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Good practice Imported

China's 2025 National Guideline on Generative AI Use in Primary and Secondary Schools

China · Beijing · See the China profile · See the Beijing profile

Evidence: Descriptive / self-reported Top 59% 47/100 · Ask Evidence Copilot about this practice

China's May 2025 national guideline tiers generative-AI school use by age: primary pupils barred from unsupervised open-ended AI, middle-schoolers examine its logic, high-schoolers build models -- with mandatory data-protection rules and tool whitelists.

China's 2025 National Guideline on Generative AI Use in Primary and Secondary Schools

Details

Promoter
Ministry of Education of the People's Republic of China (Committee on Basic Education Teaching Guidance)
Period
Issued May 2025; implementation ongoing
Keywords
AI governance, K-12 policy, generative AI regulation, data protection, curriculum guidance

Context

In May 2025, the education-ministry-affiliated Committee on Basic Education Teaching Guidance issued China's first national 'Guide to Using Generative Artificial Intelligence in Primary and Secondary Schools.' It follows several years of controversy over facial-recognition and behaviour-monitoring cameras in Chinese classrooms, which the Ministry of Education had already pledged in 2019 to 'curb and regulate' after a public backlash at China Pharmaceutical University.

Objectives

To tier permitted generative-AI use by school age, protect student data, and ensure AI complements rather than replaces human-led teaching and assessment.

Activities

Primary-school pupils are barred from independently using open-ended generative AI tools and may only use them under direct teacher supervision; middle-school students may examine the logical structure behind AI-generated content; high-school students may design, test and critique AI models as part of interdisciplinary and systems-level projects. The guideline bans teachers from using AI to grade students, answer exam questions on their behalf, or process sensitive personal data, and bans students from submitting AI-generated work as their own or using AI to cheat. It instructs local education authorities to formulate area-specific AI management rules, set up data-protection safeguards, run ethical-review mechanisms, and maintain a dynamic whitelist of generative-AI tools approved for use on school grounds.

Conclusions

As a compulsory national policy rather than a voluntary recommendation, the guideline is unusually prescriptive by international standards, but it is also brand new: as of mid-2025 there is no independent evaluation of how consistently schools maintain whitelists, run ethical reviews, or enforce the age tiers in practice.

Implementation

Indicative cost
Low (< €50k) — Not separately quantified; as a compulsory regulatory guideline rather than a funded programme, direct central cost is low, though downstream local implementation costs (whitelisting, ethical review, data-protection safeguards) are not quantified in available sources.
Time to results
Short (< 1 year) — Issued May 2025; implementation ongoing; too recent (as of mid-2025) for independent evaluation of enforcement consistency.
Staffing & skills
Committee on Basic Education Teaching Guidance (Ministry of Education of China), local education authorities, tasked with area-specific rules, data-protection safeguards, ethical-review mechanisms and tool whitelists, teachers, assigned supervisory responsibility across all three school tiers

Conditions for success

  • consistent enforcement of age-tiered permissions across schools
  • functioning dynamic whitelist and ethical-review mechanisms at local level
  • adequate teacher supervision capacity, given no accompanying training programme is documented

Common failure modes

  • compulsory policy but no independent evaluation yet of how consistently schools maintain whitelists, run ethical reviews, or enforce the age tiers in practice
  • no accompanying teacher-training programme documented despite assigning teachers supervisory responsibility

Where it fits

Governance type
national compulsory regulation implemented via local education authorities (unitary state, top-down)
Scale
national (all primary and secondary schools)
Income level
upper-middle income

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

Attachments

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