An English course practice evaluation system based on multi-source mobile information and IoT technology

Abstract

With the increased use of online English courses, the quality of the course directly determines its efficacy. Recently, various industries have continuously employed Internet of Things (IoT) technology, which has considerable scene adaptability. To better supervise the specific content of English courses, we discuss how to apply multi-source mobile Internet of Things information technology to the practical evaluation system of English courses to boost the performance of English learning evaluation. Therefore, by analyzing the problems of existing English course evaluation and the characteristics of multi-source mobile Internet of Things information technology, this article designs an English course practical evaluation system based on multi-source data collection, processing, and analysis. The system can collect real-time student voices, behavior, and other data through mobile devices. Then, analyze the data using cloud computing and data mining technology and provide real-time learning progress and feedback. We can demonstrate that the accuracy of the evaluation system can reach 80.23%, which can effectively improve the efficiency of English learning evaluation, provide a new method for English teaching evaluation, and further improve and optimize the English education teaching content to meet the needs of the actual teaching environment.

Keywords

• English course practice
• Evaluation system
• Mobile Internet of Things
• Self-attention
• K-means