The development of new productive forces has promoted the reform of university physics courses. According to the “Basic Requirements for Teaching Physics Courses in Science and Engineering Universities” issued by the Ministry of Education in August 2023, which states that “professional connection refers to organizing targeted thematic modules for teaching in different professional directions”, we have set up two courses, “College Physics (Precision) Ⅰ” and “College Physics (Precision) Ⅱ”, respectively, for information and civil engineering students in our university. Based on the characteristics of these two major categories of disciplines, we have placed different emphases, communicated fully with the corresponding colleges, and established teaching content and cases that meet the talent training goals of the two major categories. At the same time, we focus on the integration of industry and education, actively visit enterprises, establish industry-university-research connections, fully understand the needs of enterprises and the status of enterprise automation, combined with university physics teaching, which can provide students with first-hand information on enterprise technological transformation, expand their horizons, and enhance their scientific and technological innovation spirit. All these measures can promote the development of new quality productive forces in the future while improving students' scientific literacy.

In the context of AI empowering education, the Physics Teaching and Research Office of Tongji University is also considering how to integrate AI into physics teaching. To this end, we conducted a school wide survey on the application of AI in students' physics learning in the first half of the year, and received a total of 2034 valid questionnaires. Based on the results of this survey, we have carried out targeted measures to integrate AI, such as establishing an AI Q&A intelligent agent, collaborating with the student union to strengthen the construction of Q&A video library on Bilibili, building a knowledge graph, digital lecture notes and question bank on a digital platform, and establishing a learning situation warning system based on Canvas system. Of course, the above measures are only using AI to optimize our teaching and evaluation methods, but we believe that it is more important to find physics knowledge points and application scenarios that can integrate AI. Therefore, we have given an example as inspiration.