Curriculum alignment · United Arab Emirates

UAE National AI Literacy Curriculum Framework (K–12, 2026)

We checked the LittleAIMaster Grade 1–12 AI course against all 37 rated requirements of this framework: 29 fully covered, 8 mostly covered. Open a requirement to see what learners do and the exact lessons.

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Fully covered 29Mostly covered 8of 37 requirements

Source documents (2)

Announced 4 May 2025; in force from 2025-26 academic year in public schools; Cabinet approved 2 Sep 2026 extension to all public AND private schools plus export of the programme to other countries
2026 manual, reported ~12-14 Feb 2026

Alignment chart

Every UAE requirement, rated

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

Showing 37 of 37 requirements

Cycle 1 (K–4)

AI = human-created tools that follow instructions and use data

Framework grades K–4
Mostly covered

Students are asked to: identify humans make AI tools; differentiate pretend robots from real AI (KG); explain AI follows human instructions; identify how unclear instructions cause mistakes; explain some AI learns from examples; explain AI uses rules for choices

Our course Mostly covered
What learners do

In Grade 2 'Rules or Examples?', learners see a smart machine take in data and work it out by rules a person wrote or by learning, use a rule-based plant doctor, and choose rules or examples for a job.

Still to add

The word AI is still defined as learning from examples, and rule-following machines are not called AI, which the UAE outcome asks for.

Where it is taught

Compare AI with humans (Cycle 1 part)

Framework grades K–4
Fully covered

Students are asked to: identify people have feelings and AI does not; compare human-only vs copyable actions; describe empathy/imagination; explain AI cannot make moral choices

Our course Fully covered
What learners do

In Grade 2 'Machines That See' and 'Machines That Hear' and Grade 4 'Thinking Well', children compare how humans and machines sense and think, for example an eye and a camera, and learn a machine cannot know, choose or care.

Note

What smart means is never spelled out as a claim.

Explain how AI uses data to learn

Framework grades K–4
Fully covered

Students are asked to: describe learning by repeated patterns; identify grouping by size/colour/shape; identify good vs bad data; describe more data improves performance; define machine learning; describe if–then decisions; explain prediction from past data

Our course Fully covered
What learners do

In Grade 2 'Learning From Examples', Grade 3 'Data' and 'Training' and Grade 4 'How AI Is Built', children build and use example sets to see how machines learn from data.

Note

Practice tasks check against a fixed key, so the work is sound but narrow.

Where it is taught

Identify safe and fair ways to use AI

Framework grades K–4
Fully covered

Students are asked to: explain safe actions; identify fair/unfair choices; explain more diverse examples → fairer AI; describe what bias means; analyse how biased data affects responses; identify when AI should not decide; describe why people decide what is fair

Our course Fully covered
What learners do

In Grade 1 'Safe and Kind with Machines' and Grade 4 'AI and Creativity', 'Wrong, and How Sure' and 'Thinking Well', children learn safe and fair AI use, including picking the fairer rewrite in bias lessons.

Note

Every case is an invented scenario; no real incident appears.

When to trust AI output, when a human must judge

Framework grades K–4
Fully covered

Students are asked to: discuss situations needing human review; analyse over-reliance leading to mistakes; describe checking results first

Our course Fully covered
What learners do

In Grade 4 'Checking' and 'Made-Up Answers', children learn to stop, check a second source and decide, and learn when a human must judge. Earlier lessons cover AI as a guesser.

Humans control AI; protect personal information

Framework grades K–4
Fully covered

Students are asked to: explain humans are responsible (KG); identify machines can't decide alone; describe why clear, fair rules matter; demonstrate safe/unsafe choices; identify private information; explain how AI collects personal information online

Our course Fully covered
What learners do

In Grade 1 'Safe and Kind with Machines' and Grade 4 'Thinking Well', children learn that people control AI and protect personal information, by picking the safe choice from fixed options.

Note

Children show this by choosing from fixed options, which fits their ages.

Where it is taught

Everyday uses of AI across sectors

Framework grades K–4
Mostly covered

Students are asked to: discuss/identify AI at home, school, city; describe AI helping doctors and safety workers; explain translation; show summarising; compare AI in transport; describe environmental monitoring; explain how AI in UAE sectors works together

Our course Mostly covered
What learners do

In Grade 3 and 4 lessons on sectors such as the Dubai Metro, hospitals, power and water, summarising and environmental monitoring, children sort, match and order how AI is used across sectors.

