On April 2, the Ministry of Education of China, in conjunction with the National Development and Reform Commission, the Ministry of Industry and Information Technology, the Ministry of Science and Technology, and the National Data Bureau, issued the “Artificial Intelligence + Education” Action Plan. This marks the first time a clear stance and posture of actively and comprehensively embracing AI has been demonstrated. The full text of the plan is as follows:
In accordance with the strategic deployment of the Outline of the National Plan for the Construction of a Powerful Education Country (2024–2035) and the requirements of the Opinions of the State Council on the Deep Implementation of the “AI+” Action, this plan is hereby formulated.
I. General Requirements
Guided by Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, we shall thoroughly implement the spirits of the 20th National Congress of the CPC, all plenary sessions of the 20th Central Committee, and the National Education Conference. We will fully implement the Party’s education policy, fulfill the fundamental task of fostering virtue through education, and deeply execute the national education digitalization strategy. Adhering to the principles of student-centeredness, literacy-first, application-orientation, and AI for good, we shall give full play to the engine role of AI in empowering educational transformation. We aim to promote the integration of smart technologies with all elements of education, throughout all processes and across all scenarios. We will coordinate the promotion of AI talent cultivation and application innovation, synergize the construction of basic environments and innovation ecosystems, and accelerate the construction of a new form of smart education characterized by human-machine collaboration, the integration of virtual and real worlds, and ubiquitous accessibility. We strive for the unification of large-scale education with personalized cultivation, knowledge transmission with capability building, and technical application with humanistic care, focusing on nurturing high-quality talents competent for the smart era, providing strong momentum for accelerating the construction of a powerful education country and providing education that satisfies the people.
By 2030, a pattern of deep integration between AI and education will be basically formed. A longitudinal and horizontal system for AI education across all levels of schooling and general education for the whole society will be established. The scale and quality of AI talent cultivation will be significantly improved, and a long-term mechanism for fostering AI literacy among the entire populace will be formed. Systematic transformations in education and teaching models, scientific research paradigms, and governance modes will be achieved. The supply capacity of educational services and the level of modernization will be greatly enhanced. The basic supporting environment will be more intensive and efficient, the innovation ecosystem will be more open and collaborative, and the application of smart technologies will be more inclusive, safe, and efficient. A batch of high-value, replicable, and scalable application scenarios will be created, and a new form of smart education will be basically established, with its global influence ranking among the forefront.
II. Promoting AI Talent Cultivation and Literacy Enhancement
(1) Accelerating the popularization of AI education for primary and secondary students. Continuously improve the Guidelines for General AI Education in Primary and Secondary Schools, and ensure that AI-related courses are fully offered and well-taught. Promote the comprehensive inclusion of AI education into local curriculum systems, and guide various regions in developing AI curriculum guidelines to clarify curriculum goals, content, and class hour requirements for each schooling stage. Encourage interdisciplinary AI teaching and promote the integration of AI education into after-school services and study tour practices. Persist in combining science and technology education with humanistic education, focusing on enlightening students’ wisdom and nurturing their souls, guiding students to understand and utilize smart technologies scientifically and rationally, enhancing their smart literacy, stimulating curiosity, cultivating innovative thinking, and improving cognitive thinking and the ability to solve complex problems. Strengthen AI education bases for primary and secondary schools, and support schools in rural and remote areas in utilizing national platforms to offer quality AI courses.
(2) Nurturing high-level talents for the smart era. Promote AI as a general foundational course in universities, compile course textbooks categorized by disciplines and majors, and encourage all students to master AI knowledge. Based on the characteristics of AI technology, create “short, practical, and new” frontier innovation courses. Optimize talent cultivation schemes for traditional disciplines and majors, guide universities in offering AI cross-integration courses, and enrich interdisciplinary and cross-professional course groups to cultivate composite cross-disciplinary talents. Adjust the setting of disciplines and majors according to the intelligent upgrading of the industrial structure, and establish a batch of new disciplines and majors adapted to new technologies, industries, and business formats. Integrate the strengths of high-level research universities, leading technology enterprises, and national laboratories to deepen interdisciplinary integration, the integration of industry and education, and the convergence of science and education, exploring new models for cultivating top-notch innovative talents in AI.
