Creating robust opportunities for student success through real-world, organized, and applied data science

Clark University received a $992,671 Project Grant from the National Science Foundation's Division of Undergraduate Education under the STEM Education program (CFDA 47.076), effective September 15, 2025 through August 31, 2028. The award funds the CROSSROADS (Creating Robust Opportunities for Student Success Through Real-World, Organized, and Applied Data Science) initiative, which establishes an interdisciplinary educational ecosystem designed to broaden data science literacy across the undergraduate student population while addressing the current gap in data science education for non-majors.

The project delivers three primary components: (1) Domain Exploration Modules that integrate data science concepts into diverse academic disciplines to enhance data literacy among general students and enrich existing data science major and minor programs; (2) a Data Science Studio functioning as a practicum system offering hands-on, experiential learning through student collaborations with community partners on real-world challenges; and (3) Data Science Collaborative Workshops that foster partnerships among educators, students, and community organizations to drive curriculum innovation. These coordinated efforts aim to create flexible pathways for students across all disciplines to develop essential data skills and recognize the connections between data science and their respective fields.

Abstract

Data science is a transformative field that has come to profoundly impact every aspect of society. As such, providing widespread data science education is essential for cultivating a skilled and engaged workforce while ensuring national competitiveness in this rapidly growing domain. Currently much of the focus in undergraduate education has been on creating courses and programs for majors and minors, yet this approach leaves a significant GAP: students outside data science programs often lack opportunities to develop essential data skills and fail to recognize valuable and innovative connections to data science. However, data literacy is critical for college students across all disciplines, enabling them to thrive in both their personal and professional lives. Therefore, connecting data science to diverse fields and real-world challenges while fostering collaborations with domain experts and community partners will inspire, prepare, and engage students with a data-driven world. The crossroads (creating robust opportunities for student success through real-world, organized, and applied data science) program is designed to create flexible pathways into, through, and beyond data science education for a broad spectrum of students while promoting engagement with real-world applications. This project aims to establish an interdisciplinary education ecosystem through three key components: (a) domain exploration modules that integrate data science into diverse disciplines to enhance data literacy among general students and enrich data science education for majors and minors; (b) data science studio, as the core of a practicum system that provides hands-on learning through student collaborations with community partners; and (c) data science collaborative workshops, fostering partnerships among educators, students, and community organizations to drive curriculum innovation and impactful community service. Additionally, the resources and findings developed by the project will be freely available online, enabling other institutions to adopt and adapt these creative approaches and thoughtfully designed materials to strengthen their curricula. Through these efforts, the project addresses critical gaps in data science education and provides a holistic model that promotes real-world learning opportunities for all students while contributing to the development of a competitive and skilled national workforce. This project is supported by the data science corps program, which supports data science education and training to build a strong national data science infrastructure and 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.- subawards are not planned for this award.