Recently, the Digital Alliance for AI Experimental Teaching (Electronics and Information Category) was officially established at a launch ceremony held in Yinchuan, jointly initiated by the Higher Education Teaching Guidance Committee for Electronic Information Majors of the Ministry of Education and the Community for the "Digitalization of Experimental Teaching and Personalized Evaluation System." DNUI, as one of the founding units, received the inauguration plaque at the ceremony. The establishment of the alliance marks a new phase for experimental teaching in electronic information majors in China, deeply empowered by big data and artificial intelligence. It is committed to building a national-level digital hub platform for electronic information experimental teaching, tackling challenges in traditional methods including the difficulty in tracking student processes and lack of basis for personalized learning profiles. This significant moment was witnessed by four academicians, 23 members of the Electronic Information Teaching Guidance Committee, and over 400 leaders and key faculty members from electronic information-related schools of more than 200 universities.  

       The alliance brings together 70 universities and enterprises in a powerful collaboration. DNUI stands alongside South China University of Technology, Xidian University, Xiamen University, Beihang University, Harbin Institute of Technology, Dalian University of Technology, and Shenzhen Yixingbiao Technology Co., Ltd. The alliance will adhere to the philosophy of "co-creation, co-building, sharing, and co-growth," deeply exploring the process-based big data of experimental courses in electronic information majors (such as electrical and electronic engineering) and constructing a precise evaluation system covering the entire experimental cycle. Leveraging the alliance's open and collaborative innovation platform, member units will share experimental teaching data, forming a cross-institutional, large-scale database of experimental learning processes. Furthermore, the alliance will introduce advanced industry AI knowledge base models and knowledge graphs to enable in-depth analysis of learning behaviors and personalized content delivery.