When AI does the thinking: The risks of over-reliance on artificial intelligence in higher education language learning

The integration of artificial intelligence (AI) in language education has introduced personalised learning experiences, adaptive feedback, and enhanced accessibility. However, alongside these benefits, concerns have emerged regarding cognitive harms associated with AI-assisted language learning. This paper examines how AI tools may contribute to cognitive offloading, reducing learners’ reliance on their own memory and analytical skills, ultimately leading to dependency. Furthermore, AI-driven instruction can encourage surface learning, where learners passively absorb content rather than engaging in deep processing and critical thinking. The structured nature of AI-mediated learning environments may also weaken adaptive learning skills, leaving students less prepared for real-world language use. By drawing on cognitive theories, empirical studies, and case study evidence, this paper explores these cognitive drawbacks and their implications for AI design and educational practice. To mitigate such effects, AI-based language learning platforms must be designed to promote active engagement, problem-solving, and independent thought. The findings highlight the need for a balanced approach in AI-assisted education, ensuring that AI serves as a tool to enhance rather than replace learners’ cognitive development.