Still to add

The lesson on sectors working together is set in an unnamed city, so UAE examples are mostly generic; all actions are fixed-option taps.

Where it is taught

Design AI projects that support humans

Framework grades K–4
Mostly covered

Students are asked to: identify group roles; describe a real problem; list several ideas; choose a solution; draw/develop a model (G2: robot from basic materials); improve with feedback; design a poster; develop a presentation (G4)

Our course Mostly covered
What learners do

In Grades 2-4, children run a project cycle in the app: plan a helper, teach a first version, test it on new items, use feedback and build version two. Grade 5 'Build It, Test It, Improve It' continues it.

Still to add

No lesson has children build a robot model from basic materials, in-app projects use preset plan choices, and open design and live presenting happen only in teacher-led sessions.

Where it is taught

Cycle 2 (G5–8)

Compare AI with humans (Cycle 2 part)

Framework grades 5–8
Fully covered

Students are asked to: describe differences in perception; differentiate AI-generated emotion vs empathy; explain how AI learns complex tasks vs humans; compare creativity; identify tasks needing human values; analyse differences in perception, reasoning, problem-solving

Our course Fully covered
What learners do

In Grade 6 'Your Brain Finds Patterns', Grade 7 'How AI Sees' and 'AI Writing Stories', learners compare AI with humans, for example brain versus AI and human versus computer vision.

Learn from data; algorithms make decisions

Framework grades 5–8
Fully covered

Students are asked to: explain algorithms as ordered steps; analyse how rule changes change decisions; describe supervised learning with labelled data; explain grouping unlabelled data; differentiate supervised / unsupervised / reinforcement; explain graphs for patterns; analyse bad data → error/bias; use datasets of varying quality; explain testing on new data

Our course Fully covered
What learners do

In Grade 7 'What is Training?' and 'Supervised Learning Basics', learners study the training loop, overfitting and sealed test sets. They group unlabelled drawings and sort jobs by learning type, and see bias appear with imbalanced data.

Note

Clustering is done by hand sorting, not with k-means code.

How advanced models process information (neural networks)

Framework grades 5–8
Fully covered

Students are asked to: identify the parts of a neural network; demonstrate data moving through input/hidden/output layers; differentiate single- vs multi-layer; examine deep-learning applications

Our course Fully covered
What learners do

In Grade 6 'The Deep Learning Revolution', learners match network layers to a dog photo, sort input, hidden and output layers, work through a truth table, and use the Neural Network Playground to train XOR.

Note

The Playground step can be skipped, so the hands-on work is optional.

Evaluate model performance

Framework grades 5–8
Fully covered

Students are asked to: describe/examine accuracy; explain the confusion matrix, precision, recall

Our course Fully covered
What learners do

In Grade 7 'Testing What AI Learned' and Grade 8 'Testing AI Solutions', learners compute accuracy, precision and recall by hand from counts, and use the Confusion Matrix tool.

How AI generates outputs from learned patterns

Framework grades 5–8
Fully covered

Students are asked to: identify face patterns; identify how voice assistants are trained on human data; explain predictions from personal behaviour data; explain content suggestion; explain how machines process language

Our course Fully covered
What learners do

In Grade 7 'Face Detection Magic' and 'Voice Assistants Explained' and Grade 6 'AI Recommends For You', learners see how AI produces outputs from learned patterns, training a toy face model and studying voice pipelines and recommenders.

Ethics, cultural values and inclusion guide AI decisions

Framework grades 5–8
Fully covered

Students are asked to: identify bias from unbalanced data; demonstrate fairer data reducing bias; examine how cultural values shape AI use; discuss AI ignoring culture; explain ethical vs unethical; differentiate accuracy vs fairness; analyse real cases; identify unintended discrimination; describe protections

Our course Fully covered
What learners do

In Grade 6 'AI Can Be Unfair' and Grade 7 'AI and World Languages', learners study ethics and inclusion through cases such as Gender Shades, photo apps under EU, US, India and UAE rules, and speech recognition across accents.

