Chenlin Gu

The digitalization of teaching resources is the core link in the digital transformation of education, as well as the material foundation for the effective implementation of curriculum reform in industry-education integration. Nevertheless, current industry-education integration courses in universities are generally confronted with prominent problems such as severe lag in the development of teaching resources, difficulty in introducing high-quality industrial resources, and obstacles in generating personalized resources. From the perspective of AI empowerment, this paper systematically analyzes the bottlenecks of traditional teaching resource development methods, and proposes a digital development path for teaching resources driven by AI technology, namely precision collection — intelligent processing — dynamic generation — personalized recommendation. This paper focuses on exploring methods for intelligent capture and transformation of industrial resources, structured decomposition of scientific research achievement resources, personalized generation of interactive learning resources, and construction of intelligent resource labeling and recommendation systems. It aims to provide theoretical guidance and practical strategies for universities to efficiently and high-quality develop industry-education integrated teaching resources by leveraging AI technology.

Artificial Intelligence; Industry-Education Integration; Teaching Resources; Digital Development; Resource Generation

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