INNOVATIVE STRATEGIES FOR ENHANCING ORAL COMMUNICATIVE COMPETENCE VIA ARTIFICIAL INTELLIGENCE SYSTEMS IN SENIOR SECONDARY EDUCATION

Abstract

This study explores the integration of generative artificial intelligence (AI) into foreign language education as a tool for designing and modeling tasks aimed at developing students’ oral communication skills. In contrast to approaches that position AI as a conversational partner, this research conceptualizes AI as an instructional design instrument used to create structured, communicatively rich learning scenarios. A four-month comparative experiment was conducted with two Grade 11 groups differing in proficiency and classroom engagement: Class B (n=17, B2 level, high activity) and Class V (n=9, B1/A1 level, lower activity).
The results indicate that while the more active group demonstrated a moderate but con-sistent increase in participation (5–8%), the lower-activity group showed a substantially higher improvement (approximately 20%) in oral production. This suggests that AI-modeled scaffolding is particularly effective for learners with lower initial engagement, as it provides clear structure and reduces cognitive and affective barriers to participation. Additionally, the use of standard-ized assessment criteria combined with creatively designed communicative tasks contributed to increased learner confidence and more consistent performance across both groups.
Overall, the findings support the view that AI can enhance foreign language instruction not through direct interaction with students, but through its capacity to generate pedagogically meaningful tasks that simulate authentic communication. Such an approach not only fosters greater student involvement but also facilitates a gradual transition toward higher levels of communicative competence.