Curriculum alignment · International

International Baccalaureate (PYP, MYP, DP)

We checked the LittleAIMaster Grade 1–12 AI course against all 37 rated requirements of this framework: 23 fully covered, 8 mostly covered, 6 partly covered. Open a requirement to see what learners do and the exact lessons.

84%
Fully covered 23Mostly covered 8Partly covered 6of 37 requirements9 taught earlier than the framework asks

Source documents (4)

IB Diploma Programme Computer Science (new syllabus)
International Baccalaureate Organization (IBO)
First teaching August 2025, first assessment May 2027
IB Middle Years Programme (MYP) Design
International Baccalaureate Organization (IBO)
MYP Design guide, curriculum from 2014 (subject brief published 2015; current guide as linked from ibo.org)
Page last updated 19 February 2026
IB Primary Years Programme (PYP) curriculum framework
International Baccalaureate Organization (IBO)
Current PYP framework (transdisciplinary; no separate published digital/AI-literacy subject document found)

19 of 37 requirements are worded from secondary summaries or could not be checked against the primary document; they are marked.

Alignment chart

Every IB 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

IB Diploma Programme Computer Science (new syllabus)

Theme A: Concepts of computer science

Explain how core computer hardware, operating systems, and cloud computing concepts underpin computing systems

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

Grade 11 and 12 lessons such as 'Storage for AI Workloads' and 'AI Accelerators' cover storage types, GPUs, memory limits and software layers, but only as AI infrastructure.

Still to add

Learners are not taught how components communicate (buses, device-driver-OS-app path), and common hardware faults and diagnosis are not taught at any grade.

Describe network structures, protocols, and security threats (encryption, firewalls, phishing, DDoS attacks)

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

In Grade 11 'From Prototype to Planet-Scale' and 'Beyond the Model', learners study load balancing, caching, edge deployment and redundancy. Packets, protocols and addressing are taught earlier in Grade 8.

Still to add

Packets, protocols, IP addressing, DNS and network topology are not taught at Grades 11-12, and network design for reliability is covered only as service redundancy.

Design and query relational databases using SQL as core (mandatory) content for all students

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

In Python Lab Module 22 'SQLite Databases', learners write SQL to create tables, insert, query and update data. Grade 11 chapters on storage tiers and data pipelines cover how storage choices trade off.

Where it is taught

(HL only) Explain NoSQL database models and their use cases relative to relational databases

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

In Python Lab Module 22 'SQLite Databases', learners write SQL to create tables, insert, query and update data. Grade 11 chapters on storage tiers and data pipelines cover how storage choices trade off.

Where it is taught

Theme A: Concepts of computer science / machine learning

Explain fundamental machine learning concepts, including how models are trained on data to make predictions or decisions

We start Grade 2 · framework Grade 11Framework grades 11–12· secondary source
Fully covered
Our Grades 11–12 Fully covered
What learners do

Learning from examples, generalising to unseen data and predicting on new input are taught and practised from Grade 2 'Learning From Examples' through Grade 7 chapters such as 'What is Training?'.

Where it is taught

Distinguish supervised, unsupervised, and reinforcement learning approaches to machine learning

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

In Grade 11 'The Gaming Champion', 'AI in Finance' and 'AI in Retail', learners define the three families, repeatedly sort tasks into supervised, unsupervised or reinforcement learning, and run k-means.

Where it is taught

Describe deep learning at an introductory level as a machine learning technique

We start Grade 10 · framework Grade 11Framework grades 11–12· secondary source
Fully covered
Our Grades 11–12 Fully covered
What learners do

In Grade 10 chapters such as 'Convolution Operations', 'Building a CNN' and 'Object Detection Basics', learners build CNNs in Keras for image tasks and LSTMs for text; GANs, diffusion and transformers are described in Grade 11.

Where it is taught

(HL only) Apply data preprocessing and feature selection techniques when preparing data for a machine learning model

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

Grade 9 chapters such as 'The Mysterious Gaps' and 'The Messy Data Monster' have learners handle missing values, outliers, encoding, scaling and leakage-safe train/test splitting with pandas and scikit-learn.

