Intelligent IoT Devices and Data Analytics as a Guide to Enhancing the Effectiveness of English Language Teaching and Learning

With the wide application of Internet of Things (IoT) technology, Artificial Intelligence (AI), Big Data and other technologies in the field of school education, smart education has emerged. Based on the sensing technology and data processing technology of IoT devices, this paper constructs the general framework of the conceptual model of smart classrooms by combining the needs and design concepts of smart classroom sensing systems. The data set of student behavior in English classrooms is designed to analyze the degree of episodic learning behavior of learners through clustering. Then, the correlation analysis of the externally apparent learning behaviors and the implicit learning behaviors is carried out, the correlation value between the two is calculated, and the behavioral features are scored and ranked using the random forest algorithm. The experimental results show that the learning behaviors in the English classroom can be analyzed according to the data analysis algorithm in the smart classroom environment, and it is also found that the abnormal behavior in the classroom has a significant negative correlation with academic effectiveness (P=-0.398), and the degree of significance of this behavior reaches 0.142. This result validates the validity of the data analysis of learning behaviors, and also supports the implementation of personalized English teaching, with guiding significance.