Science Mapping of AI as an Educational Tool Exploring Digital Inequalities: A Sociological Perspective

Abstract

This study aims to explore the evolution of the literature on the sociological implications of integrating artificial intelligence (AI) as an educational tool, particularly its influence on digital inequalities. While AI technologies, such as AI-based language models, have begun transforming educational practices by personalizing learning, fostering student autonomy, and supporting educators, concerns remain regarding access disparities, ethical implications, and the potential reinforcement of existing social inequalities. To address these issues, a bibliometric analysis employing science mapping was conducted on 1515 studies sourced from the Web of Science Core Collection. This analysis traces the thematic evolution of social science perspectives on AI’s role in education and its relationship with digital inequalities. The results indicate a growing academic interest in AI in education, with a notable progression from understanding its basic impact to exploring complex themes such as vulnerability, disability, bias, and community. The studies show that AI’s application has expanded from isolated research on specific populations to broader discussions on inclusivity, equity, and the impact of AI on governance, policy, and community. However, the findings also reveal a significant gap in sociological perspectives, particularly regarding issues like digital illiteracy and socio-economic access disparities. Although AI holds promise for promoting more inclusive education, further research is essential to address these sociological concerns and to guide the ethical, equitable implementation of AI as its influence on governance, policy, and community impact continues to grow.