Author: Mrs. Rohini Bhattarai
DOI Link: https://doi.org/10.70798/Bijmrd/04100001
Abstract: Artificial intelligence (AI), including generative AI, is now embedded in personalized learning, tutoring, assessment, learning analytics, accessibility, and educational administration. These uses may support teaching and learning, but they raise concerns about privacy, bias, transparency, accountability, academic integrity, learner autonomy, and unequal access. This conceptual paper synthesizes selected peerreviewed studies and international guidance on ethical AI in education, updates the evidence base with 2026 surveys, policy reports, and regulatory developments, and proposes a lifecycle-oriented framework for translating ethical principles into institutional practice. The literature is organized around ten connected principles: privacy and data protection; fairness and non-discrimination; transparency and explainability; accountability; meaningful human oversight; academic integrity; inclusion and accessibility; safety and security; learner autonomy and well-being; and ethical governance with continuous monitoring. The framework has seven stages: planning and needs analysis, ethical risk assessment, ethical design and selection, implementation, human oversight, monitoring and evaluation, and continuous improvement, with stakeholder participation across all stages. Current evidence shows near-universal student use and rapidly growing teacher use, while formal institutional policy, training, and assessment redesign lag behind. The paper also identifies implementation challenges and a future agenda centred on governance, AI literacy, assessment redesign, equity, auditing, and evidence-based adoption. Because the study is conceptual, lacks a recorded database-by-database screening log, and does not empirically test the framework, the model should be treated as provisional rather than validated.
Keywords: Artificial Intelligence; AI in Education; Generative AI; Educational Technology; AI Ethics; AI Governance; Human-Centred Framework.
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