A Genre-based Approach with GenAI feedback to Teaching Written Exposition in a Tertiary EFL Context in Indonesia

Despite the inclusion of the Genre-based Approach (GBA) in Indonesian educational curricula, GBA studies remain limited, particularly when a Generative Artificial Intelligence (GenAI) tool is integrated as a feedback agent. This study investigated the implementation of GBA with GenAI feedback in teaching exposition writing to undergraduate EFL students in Indonesia through an embedded single-case study. Fifteen students’ diagnostic tests, three drafts with GenAI feedback, and a final test were scored. Writing scores were analyzed using repeated-measures procedures across overall quality, schematic structure, and linguistic features based on Systemic Functional Linguistics (SFL) metafunctions. Students’ experiences with GenAI feedback were analyzed through thematic analysis of students’ notes and interviews. The results indicate that students’ writing development appears to be associated with explicit instruction and teacher scaffolding alone, as development was observed only from the diagnostic test to the first draft. Despite students’ appreciation of GenAI feedback for its immediacy and comprehensive coverage, no development was observed during revision and editing with the feedback. Students also reported challenges related to prompting, feedback language, and feedback volume. These findings suggest that integrating GenAI feedback into GBA requires critical consideration. Pedagogical implications and study limitations are briefly discussed.