一年覆盖2万学生后 学而思“给孩子的一节AI课”为何还在升级？

This article introduces the development and core content of "One AI Lesson for Kids", an AI science popularization public welfare program initiated by TAL. Key takeaways are as follows:

1. Program progress: The program launched its 1.0 version with a single trial class in 2025. Within one year, it partnered with volunteer teaching teams from 29 universities, reaching more than 120 primary schools across China and covering 20,000 students. It was upgraded to version 2.0 in 2026, adjusted to a 10-lesson series that systematically teaches core AI capabilities including text generation, text-to-image, and text-to-video.

2. Core curriculum design: The course features a "four-step questioning method" and a "structured prompt framework" to teach children how to interact with AI properly. It also includes dedicated sessions on AI hallucination, probabilistic output mechanisms and other foundational knowledge, helping students build habits of information verification and understand that AI cannot replace human judgment. This design aligns with China’s national requirements for AI literacy cultivation.

3. Supporting public welfare initiatives: TAL partnered with Peking University and other universities to launch the "Science Mentor" program to train frontline science teachers. It also donates teaching aids and learning tablets to grassroots primary schools, and assigns dedicated staff to track long-term program implementation and maintain continuous engagement with schools and students.

This article provides actionable insights for education brands on brand building, product layout and partnership models. Key takeaways are as follows:

1. Consumption trend and demand assessment: Today’s primary school students are the first generation growing up with AI. They already have scattered exposure to AI but lack systematic AI literacy cultivation. China’s 15th Five-Year Plan explicitly requires promoting AI education across all school stages and improving youth scientific literacy, making AI literacy education a policy-aligned blue ocean market.

2. Reference for brand marketing paths: Brands can adopt a "public welfare + core business" strategy to enter the grassroots youth science education space. By addressing the current pain points of lack of AI courses and qualified teachers in grassroots schools, brands can not only respond to policy demands but also build a positive image of corporate social responsibility and earn public recognition.

3. Reference for university-enterprise cooperation models: Brands can learn from TAL’s progressive cooperation model with Peking University: starting with resource donation in the first year, moving to teacher empowerment in the second, and building a long-term mechanism through co-developing courses in the third. This gradual deepening of cooperation activates the initiative of frontline participants, amplifies program impact, and avoids ineffective one-off charity investments.

This article summarizes policy orientations, market opportunities and actionable insights for education sellers. Key takeaways are as follows:

1. Policy and market opportunities: China’s 15th Five-Year Education Plan explicitly requires promoting AI education across all school stages and improving students’ AI literacy and critical thinking, making AI literacy education a clearly supported growth track. Public data shows that China currently has only 1.9 full-time science teachers on average per primary school, with even larger gaps in rural areas. Grassroots schools have massive unmet demand for systematic AI courses and professional teacher training.

2. Actionable implementation references: Sellers can follow TAL’s model: start by providing systematic AI course content, pair it with teacher training to solve the "how to teach" pain point for grassroots teachers, and achieve sustained regular implementation through dedicated long-term follow-up, turning a short-term project into a sustainable long-term business. Sellers can also partner with universities and public welfare foundations to build a program IP and access more resource support.

3. Risk warning: When entering this space, players should not focus solely on hardware sales while neglecting content support and long-term operation. Only by solving the problems of teacher capacity and sustained usage can the market be truly unlocked.

This article sorts out product demand, business opportunities and digital transformation insights for education teaching aid and hardware manufacturers. Key takeaways are as follows:

1. Product design and development demand: Grassroots schools have clear bulk demand for teaching aids and learning hardware adapted for AI and science education. In this TAL program alone, 1,500 sets of science teaching aids and 65 learning tablets were donated to three primary schools in Yutian County, covering more than 5,500 students. The demand scale for hardware in down-county and rural schools is considerable, so manufacturers can develop targeted cost-effective adapted products.

2. Business opportunity expansion: Manufacturers can connect with the procurement needs of education brands and public welfare programs, leverage public welfare projects to enter the grassroots school market, open up new B2B sales channels, and expand market growth.

3. Insights for digital and business upgrading: AI education is a clear future development direction. Manufacturers can upgrade product design around AI education scenarios to adapt to the needs of AI course usage. They can also partner with education content brands to adopt a "hardware + content" bundled model, increase product added value, meet schools’ demand for both hardware and supporting content services, and enhance product competitiveness.

This article sorts out industry trends, core pain points and reference solutions for K12 education service providers in the AI education space. Key takeaways are as follows:

1. Industry development trend: AI literacy education is now an educational direction explicitly required to be promoted by national policy. With the popularization of AI, demand for systematic AI education services from grassroots schools will continue to grow, creating broad market space.

2. Core pain points of target clients: The core bottleneck for AI education implementation in grassroots primary schools is not insufficient hardware, but lack of systematic AI course content and teachers with AI teaching capabilities. Frontline teachers’ inability to teach AI courses is the core problem blocking AI education implementation.

3. Reference solutions: Service providers can learn from TAL’s solution: on one hand, develop systematic AI literacy courses that focus on cultivating students’ ability to ask questions to AI and distinguish the authenticity of AI information, which aligns with policy cultivation requirements; on the other hand, provide supporting frontline teacher training to solve the problem of teachers lacking teaching capacity, and establish a long-term follow-up service mechanism to ensure regular course implementation, turning one-off services into sustainable long-term services. Providers can also partner with universities and public welfare foundations to enhance service credibility.

This article sorts out market demand, operation direction and risk avoidance insights for platform operators focusing on K-12 education. Key takeaways are as follows:

1. Market demand assessment: Grassroots schools currently have strong unmet demand for AI literacy education and science education. Platforms can position AI literacy education services as a new business growth point and connect with relevant demands from schools and public welfare programs.

2. Platform operation and partnership direction: Platforms can integrate resources from content brands, universities, public welfare foundations and other stakeholders to build an AI education service ecosystem, providing one-stop services including courses, teacher training and hardware matching for grassroots schools, and solving industry pain points that single institutions cannot address alone.

3. Partner recruitment and risk avoidance: Platforms can invite brands with course development capabilities and public welfare operation experience to settle in and jointly explore the grassroots market. Platforms need to avoid the pitfalls of prioritizing traffic over operation and prioritizing donation over implementation. Instead of only running one-off projects, they should promote the establishment of long-term follow-up operation mechanisms, continuously match schools’ demands and ensure long-term program implementation, so as to earn long-term recognition from partners and users.

This article provides new trends and a new case study for education industry researchers on AI literacy education implementation and educational public welfare model innovation. Key takeaways are as follows:

1. New industry trends: AI literacy education has now moved from national policy requirements to implementation in grassroots school scenarios. The participation of market-oriented education brands, in partnership with universities and public welfare foundations, in providing grassroots AI education resources is a new exploration on the supply side of the education industry. Social force participation to fill gaps in grassroots education resources has become a new development direction.

2. New emerging industry problems: This article clarifies the core contradiction of current grassroots AI education: while hardware is easy to obtain, there are large gaps in teacher capacity and systematic course supply, and traditional one-off public welfare donations cannot solve the problem of long-term implementation. How to activate the endogenous motivation of grassroots educators is a new problem that the educational public welfare industry needs to solve.

3. Insights on innovative models: This article presents an innovative model for sustainable educational public welfare: progressive upgrading along the path of resource donation → teacher empowerment → co-developed courses → long-term operation, which ultimately activates the initiative of frontline principals and teachers to develop local educational resources, turning one-off public welfare activities into long-term regular education mechanisms. This provides a researchable new case for social forces participating in the implementation of national education policies.