The rapid integration of Generative Artificial Intelligence (GenAI) in higher education has exposed the need for significant changes in academic assessment and instructional practices. Due to its focus on linguistic competencies, language education in general, and English for Academic Purposes (EAP) in particular, is potentially more at risk of misuse of GenAI by students. This involves obscured evidence of learning and makes assessment of academic progress and language acquisition more challenging. It is, therefore, essential to integrate AI literacy into language education and reconsider the nature of language assessment in alignment with the new teaching and learning context. This would equip students with the necessary skills to engage with GenAI tools more critically, supporting their language acquisition rather than bypassing it, and better prepare them for future employment in the AI era. This presentation reports on strategies designed to develop AI literacy and applied to EAP assessments with the aim of preserving the integrity of language education at university. The context of the study is a university in Vietnam with English as a medium of instruction and a top-down AI acceptance policy. Experiential learning theory has been used as the major framework, where all suggested interventions followed the experiential learning cycle, inviting students to continuously reflect on their learning experience and to take accountability for learning outcomes. Students’ reflections have provided a substantial pool of qualitative data, whose analysis indicates a more critical approach to AI use by students and an overall positive reception of the new AI-friendly assessment format.

Authors:
Yulia Tregubova, British University Vietnam, Vietnam

About the Presenter(s)
Dr. Yulia Tregubova is currently an EAP (English for Academic Purposes) Lecturer and the head of the EAP department at British University Vietnam in Hanoi, Vietnam.

See this presentation on the full schedule – Thursday Schedule

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