STUDENT ENGAGEMENT AND LEARNING OUTCOMES IN AI-BASED FLIPPED LEGAL ENGLISH CLASSROOMS: MIXED METHODS INVESTIGATION - Silvia, Resi; Desmiyanti; Menrisal (Information Technology Education Department, 2026)
This study examined the effectiveness of an AI-based flipped classroom in improving Legal English learning outcomes and student engagement among undergraduate law students in an English for Specific Purposes (ESP) context. Using an explanatory sequential mixed methods design, the study involved 34 undergraduate law students enrolled in a Legal English course at a private university in Jambi City, Indonesia. Quantitative data were collected through a pretest-posttest Legal English achievement test and a student engagement questionnaire, while qualitative data were obtained from classroom observations, reflective responses, and semi-structured interviews. The intervention was implemented over 10 instructional weeks through three stages: AI-supported pre-class preparation, active in-class learning, and post-class reflection. Quantitative findings indicated a statistically significant improvement in Legal English performance, with mean scores increasing on the posttest. Student engagement also increased significantly. Qualitative findings revealed that students gradually shifted from literal translation to contextual interpretation of legal terminology, became better prepared before class, participated more actively in classroom discussion, and viewed AI as a useful scaffold for initial understanding, although lecturer guidance remained essential for disciplinary accuracy. These findings suggest that an AI-based flipped classroom is a pedagogically promising approach for Legal English instruction in non-English-major ESP settings. Keywords: Artificial Intelligence; Flipped Classroom; Legal English; English for Specific Purposes; Student Engagement.