北卡罗来纳州立大学全方位数据科学和人工智能项目式教学与学习（ADAPT）模型：促进跨学科参与的职场相关学习机制
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
AI总结：
北卡罗来纳州立大学提出ADAPT模型，通过跨学科整合推动数据科学和人工智能在教学、研究和参与方面的应用，打破传统学科壁垒。
摘要：
学术机构面临数据科学和人工智能迅速发展为学科、学位和职业的挑战。为提供学习体验，出现了新型证书、重命名的部门、新学院甚至额外学院。通常这些方法在某些方面是孤立的，可能将STEM学生与人文学生分开，或使教授与同事分开。北卡罗来纳州立大学决定采取新方法，创建名为学院的新实体，跨越所有学科、部门、学院、中心和研究所，推动数据科学和人工智能在大学使命的各个方面发挥作用：教学、研究和参与。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
