An Application of English Reading Mobile Teaching Model Based on K-Means Algorithm

Abstract

The rapid development and maturity of emerging technologies such as mobile Internet and artificial intelligence have had a subversive impact on all aspects of teaching, and mobile learning has become the normal learning of students. Educational technology has developed from traditional technology and ordinary media technology to multimedia information network technology. Personal computers and wired networks have been more and more widely used. Wireless communication technology and mobile Internet technology of mobile computing devices will be popularized, and the trend from digital learning to mobility will be more and more obvious. This study uses the k-means algorithm to analyze the English reading performance, finds out the factors affecting the test performance, provides guidance for improving the pass rate of CET-4, and focuses on the rise of mobile learning under this background and its specific application in English teaching. The experimental results show that 39 students (55%) believe that mobile reading learning provides rich and real reading materials, can obtain real and authentic language input, and increase their interest in English reading. 31 students (44%) believed that the learning model was helpful to enhance autonomous learning ability. Therefore, one of the biggest advantages of this clustering algorithm is that it has high scalability and efficiency in the processing of large data sets. The mobile teaching model of English reading based on the k-means algorithm can more effectively promote the interaction of English reading teaching and improve students’ English text reading comprehension ability than the traditional teaching model. In addition, it can promote students’ active learning and cultivate students’ awareness of autonomous learning and cooperation.