Teaching AI competencies: Experiences from coaching interdisciplinary teams to develop AI prototypes

Artificial Intelligence (AI) is changing and revolutionizing today’s economy and work life. A basic understanding of this technology is beneficial for even non-technical roles, highlighting the interdisciplinary nature of AI and its diverse applications. However, it is difficult to create significant, practically relevant learning experiences related to AI for students of different backgrounds, especially for students outside of computer science programs. To tackle this problem, we designed and evaluated an interdisciplinary, project-based course combined with creativity methods, where students from diverse study programs worked on an everyday challenge and tried to build AI prototypes to address it. The interdisciplinary nature of the course enabled students from diverse disciplines to collaborate and learn from one another. The course focused on project-based learning, providing students with hands-on experience in AI product design and implementation. It also incorporated teamwork and collaboration activities that enabled students to gain a better understanding of AI jointly. The course has been conducted and evaluated across two consecutive editions, involving a total of 32 students, providing a robust basis for the analysis presented in this study. Overall, the student feedback was favorable, indicating an enhanced sense of confidence in their AI abilities. We provide evidence that a project-based, interdisciplinary AI course incorporating creative methods can be an effective approach for students from diverse academic backgrounds to expand their knowledge and gain a more nuanced grasp of AI technologies. • A reusable university course design to teach AI and programming competencies • Encouraging students to apply creativity and innovation methods during project work • Fostering student collaboration, communication, and effective teamwork • Lessons learned and takeaways to support other AI educators