Where it is taught

Theme A: Concepts of computer science / machine learning ethics

Evaluate ethical implications of AI/ML systems, including bias, fairness, and transparency, as part of the machine learning content

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

In Grade 11 'AI Ethics in Practice' and Grade 12 'The Council Decision', learners apply fairness, accountability, transparency and ethics criteria and governance principles to systems, judging where each falls short.

Theme B: Computational thinking and problem-solving

Apply computational thinking strategies (decomposition, abstraction, pattern recognition, algorithm design) to solve problems

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

In Grade 12 'The Whiteboard Challenge', learners practise parts of this without the computational-thinking label. They use a 5-step problem-solving framework, match problems to coding patterns, order the method and trace by hand.

Still to add

The four strategies are never named together as computational thinking, abstraction is not taught as a problem-solving move, and computational thinking is not assessed on an AI problem.

Where it is taught

Construct and trace algorithms expressed in pseudocode, independent of a specific programming language's syntax

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

In Grade 12 'The Whiteboard Challenge', learners read pseudocode and trace it row by row with a trace table, and order the method of pseudocode, code and trace. Flowchart symbols are mentioned in one sentence.

Still to add

Learners never write their own pseudocode or read, build or trace a standard-symbol flowchart, and the trace is multiple choice rather than a filled table.

Where it is taught

Write programs in a chosen language (Java or Python, selected at school/department level) that implement given algorithms

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

In Python Lab Modules 24, 27, 28 and 46, learners write graded programs using types, loops, conditionals and arrays. In Module 27 'Look Inside Python', they look at how Python code is translated and run.

Apply object-oriented programming principles (classes, objects, inheritance, encapsulation) as mandatory content for all students

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

In Python Lab Module 17 'Challenge: Split the Pipeline', learners write a package of modules and import functions from it. In Module 28 they define objects with Enum, NamedTuple and dataclasses.

(HL only) Implement abstract data types such as stacks, queues, linked lists, and trees

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

In Grade 11 'The Q Revolution', learners trace a replay queue and sort situations into queue or stack. In Grade 12 'The Whiteboard Challenge' they match problems to patterns, and Python Lab Module 28 covers stacks, linked lists and trees.

Where it is taught

Internal assessment

Design, develop, and document a self-identified computational solution (~35 hours) as the internal assessment, including a problem specification, planning, system overview, development, and evaluation

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

In Grade 12 'Development Phase 3', learners let three people try their assistant on one real task, log issue severity, make one change from the feedback, re-run the eight-case suite twice, and record before and after pass counts.

Where it is taught

Evaluate the success of a computational solution against its own requirements and identify possible improvements

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 write test cases, run each twice, fix a line and re-run the suite. A Raise Your AI held-out test checks fairness across users.

Still to add

Environmental criteria (energy per use) and personal criteria (privacy, wellbeing) are not part of evaluating their own build, and the requirements document is not re-checked against it.

Group 4 collaboration

Collaborate with students from other Group 4 (sciences) subjects on shared scientific investigation and collaborative-sciences project skills

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

In Grade 12 'Research as a Team', learners run a practice repository with scripted or paired teammates: fill a roles table, open issues with owners and due days, review pull requests, resolve a merge conflict, re-plan a slipped task, and write a team log.

Still to add

The team build happens in a practice repository with scripted teammates, not on a real shared project, and the team log is self-reported.

Academic integrity

Credit and reference any AI-generated content used in coursework in the body of the text and in the bibliography, per IB academic integrity requirements

We start Grade 10 · framework Grade 11Framework grades 11–12
Mostly covered
Our Grades 11–12 Mostly covered
What learners do

In Grade 12 'Crediting AI in Your Paper', learners study APA and MLA forms for citing an AI tool, fix reference entries, then write an AI-use statement with a reference and in-text citation for their own capstone report.

Still to add

Learners who used no AI practise on a labelled example, and the statement is kept in their notes rather than checked inside a finished report.

IB Middle Years Programme (MYP) Design

Criterion A: Inquiring and analysing

Given a design situation, identify a problem that needs to be solved and analyse the need for a solution

Framework grades 6–8, 9–10
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.

Our Grades 9–10 Fully covered
What learners do

Learners practise six-step design thinking with user research and a problem statement in Grade 8 'Designing AI Solutions'. In Grade 9 'The Right Question' they reframe problems as X, y and data and write SMART specifications.

