Artificial Intelligence in Curriculum Decision-Making: A Human–AI Comparison of Core Knowledge Selection in Patent Law Education

Abstract

With the rapid development of generative artificial intelligence, its potential role in professional decision-making and curriculum design has attracted increasing scholarly attention in higher education. In specialized courses such as intellectual property and patent law for design students, instructors must select core knowledge from intricate legal frameworks based on teaching objectives, professional relevance, and students’ learning needs. This process involves professional judgment that is often rooted in instructors’ accumulated experience and tacit knowledge, and is therefore difficult to standardize or replicate. This study investigates whether artificial intelligence can effectively participate in professional knowledge selection and instructional decision-making in specialized education. Using all 159 articles of the current Patent Act of the Republic of China as the shared evaluation framework, this study adopts a human–AI comparative research design. Artificial intelligence and an experienced instructor teaching intellectual property courses in a design department independently selected core legal provisions under the same teaching scenario. The overlap and differences between their selections were then systematically examined. The results reveal a notable degree of convergence between artificial intelligence and the human instructor in provisions related to ownership of service inventions and designs, definitions of inventions and designs, novelty requirements, and core regulations of design patents. However, marked divergences emerge in the emphasis on on procedural and institutional provisions. Artificial intelligence tended to focus on provisions related to design protection, novelty risks, and scope of patent rights, whereas the human instructor placed greater emphasis on the systemic coherence of the patent framework and its underlying procedural architecture. Overall, the findings underscore that artificial intelligence demonstrates considerable potential in supporting professional judgment and curriculum decision-making, particularly in identifying core knowledge related to practical risks and application strategies. In the era of digital content, virtual products, and Metaverse creation, where intellectual property issues are becoming increasingly complex, artificial intelligence may serve as a valuable decision-support tool for curriculum design and teaching content planning. Nevertheless, instructors’ institutional understanding and teaching experience remain indispensable to the effective integration of artificial intelligence into specialized education.