Abstract
The rapid development of Artificial Intelligence (AI) is transforming traditional educational models, gradually shifting from 'human-to-human' to 'human-machine collaboration' (HMC). Human-Machine Collaboration (HMC) is gradually becoming an important paradigm in the field of education, especially in foreign language teaching. This paper explores the application of human-machine collaboration in foreign language teaching, focusing on its theoretical foundations, practical cases, advantages, and challenges. Based on Cognitive Load Theory, Constructivist Learning Theory, and Personalized Learning Theory, this paper analyzes how human-machine collaboration can optimize teaching efficiency and enhance personalized learning experiences. Through case studies such as AI language platforms and real-time translation technolo-gies, this paper demonstrates the potential of human-machine collaboration in providing immediate feedback, customizing learning paths, and fostering inter-cultural communication competence. However, the paper also points out the challenges posed by over-reliance on technology, the weakening of critical thinking, and issues related to data privacy. Finally, this paper looks forward to future development directions, emphasizing the transformation of teachers' roles and the necessity of a balanced combination of artificial intelligence and human wisdom to promote comprehensive innovation in foreign language teaching.
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How to cite this paper
Theories and Practices of Human-Machine Collaboration Model in English Language Teaching: Advantages, Challenges, and Future Development
How to cite this paper: Zhiqin Wang. (2025). Theories and Practices of Human-Machine Collaboration Model in English Language Teaching: Advantages, Challenges, and Future Development. The Educational Review, USA, 9(1), 92-97.
DOI: http://dx.doi.org/10.26855/er.2025.01.013