Construction of Personalized Learning Platform Based on Intelligent Algorithm in the Context of Industry Education Integration

Abstract

In order to meet the personalized needs of different students and provide students with a variety of intelligent learning strategies and learning content, this research is aimed at the current lack of intelligent function design in the network teaching platform of colleges and universities. Based on the concept of integration of production and education, with the help of intelligent recommendation algorithm of reinforcement learning, a personalized learning platform based on intelligent algorithm is constructed. First, through the method of questionnaire survey to understand the students’ needs for personalized learning and the functions of online teaching platform, on this basis, build a personalized learning platform based on reinforcement learning and data mining intelligent algorithm. The system test results show that when the number of accesses is less than 2000, the CPU and memory resources of the system basically remain unchanged. When the number of accesses is less than 3000, the CPU utilization rate reaches 70%, and the performance decreases, but it can also ensure normal operation.