Enhancing English for Legal Purposes through Generative AI: Evidence from Islamic Family Law Students

Generative artificial intelligence (GenAI) is increasingly used in language education, yet its role in English for Legal Purposes (ELP), particularly among Islamic Family Law students, remains underexplored. This study investigated the effects of GenAI-supported ELP instruction on legal vocabulary mastery and legal reading comprehension and examined students’ experiences of using GenAI during discipline-specific English learning. An explanatory sequential mixed-methods design was employed with 60 undergraduate students from two intact classes at the Faculty of Sharia, Universitas Islam Negeri Raden Intan Lampung, Indonesia. Thirty students received GenAI-supported instruction, while 30 students followed conventional ELP instruction over eight weeks. Data were collected through legal vocabulary and reading comprehension tests, learning reflections, prompt-response records, and semi-structured interviews. Quantitative data were analyzed using ANCOVA, while qualitative data were examined thematically. The results showed that the GenAI-supported group achieved higher adjusted posttest scores in legal vocabulary, F(1, 57) = 52.84, p < .001, ηp² = .481, and legal reading comprehension, F(1, 57) = 30.67, p < .001, ηp² = .350. Qualitative findings indicated that students valued GenAI for contextualized vocabulary explanations, simplification of difficult legal texts, and iterative clarification. However, they also emphasized the need to verify AI-generated information and expressed concerns about overreliance and inaccurate legal explanations. The findings suggest that GenAI can support ELP learning effectively when integrated through structured tasks, critical verification, and lecturer guidance.