A specialized training program focused on "Artificial Intelligence + Education" technology applications for agricultural universities was recently held at Nanjing Agricultural University. More than 60 experts and participants from agricultural colleges, agricultural and rural departments, and related enterprises nationwide gathered to engage in in-depth discussions on cutting-edge AI technologies, digital empowerment in education, and agricultural modernization practices.
Liu Yuqiang, Vice President of Nanjing Agricultural University, stressed that all participants should focus on strengthening the agricultural nation-building goal, integrate AI technology with their teaching and research, and convert short-term training into long-term collaboration. Zhang Shaogang, the Supervisor of the China Educational Technology Association, highlighted that AI is advancing from general to specialized applications, from single-modal to multi-modal capabilities, and from passive response to proactive service. He suggested strengthening human-machine collaborative instructional design and building a smart education ecosystem tailored to agricultural disciplines.
During the keynote report session, Zhang Shaogang presented a lecture titled "Educational Digital Humans - Opening a New Gateway to Smart Education," explaining the value of AI digital humans in breaking down spatial and temporal limitations of quality resources and promoting personalized learning. Professor Jin Ying from Nanjing University analyzed the reconstruction of human social value systems and its deep impact on education. Liu Tao from Sichuan Agricultural University shared systematic approaches to empowering high-quality education development with AI. Professor Wang Dongbo from Nanjing Agricultural University delivered insights on vertical domain large language models, including practical experience with agricultural models like "Sinong" and "Lvdun."
The three-day training combined theoretical instruction, case analysis, and hands-on practice. The Information Construction Center and Professor Wang Dongbo's team at Nanjing Agricultural University provided systematic instruction on core modules including fundamental principles of large language models, vertical domain model construction, prompt engineering, RAG technology, and AI agent development. An accompanying certification examination on "AI + Education" professional competencies was also organized.
Researcher Ye Zemin, a participant from King Abdullah University of Science and Technology in Saudi Arabia, noted that the training deepened his understanding of the technical pathways for AI-empowered agricultural education. He found the application practices of Nanjing Agricultural University's "Sinong" large model particularly useful as a reference for his ongoing research in agricultural artificial intelligence.
Wang Dongbo, Deputy Director of the Information Construction Center at Nanjing Agricultural University, stated that the university will continue to expand the integration of artificial intelligence in teaching, research, institutional governance, and agricultural industry development. The goal is to cultivate replicable and scalable "AI + agricultural education" application outcomes that provide strong support for the digital transformation of agricultural education and agricultural modernization.