Thực trạng và giải pháp ứng dụng AI trong việc nâng cao kĩ năng khẩu ngữ cho sinh viên ngành Trung Quốc học tại Trường Đại học Khoa học - Đại học Thái Nguyên
Tóm tắt
The rapid development of artificial intelligence (AI) in higher education has opened up new opportunities for foreign language teaching, especially oral Chinese skills. This study was conducted to analyze the current state of oral language training among students at the University of Science - Thai Nguyen University and propose a system of appropriate and effective AI-based solutions. A survey of 120 students revealed that the majority of learners face difficulties with pronunciation and intonation, lack confidence in communication, and lack a real-world speaking practice environment. The study also proposes five groups of AI-based solutions: 1 - using speech recognition technology (ASR) to correct pronunciation and intonation; 2 - applying large language models (LLM) to simulate conversations and increase opportunities for communication practice; 3 - personalizing speaking practice paths based on error analysis for each student; 4 - integrating AI into classroom teaching activities to increase the effectiveness of support and feedback; 5. Develop an AI-based oral assessment system based on the HSKK standard. These solutions not only help overcome existing limitations but also open up a new approach to personalized Chinese oral skills training, enhancing practice and effectively utilizing technology.
Tài liệu tham khảo
Bùi Trọng Tài, Nguyễn Minh Tuấn (2024). Nghiên cứu ảnh hưởng của trí tuệ nhân tạo trong giáo dục tới hoạt động học tập của sinh viên. Tạp chí Giáo dục, 24(10), 6-11. https://tcgd.tapchigiaoduc.edu.vn/index.php/
tapchi/article/view/1863
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268.
Li, B., & Jeong, H. (2022). Automatic speech recognition feedback and L2 speaking performance: A meta-analysis. Language Learning & Technology, 26(3), 1-25.
Lin, C.-H., Gao, Y., & Zhang, K. (2023). AI-assisted language learning: A systematic review. Computers & Education, 205, 104850. https://doi.org/10.1016/j.compedu.2023.104850
Liu, M., & Jackson, J. (2021). Anxiety and participation in oral English classrooms: A systematic review. System, 96, 102426.
Nguyễn Thị Minh, Lê Quang Phúc (2023). Ứng dụng trí tuệ nhân tạo trong học ngoại ngữ ở sinh viên Việt Nam: Nhận thức và hành vi sử dụng. Tạp chí Khoa học Giáo dục Việt Nam, 22(4), 55-67.
Sun, Y., & Wang, X. (2024). ChatGPT in second language learning: Opportunities and challenges. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12172-0
Swain, M. (1985). Communicative competence: Some roles of comprehensible input and comprehensible output in its development. In S. Gass & C. Madden (Eds.), Input in Second Language Acquisition (pp. 235-253). Newbury House.
Wang, Y., & Xu, J. (2021). Intelligent speech evaluation in Mandarin L2 learning. ReCALL, 33(3), 234-251.
Zawacki-Richter, O., Victoria I. Marín, Melissa Bond & Franziska Gouverneur (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
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