(3) Promoting the upgrade and transformation of traditional majors in vocational education. Timely assess the structural impact of AI on vocational education, adjust and optimize requirements for skilled talent cultivation, and promote the intelligent upgrading of traditional majors. Scientifically design “AI+” professional systems, curriculum systems, and teaching systems to improve the alignment of professional settings with industrial development. Align with the national AI industry development needs, focus on nurturing emerging and future industries, implement high-skilled talent cluster cultivation plans in the AI field, and jointly formulate talent cultivation schemes with industry enterprises. Update curriculum systems, co-build internship, training, and practice bases, and provide targeted training for high-skilled talents in emerging positions.
(4) Promoting AI general education for the whole society. Continuously enrich digital resources on national platforms, aggregate and develop AI general education resources, and encourage universities and enterprises to develop specialized AI resources open to teachers, students, and social learners. Incorporate AI into the “Double Thousand” plan for improving the employability of university students, and encourage the offering of relevant micro-major courses and micro-certificate projects to support high-level employment. Leverage the role of universities and the Open University system to customize and develop AI literacy and skill courses for key groups, provide personalized post-vocational training services, and promote the inclusion of relevant learning outcomes into credit banks. Optimize and adjust the professional layout and talent cultivation schemes for formal continuing education, and support self-study examinations in offering AI-related majors.
(5) Improving the smart literacy and skills of teachers. Formulate smart literacy standards for teachers, clarifying the AI literacy and capabilities they should possess. Conduct tiered and categorized AI literacy training based on different job requirements to achieve full coverage through various means. Build contextualized assessment systems, develop intelligent and graded assessment tools, and encourage regions and schools to conduct large-scale teacher literacy assessments, targetedly improving teacher literacy and capability based on assessment results. Promote the reform of teacher education, incorporating frontier technology knowledge such as AI into the curriculum and updating the knowledge system. Include AI in teacher qualification examinations and certification content, and establish smart education projects in national and provincial teaching achievement awards to stimulate the endogenous drive for AI innovation.
III. Promoting Deep and Extensive Integration of AI and Education
(6) Utilizing AI to empower student learning. Based on promoting the comprehensive development of students in morality, intelligence, physique, aesthetics, and labor, develop intelligent study companions. Develop large models for ideological and political education, enrich smart applications in this field, and establish a holographic, cross-domain, all-member, and all-time immersive education model. Construct digital student files to dynamically optimize learning paths based on students’ abilities, traits, and interests, better meeting diversified learning needs. Explore effective paths for AI to empower physical education, aesthetic education, labor education, and science education to help students grow personally. Promote the application of smart technologies in central and western regions and rural schools to help students conduct independent learning, promote the national common language and script, and foster high-quality and balanced education. Develop and apply intelligent assistive devices to support the monitoring, assessment, and rehabilitation training of students in special education, promoting inclusive educational development.
(7) Utilizing AI to empower teacher instruction. Focusing on the entire process of education and teaching before, during, and after class, strengthen the application of intelligent teaching systems to reduce burdens and increase efficiency for teachers. Support teachers’ lesson preparation, assist in learning situation analysis, and support the automatic generation of multi-modal teaching resources, plan optimization, and teaching process simulation to achieve human-machine co-creation in lesson preparation. Explore human-machine collaborative teaching models, utilize smart systems to participate in teaching segments, and develop highly interactive virtual simulation experiments to enhance immersive experiences and personalized evaluation feedback, improving classroom effectiveness. Assist teachers in homework management, promoting intelligent grading, Q&A, and tutoring. Utilize smart technology to analyze classroom teaching behavior, conduct AI evidence-based teaching and research practices, and construct a teacher training model adapted to the smart era to help teachers improve teaching quality.