Conduct an inquiry into the nature of a design problem to inform the design brief

Framework grades 6–8, 9–10
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.

Our Grades 9–10 Fully covered
What learners do

Learners practise six-step design thinking with user research and a problem statement in Grade 8 'Designing AI Solutions'. In Grade 9 'The Right Question' they reframe problems as X, y and data and write SMART specifications.

Criterion B: Developing ideas

Write a detailed design specification that drives the development of a solution

Framework grades 6–8, 9–10
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.

Our Grades 9–10 Fully covered
What learners do

Learners practise six-step design thinking with user research and a problem statement in Grade 8 'Designing AI Solutions'. In Grade 9 'The Right Question' they reframe problems as X, y and data and write SMART specifications.

Develop and present a proposed design solution derived from the specification

Framework grades 6–8, 9–10
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.

Our Grades 9–10 Fully covered
What learners do

Learners practise six-step design thinking with user research and a problem statement in Grade 8 'Designing AI Solutions'. In Grade 9 'The Right Question' they reframe problems as X, y and data and write SMART specifications.

Criterion C: Creating the solution

Plan the creation of the chosen solution and follow that plan to build a prototype sufficient for testing and evaluation

Framework grades 6–8, 9–10
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 7 'The 70% Problem' and Grade 8 'Building & Training AI', learners build and evaluate prototypes, such as a Teachable Machine classifier improved from 70 to 91 percent and a Python chatbot traced end to end.

Our Grades 9–10 Fully covered
What learners do

In Grade 9 'Science Fair Star' and Python Lab Module 44, learners audit data, train and compare a controlled model change, then implement a callable predictor that returns a plain-language result, and run an evaluation.

Where it is taught

Criterion D: Evaluating

Design tests to evaluate a solution, carry out those tests, and objectively evaluate the solution's success

Framework grades 6–8, 9–10
Mostly covered
Our Grades 6–8 Mostly covered
What learners do

In Grade 7 'Refinement Week!' and Grade 8 'The Global Goals Project', learners test their own classifiers on unseen examples, change the weak class and retest. They also practise normal versus edge-case testing.

Still to add

Personal, social and environmental criteria are not combined with the learner's own requirements to score their own build, and learners do not write an improvement list from such a scorecard.

Where it is taught
Our Grades 9–10 Mostly covered
What learners do

In Grade 9 'Science Fair Star', learners lock away test rows, compare the test score to a no-model baseline, name one limit and self-score against a guide. Grade 10 'Spark of Inspiration' covers values checks.

Still to add

Evaluation checks only the learner's own success test against a baseline; personal, social and environmental criteria are not in the Grade 9 rubric or scoring guide.

Where it is taught

Identify areas where a design solution could be improved and explain the solution's impact on the client or target audience

Framework grades 6–8, 9–10
Mostly covered
Our Grades 6–8 Mostly covered
What learners do

In Grade 7 'Refinement Week!' and Grade 8 'The Global Goals Project', learners test their own classifiers on unseen examples, change the weak class and retest. They also practise normal versus edge-case testing.

Still to add

Personal, social and environmental criteria are not combined with the learner's own requirements to score their own build, and learners do not write an improvement list from such a scorecard.

Where it is taught
Our Grades 9–10 Mostly covered
What learners do

In Grade 9 'Science Fair Star', learners lock away test rows, compare the test score to a no-model baseline, name one limit and self-score against a guide. Grade 10 'Spark of Inspiration' covers values checks.

Still to add

Evaluation checks only the learner's own success test against a baseline; personal, social and environmental criteria are not in the Grade 9 rubric or scoring guide.

Where it is taught

Course aims

Use and apply technology effectively to access, process, and communicate information, and to model and create solutions to problems

Framework grades 6–8, 9–10
Partly covered
Our Grades 6–8 Fully covered
What learners do

In Grade 6 'How to Learn More', Grade 7 'Two Presentations' and Grade 8 'Building a Portfolio', learners pick free platforms for a goal, produce posters and demos, choose portfolio platforms for code, visuals, documents and video, and plan to keep learning.

