A SYSTEMATIC REVIEW OF AI IN CHINESE COLLEGE ENGLISH EDUCATION BEFORE GENERATIVE AI: TYPES, ROLES, AND FUNCTIONS - Sun, Kun; Chew, Fong Peng; Lau, Su Kia (Jurnal Gramatika, 2025)
The impact of artificial intelligence (AI) on language learning has grown rapidly, with various AI-based tools emerging. However, comprehensive reviews of its role in College English education in China remain scarce. Following PRISMA guidelines, this study systematically reviewed peer-reviewed empirical articles published between August 2013 and August 2023 across nine databases, including CNKI. Of the 1,224 screened studies, 15 empirical works from China (two in Chinese) were included, and a comparative analysis was conducted on the types of AI applied and their relevance to College English teaching. The findings indicate a generally positive attitude toward AI integration in College English, with particular emphasis on AI assessment systems and visual technologies. However, the review also identifies a techno-instrumentalist bias, with AI primarily framed as a tool for performance enhancement, while its implications for learner agency and identity construction remain underexamined. This review summarizes the decade's research trends, revealing that studies predominantly used quantitative and experimental methods, while qualitative research and mixed-methods studies were relatively scarce. Notably, research between 2019 and 2023 surged around immersive and automated systems, raising questions about which types of AI attract academic and institutional focus. Future research should diversify methodologies and address sociocultural, ethical, and equity issues in AI use. Though generative AI is emerging, its accessibility and ease of use mark a shift from resource-intensive tools like VR. Yet, its growing adoption requires critical inquiry into whose knowledge it privileges and what ideologies it reinforces in English education.