2024 ASEE Annual Conference & Exposition

Background: Accompanied by the breakthrough progress of AI technology and its wide application in various industries, the worldwide demand for AI talents is growing explosively, and more and more non-AI majors are eager to learn the basic knowledge and application skills of AI. However, worldwide research and practice of AI education are still in the exploratory stage and face the reality of shortage and dispersion of AI educational resources. How to design AI interdisciplinary program is an urgent problem in the field of engineering education.
Purpose: This study took an ongoing and successful AI interdisciplinary certification program as research object, and deconstructed the whole process of the program’ s design, implementation, and operation from three dimensions of vision, teaching, and support to summarize its successful experience in the AI talents cultivation and interdisciplinary education.
Method: Adopting an exploratory case study methodology, we conducted semi-structured interviews with 5 instructors and professors involved in this program, and collected 10 documented materials about the program from internal channels, official websites, and mainstream media to ensure the authenticity, richness, and completeness of the qualitative data.
Results: This program reflects an embedded interdisciplinary educational program design scheme. On the one hand, the program satisfies the personalized learning needs of interdisciplinary students by designing a modular curriculum structure. On the other hand, open teaching platform plays an important role in supporting program operation, which solves the problem of dispersed interdisciplinary educational resources and effectively integrates AI educational resources from different disciplines and subjects.
Conclusion: This study has two main contributions. Firstly, we provided a reference instructional design scheme for AI educational program, which fills the current shortage of research in AI education. Secondly, the research results also contribute to the field of interdisciplinary engineering education by providing empirical experience for embedded interdisciplinary educational program design.