Development of College English Teaching System based on Artificial Intelligence Algorithm

As traditional English teaching methods struggle to meet the diverse needs of modern learners, this study introduces an AI-Powered College English Teaching System that combines sentiment analysis, adaptive learning algorithms, and personalized feedback to revolutionize language education. While AI-driven systems offer remarkable efficiency and scalability, this paper also addresses critical challenges such as emotional disengagement, algorithmic bias, and the need for human-centred design. The system leverages DistilBERT for real-time sentiment detection, reinforcement learning for dynamic content adjustment, and multimodal analysis to tailor instruction to each student’s emotional and cognitive state. By integrating these approaches, the model achieves 93.5% accuracy, 94.1% recall, and a 93.4% F1-score, outperforming conventional teaching tools. Experimental results demonstrate that it not only identifies learning gaps with precision but also adapts feedback tone to boost confidence and reduce frustration. More than just a smart tutor, this system represents a paradigm shift in education—where technology doesn’t standardize learning but humanizes it, turning the classroom into a space of dynamic, emotionally intelligent instruction.