Exploring the Role of Generative AI in Enhancing Language Learning: Opportunities and Challenges

Abstract

Contemporary advances in generative AI technology have sparked considerable interest regarding its application in language education. This article explores the innovative impact that AI-powered linguistic educational tools may have, such as customised learning journeys, dynamic content, and individualised feedback mechanisms, which collectively have the potential to enhance language acquisition and literacy. At the same time, it is important to recognise the constraints associated with such technologies in the educational sphere. Concern about maintaining precision and genuineness within AI-crafted language texts is a concern in the literature. There is also caution about AI's current inclination to standardise language expression and to propagate limited cultural narratives, alongside the risks of over-reliance on technology which may diminish analytical thought and inventiveness. This article examines the ethical considerations involving generative AI, such as the authenticity of creative work and the ownership of intellectual output. Emphasising the necessity for clarity and conscientious in the application of AI, this conceptual article outlines the opportunities, limitations and ethical concerns associated with generative AI in language instruction. The core message of the article advocates for a well-rounded strategy that leverages the positive aspects of generative AI within language education, while also addressing possible drawbacks and championing an ethical and equitable approach to language learning in the emerging AI-centric digital landscape. A model for forging thinking in this new research and practice space is designed to synthesise many of the possibilities of generative AI in language education.

Received: 18 January 2024 | Revised: 7 March 2024 | Accepted: 1 April 2024 

Conflicts of Interest

The author declares that he has no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.