AI-DRIVEN STRATEGIES FOR ENHANCING VOCABULARY DEVELOPMENT IN ENGLISH AND YORUBA AMONG SENIOR SECONDARY SCHOOL STUDENTS IN MULTILINGUAL CLASSROOM IN ONDO STATE

Abstract

This study investigated the effectiveness of artificial intelligence (AI)-driven strategies in enhancing vocabulary development in both English and Yoruba among Senior Secondary School One (SSS1) students in multilingual classrooms in Ondo State, Nigeria. Based on concepts of constructivist and socio-cognitive learning theories, the study explored how AI tools such as intelligent tutoring systems, gamified language apps, and speech recognition platforms support vocabulary acquisition in a linguistically diverse setting. A mixed-methods design was employed, combining quantitative and qualitative approaches. The sample size was 180 SSS1 students and 12 teachers of languages from six state-owned secondary schools in urban, semi-urban, and rural areas. Data were gathered using structured questionnaires, pre- and post-vocabulary tests, classroom observation schedules, and semi-structured interviews. Quantitative data were examined using descriptive statistics and inferential statistics, while qualitative data were explored thematically. Findings showed that AI-driven learning enhances vocabulary acquisition, pronunciation, and contextual use of the two languages significantly, with impacting effects being felt in hitherto under-supported schools during language learning. The study concluded by recommending policy-level integration of AI tools in language learning syllabuses, AI capacity development for teachers, and culturally tailored AI solution development in order to mitigate multilingual classroom issues in Nigeria.