AI-manipulated media: safety and security

Framework grades 5–8
Fully covered

Students are asked to: identify real vs AI-generated; describe AI detecting threats and creating risks; explain false text/images/video; identify ways to detect manipulation; describe deepfake spread; evaluate ethical/societal impact

Our course Fully covered
What learners do

In Grade 6 'Real vs Fake: Deepfakes', Grade 7 'Text to Speech' and Grade 8 'Liam's Art Dilemma', learners use the STOP method, study voice cloning and image generators, and critique real and generated images.

Privacy, accountability and personal rights

Framework grades 5–8
Fully covered

Students are asked to: explain AI learns from personal data; discuss sharing risks; explain why rules are needed; identify who is responsible; discuss AI in law enforcement and courts; analyse its benefits and risks; examine explainability; explain accountability for hard-to-interpret decisions

Our course Fully covered
What learners do

In Grade 6 'AI and Privacy', Grade 7 'Computer Vision in the Real World' and Grade 8 'Testing AI Solutions', learners study privacy, a courtroom risk score case and who answers for an opaque decision.

How AI is governed through national policies

Framework grades 5–8
Fully covered

Students are asked to: compare how countries regulate AI; explain how the UAE promotes ethical AI through national governance and regulation; describe how global bodies, governments and companies shape regulation

Our course Fully covered
What learners do

In Grade 8 'How the World Governs AI', learners sort laws, plans and principles, study the EU risk tiers and UAE strategy, minister and charter, and place use cases in each rulebook. 'Reflection & Growth' has them draft a rule set.

AI applied across sectors

Framework grades 5–8
Mostly covered

Students are asked to: describe transport; explain smart city, healthcare, environment; examine how national AI strategies shape productivity and wellbeing in the UAE (G7); assess service systems; investigate public-safety AI (crime detection, facial recognition); explain automation and careers

Our course Mostly covered
What learners do

In Grade 7 'The Great Project Choice' and Grade 8 'How the World Governs AI', learners study national AI strategies, including the UAE's, sort six projects by productivity or wellbeing, and see the UAE strategy and charter as governance tools.

Still to add

The UAE is one row of a three-country table, and the six projects sorted are generic, so learners do not examine how the UAE plan shapes productivity or wellbeing.

Where it is taught

Global challenges: sustainability, humanitarian aid, social impact

Framework grades 5–8
Fully covered

Students are asked to: identify AI for pollution, hunger, safety; explain smarter, sustainable societies; evaluate community solutions; determine AI in disaster response, emergency services, humanitarian efforts; analyse the environmental impact of AI

Our course Fully covered
What learners do

In Grade 6 'AI for Good' and Grade 8 'The Global Goals Project', learners sort uses such as damage maps, flood warning and aid logistics, and take a Global Goal through a local problem, helper design, footprint and fair trial.

Use generative AI models to create new content

Framework grades 5–8
Mostly covered

Students are asked to: explain how generative models learn patterns; use a generative AI tool to produce content; compare several outputs for patterns and differences

Our course Mostly covered
What learners do

In Grades 6 to 8, learners finish a tune or picture with an on-device pattern model, run it three times, keep one result and say what they chose versus what the model chose.

Still to add

The model is a small pattern model; no lesson sends learners to Prompt Lab or a live text or image generator to create and compare outputs.

Where it is taught

Design AI projects for real-world problems

Framework grades 5–8
Fully covered

Students are asked to: research needs; identify requirements; compare solutions; create/construct a prototype; evaluate fairness, safety, privacy; modify with feedback; present; G8: define a UAE or global challenge, work through the full build stages, optimise the solution

Our course Fully covered
What learners do

In Grade 7 'The Great Project Choice' and Grade 8 'The Global Goals Project', learners choose their own problem, build and test a model with Raise Your AI, and plan a trial. Grade 8 'Capstone Project' continues this.

Note

The Grade 8 build uses set categories, optimising is one fix-and-retest loop, and presentations are planned in the app rather than delivered.

Cycle 3 (G9–12)

How AI systems work; data and design choices

Framework grades 9–12
Fully covered

Students are asked to: analyse data quality, design and human decisions; identify core components; explain logic-based (rules and reasoning), optimisation-based (objectives and constraints) and ML systems (G9)

Our course Fully covered
What learners do

In Grade 9 'Welcome, AI Engineers!', learners sort eight systems into logic rules, optimisation or machine learning. In Grade 12 'Can AI Really Think?' they sort capabilities into narrow AI or AGI.

Note

Narrow versus general AI is taught in Grade 12, later than the Grade 9 placement.

