Intelligent Technology-Driven Hybrid English Classroom Model for Enhanced Personalization and Learning Efficiency

Traditional English teaching methods often rely on face-to-face classes, and lack flexibility and personalized support. It is not easy to improve students’ learning efficiency continuously. However, most of the current hybrid classroom teaching lacks interactivity, which leads to inadequate learning effects, needing more systematic design and personalized support for different students’ needs. This paper designs an English hybrid classroom teaching model based on intelligent technology, which provides customized learning support through intelligent technology and optimizes the teaching process. The study designed a personalized learning recommendation system to automatically push appropriate learning content and tasks based on students’ learning progress and interests. The study designed a personalized learning recommendation system based on a collaborative filtering algorithm. The system automatically pushes learning content and tasks that meet students’ needs by analyzing their learning behavior based on their historical learning data, learning progress and interests. The model uses naive Bayes classifiers and convolutional neural networks (CNN) to analyze students’ online interactions and classroom feedback and adjusts learning materials and teaching strategies in real time. In the online and offline classroom structure, integrating augmented reality (AR) and virtual classroom technology enhances classroom interactivity and encourages students’ active participation. Based on machine learning algorithms, the intelligent assessment system evaluates students’ learning status in real time, provides instant feedback and learning suggestions, and promotes students’ learning motivation and participation. The experimental results show that the experimental group (the teaching model in this paper) has made significant progress in listening, speaking and final test scores. The listening ability has improved by about 20.7%, the speaking ability has improved by about 21.3%, and the final test score has improved by about 18.8%. The control group of traditional teaching methods improved their grades, but the increase was less than 10%. Classroom participation analysis showed that the frequency of classroom speaking and participation in group discussions in the experimental group increased by 68% and 80.6%, respectively, significantly higher than the 16.7% and 18.8% of the control group. In the questionnaire survey on learning interest and satisfaction, the learning interest and satisfaction scores of the experimental group increased by 53.6% and 50%, respectively, compared with before the experiment, while the control group increased by only about 10%. In addition, teacher feedback shows that the introduction of intelligent technology can effectively improve teaching efficiency and personalized guidance capabilities, enhance students’ learning interest and classroom participation and improve overall teaching quality.