Our Grades 9–10 Partly covered
What learners do

In Grade 9 'The Right Question' and Grade 10 'Presentation and Demo', learners use an AI chat tool on their own textbook paragraph, write a project Gantt chart, plan a goal with AI, and record and self-score a 3-minute demo.

Still to add

Learners do not practise finding information with search tools, managing information across subjects, or keeping their tool knowledge current; those are only told.

Develop an appreciation of the impact of design and technology innovations on life, global society, and environments, including their historical, political, and social contexts

We start Grade 4 · framework Grade 6Framework grades 6–8, 9–10
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 6 'Birth of Computers', 'AI and Jobs' and 'AI in 2030', learners compare human computers, ENIAC and a phone, study six historic jobs reshaped by technology and the new job each created, and make hedged 2030 predictions.

Our Grades 9–10 Covered earlier · Grade 4
What learners do

In Grade 4 'Then, Now, Next', learners sort life before and after mobile phones, order four big changes in work, follow farming through time, and make a forecast card about work in five years.

Where it is taught

Act with integrity and honesty and take responsibility for one's own actions when making design decisions

Framework grades 6–8, 9–10
Fully covered
Our Grades 6–8 Fully covered
What learners do

In Grade 6 'Being a Good Digital Citizen' and 'You Control AI', learners study six digital-citizenship pillars, write and commit to a personal AI boundary, separate 'can we build it' from 'should we', and make a closing pledge.

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.

Digital design option

Where a school offers digital design (rather than or alongside product design), demonstrate digital-tool competencies such as prototyping, graphic/web design, and multimedia editing through the same four-criterion design cycle

We start Grade 3 · framework Grade 6Framework grades 6–8, 9–10· secondary source
Mostly covered
Our Grades 6–8 Mostly covered
What learners do

In Grade 5 'My Digital Toolkit', learners rebuild a saved chart as a page for younger readers, check it for colour-only bars and overclaims, and present it. In Grade 3 and 4 they combine chart, picture and caption on a poster.

Still to add

The Grade 5 poster is assembled from ready-made cards, so learners do not yet create the repurposed piece themselves.

Where it is taught
Our Grades 9–10 Mostly covered
What learners do

In Grade 10 'Presentation and Demo', learners present, record and score a 3-minute demo, then fix the lowest-scoring part. In Grade 9 'Write the Canteen Data Story' they write a data story for the canteen manager and a second title for students.

Still to add

Learners are not asked to plan which applications to combine, or to repurpose their work into a second format for a different audience with an explicit trust and usability check.

Where it is taught

IB position statement: Artificial intelligence (AI) in learning, teaching, and assessment

AI literacy and academic integrity

Understand the bias inherent in content produced by an AI tool and be able to critically review AI-generated output

We start Grade 6 · framework Grade 9Framework grades 9–10, 11–12
Fully covered
Our Grades 9–10 Fully covered
What learners do

In Grade 10 'Deepfakes and Misinformation', learners pause, check and verify before sharing; this builds on risk-based checking in Grade 6 and verifying AI-generated information in Grade 8.

Our Grades 11–12 Fully covered
What learners do

In Grade 12 'AI That Writes Code', learners verify AI maths and review AI-generated code before shipping; Grade 6 lessons teach SIFT-style source checking.

Where it is taught

Understand that any AI-generated work included, even in part, in a piece of assessment is not considered the student's own unless it is clearly credited in the text and referenced in the bibliography

Framework grades 9–10, 11–12
Mostly covered
Our Grades 9–10 Mostly covered
What learners do

In Grade 10 'Choosing and Judging AI Tools', learners learn that AI-written work handed in is not theirs, see what a good AI note includes (tool, date, prompt, what was kept or changed), judge sample notes, and write their own AI note.

Still to add

Disclosure is practised only as a separate AI note; no in-text acknowledgement or reference entry for an AI tool is written, and MLA and APA formats are named but not shown.

Where it is taught
Our Grades 11–12 Mostly covered
What learners do

In Grade 12 'Crediting AI in Your Paper', learners study APA and MLA forms for citing an AI tool, fix reference entries, then write an AI-use statement with a reference and in-text citation for their own capstone report.

Still to add

Learners who used no AI practise on a labelled example, and the statement is kept in their notes rather than checked inside a finished report.

