FROM CHALKBOARD TO CHATBOT: INTEGRATING AI-DRIVEN CONVERSATIONAL AGENTS TO FOSTER AUTONOMOUS EFL LEARNING

Abstract

Despite the persistent teacher-fronted pedagogy in low-resource university contexts, EFL learners continue to struggle with autonomy and speaking opportunities. This study therefore investigates the extent to which integrating AI-driven conversational agents can foster autonomous EFL learning among Beninese university students. A mixed-methods quasi-experimental design was adopted with 86 second-year EFL students divided into an experimental group using a ChatGPT-based conversational agent for 12 weeks and a control group receiving traditional instruction. Data were collected through pre/post oral proficiency tests, learner autonomy questionnaires based on Benson (2013), and semi-structured interviews. Quantitative data were analyzed using ANCOVA, while thematic analysis was applied to qualitative data.The experimental group showed statistically significant gains in oral fluency, lexical complexity, and learner autonomy compared to the control group (p < .001, d = 0.87). Qualitatively, learners reported increased motivation, reduced speaking anxiety, and enhanced self-regulation. The AI agent provided 24/7 personalized feedback, thereby compensating for large class sizes and limited teacher contact time. The findings confirm that AI- driven conversation al agents constitute a viable, scalable pedagogical tool for promoting learner autonomy in low-resource EFL contexts.