The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes
Jasper Roe (1), Mike Perkins (2), Yulia Tregubova (2) ((1) James Cook, University Singapore, (2) British University Vietnam)

TL;DR
This paper introduces the EAP-AIAS, a framework adapted from the AI Assessment Scale to guide ethical and effective integration of Generative AI tools in English for Academic Purposes assessments, supporting language development and academic integrity.
Contribution
It presents a novel five-level framework tailored for EAP contexts to manage AI usage in assessments, addressing unique language learning needs and ethical considerations.
Findings
Proposes a structured five-level AI usage framework for EAP assessments
Explores applications across writing, presentations, and research tasks
Aims to support ethical AI integration in language education
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…
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Taxonomy
TopicsOnline Learning and Analytics
MethodsFocus
