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

2026-04-02

AI Summary

This work addresses the persistent challenges of disciplinary fragmentation and institutional silos in traditional universities, which hinder effective interdisciplinary and industry-oriented education in data science and artificial intelligence. To overcome these barriers, the project innovatively establishes a university-wide “Academy” mechanism that bridges STEM and humanities/social sciences. By implementing project-based learning (PBL), it integrates multidisciplinary resources into a unified, cross-departmental teaching and experiential platform. This model achieves dual alignment—both in faculty affiliation and curriculum design—thereby systematically fostering deep integration of data science and AI across teaching, research, and societal engagement. As a result, students’ capacity to tackle real-world industrial challenges is significantly enhanced.

Technology Category

Application Domains: Humanities & Computational Social ScienceHumans and AI: Teamwork, Team formationMachine Learning: Multimodal Learning

Application Category

Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactionsEconomics, Online Markets and Human Computation: Research challenges in human and human-AI computationWeb Mining and Content Analysis: Machine learning and data science for the Web

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.

Problem

• data science
• artificial intelligence
• interdisciplinary engagement
• workforce-relevant learning
• academic silos

Innovation

• interdisciplinary engagement
• project-based learning
• data science education
• AI workforce development
• university-wide academy