Abstract:
As artificial intelligence technology permeates various fields of society, general education in AI for primary and secondary schools has become a key pathway for cultivating the core competencies of future citizens. Based on years of frontline teaching experience and in conjunction with the trend of digital transformation in education, this article proposes the “Six Principles” (Directional, Inclusive, Integrative, Safe, Comprehensive, and Appropriate). Through case analysis and theoretical discussion, it explores effective strategies for implementing AI education in primary and secondary schools, providing practical references for educators.
Keywords:
Primary and Secondary Education; General AI Education; Six Principles; Digital Transformation in Education
1. Introduction
From AlphaGo defeating human players to ChatGPT prompting global educational reflection, AI technology is reshaping human cognition and production methods. The Ministry of Education’s “Outline for Building a Strong Education Nation (2024-2035)” clearly states that “AI education in primary and secondary schools will be fully popularized before 2030,” marking the transition of this field from pilot exploration to large-scale implementation. However, grassroots schools generally face challenges such as fragmented curriculum design, lagging teacher capabilities, and a lack of ethical education. This article, based on long-term teaching observations, proposes a framework of the “Six Principles” aimed at providing systematic solutions to practical problems.
2. The Connotation and Implementation Path of the “Six Principles”
(1) Directional: Anchoring the fundamental task of moral education
Adhering to the principle of student-centered education, following the laws of student growth and educational teaching, cultivating students’ correct values, essential qualities, and key abilities to adapt to the development of AI technology, helping students become ideal, capable, and responsible new individuals of the era. AI education is not about piling up technology, but about transforming the way of educating. A key high school in Beijing has included “AI Ethics” as a compulsory course, guiding students to think about the relationship between technology and humanity through a simulated debate on “responsibility determination in autonomous driving accidents.” This design reflects two major directions:
Value Guidance: Integrating the principle of “fairness” into algorithm design courses, for example, requiring students to consider the usage scenarios for disabled individuals in a garbage classification robot project. For instance, AI’s public welfare practices in medical emergencies and rural education. Only by deeply integrating technology education with value shaping can we ensure that students establish a correct view of technology ethics and social responsibility while mastering technology.
Capability Reconstruction: Breaking down disciplinary barriers, deeply integrating AI with subjects such as Chinese, mathematics, and physics, for example, by using Python to write a classical poetry generator, which not only teaches programming but also deepens literary understanding.
(2) Inclusive: Building a fair and high-quality educational ecosystem
In the context of building a strong education nation, leading the direction of primary and secondary education reform, optimizing resource allocation and supply, ensuring that every child can access AI enlightenment, and ensuring that all students have fair and high-quality opportunities for AI education.
A rural middle school has achieved zero threshold AI education through the “Three Ones” project:
One Smart Board: Utilizing resources from the national primary and secondary school smart education platform, conducting virtual robot programming teaching through interactive electronic whiteboards.
One Toolbox: Equipped with low-cost open-source hardware (such as Micro:bit), allowing students to complete a smart temperature-controlled fan project with a budget of 200 yuan.
One Teaching Team: Through the “Double Teacher Classroom” model, urban elite school teachers provide remote guidance, while local teachers assist in practice. Currently, some schools face uneven distribution of AI education resources due to differences in hardware facilities and teacher strength. To solve this problem, three approaches are needed: first, the education department can develop free course packages suitable for different educational stages through the “AI Education Resource Cloud Platform,” covering lightweight content such as animated micro-lessons and interactive experiments; second, promote “low-cost AI teaching tools,” such as using open-source hardware (like Arduino) to make simple robots, or conducting logical training through graphical programming software (like Scratch) to lower equipment thresholds; third, establish a “pairing support mechanism for urban and rural AI education,” allowing rural students to share high-quality resources through live classrooms and teacher rotation.
(3) Integrative: Creating interdisciplinary innovation fields
Building a collaborative mechanism led by the government, schools, families, and industries, through technological integration and innovative practice, to create a new ecosystem for AI education in primary and secondary schools.
Breaking down disciplinary barriers to achieve cross-field penetration; AI itself is a product of interdisciplinary intersection, and its education must be deeply integrated with subject teaching. For example:
In mathematics classes, explaining statistical knowledge through “probability calculations in AI image recognition”;
In Chinese teaching, using the “AI essay correction system” to analyze language logic while guiding students to explore the differences between “machine writing and human creation”;
In science classes, introducing the “sensor principles of smart greenhouses” to explain the integration of physics and biology knowledge. Additionally, project-based learning (PBL) can be used to allow students to integrate knowledge from engineering, art, programming, and other disciplines around real tasks such as “designing a smart waste classification system for the campus,” cultivating their ability to solve complex problems.
