Task-based language teaching (TBLT) has transformed college English instruction by emphasizing active student participation and meaningful communication. This study examines how integrating AI-driven applications within the TBLT framework can enhance English proficiency and student engagement. AI tools were used to provide personalized learning pathways and real-time feedback, allowing for adaptive pre-class learning and more interactive in-class activities. Findings reveal that AI integration enhances learner autonomy, engagement, and overall language proficiency, particularly in speaking and reading skills. This research contributes practical strategies for incorporating AI in language education, offering insights for creating a more personalized and effective learning environment.

Xiaojing Huang, Yanyan Wu, Anqi Dou. AI-Enhanced Task-Based Language Teaching: Fostering Personalized College English Learning. Frontiers in Educational Research (2024) Vol. 7, Issue 10: 204-209. https://doi.org/10.25236/FER.2024.071033.

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