The State Council recently released the “Opinions on Deepening the Implementation of the Artificial Intelligence + Initiative,” which includes the deployment of “promoting AI education across all school stages and general education for the whole society.” This marks the transition of AI education in primary and secondary schools from a “pilot exploration” phase to a “systematic promotion” phase. The opinions focus on AI education and talent cultivation, constructing four core orientations: “coverage – cultivation – support – collaboration,” providing a clear direction for implementation.
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Coverage: All School Stages + Whole Society
AI Literacy as a Fundamental Skill
The policy clearly states a dual path of “education across all school stages + general education for the whole society,” breaking the limitations of previous AI education characterized by “discontinuity across school stages and singular scenarios.” General education for the whole society promotes the collaboration of “schools + families + communities,” transforming AI literacy from an “optional study” to a “necessary skill.”
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Cultivation: Breaking Traditional Frameworks
Strengthening the Foundation of Talent Development
The policy targets a dual goal of “high-level talents + leading talents,” focusing on “capability building” during the primary and secondary school stages. It moves beyond mere “technical operation training” to innovative cultivation models, such as involving students in real AI application projects, exercising logical thinking and creativity in problem-solving, laying a dual foundation of “interest + capability” for future AI talent development.
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Support: Focusing on Teacher Development
Breaking Through Core Bottlenecks
“Teacher development” is a key focus emphasized by the policy, directly addressing the current pain points of AI education, such as “insufficient technical ability of teachers and outdated teaching methods,” aiming to solve the problem of “wanting to teach but not knowing how to teach.”
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Collaboration: Building a Diverse Ecosystem
Breaking the Isolation of Education
The policy promotes an ecosystem of “industry-education integration + interdisciplinary cultivation + international cooperation,” allowing primary and secondary school AI education to move away from “singularity and isolation.”
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Forward-looking Layout
Daku Enters AI Education in 2023
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As AI technology deeply integrates into life, technology education has completed its iteration from “1.0” to “3.0,” with each generation’s core changes directly addressing educational pain points. Daku has already anchored its layout in the “3.0 era” in 2023, proactively meeting the “capability building” requirements of the Opinions:
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1.0 Era (Knowledge Transmission):
The core is “teaching theory, memorizing concepts,” primarily through textbook explanations, only conveying abstract knowledge such as basic computer skills and AI definitions. Children passively receive information without hands-on practice, leading to a disconnect between knowledge and life, making it difficult to form practical abilities;
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2.0 Era (Skill Training):
The core is “practicing operations, using tools,” incorporating simple programming or hardware usage, such as Scratch module dragging and basic sensor operations. However, it is limited to single skill practice, not integrating with real scenarios, and does not cultivate foundational thinking. Children only know how to “follow instructions” but do not understand “application;”
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3.0 Era (AI-Driven Literacy Development):
Daku synchronously lays out the 3.0 era, developing “AI + hardware” dual-track courses to achieve an educational upgrade focused on “literacy orientation.”
Goal Upgrade: Shifting from “single skill mastery” to “comprehensive literacy cultivation,” focusing on core competencies required in the AI era;
Scenario Implementation: Moving from “disconnected from life” to “real application,” allowing classroom content to connect with the principles of AI devices in life, achieving “learning is using;”
Ecological Collaboration: Transitioning from “independent teaching” to “multidimensional integration,” building a comprehensive AI teaching resource library across all school stages, forming a dedicated AI research team, and integrating interdisciplinary knowledge and project-based learning into the curriculum.
Literacy Development
Implementing Six Core Literacies for the AI Era
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The Opinions emphasize “capability building,” opposing “single technical training,” while children in the AI era need to possess six core literacies:
Cognitive Literacy (data awareness, algorithmic thinking),Innovative Thinking (design thinking, interdisciplinary integration), engineering thinking, computational thinking, critical thinking, and collaboration skills.
Daku Programming fully integrates these six literacies into the AI curriculum system, using project-based teaching to implement literacy development: no longer limited to “teaching programming and hardware,” but driven by tasks, allowing children to naturally develop abilities such as logical analysis, innovative design, and interdisciplinary integration while solving problems, perfectly aligning with the Opinions’ requirement to “exercise logical thinking and creativity.”