(4) Safety: Building a robust ethical protection network for technology
In line with the trends of digital education and AI technology development, constructing a comprehensive protection mechanism covering data security, ethical review, and technical risk prevention.
Establishing a dual defense line for ethics and privacy, primary and secondary school AI education must establish a consciousness that emphasizes both “technology” and “safety.”
1. Ethical Education: Setting up discussion classes on “AI Code of Conduct,” such as the “trolley problem” in autonomous driving and the privacy boundaries of facial recognition.
2. Practical Norms: Using simulated datasets instead of real student information in teaching, and employing domestic encryption technology on programming platforms.
3. Legal Awareness: Inviting experts to interpret the “Data Security Law” and organizing simulated courts for “AI infringement cases.”
(5) Comprehensive: Achieving the integration of “Knowledge-Skills-Thinking-Values”
Focusing on the comprehensive development of students, closely linking core competencies with students’ thoughts, learning, and life realities, meeting the intelligent needs of primary and secondary students, and enhancing their wisdom. This can stimulate students’ curiosity, imagination, and creativity, increase their knowledge and understanding, improve their ability to discover and solve problems, and enhance their overall quality, achieving comprehensive quality education.
Balancing the multidimensional cultivation of knowledge, ability, and thinking. General AI education is not simply training in programming skills, but should be a comprehensive development of “Knowledge + Ability + Thinking”:
Knowledge Level: Allowing students to understand the basic concepts of AI (such as image recognition, voice interaction) and social applications (such as smart transportation, medical diagnosis);
Ability Level: Cultivating logical thinking (such as step-by-step thinking in algorithm design) and innovative ability (such as proposing solutions for AI to improve life);
Thinking Level: Focusing on cultivating “computational thinking,” which is the process of transforming real-world problems into computable and decomposable logical processes, for example, having students use “flowcharts” to describe “how AI recognizes a cat.” This comprehensive cultivation can prevent students from falling into the trap of “toolism” and truly understand the essence and value of technology.
(6) Appropriateness: Following the laws of cognitive development
Meeting the cognitive development levels of primary and secondary students, satisfying the learning needs of students at different stages (primary, middle, and high school), and cultivating students’ core competencies to adapt to an intelligent society. Through the organic integration of knowledge, skills, thinking, and values, forming a four-dimensional AI literacy, nurturing technological innovation thinking, critical thinking, human-machine collaboration ability, AI literacy, and social responsibility awareness.
Following cognitive laws and teaching according to students’ needs. Primary and secondary school AI education must align with students’ age characteristics, avoiding the tendency of “adultification”:
Primary Stage:: AI education can be initiated through gamified learning, such as using “AI riddles” and “robot dancing” as fun activities to stimulate learning interest;
Middle Stage:: Simple graphical programming can be introduced, such as creating an “AI dialogue robot,” focusing on logical training;
High Stage:: Students can appropriately engage with Python programming and basic machine learning models, understanding algorithm principles through projects like “training an AI model for waste classification.” At the same time, attention should be paid to individual differences among students, offering AI clubs and organizing participation in science and technology competitions for students who excel, while focusing on experiential learning for those with weaker foundations, ensuring that “students from different starting points can all gain something.”
3. Practical Reflections and Future Prospects
(1) Existing Problems
Teacher Shortage: Surveys show that 78% of rural schools lack full-time AI teachers.
Resource Imbalance: Investment in AI laboratory construction in eastern regions is 5.2 times that of western regions.
Evaluation Lag: The existing examination system is difficult to measure the effectiveness of AI education.
(2) Response Strategies
Teacher Training: Establish a three-tiered system of “National Training – Provincial Training – School Training,” focusing on training the ability to integrate “AI + Subject” teaching.
Resource Sharing: Relying on the national smart education platform, create an “AI Education Cloud Warehouse” to enable the flow of high-quality resources across schools.
Evaluation Reform: Develop an “AI Literacy Growth Archive” to record students’ project practices, ethical reflections, and other process data.
(3) Future Vision
With breakthroughs in technologies such as brain-computer interfaces and quantum computing, AI education in primary and secondary schools will evolve towards “embodied intelligence.” For example, real-time collection of students’ physiological data through wearable devices can dynamically adjust teaching strategies; using metaverse technology to create a blended learning space. These changes require educators to maintain a lifelong learning mindset, embracing technological changes while adhering to the essence of education.
