The efficacy of AI-driven pedagogical strategies for foreign language acquisition in higher education

Abstract

This article investigates how AI-driven pedagogical strategies can be effectively integrated into foreign language programs within higher education, aiming to enhance learner engagement, improve proficiency, and support sustained retention. Drawing on a synthesis of recent empirical findings, the study addresses critical questions regarding the efficacy of automated feedback systems, adaptive learning technologies, and natural language processing (NLP)-enabled chatbots. To explore these dimensions, three illustrative case studies were conducted. First, an advanced academic writing course piloted an NLP-based feedback system designed to provide immediate corrections and stylistic suggestions, yielding statistically significant improvements in grammatical accuracy and coherence. Second, interactive AI chatbots were introduced to intermediate-level language learners, offering real-time pronunciation, grammar tips, and scenario-based conversations. This intervention led to notable gains in fluency, as measured by reduced hesitation and enhanced overall confidence. Finally, a semester-long deployment of an adaptive vocabulary training app demonstrated that personalized review intervals could substantially increase both short-term acquisition and long-term retention. Taken together, these findings suggest that AI-powered tools, when thoughtfully woven into conventional curricula, can deliver differentiated instruction that addresses varied learner profiles and fosters deeper skill development. Moreover, the real-time nature of automated systems allows instructors to focus on higher-order pedagogical tasks, such as designing targeted mini-lessons or encouraging critical reflection. While the potential for scalability is considerable, the article also underscores the need for ongoing investigation into ethical concerns, digital equity, and robust implementation frameworks. By situating these tools within established language acquisition theories, the study provides a roadmap for refining foreign language pedagogy in an increasingly interconnected academic landscape.

У статті досліджується ефективність інтеграції педагогічних стратегій на основі штучного інтелекту у програми вивчення іноземних мов у вищих навчальних закладах з метою підвищення зацікавленості студентів, покращення рівня володіння мовою та підтримки стійкого засвоєння матеріалу. Спираючись на узагальнення останніх емпіричних даних, дослідження розглядає важливі питання щодо ефективності автоматизованих систем зворотного зв'язку, адаптивних технологій навчання та чат-ботів на основі обробки природної мови (ОПМ). Для вивчення цих аспектів було проведено три ілюстративні тематичні дослідження