Construction of a Big Data-based Student Performance Assessment and Personalised Instruction System in Physical Education Teaching

Since the early 20th century, personalised teaching has been carried out in the United States and other western countries, and has made great progress, and its importance and effects have been recognised by countries all over the world. However, in China, the application of personalised education is mostly focused on the reform of teaching system and specific courses, but not much in the university student work. Student work plays an important role in university student management. In this paper, we use big data technology to track and analyse students' learning behaviours and performance, and combine it with personalised algorithms to tailor learning programmes and guidance suggestions to suit each student’s needs. Through the real-time feedback and adjustment of the system, students' learning motivation and performance are enhanced. The system provides an innovative way of assessment and guidance for physical education, and is expected to play an important role in improving teaching efficiency and personalised education. The experiment proved that the average value of push-ups in the experimental group was five higher relative to the control group, and the collaborative filtering model can contribute to the teaching of physical education and can improve students' physical skills.