PKU Explorations in AI-Enhanced Teaching

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https://hdl.handle.net/20.500.14069/892

As artificial intelligence and technology rapidly advance, Peking University has been actively advancing digital innovation in higher education through systematic initiatives. Positioning itself at the forefront of educational digitalization, PKU faculties are leveraging AI and other advanced technologies to develop inquiry-based learning models that integrate intelligent systems into classroom settings while modernizing traditional pedagogies.

This collection showcases research papers documenting Peking University's explorations in AI-enhanced teaching. All reports adhere to academic ethics protocols, including anonymized data processing procedures.

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    Applications of artificial intelligence and new technologies in a computer-aided architectural drawing course
    (2025) Zhang, Jianwei
    Context: The study explores the integration of artificial intelligence (AI) and emerging technologies in the Computer-Aided Architectural Drawing course for undergraduate students specializing in architectural heritage at the School of Archaeology and Museology. Traditional methods, focused on software tools, have become outdated due to rapid technological advancements. The course reform addresses the need for updated teaching methods and content to better align with modern industry demands, particularly in heritage preservation and architectural archaeology. Aims: The primary aim is to enhance the teaching content and methods by incorporating AI and technologies such as VR (Virtual Reality), 3D printing, panoramic photography, and visualization tools. Specific goals include improving teaching efficiency, increasing student engagement, and connecting course content to practical applications in real-world projects, such as heritage protection and architectural design. Methods: The revised course design adds new components alongside traditional software training. Key technologies include Twinmotion for architectural visualization, VR for immersive learning, photography-based 3D modelling, panoramic photography, and Stable Diffusion for AI-generated graphics. Teaching combines lectures, hands-on practice, VR lab sessions, and practical applications like 3D printing. Hardware and software upgrades ensured compatibility with the new tools. Findings: The implementation showed significant improvements in teaching outcomes. Students developed practical skills in architectural visualization, 3D modelling, and AI-assisted drawing, applying their knowledge to real-life projects such as campus heritage preservation. Engagement levels increased, with some students investing in personal hardware for independent learning. The cross-application of technologies, such as VR and 3D printing, enriched students' understanding and interest in modern tools, fostering proactive exploration of new technologies. Implications: The study demonstrates that integrating AI and emerging technologies can transform technical courses, enhancing student engagement and aligning learning with practical applications. Teachers in similar fields might find value in incorporating interactive tools like VR and AI to create immersive and future-ready learning environments.