FW-HTF-R: A New Bridge to the Digital Economy: Integrated AI-Augmented Learning and Collaboration

数字经济仍然是一个强大的机会中心，但该行业的大多数信息技术（IT）工作仅对拥有大学学位的工人开放。该项目团队与匹兹堡最大的社区学院合作，正在设计和部署新的人工智能增强学习技术，以加速学生在社区学院IT课程中的学习。通过提供一个可用于全国社区大学IT学位课程的蓝图，该项目可以帮助解决具有关键技术技能的工人短缺问题，同时为以前缺乏这些机会的工人创造具有成本效益的、可获得的生活工资数字经济工作的途径。该项目创造的工具和知识最终可以应用于全国其他以STEM为重点的社区大学学位课程，可能会影响数百万人的生活。 该项目正在研究如何使用学习科学家开发的理论框架，将社区大学IT课程中的知识组件与最有效的人工智能驱动的教育技术相结合，以增强和加速学习。该团队正在探索智能辅导系统（ITS），计算机支持的协作学习（CSCL）系统和基于示例的学习在多大程度上提高了学科掌握程度，减少了实现它所需的时间，并使更广泛的学习者取得成功。该项目还探索了两年制信息技术学位课程的社区学院学生与合作伙伴公司的专业人员在现实世界（云计算）问题上的合作如何通过顶点项目和实习来实现，以及该项目创建的人工智能增强课程途径是否会使学生相对于标准课程途径的学生进入IT工作。该项目团队采用严格的方法，包括课堂实验来评估学习成果，并使用倾向分数匹配和随机对照试验进行影响评估。该奖项反映了NSF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。

The digital economy remains a powerful locus of opportunity, but most information technology (IT) jobs in this sector are open only to workers with a university degree. Working with Pittsburgh’s largest community college, the project team is designing and deploying new AI-augmented learning technologies to accelerate student learning in community college IT courses. By providing a blueprint that could be used in community college IT degree programs across the country, this project could help address shortages of workers with key technical skills, while creating cost-effective, accessible pathways to living wage digital economy jobs for workers who previously lacked those opportunities. The tools and knowledge created by this project could eventually be applied to other STEM-focused community college degree programs across the nation, potentially impacting the lives of millions. This project is investigating how a theoretical framework developed by learning scientists can be used to align knowledge components in community college IT courses with the most effective AI-driven educational technologies to enhance and accelerate learning. The team is exploring the extent to which intelligent tutoring systems (ITS), computer-supported collaborative learning (CSCL) systems, and example-based learning increase subject mastery, decrease the time needed to achieve it, and enable a wider range of learners to succeed. The project is also exploring how collaborations between community college students in 2-year information technology degree programs and the professional staff of partner firms on real-world (cloud computing) problems may be effected through capstone projects and internships, and if the AI-augmented curricular pathway created by this project moves students into IT jobs relative to students in the standard course pathways. The project team is applying rigorous methods including in-class experiments to assess learning gains, and impact evaluation using propensity-score matching and randomized controlled trials.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.