ICE-TI: Thokatakiya (Towards the future)

部落学院和大学计划（TCUP）的一个目标是提高为美国土著学生服务的特定高等教育机构的科学、技术、工程和数学（STEM）教学和研究能力。扩大这些机构的STEM课程，为学生提供在STEM领域追求具有挑战性、回报丰厚的职业的机会，为可能具有文化意义的领域提供研究，并鼓励社区和世代对科学和数学教育的欣赏。该项目与这一目标直接一致，而且旨在通过开发创新课程和基于服务的体验式学习来提高区域数据科学能力，为注重主动和协作学习的科学和工程教育提供环境。本项目旨在结合传统生态知识，构建环境数据科学STEM教育模式，解决复杂的环境科学与工程问题。Tȟokátakiya（“走向未来”）项目旨在加强奥格拉拉科塔学院的环境数据科学教育和本科生研究。研究重点是推进地下水和地表水在该地区流动的理解提供了教师和学生的研究经验和社区参与的基础。利用先进的传感工具，如机载和无人机获取的激光雷达和多光谱图像，该项目旨在表征和理解复杂水文系统中结构特征的几何形状、规模和影响。课程设计围绕这些主题，并建立在拉科塔方式的认识，旨在培养未来的领导者在数据科学领域。核心能力将在环境科学和工程预科学位课程中建立。社区规划强调粮食主权，含水层健康，并为区域STEM劳动力开发自定进度的GIS证书课程。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。

A goal of the Tribal Colleges and Universities Program (TCUP) is to increase the science, technology, engineering, and mathematics (STEM) instructional and research capacities of specific institutions of higher education that serve the Nation's indigenous students. Expanding the STEM curricular offerings at these institutions expands the opportunities for their students to pursue challenging, rewarding careers in STEM fields, provides for research studies in areas that may be culturally significant, and encourages a community and generational appreciation for science and mathematics education. This project aligns directly with that goal, and moreover seeks to increase the regional capacity for data science through the development of innovative curriculum and service-based experiential learning, providing context for science and engineering education that is focused on active and collaborative learning. The project aims to build an environmental data science STEM education model through the incorporation of Traditional Ecological Knowledge to address complex environmental science and engineering questions.The Tȟokátakiya (“towards the future”) project aims to strengthen environmental data science education and undergraduate research at Oglala Lakota College. A research focus on advancing understanding of groundwater and surface water flow in the region provides a basis for faculty and student research experiences and community engagement. Using advanced sensing tools, such as airborne and drone-acquired LiDAR and multispectral imagery, the project aims to characterize and understand the geometry, scale, and effects of structural features in complex hydrologic systems. Curriculum designed around these themes and founded on Lakota Ways of Knowing aims to train future leaders in the field of data science. Core competencies will be built in courses in Environmental Science and Pre-engineering degree programs. Community programming emphasizes food sovereignty, aquifer health, and developing a self-paced GIS Certificate program for the regional STEM workforce.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.