Curriculum alignment · China

China AI general-education guidance and IT curriculum

We checked the LittleAIMaster Grade 1–12 AI course against all 20 rated requirements of this framework: 13 fully covered, 3 mostly covered, 4 partly covered. Open a requirement to see what learners do and the exact lessons.

80%
Fully covered 13Mostly covered 3Partly covered 4of 20 requirements5 taught earlier than the framework asks

Source documents (4)

中小学人工智能通识教育指南（2025年版） / Guide to AI General Education for Primary and Secondary Schools (2025 Edition)
Ministry of Education, Basic Education Teaching Guidance Committee (教育部基础教育教学指导委员会)
2025 Edition, released 2025-05-12
中小学生成式人工智能使用指南（2025年版） / Guide to Using Generative AI in Primary and Secondary Schools (2025 Edition)
Ministry of Education, Basic Education Teaching Guidance Committee (教育部基础教育教学指导委员会)
2025 Edition, released 2025-05-12
2017 edition, revised 2020
Beijing municipal compulsory AI education mandate (fall 2025 semester)
Beijing Municipal Education Commission (implementing the national 2025 Guide) — reported via Beijing schools (Haidian Experimental Primary School, Guangqumen Middle School)
Fall 2025 semester

17 of 20 requirements are worded from secondary summaries or could not be checked against the primary document; they are marked.

Alignment chart

Every China requirement, rated

5Taught at this grade5Some material5Grades the framework asks for
Open a requirement to see what learners do and the exact lessons.

Showing 20 of 20 requirements

中小学人工智能通识教育指南（2025年版）

Cognition

Students experience and recognize basic AI technologies such as speech recognition and image classification through hands-on demos

Framework grades 1–5· secondary source
Fully covered
Our Grades 1–2 Fully covered
What learners do

In Grade 2 'Machines That Talk' and 'What Is AI?', learners trace a day through a smart speaker, news app, map app, shop, game character and TV recommender, and match each to its job.

Our Grades 3–5 Fully covered
What learners do

In Grade 2 'Machines That Talk' and Grade 3 'Sorting and Deciding', learners name assistants, face recognition, recommenders, route planning and game characters and what each does for the user.

Skills

Students operate simple AI-related tools and complete visual/block-based programming tasks

Framework grades 1–5· secondary source
Mostly covered
Our Grades 1–2 Mostly covered
What learners do

In Grade 1 'Do It Again' and Grade 2 'Robo Repeats', learners assemble and run grid commands and repeats and debug the visible behaviour. In 'Notice, Then Do' they program a sensor-triggered response.

Still to add

Events are in a separate sensor-rule activity; the grid program has no event block inside the same program.

Our Grades 3–5 Mostly covered
What learners do

In Grade 3 'Byte on the Grid', learners build executable routes and repeats, observe failures and debug. In Grade 5 'Program a Gadget' they set up a live sensor event-response rule.

Still to add

The grid language has no event command linking events and loops inside one program.

Computational thinking

Students build foundational logical/computational thinking through age-appropriate AI activities

Framework grades 1–5· secondary source
Fully covered
Our Grades 1–2 Fully covered
What learners do

In Grade 2 'My Four Thinking Tools', learners use named thinking tools to repair a pattern, split a bag task, leave irrelevant detail off a map and compare valid orders.

Our Grades 3–5 Fully covered
What learners do

In Grade 4 'Thinking Tools, Real Names', learners apply named decomposition, abstraction, pattern recognition and algorithm design, and explain which tool fits the problem.

Safety & privacy

Students establish basic safety awareness and an understanding of privacy protection when using AI tools

Framework grades 1–5· secondary source
Fully covered
Our Grades 1–2 Fully covered
What learners do

In Grade 2 'Machines That Remember' and 'Teach Byte', learners follow the rule that an address and real name are not given to a machine or game without asking a grown-up; Byte refuses such requests.

Our Grades 3–5 Fully covered
What learners do

In Grade 5 'My Secrets' and 'Locks and Keys', learners answer 'I do not share that' when a chatbot asks about home or school, and learn a friend's information is not theirs to give to an app.

Cognition

Students understand the basic workflow of machine learning and the concept of supervised learning

Framework grades 6–8· secondary source
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 7 'Supervised Learning Basics', learners meet definitions of supervised, unsupervised and reinforcement learning, group unlabelled drawings, and sort nine described problems into answer key, no teacher or scoreboard.

