The conventional methods of teaching English often fall short of addressing the diverse needs of students, thereby impeding language proficiency and cross-cultural communication abilities. To enhance English instruction, artificial intelligence (AI) and natural language processing (NLP) are increasingly being employed. These technologies provide targeted learning opportunities that improve student routines and foster a deeper understanding of spoken language. Personalized education, which caters to each learner’s unique needs, forms the foundation of adaptive English teaching. This approach promotes multicultural awareness, linguistic proficiency, and confidence. This study focuses on utilizing AI and NLP to deliver personalized English instruction. It introduces an AI-driven intelligent teaching assistant—a novel framework for individualized and flexible English language education. The proposed approaches create an engaging and adaptable learning environment through advanced NLP algorithms and methodologies. By enabling quick access to information, accelerating knowledge assessment, and providing tailored training aligned with each student’s learning style, the platform reduces the cognitive load on instructors. The study proposes three strategies: designing tests and flashcards, developing innovative study plans, and monitoring and responding to student needs. The Weight-balanced AdaBoost (WB-Adaboost) algorithm was employed to develop a predictive tool that recognizes trends in student data and identifies their learning requirements. The findings have the potential to significantly advance the development of innovative instructional materials that enhance student achievement, satisfaction, and engagement. These resources can guide the development, implementation, and evaluation of AI-powered online tutoring systems in ESL programs.
Zhang et al. (Mon,) studied this question.