Where it is taught

Data characteristics shape AI decisions

Framework grades 9–12
Fully covered

Students are asked to: analyse real datasets (size, completeness, balance, relevance); identify data issues; explain probability in decisions; analyse decisions combining logic, data and probability

Our course Fully covered
What learners do

In Grade 9 'The Spam Invasion' and 'Science Fair Star', and in Python Lab, learners see how data characteristics shape AI decisions, including testing on held-out rows against a no-model baseline.

Neural network design and performance

Framework grades 9–12
Fully covered

Students are asked to: explain NN vs deep learning; explain layered processing; analyse how layers and connections (fully connected, convolutional, recurrent, residual) affect performance; examine limitations

Our course Fully covered
What learners do

In Grade 10 'Welcome to Grade 10!', the Neural Network Playground and Python Lab, learners study neural network design, including filters, pooling, a tiny convolutional network and attention.

Optimisation: goals, constraints, trade-offs

Framework grades 9–12
Fully covered

Students are asked to: explain goals; explain constraints; evaluate trade-offs (accuracy vs efficiency, performance vs fairness)

Our course Fully covered
What learners do

In Grade 11 'Solving Constraints in Code' and Python Lab 'Module 46', learners study optimisation goals, constraints and trade-offs, along with ensembles and support vector machines.

Note

This is taught in Grades 10-11 rather than Grade 9, where it is placed.

How AI models human emotion and behaviour

Framework grades 9–12
Fully covered

Students are asked to: examine how AI detects emotions (text, speech, face, physiological signals); examine how AI predicts behaviour; consider accuracy and implications

Our course Fully covered
What learners do

In Grade 9 'Emotion Detection', learners tune a sentiment scorer and sort emotion-AI outputs as measured signals or inferred guesses. In Grade 12 'How Does It Know?' they tune a recommender that predicts behaviour.

Note

Work stays at examining level: learners never test a face, voice or physiological model, and the behaviour-prediction task is a generic quality slider.

Where it is taught

Improve AI systems to match societal expectations

Framework grades 9–12
Fully covered

Students are asked to: G9: identify academic dishonesty; explain representation, algorithmic bias, mitigation, traits of trustworthy AI · G10: analyse how UI design affects inclusivity and trust · G11: analyse accessibility barriers; apply inclusive design principles; recommend design improvements · G12: compare international AI ethics principles with UAE values and national AI guidelines; justify human-vs-AI decisions

Our course Fully covered
What learners do

In Grade 11 'Building Your App', learners match barriers to fixes and write a design brief for a chosen persona using inclusive design. Grade 10 lessons judge steering screens, and Grade 12 compares ethics codes.

Note

The design brief is self-assessed and not graded by the app, and no test with real users happens.

Where it is taught

AI and human expression, behaviour, creativity

Framework grades 9–12
Mostly covered

Students are asked to: evaluate how AI responses shape opinions and decisions (wording, framing); analyse AI content and originality

Our course Mostly covered
What learners do

In Grade 10 'Deepfakes and Misinformation', learners label six screens and replies as neutral or steering. In 'Choosing and Judging AI Tools' they sort coach versus ghostwriter uses and judge AI-use notes.

Still to add

Evaluation stops at fixed-answer labelling; learners do not turn a steering reply into a neutral one or judge a real AI reply against the checklist.

Where it is taught

Effectiveness of AI governance

Framework grades 9–12
Fully covered

Students are asked to: analyse explainability for accountability; analyse the performance vs interpretability trade-off; explain data-protection guidelines; evaluate weak safeguards; analyse how rules are set nationally and internationally; evaluate compliance auditing; analyse data governance

Our course Fully covered
What learners do

In Grade 10 'AI Governance and Regulation' and Grade 12 'The Council Decision', and in sector chapters in Grade 11, learners study how effective AI governance is, including the UAE National Strategy for AI 2031.

Judge responsible AI use against governance frameworks

Framework grades 9–12
Fully covered

Students are asked to: apply responsible-AI criteria to a use case; analyse AI in government performance; explain/compare national regulation approaches; design AI-use guidelines; evaluate careers

Our course Fully covered
What learners do

In Grade 10 'Building Your AI Ethics Framework', learners judge cases. In Grade 11 'AI Ethics in Practice' and Grade 12 'The Council Decision', they draft a governance clause and a school guideline; Grade 12 also covers government AI services.

