<![CDATA[The increasing use of Artificial Intelligence (AI) writing tools has changed the way English as a Foreign Language (EFL) students seek feedback on their academic writing, particularly during the demanding process of preparing a research proposal or thesis. This study aims to explore how final-semester EFL students perceive, evaluate, and respond to AI-generated feedback while writing their proposal or thesis. Using a descriptive qualitative design, this study employed a Likert-scale screening questionnaire distributed to 24 respondents, followed by semi-structured interviews with six key informants selected through purposive sampling. The findings of the questionnaire indicate that most participants perceived AI-generated feedback favorably for surface-level writing issues, with 87.5% agreeing that it helped them identify possible errors before consulting their supervisor, while only 62.5% reported cross-checking content-level AI suggestions before applying them. From a qualitative perspective, thematic analysis organized these perceptions into four components: cognitive (understanding of how AI feedback is produced and how it differs from supervisor feedback), affective (confidence balanced with doubt about accuracy), conative (direct application of surface-level suggestions versus cross-checking of content-level suggestions), and external/internal cues (trust shaped by feedback consistency and by students’ own digital literacy). When examined through Rosenberg and Hovland’s Tripartite Attitude Model, Robbins and Judge’s theory of perception, and the concept of AI Literacy, the findings show that students who engaged more critically and selectively with AI-generated feedback demonstrated higher AI literacy, while those who applied suggestions uncritically demonstrated lower AI literacy regardless of the amount of AI feedback they received. This study offers practical recommendations for students and lecturers on the wise and critical use of AI-generated feedback in the proposal and thesis writing process.]]>
