Gendered Syntax in AI-Assisted Academic Writing in Nigerian Universities

Abstract

This study examined gendered syntactic patterns in AI-assisted academic writing among students in the Department of English and Literature, Alvan Ikoku Federal University of Education, Owerri. This study was motivated by growing concerns that AI-assisted writing tools, while supporting academic literacy, may unconsciously reproduce sociocultural biases through sentence structure. Anchored on Halliday’s Systemic Functional Linguistics (SFL) theory, the analysis focused on transitivity patterns, agency, and participant roles in selected academic texts. The data comprised a purposively selected corpus of AI-assisted and human-written academic texts. These texts were analyzed to determine how material, relational, and mental processes, as well as active and passive constructions, were used to represent gendered subjects. The findings indicated that AI-assisted texts frequently reproduced conventional syntactic patterns that foregrounded masculine agency while backgrounding feminine roles through passivation and relational clauses. These tendencies reflected broader sociocultural ideologies embedded in language use rather than deliberate technological bias. The study concluded that although AI-assisted academic writing enhanced textual organization and linguistic accuracy, it can subtly reproduce gendered discursive patterns. This study, therefore, recommended integrating critical language awareness and responsible AI literacy into academic writing instruction to promote more gender equitable language practices in Nigerian universities.