Digital Transition Framework for Higher Education in AI-Assisted Engineering Teaching

【Author】 Zhang, Yin; Zhang, Menglong; Wu, Liming; Li, Jin

【Source】SCIENCE & EDUCATION

【影响因子】2.921

【Abstract】Rapid advancements in the information age have prompted significant digitalization in global higher education, with Chinese higher education particularly adapting to the influence of artificial intelligence. This study focuses on the digital transformation in China's higher education, specifically within AI-assisted engineering education. It examines the digitalization of classrooms, expansion of teaching elements, and redesign of educational dynamics, while highlighting digital innovations in teaching methodologies and the integration of AI systems. Using the Engineering Cost Estimation as a case study, the paper showcases the practical application of AI in engineering education in China. The findings reveal the interplay between external societal, economic, political, and technological factors and internal academic aspects like curriculum quality. The study addresses the digital divide, advocates for equitable technology access, and emphasizes digital literacy as crucial in the twenty-first century. It predicts significant structural changes in universities, proposing borderless educational environments and flexible, interdisciplinary approaches, alongside a blockchain-based credit system.

【Keywords】

【发表时间】2024 2024 OCT 19

【收录时间】2024-10-28

【文献类型】案例研究

【主题类别】

区块链应用-实体经济-教育领域