2025 ASEE Annual Conference & Exposition

Background: The rapid development and widespread adoption of AI have led to a global increase in demand for AI talents, particularly those with multidisciplinary skills and AI literacy. As a result, students across various disciplines are increasingly seeking to enhance their AI literacy within higher education. Nevertheless, universities worldwide are still in the exploratory phase of AI literacy education, encountering challenges such as discrepancies in students' AI proficiency, diversity in learning objectives, and difficulties in integrating multidisciplinary resources. Designing curricula that effectively foster AI literacy among students from multiple disciplines has become a significant challenge in engineering education.
Purpose: This study investigates a series of general AI courses offered by a leading comprehensive university in China. Through an analysis of the courses' design, implementation, and feedback, we identify practical strategies for promoting AI literacy among students from multiple disciplines in comprehensive universities.
Method: This study employs an exploratory single-case study approach. Drawing on seven documents sourced from internal channels and official websites, we illustrate the entire process of curriculum design and implementation. Additionally, data were gathered from 246 questionnaires and five semi-structured interviews with curriculum designers, teaching team managers, instructors, and students, providing authentic, reliable, and comprehensive feedback on curriculum outcomes.
Results: This case presents a distinct curriculum design for cultivating AI literacy, comprising a series of three courses. Its key features can be summarized as "hierarchical content, classified objectives, centralized management." First, to address students' varying levels of AI proficiency, the courses are structured with graduated difficulty, particularly reflected in programming prerequisites and instructional content. Second, by targeting diverse learning objectives across multiple disciplines, the courses employ a range of teaching and assessment methods, including written assignments, projects, and competitions. Finally, through the integration of a multidisciplinary faculty team and a unified online AI platform, the curriculum consolidates the university's previously scattered resources and enables centralized management across the three courses.
Conclusion: This study makes two key contributions. First, it proposes a practical curricular design for cultivating AI literacy among multidisciplinary students, offering a potential solution to address the global shortage of AI talents. Second, by highlighting the distinctive features of curriculum design and implementation, this research contributes to the development of multidisciplinary general engineering courses.