Artificial intelligence is profoundly reshaping the landscape of higher education talent cultivation. However, current university-level Fundamentals of Artificial Intelligence courses commonly suffer from content confined to technical principles, instruction detached from real-world application scenarios, and monolithic assessment methods, making it difficult to effectively cultivate students’ interdisciplinary innovation literacy. Drawing on constructivist learning theory and the frontiers of generative AI in education, and grounded in the curriculum reform practice at Alibaba Business School, Hangzhou Normal University, this paper proposes and constructs a new paradigm of “AI-empowered interdisciplinary integrated teaching”. Centered on the core idea of “teaching AI with AI”, the paradigm features a flexible “core module + cross-disciplinary application module” curriculum structure, systematically implements AI-enhanced interdisciplinary project-based learning, and establishes a multi-dimensional dynamic assessment system focused on “interdisciplinary innovation literacy”. Through a closed-loop pathway of “theoretical construction – curriculum redesign – teaching practice – assessment reform – iterative dissemination”, this paper details the practical outcomes, evaluation methods, and data analysis results, and draws conclusions and future research directions. It aims to provide an actionable and replicable solution for AI general education reform in higher education.
Liu et al. (Tue,) studied this question.
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