A scoping study of reviews on artificial intelligence in education

Abstract

This scoping study synthesizes recent developments in artificial intelligence in education (AIEd), addressing knowledge structures, research priorities, learning theories, ethical considerations, and impact evaluation. A bibliometric analysis of 31 review articles (2019-2023) indexed in Scopus (Social Sciences) was conducted using VOSviewer and complementary statistical methods. The corpus is concentrated in the United Kingdom, Hong Kong, China, Germany, the United States, and Taiwan, with Asian countries accounting for 48.4%. Multidisciplinary journals attract 4.4 times more citations than education-only outlets. Findings indicate a marked rise in AIEd research, primarily led by education-affiliated scholars, yet often lacking robust pedagogical grounding and systematic impact assessment. The prevalence of small samples, limited quantitative rigor, and inconsistent contextual reporting constrain generalizability and inference. To enhance educational relevance and fairness, the field should be anchored in pedagogical frameworks and advanced through collaborative efforts that build stronger theories, methods, and practices responsive to diverse educational needs.