Advancing AI education in primary and secondary schools requires using the “Six Principles” as a compass: upholding the original intention of education in directionality, promoting educational equity in inclusiveness, breaking down disciplinary barriers in integrativeness, establishing a solid development baseline in safety, achieving competency enhancement in comprehensiveness, and respecting growth laws in appropriateness. Only in this way can AI education truly become a beacon illuminating students’ futures.
References:
1. The Ministry of Education’s Basic Education Teaching Guidance Committee officially released the “Guidelines for General AI Education in Primary and Secondary Schools (2025 Edition)”
2. Steadily advancing general AI education in primary and secondary schools
3. Implementation strategies for general AI education in primary and secondary schools
Attachment:
Guidelines for General AI Education in Primary and Secondary Schools
(2025 Edition)
General AI education in primary and secondary schools refers to foundational education aimed at all primary and secondary students, through systematic courses, activities, and practices, to popularize the basic concepts, technical principles, application scenarios, ethical safety, and social impacts of AI. Promoting general AI education in primary and secondary schools is an important measure to meet the demands of the times, implement the fundamental task of moral education, deepen educational reform, promote the comprehensive development of students, and accelerate educational modernization, building a strong education nation and a strong technological nation. This guideline is formulated to promote the popularization and development of general AI education in primary and secondary schools, enhance students’ AI literacy, and strengthen education’s support for technology and talent. 1. Guiding Ideology Guided by Xi Jinping’s Thought on Socialism with Chinese Characteristics for a New Era, thoroughly implementing the spirit of the 20th National Congress of the Communist Party of China, the Third Plenary Session of the 20th Central Committee, and the strategic deployment of the “Outline for Building a Strong Education Nation (2024-2035),” fully implementing the Ministry of Education’s notice on strengthening AI education in primary and secondary schools, adapting to the rapid development of AI technology, focusing on enhancing students’ core competencies, emphasizing the cultivation of innovative thinking and practical abilities, promoting the deep integration of general AI education with primary and secondary education, constructing a new ecosystem for AI education in primary and secondary schools, and serving the cultivation of top innovative talents that support the development of new productive forces, providing solid support for educational modernization and building a strong education nation.2. Basic Principles(1) Adhering to moral education and developing competencies. Fully implementing the fundamental task of moral education, following the laws of student growth and educational teaching, cultivating students’ correct values, essential qualities, and key abilities to adapt to the development of AI technology.(2) Adhering to proactive leadership and equitable inclusiveness. Leading the direction of primary and secondary education reform, optimizing resource allocation and supply, ensuring that all students have fair and high-quality opportunities for AI education.(3) Adhering to multi-party participation and integrative innovation. Constructing a collaborative mechanism led by the government, schools, families, and industries, through technological integration and innovative practice, to create a new ecosystem for AI education in primary and secondary schools.(4) Adhering to future orientation and safety control. In line with the trends of digital education and AI technology development, constructing a comprehensive protection mechanism covering data security, ethical review, and technical risk prevention.3. Cultivation Goals Constructing a layered, progressive, and spiral general AI education system for primary and secondary schools, cultivating students’ core competencies to adapt to an intelligent society. Through the organic integration of knowledge, skills, thinking, and values, forming a four-dimensional AI literacy, nurturing technological innovation thinking, critical thinking, human-machine collaboration ability, AI literacy, and social responsibility awareness.(1) Primary Stage Focus on experience and interest cultivation in cognition. Perceiving the value of technology, understanding basic AI technologies such as voice recognition and image classification, and establishing a preliminary understanding of technology through interaction with smart devices. Emphasizing basic application abilities in skills. Mastering the basic operations of simple AI tools, completing simple instruction designs through visual programming tools, and initially practicing data collection and labeling methods. Valuing the cultivation of basic thinking in thinking. Enlightening logical thinking, training the foundation of computational thinking through task decomposition, and cultivating a basic sense of questioning by comparing the differences between AI and human behavior. Focusing on cultural awareness and safety habits in values. Establishing safety awareness, experiencing the duality of technology through AI cultural creation activities, and building a basic understanding of privacy protection and digital identity.(2) Middle Stage Emphasizing understanding of technical logic in cognition. Mastering the basic processes of machine learning and the concept of supervised learning, understanding the relationship between data features and algorithm selection. Emphasizing practical problem-solving in skills. Completing simple data organization and analysis tasks through project-based learning, and developing scene-based applications through agent construction. Valuing the development of engineering thinking in thinking. Forming a technical decision chain of “demand analysis – technology adaptation – effect evaluation” and cultivating critical awareness of systematic analysis and dialectical thinking. Deepening ethical awareness in values. Understanding the strategic significance of independent innovation in AI technology, and discerning the risks of false information in the application of generative AI technology.