With the rapid development of Artificial Intelligence in Education (AIED), ensuring that ethical principles are fully respected and implemented as AI technology drives educational innovation has become a pressing issue. Educators are actively exploring and establishing ethical guidelines for AIED, but the fragmented nature of existing research makes it challenging to develop a comprehensive ethical framework. Through a technical analysis of the AI development process, we found significant similarities between AI development and human education. Therefore, this study uses this analogy to help educators better understand AI principles and identify key areas where AIED may lack ethical standards. Consequently, we propose a five-step, multi-layered ethical framework for AIED to guide the specific deployment and implementation of ethical guidelines, and provide a set of ethical review processes for educational policymakers to regulate and review AIED applications.

The integration of artificial intelligence (AI) into education requires frameworks that are not only technically robust but also ethically and pedagogically grounded. This paper proposes the Generalist Education Artificial Intelligence (GEAI) framework—a conceptual blueprint designed to enable privacy-preserving, personalized, and multimodal AI-supported learning in educational contexts. GEAI features a Trusted Domain architecture that supports secure, voluntary multimodal data collection via multimedia registration devices (MM Devices), edge-based AI inference, and institutional data sovereignty. Drawing on principles from constructivist pedagogy and regulatory standards such as GDPR and FERPA, GEAI supports adaptive feedback, engagement monitoring, and learner-centered interaction while addressing key challenges in ethical data governance, transparency, and accountability. To bridge theory and application, we outline a staged validation roadmap informed by technical feasibility assessments and stakeholder input. This roadmap lays the foundation for future prototyping and responsible deployment in real-world educational settings, positioning GEAI as a forward-looking contribution to both AI system design and education policy alignment.