A Systematic Literature Study on AI in Education

Abstract

Artificial intelligence in education has developed into a significant corpus of literature encompassing various viewpoints. This review study aims to address three fundamental questions: What are the main categories of AI applications examined in the education sector? What are the primary research subjects and their significant conclusions? What is the state of key research design components, including foundational ideas, methodologies, and research contexts? A bibliometric study of 2,223 research articles, accompanied by a content analysis of 125 selected papers, elucidates a thorough conceptual framework of the current literature. The existing AIED research covers a broad range of applications, including adaptive learning and individualized tutoring, intelligent evaluation and management, profiling and prediction, and innovative products. Research themes explore the technical design of educational systems as well as the analysis of the acceptance, effects, and issues related to AIED. This analysis emphasizes the variety of ideas utilized in AIED literature, the multidisciplinary characteristics of publication sites, and the inadequately studied research domains. This research provides significant insights for scholars to understand the existing landscape of AIED research and pinpoint future research opportunities in this evolving domain.