Exploring the role and impact of artificial intelligence in personalized foreign language teaching

With the rapid progress of information technology, Artificial Intelligence (AI) has permeated various aspects of education, particularly demonstrating immense potential in foreign language teaching. This work aims to investigate the application of AI technology in the personalized learning process of foreign languages and its impact on student learning outcomes. Through the study of a Long Short-Term Memory (LSTM)-based personalized recommendation system and a Transformer-based automatic scoring system, the work collects and analyzes data on student learning behaviors. The results indicate that after using the LSTM-based recommendation system, the average exercise completion rate of students increases by 8.5%, while accuracy improves by an average of 8%. The application of the Transformer-based automatic scoring system significantly reduces the time teachers spend grading assignments, saving an average of 38.5% of their weekly workload. Moreover, student satisfaction with instant feedback rises from 3.2 to 4.2 (out of 5). These findings contribute to the healthy development of AI technology in the field of education, ultimately achieving a deep integration of technology and education to enhance teaching quality and efficiency.