A SYSTEMATIC REVIEW ON COGNITIVE AND MOTIVATIONAL IMPACT ON ENGLISH LANGUAGE LEARNING THROUGH ARTIFICIAL INTELLIGENCE

Abstract

How AI can be utilized in language education field and the influences on both learning, motivation, and engagement are the core of current research. As a result of the present study, 9 papers were made part of the research. These studies cover different AI-based treatments which can help different types of learning systems from kindergarten to university classroom in various environments. The data provided evidence for theme analysis compared with previously conducted studies, and thus the methodological quality of the research was evaluated. Findings demonstrate that AI-based methods of treatment are considerably more effective than the traditional ways of teaching the same language. Students had greater cardinal direction knowledge, and each individual also had some part of the concept. Further, AI computing technologies play the part of giving learners the intrinsic motivation, selfregulation and learner autonomy. This can stimulate students’ engagement and interest in their studies. By way of the instructor support, and AI interface design the contextual factors as tools that help or hamper the effectiveness of interventions are used. Results have proven that AI is the most likely future of the language training and educators, governments, and researchers need to be kept informed. The need for longer-term viability and scalable solutions, as well as ethical aspects concern the process of AI-powered digital systems implementation requires deeper research. In view of the two-sided picture of AI-aided language learning trend, this systematic review provides outcomes that may lead to further investigation and practice of AI in the field of language learning.