Title: Foreign Language Teaching in the Era of Artificial Intelligence: Challenges and Solutions
Authors: Xiaoquan Pan, Huijuan Shao
Volume: 10
Issue: 2
Pages: 21-28
Publication Date: 2026/02/28
Abstract:
The deep integration of artificial intelligence technology is triggering a paradigm shift in foreign language education. Drawing on interdisciplinary perspectives from the philosophy of technology and the sociology of education, this study systematically analyzes the tri-dimensional transformation of foreign language teaching driven by artificial intelligence: the teaching agents transition from knowledge authorities to learning designers; instructional content evolves from a structural to an ecological paradigm; and the teaching environment leverages pervasive technologies to construct phygital (physical-digital) integrative spaces. Concurrently, the study reveals underlying predicaments of technological alienation: algorithmic dominance eroding pedagogical subjectivity, the intelligent divide exacerbating educational inequality, and instrumental rationality dissolving the humanistic value of language. To address these challenges, a novel educational ecosystem centered on "Human-Machine Co-symbiosis" is proposed. This involves a synergistic architecture encompassing an infrastructure layer, a driving layer, and a practice layer, coupled with innovative mechanisms featuring smart learning, collaborative intelligence empowerment, and dynamic assessment, thereby enhancing technical efficacy while safeguarding humanistic core values. The research emphasizes the educator's central role in fostering holistic development and advocates for constructing an ethical framework prioritizing algorithmic transparency and digital equity. This approach offers a transformative pathway for foreign language education in the intelligent era that balances technological adaptation with disciplinary integrity.