A Systematic Needs Analysis for AI Literacy Integration in English for Academic Purposes for University Learners
A Systematic Needs Analysis for AI Literacy Integration in English for Academic Purposes for University Learners

Summary/Abstract: The rapid expansion of artificial intelligence (AI) in higher education has transformed the literacy demands placed on university learners, particularly within English for Academic Purposes (EAP). This study investigates the AI literacy needs of EAP learners in Egypt through a systematic needs analysis integrating the EAP Needs Analysis model (Target Situation, Present Situation, and Learning Needs) with a contemporary AI Literacy Framework. Data were collected from 364 undergraduate students across five national universities using a structured survey that examined AI-supported academic English tasks, current AI literacy abilities, attitudes, barriers, and training needs. Results revealed widespread adoption of AI tools, with 92% of participants using AI for academic English activities, especially reading, writing, translation, and grammar support. However, participants demonstrated only fair proficiency in key AI literacy competencies, with notable gaps in prompt writing, evaluating AI-generated content, identifying bias, and tool selection. Ethical use and citation practices were accompanied by significant concerns about academic integrity and unclear institutional policies. Learners expressed moderate but consistent needs for AI literacy training and preferred structured, multimodal instructional formats. The findings highlight a clear mismatch between learners' extensive AI use and their limited critical and ethical AI competencies, underscoring the need to embed AI literacy as a core component of contemporary EAP curriculum design.

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