DIGITAL ETHICS IN EDUCATION: A SYSTEMATIC LITERATURE REVIEW

Abstract

Digital ethics has become a central concern in education as artificial intelligence (AI), generative AI, learning analytics, and data-driven systems are increasingly embedded in teaching, learning, research, and institutional decision-making. Despite rapid growth in scholarship, the literature remains conceptually dispersed, making it difficult to identify dominant ethical concerns, educational responses, and unresolved research gaps. This systematic literature review synthesizes recent scholarship on digital ethics in education by examining ethical implications of AI and generative AI, ethics education and professional development, and ethical dilemmas within professional and institutional practice. The review followed the PRISMA 2020 framework. Searches were conducted in Scopus and ERIC and were limited to English-language peer-reviewed journal articles published in 2024 and 2025. The searches identified 560 records (408 from Scopus and 152 from ERIC); following screening, eligibility assessment, and quality appraisal, 20 studies were retained for qualitative synthesis. The findings converge around three interrelated themes: ethical implications of AI and generative AI; ethics education, ethical training and professional development; and ethical challenges within professional, institutional and data-intensive practice. Overall, the review shows a shift from abstract ethical principles toward applied, context-sensitive ethical competence and governance, while empirical validation and policy evaluation remain limited. The review supports the development and testing of integrated ethical frameworks to guide responsible digital transformation in education.