The Application of Generative Artificial Intelligence in POA Guided Foreign language Teaching
- DOI
- 10.2991/978-2-38476-364-1_55How to use a DOI?
- Keywords
- Generative Artificial Intelligence; POA; classroom teaching; foreign language education
- Abstract
As a teaching method that absorbs the essence of Western second language teaching and is innovated and reformed by Chinese scholars, the Production-Oriented Approach (POA) has proved its effectiveness in improving the quality of English teaching. Generative Artificial Intelligence (Generative AI) technology is also developing rapidly. Teachers and scholars are applying it in the field of foreign language teaching which lead to the great potential for improving teaching efficiency and personalized learning in higher education. This study focuses on how to enhance the execution of POA through the introduction of Generative AI technology, aiming to create a richer, more interactive, and highly personalized learning environment for learners. By exploring the application of Generative AI in key teaching processes this paper demonstrates the process of Generative AI optimizing POA teaching, improving the quality of foreign language education, and promoting innovative and upgraded teaching methods.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yushuang Zhang AU - Miao Miao PY - 2025 DA - 2025/03/17 TI - The Application of Generative Artificial Intelligence in POA Guided Foreign language Teaching BT - Proceedings of the 2024 4th International Conference on Education, Language and Art (ICELA 2024) PB - Atlantis Press SP - 442 EP - 446 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-364-1_55 DO - 10.2991/978-2-38476-364-1_55 ID - Zhang2025 ER -