Research on Auxiliary Devices for English Teaching under Intelligent Internet of Things

Abstract

The advancement of Internet technology is promptly entering English classes, which fundamentally modifies the mode of English teaching. Internet of Things (IoT) is a better-linked and collaborative future for English education. The proliferation of smartphones and the Internet of Things (IoT) has made it easier for educational institutions to boost campus security, monitor vital resources, and broaden students' access to knowledge. Auxiliary devices and IoT devices give learners better access to everything from learning material to communication channels, and they give educators the capability to measure pupil learning process in real time. The response time is long in conventional English education, with low student satisfaction. Hence, in this study, the Internet of Things-assisted English Education Auxiliary Teaching Model (IoT-EEATM) has been proposed to increase teacher-student satisfaction. This study focuses on the education field, where the IoT can be utilized to create more important learning spaces using the Electronic Learning platform. This research suggests a system that allows learners to interact with surrounding physical objects virtually connected with a learning subject. An algorithm optimization technique is proposed, and data transformation technology is used to increase real-time teaching and management efficiency. The particle swarm optimization (PSO) algorithm further enhances the students' speculative abilities in English education. The authenticity and effectiveness of the particle swarm optimization method in the English teaching model are validated. The experimental results show that the proposed IoT-EEATM model improves student learning outcomes by 97.8%, satisfaction ratio by 96.4%, student-teacher interaction ratio by 98.8%, and participation ratio by 95.5%, reducing the execution time by 9.8% compared to other popular models.