To enhance the interactivity of IoT communication teaching, this paper utilizes data mining and swarm intelligence algorithms to establish an interactive teaching platform, aiming to extract valuable information from large-scale behavioral data during the teaching process. Strategies for improving teaching interactivity are proposed from technical, adult student, and school perspectives. Taking a group of students from a certain university as the research object, the empirical results show that the distribution of interaction indices for students at the university follows an “L” shape. Most teachers and students have interaction indices below 20, with a small portion ranging from 40 to 60. After applying the interactive teaching platform, there was a significant difference in performance between Class A and Class B at the 0.05 level.
