Development of an AI-Driven Recommender System for ‎Personalized English Language Learning Paths Based on Individual ‎Learning Styles

The rapid evolution of digital technology in education has necessitated a structural shift from ‎traditional, uniform teaching methods to personalized learning environments. In the field of ‎English Language Teaching (ELT), learners often face challenges such as cognitive overload and ‎choice paralysis due to a lack of tailored instructional materials that align with their cognitive ‎profiles. This research explores the development of an AI-driven recommender system designed ‎to curate personalized learning paths based on individual learning styles, such as the VARK ‎model. The primary objective is to establish a conceptual framework that leverages artificial ‎intelligence to bridge the gap between cognitive psychology and adaptive language pedagogy. ‎Adopting a qualitative, descriptive, and library-based methodology, this study synthesizes state-‎of-the-art literature from both international and domestic academic databases, including IEEE ‎Xplore, Scopus, SID, and Civilica. The analysis focuses on the integration of hybrid ‎recommendation algorithms—combining content-based and collaborative filtering—to ‎dynamically sequence educational resources. The findings indicate that an AI-driven approach ‎significantly optimizes the language acquisition process by delivering content that aligns with the ‎learner’s visual, auditory, or kinesthetic preferences. By continuously updating learner profiles ‎through feedback loops, the proposed system ensures that the pedagogical trajectory remains ‎within the student’s Zone of Proximal Development. Ultimately, this research concludes that the ‎synergy between AI recommender systems and cognitive profiling is essential for the future of ‎autonomous language learning, providing a robust theoretical blueprint for educational ‎technology developers and institutions aiming to implement next-generation, adaptive English ‎language instruction.‎

کلیدواژه ها:

AI Recommender Systems ، Personalized Learning Paths ، English Language ‎Teaching ، Learning Styles