Research Trends in Artificial Intelligence in Education and the Ethics of Privacy

Abstract

The integration of Artificial Intelligence (AI) into education is accelerating, enabling personalized learning, real-time feedback, and institutional automation. However, this rapid adoption raises critical ethical concerns, particularly regarding data privacy, algorithmic transparency, and accountability. This study presents a bibliometric analysis of scientific literature published between 2015 and 2024 that explicitly addresses the intersection of AI, education, and privacy. Using data extracted from the Scopus database and analyzed with Python and VOSviewer, this study examines publication trends, citation patterns, author networks, thematic keywords, and international collaboration. Results indicate a sharp increase in publications and citations since 2021, with growing emphasis on generative AI tools and data protection. Despite this momentum, the literature remains fragmented, with limited representation of pedagogical and equity-focused perspectives. The study highlights emerging thought leaders, dominant publication venues, and geographic research clusters, offering a critical overview of current scientific discourse.

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