AI-DRIVEN ASSESSMENT AND FEEDBACK IN LANGUAGE EDUCATION: A REVIEW OF2024–2025 STUDIES - ISRAILOVA, Dilkhumor Sherzod kizi (The Lingua Spectrum, 2025)
Rapid advances in generative artificial intelligence (AI) have transformed assessment and feedback practices in language education. This article synthesizes recent empirical studies (2024–2025) that examine AI-generated feedback, AI-assisted instruction, and student perceptions of AI scoring in English language learning contexts. Findings indicate that AI feedback can be pedagogically comparable to teacher feedback, particularly in EFL writing improvement, while hybrid instructional models integrating AI enhance students’ cognitive engagement and writing outcomes. However, challenges such as academic integrity, over-reliance on AI, lack oыf transparency, and unequal access persist. The article argues that effective and ethical implementation requires teacher and student AI literacy, transparent policies, and integration of AI into pedagogically grounded instructional models. The results highlight both the transformative potential and the risks of AI-driven assessment in contemporary language education.