Theory of Knowledge (TOK)

Use AI-generated content as an object of inquiry within Theory of Knowledge to examine how knowledge is produced and evaluated

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

Grade 12 'Can AI Really Think?' and 'The Unsolved Mysteries' present the understanding debate, machine consciousness and AI rights and personhood as reading and reveal cards, with one true/false item.

Still to add

Learners do not take a position on machine understanding, consciousness or rights or weigh evidence against criteria. The Turing test is not revisited after Grade 6.

Academic integrity policy

Follow the IB Academic Integrity policy's guidance on the ethical use of AI tools (per its dedicated appendix) when producing assessed work

Framework grades 9–10, 11–12
Mostly covered
Our Grades 9–10 Mostly covered
What learners do

In Grade 10 'Choosing and Judging AI Tools', learners learn that AI-written work handed in is not theirs, see what a good AI note includes (tool, date, prompt, what was kept or changed), judge sample notes, and write their own AI note.

Still to add

Disclosure is practised only as a separate AI note; no in-text acknowledgement or reference entry for an AI tool is written, and MLA and APA formats are named but not shown.

Where it is taught
Our Grades 11–12 Mostly covered
What learners do

In Grade 12 'Crediting AI in Your Paper', learners study APA and MLA forms for citing an AI tool, fix reference entries, then write an AI-use statement with a reference and in-text citation for their own capstone report.

Still to add

Learners who used no AI practise on a labelled example, and the statement is kept in their notes rather than checked inside a finished report.

IB Primary Years Programme (PYP) curriculum framework

Digital citizenship (integrated, transdisciplinary)

Use digital tools safely, respectfully, and effectively as part of transdisciplinary units of inquiry

Framework grades 1–2, 3–5· secondary source
Fully covered
Our Grades 1–2 Fully covered
What learners do

In Grade 1 'Keep It Safe Online', learners order do-not-reply and show-an-adult steps for unknown online contact, and protect a photo and a password.

Our Grades 3–5 Fully covered
What learners do

In Grade 5 'My Secrets', 'Locks and Keys', 'My Data Trail' and 'When Something Goes Wrong', learners protect their identity, treat an online claim of being ten as unverifiable, close and report scary content, and learn to be kind because it reaches a real person.

Understand basic digital-citizenship concepts: online safety, digital etiquette, and awareness of one's own digital footprint

Framework grades 3–5· unverified source
Fully covered
Our Grades 3–5 Fully covered
What learners do

In Grade 5 'My Secrets', 'Locks and Keys', 'My Data Trail' and 'When Something Goes Wrong', learners protect their identity, treat an online claim of being ten as unverifiable, close and report scary content, and learn to be kind because it reaches a real person.

Computational/algorithmic thinking (integrated, transdisciplinary)

Develop early algorithmic thinking through inquiry-based problem-solving activities embedded in units of inquiry

Framework grades 3–5· unverified source
Fully covered
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.

Agency, self-efficacy and action

Take individual or collective action informed by learning, including reflecting on the responsibilities of using technology, as part of the PYP's agency/action outcome

Framework grades 3–5
Fully covered
Our Grades 3–5 Fully covered
What learners do

In Grade 4 'Thinking Well' and Grade 5 'What I Will Build', learners take an AI guardian role, take responsibility for their own use of AI output, make a builder's promise and say how AI helped.

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.

  • Analyse a pre-seen, annually issued case study and apply theoretical course concepts to that real-world scenario in the external examination
  • Produce a short demonstration video documenting the developed computational solution, alongside a written report capped at 2,000 words
  • Study computer science through two mandatory themes for every student: Theme A (Concepts of computer science) and Theme B (Computational thinking and problem-solving), with no optional topics as in the previous syllabus
  • A first assessment session for the redesigned computer science course, with its own subject brief, exists for May 2027
  • Sit two external written papers (Paper 1 covering Theme A plus the case study; Paper 2 covering Theme B) weighted 35% each at SL and 40% each at HL, with the internal assessment worth 30% (SL) or 20% (HL)
  • Compile a design ePortfolio (design brief, specification, and development evidence) as a complete design folder demonstrating the full design cycle, for MYP Year 5 external moderation

Bring the course to your school or region

Schools, school groups, resellers and partners: we will walk you through the alignment for your board and the lessons behind it.

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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.