Age-Appropriate Adaptation:
Aligning with the Global AI Literacy Development Project’s Stage Requirements
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Daku designs age-appropriate courses around the three stages of “preschool – primary school – secondary school,” responding to the Opinions’ requirement for “coverage across all school stages:”:
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Preschool (3-6 years old)
In the “AIBL (AI Basics)” stage, the core is “learning through play.” Daku uses building block-type tools to cultivate children’s initial logical thinking and AI awareness, completing AI enlightenment;
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Primary School Stage (7-10 years old)
In the “AloT (AI + IoT)” stage, the core is “connecting everything intelligently.” Daku uses Scratch and makeblock hardware, combined with hands-on experience with smart devices, allowing children to intuitively understand the relationship between AI and the Internet of Things;
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Secondary School Stage (10-15 years old)
In the “AICD (AI Creative Development)” stage, the core is “intelligent creation without boundaries.” Daku uses mBlock & Arduino open-source hardware, combined with AIGC tools and Python programming, guiding children to break through hardware limitations and engage in AI creative development, exercising their ability to solve practical problems.
Teacher Development
Professional Team + Systematic Training
NOTICE ANNOUNCEMENT
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Top Research Team Foundation
Since 2017, the team has been formed, led by computer PhDs and NOI gold and silver medalists, including one postdoctoral researcher, three PhDs, and former engineers from Huawei/Baidu, as well as education experts from Peking University/North China Normal University, who understand technology and teaching, solving the problem of “insufficient teacher technology.”
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Teacher Qualifications are Guaranteed
All teaching staff are from computer backgrounds, all PTA certified, not only teaching programming but also guiding students in thinking, aligning with the requirement to “enhance teaching ability.”
(CCF PTA Programming Trainer Certification)
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Layered Training to Enhance Capability
Establishing “new teacher clearance + senior teacher advancement” training: new teachers practice AI knowledge and teaching methods, while senior teachers optimize courses in line with policies, ensuring adaptation to teaching across all school stages.
(Daku’s Annual Teacher Training)
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Competition Outlet: AI Education Practical Testing
Capability building needs to be exercised through real projects, and AI competitions serve as a natural testing ground for educational outcomes, forming a mature ecosystem covering all school stages and multiple levels. Daku deeply integrates these quality competition resources, organizing a large number of students to participate in practical training each year, through systematic competition preparation guidance, specialized training, and full-team support, helping students transform classroom learning into practical abilities.
Relying on a professional competition guidance system, students perform outstandingly in various AI competitions, with a high award rate validating the effectiveness of “literacy-oriented” teaching, further deepening children’s AI application abilities in real competitions, perfectly closing the educational loop of “learning – practice – testing.”
8 Years of Accumulation
Solidifying the Foundation of AI Education Services
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Daku Programming is a technology innovation company providing programming education services for youth aged 3-18. Over the past 8 years, it has opened more than twenty campuses nationwide and one high-tech R&D center, established a knowledge base operation center in Beijing, a national online course service center, and opened direct campuses in cities such as Shanghai, Beijing, Jinan, Xi’an, Qingdao, Zibo, Tai’an, Weifang, and Linyi.
In the 8 years of deepening children’s programming education, we have become a demonstration base for youth programming, a corporate member of the China Computer Federation, a council unit of the Shandong Artificial Intelligence Society, a council unit of the Jinan Computer Teaching Research Association, PTA certified, and a certification service center for the Blue Bridge Cup, ACSL, and software programming level examinations.
Daku widely conducts lectures on “Youth Programming and Artificial Intelligence” and “Programming in Schools” activities, currently collaborating with over 100 public schools, while promoting the pilot work of “AI teaching in primary and secondary schools” nationwide, conducting over 300 classes, impacting more than 100,000 primary and secondary school students.
Conclusion
Using Policy as an Anchor, Safeguarding Children’s AI Growth Path
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From responding to the Opinions’ requirement for “coverage across all school stages” with staged courses, to solving the “teacher bottleneck” with a professional team, to the service capabilities accumulated over 8 years, Daku has always aimed to “enable children to master core competencies in the AI era,” transforming policy requirements into visible and tangible teaching effectiveness. In the future, Daku will continue to deepen AI education, helping more children break the “information gap,” actively grow in the AI wave, and become future creators who understand technology and think critically.