Generative AI in English-language learning at a Sri Lankan university: Adoption, ethics, and student–teacher relations

Abstract

Generative AI (GenAI) is rapidly transforming study practices; however, Sri Lankan universities provide only limited, discipline-specific guidance on its appropriate use, creating uncertainty for both students and lecturers. This study focuses on second-year undergraduates enrolled in courses in the Department of English Language Teaching (DELT), Faculty of Social Sciences and Languages, Sabaragamuwa University of Sri Lanka. It examines students’ use of GenAI in English-language learning, their ethical views on its role in learning and assessment, and its impact on student–lecturer relationships. However, there is limited qualitative evidence from the Sri Lankan context on this topic. A qualitative case study was conducted using semi-structured interviews with 12 gender-balanced students (recruited via purposive and snowball sampling) and brief naturalistic observations. Data were analysed using reflexive thematic analysis. UTAUT2 is employed as the theoretical framework because its constructsperformance/ effort expectancies, social influence, facilitating conditions, hedonic motivation, and habit-align directly with the research questions. Findings indicate students widely use ChatGPT to understand grammar and meaning, unpack assignment tasks, and brainstorm. Participants reported peers’ unethical AI use, strong social influence (peer norms), ambiguous facilitating conditions (unclear rules, uneven detection), and evidence of hedonic use and habit. Students drew a shifting ethical line between legitimate scaffolding and prohibited substitution, sometimes crossing it under deadline pressure and perceived norms. Many expressed strong trust in AI, both as a study assistant and a “friend.” All participants believed lecturers were aware of AI tools, yet none had encountered formal, course-level rules on acceptable use. About 60% perceived reduced interaction with lecturers due to AI, while others reported no change. The study recommends faculty-level, department-level AI policies that are customised disciplinary level, transparent AI-use statements with submissions, process-oriented assessment, and targeted AI-literacy workshops. The findings contribute Sri Lanka-specific qualitative evidence and extend UTAUT2 by foregrounding trust and transparency within facilitating conditions.