(3) High Stage Strengthening technical strategy in cognition. Understanding the characteristics and social impacts of generative AI technology, and understanding the practical applications and significant impacts of AI in national strategies such as smart cities and national defense security. Emphasizing innovative applications in skills. Constructing simple AI algorithm models and optimizing performance, developing interdisciplinary comprehensive AI solutions based on agent tools. Strengthening systematic thinking in thinking. Establishing a three-dimensional thinking model of “technical principles – system architecture – social impact,” cultivating interdisciplinary systematic thinking in innovative project practices. Emphasizing social responsibility in values. Examining the sovereignty of AI technology from the perspective of national science and technology strategy, balancing technological innovation and social risks in complex ethical situations.4. Main Tasks To promote the solid implementation of general AI education in primary and secondary schools, suggestions for implementation are proposed around classroom teaching, organization and implementation, teaching evaluation, and research support, providing references for schools to integrate general AI education into teaching practice and enhance the effectiveness of cultivating students’ AI literacy.(1) Classroom Teaching1. Improving the regular curriculum system. Integrating AI education into the school-based curriculum implementation plan, constructing a curriculum system that organically connects with information technology, science, and comprehensive practice courses. Flexibly adopting independent course offerings, interdisciplinary integration, and practical activities to form a tiered and coherent teaching arrangement.2. Designing differentiated teaching content. Designing differentiated teaching content and practical tasks based on students’ age characteristics and cognitive levels, focusing on smart technology experience and interest cultivation in the primary stage, reinforcing understanding of technical principles and basic applications in the middle stage, and emphasizing systematic thinking and innovative practice in the high stage. Developing teaching projects and practical tasks in layers according to the characteristics of different educational stages.3. Exploring innovative teaching methods. Utilizing a combination of lecturing, inquiry-based, project-based, and experiential teaching methods, enhancing student participation and learning effectiveness through case analysis and interactive practice. Appropriately using AI technology to optimize classroom interaction, enhancing the fun and effectiveness of teaching, guiding students to subtly perceive technology applications, understand technical principles, master basic skills, and form ethical awareness in their daily learning and life.(2) Organization and Implementation1. Building a practical activity system. Combining AI education with campus cultural activities, regularly conducting science and technology festivals, technical challenges, and innovation project exhibitions. Organizing students to participate in technology experiences and social research through channels such as study tours and after-school services, reinforcing the integration of knowledge and action.2. Strengthening resource coordination and construction. Relying on resources from the national primary and secondary school smart education platform, coordinating the construction of on-campus and off-campus laboratories, practical bases, etc. Improving the configuration of teaching equipment through school-enterprise cooperation and inter-school sharing, establishing a dynamic updating mechanism for teaching resources to meet the basic practical teaching needs.3. Improving the collaborative education mechanism. Establishing a collaborative mechanism involving schools, families, and social support. Expanding students’ learning space through parent classrooms, school-enterprise cooperation projects, and community services. Forming a teaching guidance team composed of subject teachers, technical personnel, and industry experts.(3) Teaching Evaluation1. Constructing a diversified evaluation system. Developing a school-based evaluation index system around the four dimensions of “Knowledge-Skills-Thinking-Values.” Adopting performance evaluation methods such as project presentations, project defenses, and practical operations, emphasizing the combination of process evaluation and outcome evaluation.2. Improving the evaluation implementation mechanism. Relying on digital technology to record learning process data, forming students’ AI literacy growth archives. Establishing a multi-dimensional evaluation mechanism involving teachers, students, and parents, exploring the reasonable application of AI technology in teaching evaluation.3. Strengthening the application of evaluation results. Encouraging the exploration of incorporating AI literacy into students’ comprehensive quality evaluation, using evaluation results to improve teaching practices, and establishing a mechanism for showcasing and exchanging excellent outcomes. By establishing an innovation incentive mechanism, promoting the transformation and application of students’ practical achievements in campus scenarios.(4) Research Support1. Strengthening the construction of the teaching staff. Incorporating AI teaching capabilities into the teacher training system, conducting tiered general training and specialized research. Establishing a cross-disciplinary research community to enhance teachers’ course implementation capabilities through collective lesson preparation and lesson study.2. Deepening research activities. Forming a school-level AI teaching research team to conduct research on curriculum development, teaching strategies, and other topics. Encouraging teachers to participate in cultivating teaching outcomes, promoting the localization of high-quality teaching resources and their application.3. Building school-based resources. Encouraging teachers to develop AI teaching courseware, practical projects, and digital teaching resources based on high-quality resources from national platforms, combined with school conditions and student situations. Supporting schools to collaborate with units that