As customized artificial intelligence models faced for educational scenarios, large model for education demonstrate significant potential in achieving personalized development, improving teaching quality, and promoting educational equity. However, the development of large model for education is confronted with challenges including data quality, algorithmic safety, and ethical responsibility, alongside issues such as inconsistent underlying architecture and insufficient educational adaptation, which urgently requires guidance and support from a relevant standards system. Based on this, the paper focused on the first standard released by the World Digital Education Alliance — Large Model for Education: Overall Reference Framework. This paper first introduced its connotation, status, challenges, and clarified its theoretical foundations and design principles to elucidate the construction logic of the framework development. Subsequently, this paper elaborated on its core content, pointing out that the framework adopted a five-layer architecture (from bottom to top: infrastructure layer, data layer, model layer, interface layer, and application layer) and incorporated two key elements: “security, ethics and privacy” and “governance”. The development of the standard for overall reference framework of large model for education provided standardized support for the construction of large model for education, contributing to their scientific, orderly, and trustworthy development, and further promoting the digital transformation and high-quality development of education.

At present, emerging technologies of artificial intelligence (AI) large models are developing rapidly in various fields. Although AI large models in education could complete various intelligent tasks in knowledge production, computation, and services to provide teaching assistance, it still has limitations in function construction, data collection and management, teaching evaluation and application, etc. At the same time, there is a lack of general AI models applicable to multiple educational scenarios. Based on this, starting from the development and standardization of AI and focusing on the general AI large models, this paper defined the concept, principles, and attributes of educational general AI large models. The standardized system for educational general AI large models was proposed, which included the overall framework, information model, data specification, evaluation specification and teaching application requirements, to to standardize development, application, management, and evaluation of educational general AI large models from the perspective of guidance. Through research, the paper was aimed to standardize the application and development of general AI lerge models in the field of education, energize and empower education with intelligence, and promote high-quality development.