1 Introduction

Generative artificial intelligence technology, especially big language models, is profoundly influencing the field of foreign language education and becoming an important force driving educational reform. These technologies have improved the execution ability, knowledge production quality, and intelligent analysis and reasoning ability of language processing tasks through big data and algorithm innovation, and have had a revolutionary impact on language teaching.

2 Related research

Since the release of GPT-3.5, there has been an increasing discussion in the education sector about the impact of generative artificial intelligence. Foreign research focuses on the risks, application methods, and ethical norms of ChatGPT, while domestic research explores its effects on foreign language teaching practices, teaching models, teaching methods, as well as its impact on self-directed learning and teacher roles. Existing research mostly focuses on the macro level, with insufficient exploration of practical applications. This study takes "College Critical English Course - Intensive Reading" as an example to explore the application of the big language model in foreign language courses, analyze its impact on teaching content and organizational methods, and demonstrate its potential application value in teaching.

Teaching reconstruction supported by 3 LLMs

Large Language Models (LLMs) have demonstrated outstanding abilities in natural language processing tasks such as translation, writing, and syntactic semantic parsing in foreign language teaching, posing a challenge to traditional teaching models. The teaching content needs to be re evaluated to adapt to the changes under AI assistance, shifting the focus from basic information retrieval and shallow thinking problems to solving complex problems and cultivating critical thinking abilities. The teaching design of "College Speculative English Course · Intensive Reading" distinguishes the learning focus between in class and out of class, with a focus on basic vocabulary, grammar, and shallow thinking, while in class it focuses on training higher-order thinking and improving emotional and cognitive abilities.

Application of 4 LLMs in Teaching: Multi level Analysis of Emotions, Themes, and Narratives

Through the article "Grassland Sunrise" in "College Speculative English Course · Intensive Reading 2", this paper explores how to use Large Language Models (LLMs) to assist foreign language teaching, especially in emotional, thematic, and narrative analysis. The teacher guided students to use LLMs through pre class preview tasks, but found that students only utilized the basic question and answer function and did not delve deeply. Therefore, teachers guide students to explore more advanced applications in the classroom, such as sentiment analysis and narrative process analysis.

5 Conclusion

Generative artificial intelligence is profoundly influencing foreign language education, and teachers need to master the interaction with AI and integrate it into teaching, and develop teaching strategies. Teachers should guide students to use AI as a tool for creative intellectual activities, rather than an endpoint, and focus on cultivating students' autonomous language production ability. In the new environment supported by intelligent agents, foreign language teaching methods, content, and evaluation systems need to be reorganized to build a new paradigm of AI participation in teaching, in order to cultivate high-quality foreign language professionals.