In the era of rapid digital transformation, this study delves into the innovative integration of artificial intelligence (AI) within the curriculum framework of the History of Foreign Ancient Architecture. By systematically analyzing the structural inefficiencies in traditional pedagogical models—specifically in knowledge representation, experiential learning, and cross-cultural value transmission—the research constructs a theoretically robust framework for AI-mediated curriculum reform. Drawing on interdisciplinary insights from cognitive neuroscience, educational technology, and architectural semiotics, the study explores how AI-driven tools such as knowledge graph systems, mixed-reality simulations, and adaptive learning algorithms address long-standing educational challenges. Empirical evidence from multi-year teaching experiments is integrated to demonstrate how these technologies bridge the gap between theoretical knowledge and practical application, fostering a new generation of architectural professionals with enhanced historical awareness, technical acumen, and cultural sensitivity. The proposed strategies, including faculty capacity building and cross-disciplinary resource integration, offer both theoretical contributions and actionable guidelines for modernizing architectural history education in the digital age.

Suliu Chen. Research on AI-Enabled Curriculum Development for the History of Foreign Ancient Architecture. International Journal of New Developments in Education (2025), Vol. 7, Issue 6: 36-42. https://doi.org/10.25236/IJNDE.2025.070605.

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