Human–AI collaboration across sectors

Framework grades 9–12
Fully covered

Students are asked to: analyse shifting human roles; evaluate trade-offs; healthcare (diagnosis, genetics, personalised medicine); research acceleration; digital media shaping culture; decision-making in education, hiring, insurance, immigration; cybersecurity threat management; infrastructure protection; fraud; predictive policing

Our course Fully covered
What learners do

In Grade 12 'The Council Decision', Grade 11 'AI in Finance' and Grade 10 'Attacks on AI Systems', learners analyse human and AI roles in immigration, insurance and cyber defence, sorting steps and writing a verdict.

Where it is taught

AI in economic development and social change

Framework grades 9–12
Fully covered

Students are asked to: analyse infrastructure (transport, utilities, logistics); analyse labour markets; evaluate upskilling; analyse key UAE sectors: energy, government services

Our course Fully covered
What learners do

In Grade 9 'AI Careers: Who Builds, Shapes and Uses AI', Grade 12 'Jobs Transformed' and Grade 11 'AI in Transportation', learners study AI in the economy, including UAE energy and government services.

Humanitarian and environmental effectiveness

Framework grades 9–12
Fully covered

Students are asked to: analyse disaster response and public health; explain environmental monitoring and modelling; evaluate how well AI solves global problems

Our course Fully covered
What learners do

In Grade 11 'AI in Transportation' and 'SDG Research-and-Build Project', learners study aid routing when a map is wrong, and cases such as Flood Hub with benefit and harm metrics and a footprint estimate.

Note

Environmental monitoring is taught through cases inside the Grade 11 project, not as a modelling lesson of its own.

Evaluate different AI tools, including UAE-developed LLMs

Framework grades 9–12
Fully covered

Students are asked to: compare several AI tools, including UAE-built LLMs; evaluate strengths and reliability; evaluate limitations

Our course Fully covered
What learners do

In a Grade 10 teacher-guided activity, learners run the same bilingual task three times on each of two real tools, including a UAE-built tool where the school permits, score the results and justify their choice.

Note

The activity is supervised and depends on school tool permission and Arabic checking; a one-tool fallback does not complete the standard.

Where it is taught
  • Teacher guidesTeacher guide session

Use AI tools to work more effectively

Framework grades 9–12
Mostly covered

Students are asked to: use AI for communication style, leadership, planning, organisation, productivity; identify strategies for keeping originality

Our course Mostly covered
What learners do

In Grade 10 'Your Turn: Plan and Message With AI', learners give a real goal and limits, prompt for a weekly plan, check and fix it, rewrite an AI-drafted message in their own voice and write an AI note.

Still to add

No Grades 9-12 lesson uses AI to organise a team, plan a meeting or split roles, and the live step can be completed through worked examples.

Where it is taught

Apply effective prompting strategies

Framework grades 9–12
Fully covered

Students are asked to: identify LLM capabilities and limits; use prompting for research, reading comprehension, study; write clear prompts; modify prompts; apply prompting to reduce misinformation, bias and over-reliance (G9)

Our course Fully covered
What learners do

In Grade 9 'The Right Question', learners judge study prompts as strong or weak and write a five-part quiz-me prompt on their own textbook paragraph, then rewrite it. Later grades write and compare prompts in capstones.

Note

The Grade 9 live step can be finished through worked examples and the prompt is not saved; writing and modifying prompts is evidenced in Grades 11-12 optional capstones.

Design AI solutions with systematic design processes

Framework grades 9–12
Mostly covered

Students are asked to: G9: demonstrate project management (Gantt); investigate a community problem with real data; construct a rule-based or AI-platform prototype; evaluate fairness, privacy, explainability · G10: plan with a section on UAE AI initiatives and careers; SWOT; evaluate against UAE values · G11: plan linked to UAE workforce needs; solve with prompt engineering and LLMs · G12: create a functional working concept using LLMs; persuasive presentation

Our course Mostly covered
What learners do

In Grade 9 'The Failed Project' learners write their own Gantt chart; in Grade 10 'Spark of Inspiration' they write workforce and values sections; in 'Presentation and Demo' they record and self-score a 3-minute demo.

Still to add

Plans are not required to link to UAE future AI workforce needs, the Grade 10 presentation is self-scored, and the Grade 12 capstone has no presentation row.

Where it is taught

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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.