<p>The integration of Artificial Intelligence (AI) in education has caused increasing concerns over principles of ethics, including transparency, fairness, privacy, and accountability. Although several literature reviews have investigated these issues separately, there is a lack of consistency among research, leading to fragmented terminology and conceptual overlap. The present study aims to perform a meta-review of current literature studies to identify, categorize, and consolidate the ethical considerations associated with AI usage in education. This study systematically analyzed 13 peer-reviewed literature review articles published from 2021 to 2025, adhering to the PRISMA 2020 framework. Articles were chosen according to rigorous inclusion criteria, highlighting reviews that examined ethical issues in AI applications within various educational contexts. A qualitative thematic synthesis was employed to extract and categorize ethical concepts into broad themes. The research revealed seven key ethical themes: Transparency and Accountability, Data Protection and Security, Fairness and Non-Discrimination, Human-Centric AI design, Ethical Responsibility and Governance, Moral Principles in AI, and Technical Integrity and Robustness. These findings provide a unified thematic framework that encompasses both fundamental ethics and contemporary challenges, including those presented by generative AI. The study identifies gaps in the literature by providing a systematic ethical framework and suggests future research directions that include empirical validation, cross-cultural investigations, and an examination of generative AI risks. This review theoretically aids in establishing a cohesive ethical foundation to guide future models and governance frameworks for responsible AI in education.</p>