Where it is taught
  • Grade 7Unit 2: Teaching Machines › Supervised Learning Basics
    What is Supervised Learning?Learning Without LabelsGroup the Unlabelled DrawingsA Third Way: Learning From RewardsThree Ways to LearnKey VocabularyNani's Spotted LeavesInput or Label?The Two Piles Nobody Can NameTraining PhaseFair Exam or Not?Every Label Is a Human DecisionConcept MatcherOne Wrong Label Bends Every Prediction After ItClassification ExplainedBinary or Multi-class?Regression ExplainedWhere the Numbers Come From

Skills

Students collect, organize and analyze data, and solve real-world problems through project-based learning

Framework grades 6–8· secondary source
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 6 'What is Data?' and Grade 8 'The Phone Book Problem' and 'The Living Dictionary', learners collect and type data, then store, retrieve and modify it in lists, dictionaries and nested structures in Python.

Engineering thinking

Students apply a 'needs analysis → technology matching → outcome evaluation' engineering-thinking framework to AI projects

Framework grades 6–8· secondary source
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 8 'Designing AI Solutions' and 'The Wrong Solution', learners use six-step design thinking on school food waste, do 5 Whys root-cause work, run user interviews and sort problem statements as strong or too vague.

Ethics & misinformation

Students deepen ethical understanding and critically identify misinformation/hallucination risks in generative-AI outputs

Framework grades 6–8· secondary source
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 6 'When to Trust AI', Grade 7 'AI Writing Stories' and Grade 8 'Carlos's Writing Helper', learners study training cut-offs and hallucination, sort what a model could and could not know, and judge real passages before trusting them.

Cognition

Students understand the technical characteristics of generative AI and its significance to national strategy

We start Grade 7 · framework Grade 9Framework grades 9–10· secondary source
Fully covered
Our Grades 9–10 Fully covered
What learners do

In Grade 7 'AI Understands Words', Grade 8 'Maya's Discovery' and Grade 10 'Transformer Preview', learners contrast generative with sorting AI, and study diffusion and text-to-image, and Transformers and generation.

Skills / applied creation

Students construct/build simple AI algorithm models and develop cross-disciplinary solutions using accumulated AI knowledge

Framework grades 9–10· secondary source
Mostly covered
Our Grades 9–10 Mostly covered
What learners do

In Grade 9 'The Right Question' and 'Science Fair Star', learners choose and scope their own problem, build a model in Python Lab and give a 5-minute pitch. In Grade 10 they record a 3-minute demo.

Still to add

The own-problem path is optional, and the Grade 10 project learners chose is never built, so the recorded demo has no required AI artefact.

Systems thinking

Students build a three-dimensional 'technical principle → system architecture → social impact' way of reasoning about AI

Framework grades 9–10· secondary source
Partly covered
Our Grades 9–10 Partly covered
What learners do

In Grade 10 'Face Recognition', learners study embeddings and thresholds, the detect-align-embed-compare pipeline, and privacy and consent, and link threshold to impact, for example a false accept can mean a wrongful arrest.

Still to add

No task has learners explain one system on all three levels together, such as a pipeline design choice changing a social outcome; explanation prompts cover only one or two levels.

Where it is taught

Social responsibility

Students practice social responsibility, weighing technological innovation against societal risk when using or designing AI

We start Grade 6 · framework Grade 9Framework grades 9–10· secondary source
Fully covered
Our Grades 9–10 Fully covered
What learners do

In Grade 10 'Building Your AI Ethics Framework', learners weigh innovation against social risk across user, creator and citizen roles and take responsibility for technology choices.

Innovation practice

Senior secondary students progress to applied innovation: refining AI algorithm models and interdisciplinary systems thinking (continuation of the 9-10 strand into upper senior grades)

Framework grades 11–12· secondary source
Partly covered
Our Grades 11–12 Partly covered
What learners do

Grade 11 'Beyond the Model' and Grade 12 'The Blueprint Before the Building' teach architecture layers, scaling, cost and energy per query, and learners answer design reviews of supplied systems. The 'Design an ML API' capstone covers the interface layer.

Still to add

Learners never specify data, model and interface layers for their own system, justify framework choices or set a compute, cost or energy budget.

Where it is taught

Beijing municipal compulsory AI education (fall 2025)

Cognition (municipal example)

Lower-primary students build basic AI awareness (example: Haidian Experimental Primary School)

Framework grades 1–2
Fully covered
Our Grades 1–2 Fully covered
What learners do

In Grade 2 'Machines That Talk' and 'What Is AI?', learners trace a day through a smart speaker, news app, map app, shop, game character and TV recommender, and match each to its job.

Middle-primary students learn fundamental AI principles (example: Haidian Experimental Primary School)

We start Grade 2 · framework Grade 3Framework grades 3–5
Fully covered
Our Grades 3–5 Fully covered
What learners do

In Grade 3 'Robots' and 'AI at Work', learners sort machines into those told the steps and those shown examples, see that a toaster needs no AI, and learn AI as a machine that learns.

Skills (municipal example)

Upper-primary/junior students apply smart-hardware applications (example: Haidian Experimental Primary School)

Framework grades 6–8
Partly covered
Our Grades 6–8 Partly covered
What learners do

In Python Lab Module 48 'Sensors and Gestures', learners write code that reads a phone's live accelerometer and gyroscope and react to gestures. The Motion Trainer and micro:bit simulator export rules for a real board.