(8) Utilizing AI to empower educational governance. Focus on convenient services, precise management, and scientific decision-making to create an “Educational Intelligent Brain.” Build a national big data platform for talent supply and demand docking to conduct talent demand surveys, predictive analysis, and evaluation feedback. Use smart technology to scientifically predict population changes and industrial development trends, and improve mechanisms for the overall allocation of resources and the adjustment of discipline and major settings. Promote applications such as intelligent item generation, intelligent paper construction, intelligent proctoring, and intelligent grading. Develop intelligent tools for educational evaluation, exploring longitudinal evaluation of the entire learning process and horizontal evaluation of all elements including morality, intelligence, physique, aesthetics, and labor. Build an intelligent employment service system to achieve intelligent recommendation of job positions for university students and promote high-quality and full employment for graduates. Efficiently analyze massive multi-modal monitoring data to improve real-time early warning and emergency response capabilities for campus safety risks, supporting the construction of safe campuses.
(9) Utilizing AI to empower scientific research. Focusing on natural sciences, engineering sciences, and philosophy and social sciences, explore the construction and promotion of scientific agents and intelligent tools through forms such as “揭榜挂帅” (open competition for selecting the best candidates) to help researchers discover and summarize laws and solve complex problems. Build AI interdisciplinary innovation platforms, strengthen multi-disciplinary fusion development driven by AI, expand knowledge boundaries, and accelerate the exploration of new research paradigms in the smart era. Promote the intelligent upgrading of basic research platforms and technological infrastructure, build intelligent laboratories and autonomous experimental clusters to achieve automated design of experimental plans, execution of experiments, and analysis of data, improving the efficiency of scientific innovation. Deepen the application of the “Ke Jiao Hui” (Scientific Exchange) agent on the university technological achievement trading platform to achieve intelligent perception of enterprise needs and intelligent matching of converted achievements, nurturing new quality productive forces.
IV. Strengthening the Basic Environment for “AI + Education”
(10) Constructing an intensive and efficient smart education foundation. Build a national education intelligent computing service platform to effectively aggregate AI innovation resources such as computing power, data, models, and tools. Make good use of education and research computer networks to connect national computing training grounds, national computing hubs, enterprises, and universities, integrating intelligent, general, and supercomputing resources from all parties. Encourage provincial educational administrative departments to utilize the national integrated computing network to provide computing power guarantees for AI applications. Organize the development of national basic corpora focused on ideological and political education, disciplinary knowledge, and scientific research, and encourage local authorities and universities to develop domain-specific characteristic datasets. Strengthen the National Education Big Data Center, establish a cross-departmental, cross-regional, and cross-platform data network, and explore dynamic update mechanisms based on platforms, journals, and terminals. The state will conduct organized research and development of AI education large models categorized by educational stages, strengthening capabilities in value alignment, logical reasoning, and safety ethics to provide support for local and university applications, effectively avoiding resource waste and low-level repetitive construction.
(11) Nurturing a co-created and shared intelligent application system. Deeply promote the intelligent upgrade of national platforms to achieve personalized resource recommendation, intelligent service processing, and intelligent data analysis. Establish a collaborative mechanism between higher education institutions and primary/secondary schools to jointly develop AI curricula and applications. Plan and build national AI (Education) application pilot bases, providing public products such as students’ knowledge, ability, and quality maps to lower the threshold for application innovation, nurture application service systems, and accelerate the implementation of smart products and services. Build AI learning communities, aggregate open-source courses, provide innovative resources, and conduct achievement certification. Encourage teachers and students to participate in the open-source ecosystem, achieving co-construction of corpora, co-testing of models, and co-creation of applications to continuously nurture high-quality educational intelligent applications. Establish an evaluation system for intelligent application capabilities, selecting educational agents for different educational roles and scenarios to be launched on national platforms. Organize AI pioneering application scenario projects to create a batch of high-value benchmark applications.
(12) Creating a future educational space integrating virtual and real worlds. Create future classrooms, future schools, future learning centers, and future training centers to bridge the “last mile” of AI application. Deploy teaching and practice capability centers in key discipline areas, creating high-quality AI interdisciplinary courses and practice projects to support intelligent upgrades of disciplines. Pilot the development of digital textbooks, launch a new generation of smart MOOCs, deepen the construction of virtual simulation experiments, enrich the forms of digital education resources, and build immersive teaching spaces and new human-machine collaborative teaching models. Promote the application of intelligent terminals, build student user profiles through big data analysis, and configure learning resources centered on students to support personalized learning within large-scale education. Integrate educational large models and agent tools to create a batch of thematic learning scenarios, promoting project-based, inquiry-based, and scenario-based education, guiding students to learn how to think and cultivating capabilities competent for the smart era.
