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The discussion revolves around the application and impact of artificial intelligence technology, particularly large language models like ChatGPT, in foreign language education. Scholars believe these tools can enhance students' language skills and play multifaceted roles in teaching and research. Feng Qinghua and Zhang Kaiyi analyzed the capabilities of ChatGPT-4 and Wenxin Large Model 4.0 based on language service competence and proposed teaching strategies. Wen Qiufang introduced a new curriculum model incorporating AI, emphasizing its role in teaching and material development. Some researchers have explored the application of AIGC (AI-generated content) in English writing instruction through empirical studies, examining its effects on students and teachers. This study aims to investigate how tools like ChatGPT can improve the quality of college English teaching and student experiences through teaching practices, employing qualitative and quantitative methods to evaluate teaching effectiveness and student experiences.

1. Research Design

This section introduces an empirical study on the impact of generative AI (AIGC) tools on Chinese university students' English learning. The research focuses on the influence of tools like ChatGPT on learning outcomes and experiences, as well as the challenges of applying AIGC in college English instruction. The study involved 34 first-year students with prior experience using AIGC tools. The methodology included training sessions on tool usage, designing project-based tasks aligned with course materials, and collecting data via questionnaires and interviews at the end of the semester. The questionnaire employed a Likert five-point scale to assess learning experiences, while interviews provided deeper insights into AIGC's impact and challenges. Data analysis involved descriptive statistics using SPSS, with qualitative data examined through coding and thematic analysis to explore the effects and challenges of AIGC-enhanced English learning.

2. Research Findings and Analysis

Interview data revealed students' perceptions of AIGC's role in enhancing college English learning. Students generally found AIGC highly effective for writing and vocabulary acquisition but less impactful for listening and reading. Tools like ChatGPT were praised for inspiring writing ideas, providing instant feedback, and offering authentic expressions, though concerns were raised about over-reliance on AI-generated content and diminished critical thinking. As an instant dictionary, AIGC expanded students' vocabulary and depth of understanding, yet issues like metacognitive awareness and insufficient absorption persisted. In translation learning, AIGC improved speed and quality, but students lacked familiarity with translation techniques. While AIGC provided targeted grammar feedback, its effectiveness in speaking and listening remained limited due to the absence of direct human-machine interaction and operational inconveniences.

Students rated AIGC tools highly for usefulness, ease of use, and satisfaction, but perceived learnability as moderate to low. They acknowledged the tools' problem-solving capabilities and intuitive interfaces but found advanced applications challenging. Despite difficulties, students maintained a generally positive attitude toward AIGC tools.

Challenges in AIGC-enhanced English learning included risks of technological dependence, insufficient knowledge and skill transferability, and weak human-machine interaction negotiation skills. Students relied heavily on AIGC for solutions, reducing independent exploration; AI-generated information was fragmented and hard to apply; and students needed improvement in questioning, information processing, and strategic adaptation. These limitations hindered deep learning and comprehensive English proficiency development.

3. Research Discussion

This section examines the innovative potential and practical value of AIGC tools in college English teaching, particularly in improving writing and vocabulary. AIGC tools exhibit teacher-like functions in personalized learning and instant feedback, but their application in speaking, listening, and deep reading skills requires further exploration. Students' positive attitudes stem from AIGC's multimodal features and real-time responsiveness. However, challenges persist in human-machine interaction, partly due to AI's technical constraints and the adaptation from traditional to AI-enhanced learning models. Students' learning strategies, cognitive approaches, and digital literacy levels also limit the full realization of AIGC's pedagogical value.

4. Conclusion

This section summarizes AIGC's impact on Chinese university students' English learning, highlighting its significant role in writing and vocabulary while acknowledging existing issues. The authors recommend emphasizing teachers' roles in AIGC-enhanced learning, developing blended teaching models, and designing task-based activities to strengthen speaking and listening skills. Additionally, they propose courses on AIGC tool usage to cultivate digital literacy and human-machine interaction skills. Finally, they advocate for institutional mechanisms to support AIGC-integrated education, including quality assurance systems, teacher training, and sharing of exemplary teaching cases, ensuring systematic implementation in language education.

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