AI-ASSISTED ENGLISH GRAMMAR TEACHING TO FIRST YEAR ENGLISH MAJOR UNIVERSITY STUDENTS

Conventional pedagogical approaches to grammar instruction frequently prove inadequate in addressing the linguistic challenges encountered by first-year university students majoring in English.Despite extensive prior instruction, many students demonstrate a disparity between theoretical grammatical knowledge and the practical application required for complex academic writing.This deficiency is exacerbated by "linguistic anxiety," and native language interference.Consequently, slow progression in grammatical accuracy remains a significant barrier to success in advanced disciplinary coursework.This article advocates for the strategic implementation of a framework integrating Artificial Intelligence (AI) into the instruction of practical English grammar.It seeks to establish how AI-assisted tools can transform traditional instruction into a more dynamic, efficient, and student-centred practice that addresses the diverse proficiency levels of contemporary English majors.Drawing upon a synthesis of current empirical research, the study evaluates the efficacy of Automated Writing Evaluation (AWE) systems and Large Language Models (LLMs) in the tertiary classroom.The analysis focuses on the capacity of these tools to facilitate self-regulated learning through real-time diagnostic feedback.Furthermore, the article proposes a blended instructional model, categorizing feedback mechanisms into automated surface-level correction and human-led higher-order discourse analysis.The research identifies three fundamental pillars for successful integration: personalized adaptive practice, blended feedback structures, and the maintenance of academic integrity.While AI tools such as Grammarly, QuillBot, and various LLMs,