The NC State All-campus Data Science and AI Project-based Teaching and Learning (ADAPT) Model: A mechanism for interdisciplinary engagement in workforce-relevant learning

TL;DR

The paper presents the ADAPT model at NC State University, a cross-disciplinary initiative designed to enhance data science and AI education, research, and engagement across all university departments.

Contribution

It introduces a novel interdisciplinary Academy structure that bridges departments and colleges to foster collaborative data science and AI efforts.

Findings

Established a university-wide interdisciplinary framework.

Facilitated collaboration across diverse academic units.

Enhanced engagement in data science and AI initiatives.

Abstract

Academic institutions have been challenged to adapt as data science and AI have rapidly evolved into disciplines, degrees and careers. Efforts to provide students with learning experiences have led to the development of novel credentials, renamed departments, new schools and even additional colleges within universities. Generally, these approaches are siloed in some way, perhaps separating STEM students from those in the humanities or separating faculty assigned to these courses from their colleagues in their home departments. NC State University decided to take a novel approach by creating a new type of entity called an Academy that would reach across all disciplines, departments, colleges, centers and institutes to catalyze work in data science and AI in all points of the university's mission: teaching, research and engagement.