Catalyst DataWISE: Data Science Workforce Initiative for Skills and Education

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.