We find ourselves at a pivotal moment where the role of generative AI and other technological tools is reshaping the way we teach and learn languages. The question that lies before us is not whether these innovations will shape the future, but rather how we, as educators, will harness their potential to create meaningful and effective language instruction.
The title of our conference, No Fate: The Future is Not Set, underscores our belief that the future is not predetermined. We hope that our conference will serve both as a platform for collaboration and a catalyst for change as it is via the collective effort of educators, researchers, and innovators that the trajectory of language teaching and learning will be determined. By fostering collaboration, sharing insights, and pushing the boundaries of what is possible, we can shape the future of language education.
Recent advancements in generative AI-assisted learning tools such as QuilBot, ChatGPT, and Murf have been integrated into language learning frameworks (Fitria, 2021; Shaikh et al., 2023). Despite these integrations, the degree to which AI is used for language learning in higher education is unclear. The current study investigated this issue by surveying university students varying in demographics and language backgrounds. A total of 354 participants’ (N male = 76, M age = 21 years) engagement with AI technologies was assessed. Overall, a low engagement rate with AI-based technologies was observed. Logistic regression analyses revealed no significant differences in the use of AI tools with respect to age, gender, GPA, or language background (ps > .05), suggesting a universally low adoption of AI technology in students’ language learning from various backgrounds. The findings highlight the need for more specialized and effective strategies and instructions to enhance the utilization of AI technologies in educational contexts.
