Performance evaluation of political teaching MOOC system based on task scheduling and AI system

Abstract

Abstract In the network control system, due to the limitation of network bandwidth and control system conditions, the information transmission of sampling and control must be completed in a certain time, otherwise it will cause information transmission delay, thus reducing the control performance of the network system. This paper builds a MOOC political teaching platform based on task scheduling and artificial intelligence system, and the use of MOOC ideological and political education model can improve students' participation and practicability. Under the MOOC model, students should be able to learn by participating in online video courses, skillfully applying theoretical knowledge of ideological and political education, and then by participating in physical classroom discussions. The simulation results show that the system can realize real-time data transmission, and the information transmission of sampling and control must be completed in a certain time, otherwise it will cause information transmission delay, thus reducing the control performance of the network system. Due to the limitation of network bandwidth, if multiple control systems work together, there will be transmission delays and other situations, which will directly affect the control performance of the system and cause system instability.