The development of artificial intelligence technology brings new opportunities for education management. This paper proposes a classroom management optimization method for foreign language teachers in colleges and universities based on AIGC technology, and constructs a multilevel decision model by improving Apriori algorithm. The system design contains six functional modules: teacher management, class creation, student information, course information, evaluation management and classroom assessment, and the improved association rule mining algorithm is used to extract the association relationship between classroom evaluation indicators. The experimental results show that under the parameter settings of minimum support 0.3, minimum confidence 0.5 and minimum interest 0.3, the improved algorithm extracts 12 strong association rules, which effectively suppresses the generation of misleading rules compared with the 24 rules of the traditional Apriori algorithm. Video analysis shows that the average number of abnormal behaviors per 20 seconds in the experimental class using the system is 4.15, which is lower than that of the control class, which is 5.13, and the classroom participation of students is significantly improved. The system provides an intelligent solution for foreign language classroom management in colleges and universities, which helps teachers accurately grasp students’ learning status and improve teaching quality.
