Theories and Practices of Human-Machine Collaboration Model in English Language Teaching: Advantages, Challenges, and Future Development

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 becom-ing 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 hu-man-machine collaboration can optimize teaching efficiency and enhance person-alized learning experiences. Through case studies such as AI language platforms and real-time translation technologies, this paper demonstrates the potential of hu-man-machine collaboration in providing immediate feedback, customizing learn-ing paths, and fostering intercultural 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 transfor-mation of teachers' roles and the necessity of a balanced combination of artificial intelligence and human wisdom to promote comprehensive innovation in foreign language teaching.