Still to add

Only sensing is met; outputs are on screen, learners do not write or upload device code, and no lesson covers driving a motor, servo or buzzer.

普通高中信息技术课程标准 — 人工智能初步

Knowledge/concepts

Students learn core AI concepts, theory, and application domains

We start Grade 9 · framework Grade 11Framework grades 11–12· secondary source
Fully covered
Our Grades 11–12 Fully covered
What learners do

Learners sort technologies into vision, language and data-science families and match applications to the AI domain that solves them in chapters such as Grade 11 'AI in Industry Review' and Grade 12 'Beyond Simple Image Recognition'.

Where it is taught

Algorithms & implementation

Students learn the basic process, implementation principles and core algorithms behind AI systems

Framework grades 11–12· secondary source
Partly covered
Our Grades 11–12 Partly covered
What learners do

In Grade 11 'Beyond the Model', learners work through the chain from data pipeline to model to serving to output, and match system components to their jobs. Grade 12 mentions rule-based expert systems briefly.

Still to add

Grades 11-12 never name the knowledge base, rule base and inference engine, trace a worked expert system, or contrast it with the learned-model chain; the full parts appear in Grade 8.

Development & transfer

Students learn to develop AI applications and transfer that capability to solve problems in other real-life contexts

Framework grades 11–12· secondary source
Mostly covered
Our Grades 11–12 Mostly covered
What learners do

In Grade 11 'Building Your App' and Grade 12 'The Blueprint Before the Building', learners choose their own problem, build and test an assistant in Prompt Lab, and write a pitch. Grade 12 also trains and tests a Raise Your AI companion.

Still to add

The finished build is not delivered as a recorded talk at these grades, and the build is a system-prompt assistant rather than a model or pipeline the learner owns.

Ethics & security

Students understand the ethics and challenges of a smart/AI-driven society, strengthening information-security awareness, responsibility, and dialectical (balanced) views of AI

We start Grade 6 · framework Grade 11Framework grades 11–12· secondary source
Fully covered
Our Grades 11–12 Fully covered
What learners do

In Grade 12 'The Right Thing', 'The Foundation of Trust' and 'Graduation Day', learners work through scenarios on workplace ethics, research integrity and digital citizenship, ending on the idea that their values decide what AI amplifies.

School and system rules (not rated)

These apply to schools and education systems (hours, delivery, assessment, staffing, age rules). A course cannot meet them on its own.

  • Students develop values, character and capabilities suited to AI-technology development, framed as moral character cultivation (立德树人) rather than pure technical training
  • All students, regardless of region or school resourcing, are guaranteed equitable access to quality AI education opportunities
  • Curriculum is delivered under a full-chain safety/ethics safeguard covering data security and ethical risk control
  • Primary-level students are prohibited from independently using open-ended generative-AI content creation without teacher mediation
  • Grades 1-4 must receive at least 6 hours of AI education per year
  • Grades 5-9 (spans upper primary and junior secondary) must receive at least 10 hours of AI education per year
  • Grades 10-11 must receive at least 1 class hour of AI education every two weeks
  • Schools may deliver AI education flexibly: as a standalone course, integrated into the Information Technology/Information Science subject, or through practical activities (science festivals, research/study practice), rather than a single mandated fixed module — the national guide itself does not fix a specific class-hour count or standalone module
  • Primary students may not independently use open-ended generative content creation tools; use must be teacher-mediated
  • Teachers are prohibited from using generative AI as a substitute for their core teaching responsibilities (e.g., lesson delivery, grading judgment)
  • Beijing schools (1,400+) must provide no fewer than 8 class hours of AI education per semester across all grade levels
  • AI knowledge is integrated into Information Technology class starting from grade 3, supplemented by extracurricular robotics/coding clubs (example: Guangqumen Middle School)
  • Instruction uses block-based programming platforms, AI robots with image recognition (e.g., iFlytek), and large language models as classroom tools
  • 'Introduction to AI' (人工智能初步) is an elective-compulsory (选择性必修) module of the senior-secondary Information Technology curriculum; completion is recorded as part of students' comprehensive quality evaluation (综合素质评价)
  • Module content is delivered through a coherent project sequence in which students design and implement simple intelligent applications, emphasizing understanding, hands-on experience, and the process of design-and-programming rather than only theory
  • The AI module is built to connect logically and conceptually with the compulsory Information Technology modules, reinforcing the subject's core concepts and core competencies (核心素养)

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See how the course maps to the other 13 curricula on the curriculum alignment overview, or browse the course grade by grade.

Our own reading of our own course, ratings reviewed 22 October 2026. It is not an endorsement, certification or accreditation by any authority named here, and it makes no claim about learning results.