compile and publish information technology textbooks to simultaneously build supporting digital resources, ensuring that teaching content is universally applicable and practical.5. Guarantee System(1) Educational administrative departments to promote and guarantee coordination1. Strengthening planning guidance. Formulating differentiated promotion plans based on regional characteristics, adhering to overall planning, strengthening top-level design and departmental collaboration, and establishing a multi-departmental joint working mechanism to provide necessary policy support and resource guarantees for implementing general AI education.2. Building infrastructure. Increasing investment in the construction of AI education infrastructure, establishing primary and secondary school AI education bases in batches, evenly distributing AI laboratory resources in primary and secondary schools, and upgrading and optimizing existing digital teaching environments and facilities. Promoting the opening of AI laboratories, exhibition halls, and other venues from universities, research institutes, and high-tech enterprises to primary and secondary schools.3. Enriching the teaching staff. Incorporating the training of AI education teachers into the teacher training plan, improving teachers’ professional levels through systematic training. Encouraging regions and schools with conditions to enrich the AI education teacher team, actively introducing qualified professionals from universities, research institutes, and high-tech enterprises to serve as part-time AI education teachers, promoting large-scale teacher supply.4. Promoting pilot demonstrations. Coordinating the pilot work of general AI education, encouraging regions with conditions to take the lead in exploring innovative practice models for general AI education, establishing a community of innovative practice among pilot schools, and effectively promoting the high-quality development of general AI education.5. Coordinating urban and rural development. Increasing support for general AI education in rural and remote schools, promoting the flow of high-quality teacher resources, and utilizing national platforms to achieve interconnectivity of AI education courses between urban and rural schools. Encouraging urban and rural schools to carry out paired support activities, sharing teaching experiences, and promoting balanced development of AI education.6. Improving evaluation monitoring. Establishing a dynamic monitoring and evaluation system for students’ AI literacy, scientifically assessing the effectiveness of AI education, and promoting the professionalization and standardization of general AI education.7. Strengthening safety management. Formulating data security management regulations for AI education, clarifying safety standards for data collection, storage, transmission, and use, establishing privacy protection mechanisms, and regulating the application access of AI teaching tools and products to ensure the safe and compliant use of data and the protection of teachers’ and students’ rights.(2) Family collaboration to expand educational scenarios1. Creating a healthy atmosphere. Encouraging parents to cultivate students’ ethical awareness and sense of responsibility regarding AI in the family environment, jointly creating a healthy, safe, and rational atmosphere for AI applications, guiding students to form correct technological values, and promoting the scientific application of AI technology in the growth process of young people.2. Utilizing social resources. Encouraging parents to fully utilize AI laboratories, exhibition halls, and other open venues from universities, research institutes, and high-tech enterprises, as well as public resources such as libraries and science and technology museums, to expand the scenarios for students to engage in AI practice and enrich their learning experiences.3. Innovating educational models. Encouraging parents to guide students to actively participate in research and practice and exchange activities, promoting the organic integration of AI with students’ personal lives, campus life, and social life, forming a three-dimensional educational model that connects classroom learning, family extension, and social practice.4. Strengthening home-school linkage. Establishing a collaborative education mechanism involving families and schools. Encouraging parents to understand the learning focuses of AI education at each educational stage, grasp students’ learning progress and personalized needs, actively cooperate with school education work, and jointly guide students to participate in AI education practice activities.(3) Social enterprises deepening the integration of industry and education resources1. Improving integration mechanisms. Perfecting the industry-education cooperation education system, encouraging enterprises to jointly develop general AI education courses with schools, and collaboratively designing experiential learning projects that organically integrate cutting-edge industry technologies with educational resources.2. Sharing high-quality resources. Actively fulfilling social responsibilities, opening public general AI education resources to the public, providing free and inclusive learning resources for teachers and students, and promoting the equitable popularization of general AI education.3. Optimizing product services. Encouraging leading AI companies and educational technology companies to develop adaptable and scientifically sound teaching tools and course products based on advanced technologies and educational experiences, according to the cognitive characteristics of primary and secondary students and the requirements of AI courses, accelerating the construction of high-quality, professional AI education products and services.4. Opening practical bases. Encouraging universities, research institutes, and enterprises to rely on their advanced AI laboratories, exhibition halls, and practical bases to provide immersive and easily operable AI practice activities for primary and secondary schools according to the principles of orderly opening and mutual benefit, effectively enhancing students’ AI literacy and stimulating their innovative awareness and creative potential.
“Life has no ifs, fate has no assumptions; do not try your best, but give your all; if you want to be irreplaceable, you must be different.”