V. Optimizing the “AI + Education” Development Ecosystem
(13) Carrying out research and innovation in “AI + Education”. Promote the intersection of AI with cognitive science, brain science, psychology, pedagogy, and other multi-disciplinary fields, innovate educational research paradigms, and deepen the understanding of educational laws and cognitive development. Continuously conduct AI social experiments, deepen research on AI ethics, and scientifically evaluate the impact of technology on education. Build a technical innovation system for “AI + Education,” strengthen joint research platforms and educational practice research bases, organize research on common key technologies, and encourage universities, enterprises, and research institutes to participate in the “AI + Education” ecosystem. Guide long-term, patient, and strategic capital from both state-owned and social sectors into educational technology innovation, promoting more advanced technologies to serve human development.
(14) Strengthening condition guarantees for “AI + Education”. Strengthen systems for AI education training, application innovation, technology R&D, and safety assurance, and build an educational policy and system framework adapted to AI development requirements. Encourage educational institutions, enterprises, and research units to focus on AI applications in the education sector, large model evaluation, and data security to develop a batch of standards and specifications. Innovate the model for talent team building, introduce talents from universities and enterprises to participate in construction, and nurture a composite, high-level engineering technology team. Support and encourage innovative investment models such as purchasing services, and build a diversified investment mechanism led by the government with the participation of universities, society, and enterprises.
(15) Promoting international cooperation in “AI + Education”. Continue to host international conferences such as the World Digital Education Conference, the World MOOC and Online Education Conference, and the International Conference on AI and Education. Strengthen the AI Open Alliance, the World Digital Education Alliance, and the World MOOC and Online Education Alliance to create a series of international exchange flagship platforms. Fully leverage bilateral and multilateral mechanisms to promote international educational cooperation by country and region, sharing multilingual AI courses, educational large models, and agents, and strengthening mutual learning and appreciation of high-quality educational resources and experiences. Actively participate in global education governance, relying on platforms of important international organizations such as UNESCO, and deeply participate in the formulation of international agendas, rules, and standards in the field of AI education, continuously enhancing the international influence of China’s digital education.
(16) Building a solid safety barrier for “AI + Education”. Establish a safety protection system for AI educational applications and determine safety protection standards by category and level. Deepen the establishment of safety review mechanisms for educational large models to ensure that generated content is positive, healthy, and benevolent. Establish safety assessment standards for AI educational applications, ensuring the safety of model algorithms, data resources, infrastructure, and application systems in an integrated manner, and ensuring that technical applications comply with educational laws. Promote software legalization to ensure that AI applications are safe, credible, and controllable. Strengthen the management of AI entering campuses, clarifying application specifications for smart products and terminals. Improve mechanisms for AI evaluation and filing, technical monitoring, risk early warning, and emergency response, effectively preventing problems such as AI-facilitated fraud, academic misconduct, examination-oriented “involution,” and privacy leaks.
VI. Organization and Implementation
Adhere to the Party’s leadership throughout the entire process of “AI + Education,” strengthening organizational leadership, overall planning, guidance, supervision, and condition guarantees. The education department is responsible for formulating the action plan and coordinating its implementation; the development and reform department will strengthen overall coordination and support the construction of projects that meet requirements; the science and technology department is responsible for strengthening research layouts in key fields; and the industry and information technology and data management departments are responsible for providing policy support and promoting open source and data interconnectivity. Regions and schools should incorporate “AI + Education” into their development plans, formulate implementation schemes tailored to their own realities, and actively carry out application demonstrations. Strengthen the construction of think tanks and consulting agencies, strengthening policy strategy research, frontline guidance, and suggestions. Organize special training to enhance the AI leadership of management officials. Deeply implement pilot actions for AI-empowered education, build a normalized application supervision mechanism based on data, and timely summarize and publicize excellent experiences and practices.