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

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arxiv 2408.01075 v1 pith:6P4QTRIG submitted 2024-08-02 cs.CY cs.AI

classification cs.CYcs.AI
keywords academiceap-aiasassessmentgenailanguageadaptationeducationenglish
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 6 citations worldwide. Full citation record

  1. GenAI as Digital Plastic: Understanding Synthetic Media Through Critical AI Literacy

    cs.CY 2025-02 conditional novelty 5.0 of 10

    AI-generated content resembles plastic: cheap, useful, long-lasting, and capable of polluting digital spaces, so learners need critical AI literacy to handle it.

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