Integrating AI to Beninese ESP learners’ curriculum: A technical school-based study - Hounhanou, Arlette Joseline Viviane (Edelweiss Applied Science and Technology, 2025)
This study evaluates the effectiveness of AI-based language learning apps (LLAs) in enhancing the oral communicative competence of secretarial English for Specific Purposes (ESP) learners in Benin. A mixed-methods design was employed at the Porto-Novo Technical and Vocational High School, where data were collected from 60 secretarial students and 10 ESP teachers using structured questionnaires and classroom observations across traditional and AI-enhanced lessons. Quantitative data were analyzed via descriptive statistics, and qualitative data were thematically coded. The results reveal that learners face significant barriers, including a lack of authentic materials, teacher-centered pedagogy, and high anxiety (80%). The study demonstrates that AI-LLAs significantly improved learning outcomes by 85% (post-test mean = 261.67 vs. pre-test mean = 203.33), particularly in fluency, accuracy, and task performance, benefits attributed to personalized feedback and gamification. However, challenges for effective implementation include poor internet access, uncontextualized content, and teachers’ digital literacy gaps. The research concludes that AI-LLAs are powerful supplements to traditional ESP instruction when integrated thoughtfully, with practical implications recommending hybrid implementation, offline app features, teacher training, and contextualized content design to ensure equitable access and pedagogical alignment.