The Impact Of Ai-Powered Tools On Language Learning And Assessment In Higher Education

Abstract

The rapid maturation of artificial intelligence (AI) — especially generative models and advanced machine-learning systems — is reshaping how languages are taught, learned, and assessed in higher education. AI tools now provide adaptive practice, immediate formative feedback, automated scoring, personalized content generation, pronunciation evaluation, and administrative support. These affordances promise greater access, scalability, and individualized pathways for learners, but they also create risks: validity threats in assessment, academic integrity challenges, inequities due to differential access, and ethical questions around transparency and data privacy. This article synthesizes recent empirical and policy literature to examine how AI tools are changing pedagogical practice and assessment design in university language programs, evaluates evidence on learning outcomes and measurement validity, and offers practical recommendations for instructors, programs, and institutions seeking to harness AI responsibly. Keywords: artificial intelligence, language learning, higher education, automated scoring, adaptive learning, assessment validity, academic integrity.