CAP: Expanding AI Curriculum and Infrastructure at Texas State University to Advance Interdisciplinary Research and Grow a Diverse AI Workforce

CAP：扩展德克萨斯州立大学的人工智能课程和基础设施，以推进跨学科研究并培养多元化的人工智能劳动力

• 批准号: 2334268
• 负责人: Tahir Ekin
• 金额: $ 40万
• 依托单位: Texas State University - San Marcos
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334268&HistoricalAwards=false
• 关键词: CAP; Expanding; AI; Curriculum; Infrastructure

This project is an ExpandAI Capacity building pilot (CAP), which focuses on establishing and growing AI related activities at Texas State University - San Marcos. This project aims to significantly expand access to AI education, infrastructure, and research opportunities through widespread integration of AI technology into non-AI disciplines such as criminal justice, psychology, firefighting and agriculture. By leveraging the collective expertise and resources of the team, the project will promote interdisciplinary research and education to grow a diverse pool of AI practitioners that will drive sustainable expansion of AI technology across the Texas State University San Marcos campus and in the nearby community. Led by a diverse team of researchers from various academic departments, the project will catalyze institutional change at Texas State University San Marcos by providing comprehensive training to underrepresented individuals, empowering them to pursue AI-related careers thereby enriching the field with diverse perspectives.The proposal describes a four-pronged approach to AI-related institutional transformation at Texas State University San Marcos: (i) enhancing instructional and curricular capacity by developing innovative models for teaching and learning using AI; (ii) improving the efficiency of AI research by providing high-performance computing training that will speed up data pre-processing and neural network training; (iii) investing in foundational and use-inspired AI research and (iv) workforce development initiatives for individuals traditionally underserved in AI. Curriculum development initiatives include the establishment of an Applied AI Summer School and the development of several new AI-related course modules in areas such as Data Analytics, Python programming, Deep Learning, Natural Language Processing and Computer Vision. Evidence-based pedagogical approaches - such as inclusive pedagogy, reflective practices and contextualization – will be employed to support student learning. In collaboration with the Texas State University San Marcos Center for Analytics and Data Science, this project will establish an inclusive AI ecosystem and promote interdisciplinary collaboration, driving groundbreaking research in use-inspired AI. The ExpandAI Program supports AI-powered education and workforce development, infrastructure and research at Minority Serving Institutions to strengthen and diversify U.S. research and education pathways and provide historically marginalized communities with new opportunities in STEM careers.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.

该项目是一个 ExpandAI 能力建设试点项目 (CAP)，重点是在德克萨斯州立大学圣马科斯分校建立和发展与人工智能相关的活动。该项目旨在通过人工智能的广泛整合，显着扩大人工智能教育、基础设施和研究机会。通过利用团队的集体专业知识和资源，该项目将推动跨学科研究和教育，培养多元化的人工智能从业者，从而推动人工智能领域的可持续发展。德克萨斯州立大学的人工智能技术该项目由来自各个学术部门的多元化研究人员团队领导，将通过为代表性不足的个人提供全面的培训来促进德克萨斯州立大学圣马科斯分校的制度变革，从而使他们能够从事与人工智能相关的职业。该提案描述了德克萨斯州立大学圣马科斯分校与人工智能相关的机构转型的四管齐下的方法：（i）通过开发使用人工智能的创新教学模型来增强教学和课程能力（ii）通过提供高性能计算培训来加快数据预处理和神经网络培训，提高人工智能研究的效率；(iii) 投资基础和受使用启发的人工智能研究；(iv) 为传统上服务不足的个人提供劳动力发展计划；人工智能课程开发计划包括建立应用人工智能暑期学校以及开发数据分析、Python 编程、深度学习、自然语言处理和基于证据的教学方法等多个新的人工智能相关课程模块。 - 例如包容性该项目将与德克萨斯州立大学圣马科斯分析和数据科学中心合作，利用教学法、反思实践和情境化来支持学生的学习，建立一个包容性的人工智能生态系统，促进跨学科合作，推动突破性的应用研究。 ExpandAI 计划支持少数族裔服务机构的人工智能教育和劳动力发展、基础设施和研究，以加强和多样化美国的研究和教育途径，并为历史上边缘化的社区提供 STEM 职业的新机会。该奖项由 NSF 授予法定使命，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。