The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) presents both opportunities and challenges for English for Academic Purposes (EAP) instruction. This paper proposes an adaptation of the AI Assessment Scale (AIAS) specifically tailored for EAP contexts, termed the EAP-AIAS. This framework aims to provide a structured approach for integrating GenAI tools into EAP assessment practices while maintaining academic integrity and supporting language development. The EAP-AIAS consists of five levels, ranging from "No AI" to "Full AI", each delineating appropriate GenAI usage in EAP tasks. We discuss the rationale behind this adaptation, considering the unique needs of language learners and the dual focus of EAP on language proficiency and academic acculturation. This paper explores potential applications of the EAP-AIAS across various EAP assessment types, including writing tasks, presentations, and research projects. By offering a flexible framework, the EAP-AIAS seeks to empower EAP practitioners seeking to deal with the complexities of GenAI integration in education and prepare students for an AI-enhanced academic and professional future. This adaptation represents a step towards addressing the pressing need for ethical and pedagogically sound AI integration in language education.

References in corpus (4)

• The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment
• The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment- A Preprint
• Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective
• The AI Assessment Scale Revisited: A Framework for Educational Assessment

Cited by in corpus (1)

• GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education