This study focuses on the application of large language models(LLMs)in key areas of L2 teaching,including grammatical error correction,language translation,AI-assisted writing and scoring,and AI-assisted spoken language learning and assessment.By comparing the performance of LLMs with specialized AI systems in specific L2 teaching scenarios,the study explores the prospects of LLMs application and its impact on the effectiveness of L2 learning.It highlights the strengths of LLMs in providing real-time feedback,personalized learning experiences,and multi-language support,while also acknowledging their limitations,such as challenges in context understanding.The study aims to clarify the applicability and limitations of LLMs in L2 teaching,and provide useful reference for the selection and adoption of AI tools in L2 teaching and development of educational technology.
large language modellanguage intelligenceL2 teachingapplication efficacy
NETL
NSTL
万方数据
