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.

该项目是一个扩展的能力建筑飞行员（CAP），它着重于在得克萨斯州立大学（San Marcos）建立和发展与AI相关的活动。该项目旨在通过将人工智能技术纳入诸如刑事司法，心理学，消防和农业等非AI学科，从而大大扩大对AI教育，基础设施和研究机会的访问。通过利用团队的集体专业知识和资源，该项目将促进跨学科的研究和教育，以发展一群不同的AI实践者池，这些实践者将推动在得克萨斯州立大学圣马科斯校园和近乎社区中AI技术的可持续扩展。该项目由来自各个学术部门的一组不同的研究人员团队领导，通过为不足的人提供全面的培训，促进德克萨斯州立大学圣马科斯的机构变革，使他们有能力从事与AI相关的职业，从而使领域丰富了领域，从而以潜水员的方式丰富了领域。通过开发使用AI的教学和学习创新模型的能力； （ii）通过提供高性能计算培训来提高AI研究的效率，从而加快数据预处理和神经网络培训； （iii）投资于基础和使用启发的AI研究以及（iv）劳动力发展计划，该计划在AI中传统上服务不足的个人。课程开发计划包括建立应用的AI暑期学校，以及在数据分析，Python编程，深度学习，自然语言处理和计算机视觉等领域的几个新的与AI相关的课程模块的开发。将聘请基于证据的教学方法，例如包容性教学法，反思性实践和情境化，以支持学生学习。该项目与德克萨斯州立大学圣马科斯分析与数据科学中心合作，将建立一个包容性的AI生态系统，并促进跨学科的合作，推动在使用使用的AI中进行突破性的研究。 Expandai计划支持少数派服务机构的教育和劳动力发展，基础设施和研究，以加强和多样化美国的研究和教育途径，并为历史上的边缘化社区提供了STEM职业的新机会。该奖项反映了NSF的法定任务，并通过对基金会的智力进行了评估，以评估良好的支持。