术，以创建定制的、适应性强的学习环境，以支持 STEM 学习成果。通过提高有关设计和设计的知识来实现​​国家利益为 STEM 创建基于游戏的自适应互动学习环境，将代表性不足的少数族裔和女性学习者纳入这些学习环境的设计阶段，其可移植性以及这些环境的定制和适应性能力有可能得到增强。教育平等、参与度和学习成果，并将其可用性扩展到多个 STEM 领域。此外，叙述和模拟模型受到现实世界系统的启发，因此，学习环境有望增强学习者对复杂系统概念的理解。使用传统方法很难理解拟议的新兴技术不一定需要专用设备，这消除了可扩展性和边界实施和使用的障碍。自动定制和调整基于游戏的三维 (3D) 模拟学习环境，以提高参与度，并更深入地了解其设计、开发和部署、对学习和自我调节学习 (SRL) 技能的影响以及知识可转移性从学习环境到该项目解决了以下重点领域缺乏科学证据和/或工作的问题：1）使用新兴和先进的机器学习方法减少基于 3D 模拟游戏的学习环境的内容生成障碍的潜力。 2) 创建定制内容和基于游戏的自适应 3D 模拟学习环境，以提高和维持学习者的积极性和参与度，通过教学辅助内容支架增强学习，并提高知识从游戏到现实生活应用的可转移性 3) 评估学习的有效性；适合所有人的学习环境在线和住宅环境中的学习者群体；4) 探索基于模拟游戏的学习环境中的学习者决策和行为数据以及眼动追踪、面部表情、生物信号和使用数据如何增强对关系的了解该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。