Catalyst datawise: data science workforce initiative for skills and education

The National Science Foundation Division of Undergraduate Education awarded Tennessee State University $200,000 on August 15, 2026, under the STEM Education program (CFDA 47.076) to establish a data science workforce initiative at the historically black university.

Tennessee State University will develop a comprehensive data science educational and research ecosystem designed to prepare undergraduates for roles in the data economy. The initiative establishes a formal undergraduate data science concentration with theoretical and applied foundations, including senior capstone projects addressing industry-relevant problems. The program integrates three pillars: the undergraduate concentration emphasizing applied and theoretical rigor; a research-first culture that supports peer-reviewed publications and matriculation into thesis-based master's and Ph.D. programs in engineering and computational sciences; and an expanded collaborative network with regional industry partners including Google, Amazon, and Oracle, alongside interdisciplinary TSU partners in health sciences and agriculture.

The curriculum infuses state-of-the-art data science components—distributed machine learning, explainable artificial intelligence, and data engineering—into core coursework. The project investigates novel pedagogical frameworks such as adaptive learning platforms and flipped classrooms to optimize student readiness for complex workforce roles.

Place of performance is Nashville, Tennessee. The period of performance runs from August 15, 2026, through July 31, 2028. The award is classified as a Project Grant, a standard assistance type under NSF's STEM Education program supporting HBCU capacity-building in science and technology undergraduate education and research.

Abstract

Catalyst projects provide support for historically black colleges and universities to work towards establishing research capacity of faculty to strengthen science, technology, engineering, and mathematics undergraduate education and research. The goal of this project is to infuse state-of-the-art data science (DS) components - including distributed machine learning, explainable artificial intelligence, and data engineering - into the core curriculum, ensuring students are equipped to solve real-world technical challenges. The data science workforce initiative for skills and education (datawise) at tennessee state university (TSU) proposes to establish a high-impact, use-inspired educational and research ecosystem designed to accelerate the transition of students into the rapidly evolving global data economy. The project aims to accomplish this goal by investigating the effectiveness of novel pedagogical frameworks - such as adaptive learning platforms and flipped classrooms - to assess and optimize student readiness for complex roles in the workforce. The project will achieve this through three integrated pillars: first, by establishing a formal undergraduate DS concentration that emphasizes a theoretical and applied foundation, culminating in senior capstone projects that tackle industry-relevant problems; second, by immersing undergraduates in a ?research-first? Culture that yields peer-reviewed publications and motivates matriculation into TSU?s thesis-based master?s and PH.d. Programs in engineering and computational sciences; and third, by expanding a collaborative network that includes regional industry leaders like google, amazon, and oracle, alongside interdisciplinary TSU partners in health sciences and agriculture. Datawise activities have the potential to align academic rigor with the operational needs of the nashville community and the national workforce. The project has the potential to contribute to undergraduate stem education by demonstrating a model for integrating innovative training models into data science courses. The project is expected to improve student engagement, strengthen data science curriculum offerings, and provide a model for other institutions seeking to improve undergraduate science education and broaden participation in the science 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.