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

arXiv: https://arxiv.org/abs/2408.01075 · HTML: https://mlsanity.com/paper/2408.01075/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 67 references that are in the map.
- First posted on arXiv 2 Aug 2024.

## Builds on (most cited first, 11 of 11)

- [GPT detectors are biased against non-native English writers](https://mlsanity.com/paper/2304.02819/) (2023)
- [Testing of Detection Tools for AI-Generated Text](https://mlsanity.com/paper/2306.15666/) (2023)
- [Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education](https://mlsanity.com/paper/2305.00290/) (2023)
- [Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals](https://mlsanity.com/paper/2107.06751/) (2021)
- [Game of Tones: Faculty detection of GPT-4 generated content in university assessments](https://mlsanity.com/paper/2305.18081/) (2023)
- [The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment](https://mlsanity.com/paper/2312.07086/) (2023)
- [The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment- A Preprint](https://mlsanity.com/paper/2403.14692/) (2024)
- [Deepfakes and Higher Education: A Research Agenda and Scoping Review of Synthetic Media](https://mlsanity.com/paper/2404.15601/) (2024)
- [Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective](https://mlsanity.com/paper/2306.01798/) (2023)
- [Comprehensive AI Assessment Framework: Enhancing Educational Evaluation with Ethical AI Integration](https://mlsanity.com/paper/2407.16887/) (2024)
- [Understanding Student and Academic Staff Perceptions of AI Use in Assessment and Feedback](https://mlsanity.com/paper/2406.15808/) (2024)

## Abstract (arXiv)

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.