Research on the impact of AI chatbot-based learning on English learning engagement

To address the ongoing challenges in traditional English education, such as limited interactivity and declining learner motivation, this study integrates a series of perceptual technologies. These include Natural Language Processing (NLP) for real-time language comprehension, personalized recommendation algorithms for adaptive content delivery, and sentiment analysis for detecting learners' emotional states. Based on the integration of these technologies, we have developed an AI chatbot English learning system. This system adopts a modular architecture, which tightly integrates learning terminals, cloud-based service infrastructure, and educational software components through an AI-assisted mechanism. Based on the integration of these technologies, we have developed an AI chatbot English learning system adopting the architecture of \frontend ACT (Dedicated Interactive Terminal) + backend ACS (Cloud-Local Dual Backup Server)\. Compared with the existing traditional learning systems featuring \single terminal + basic server\, this architecture has achieved breakthroughs in \terminal specialization, computing cloudification, and dual data backup\. Meanwhile, through the in-depth synergy of NLP (Natural Language Processing), personalized recommendation, and sentiment analysis, it addresses the core pain points of existing systems, namely \single technology, delayed response, and lack of emotional engagement\. Finally, an experimental study was conducted over one semester, involving 215 undergraduate students from University A who had passed CET-4 (College English Test Band 4). The participants were divided into a control group and an experimental group. The experimental results show that the AI chatbot, by leveraging perceptual technologies to provide personalized and emotionally responsive learning experiences, can significantly enhance learners' engagement at the cognitive, behavioral, emotional, and social interaction levels. Additionally, it effectively stimulates students' interest in English learning and strengthens their enthusiasm and initiative. This system successfully resolves the interactivity and motivation issues in traditional English learning, providing practical evidence and directional references for the innovation of college English teaching models and the development of digital learning tools.