In order to improve the effect of English teaching, this paper proposes a complex interactive collective behavior recognition method based on dynamic kernel density, which can more accurately identify classroom behavior patterns with complex interactions. Moreover, this paper proposes a dynamic crowd path planning method based on the emotional communication model. This method introduces the subjective factor of emotions in path planning, which can more realistically show the diversity of group path choices. At the same time, this paper combines the actual needs of English teaching to build a student status monitoring system based on group feature recognition, which can monitor the status of groups and individuals in real time. In addition, this paper introduces emotion algorithms to recognize student emotions, and combines action recognition to complete student state monitoring. Finally, this paper designs experiments to verify the performance of the system constructed in this paper. The research results show that the system constructed in this paper has certain effects and can provide theoretical reference for related research.