Abstract
The rapid integration of generative AI into foreign language education has reshaped how students complete coursework and how teachers assess. As students increasingly rely on AI to assist with coursework, teachers often cannot reliably distinguish AI-generated from human-authored work, which raises pressing concerns about assessment fairness. Yet how assessment unfairness is actually experienced and perceived, and how learners describe its psychological significance remain under-explored. Drawing on self-determination theory, this study investigates the forms of AI-related assessment unfairness perceived by students who reported experiencing such unfairness, and its perceived implications for students' basic psychological needs. Based on semi-structured interviews with 15 university EFL students, the findings suggest that perceived AI-related assessment unfairness takes the form of false suspicions about AI-generated coursework, unstable or opaque standards, and reward misalignment. Additionally, participants described experiences of frustration in their needs for autonomy, competence, and relatedness in relation to perceived AI-related assessment unfairness, though its perceived intensity varied with learners and contextual factors. The study offers practical implications for redesigning assessment, developing teacher capacity, and establishing institutional guidelines that support fairer, more motivationally sustaining practices.