The CBSE CT and AI curriculum, Classes 3 to 8
Every hour figure and learning outcome below is transcribed from Curriculum Framework for Computational Thinking (CT) and Artificial Intelligence (AI), Classes III-VIII, session 2026-27, issued under Circular Acad-15/2026, dated 01.04.2026. The framework itself is public.
The same content is available as JSON at /api/curriculum.
Time allocation
Classes 3 to 5
50 hours a yearCT embedded in Mathematics and The World Around Us, by the subject teachers.
| Component | Hours a year |
|---|---|
| Computational Thinking | 50 |
Classes 6 to 8
100 hours a yearSubject teachers for CT and the computer teacher for AI literacy, collaborating. Projects are assessed by the computer teacher.
| Component | Hours a year |
|---|---|
| Advanced CT skills | 40 |
| AI literacy | 20 |
| Interdisciplinary projects | 40 |
CT learning outcomes, Classes 3 to 5
Four competencies run through every grade. What changes is the level.
Class 3
| Abstract thinking | Solve problems with hidden or unseen ideas: different viewpoints of 3-D objects; changes in shapes after flips, turns, folds or rotations; hidden or missing parts in incomplete shapes or patterns. |
|---|---|
| Pattern recognition | Identify simple patterns involving one or two changes in consecutive terms, using numbers, shapes, letters, or a mix. |
| Decomposition | Break down problems involving two or three clues from number clues, 3-D objects and their parts, step-by-step exchanges or transfers, and tables or charts holding several pieces of information. |
| Algorithmic thinking | Follow clear step-by-step rules for number sequences, movements on grids or direction paths, events ordered by before/after/in-between clues, values that rise or fall across steps, and multi-step instructions. |
Class 4
| Abstract thinking | Solve moderate problems with partially visible or incomplete ideas, adding mirror images and identical halves based on symmetry to the Grade 3 set. |
|---|---|
| Pattern recognition | Identify patterns involving one or more changes, using numbers, shapes, letters, or a mix. |
| Decomposition | Break down problems with a cluster of moderate clues, adding place value and sum/difference/product, and conditions for counting, grouping or sorting items. |
| Algorithmic thinking | Follow well-defined elaborate conditions for moderate to complex problems, adding swaps, and people or events ordered by attributes or chronology. |
Class 5
| Abstract thinking | Solve complex problems with multi-layered hidden cues, adding changes in order and direction (clockwise or counter-clockwise) and mirror or water images. |
|---|---|
| Pattern recognition | Identify progressive patterns involving multiple changes, using numbers, shapes, letters, or a mix. |
| Decomposition | Break down higher-order problems with interconnected clues, adding pictures or visuals that stand for numerical values. |
| Algorithmic thinking | Follow multi-layered rules for advanced problems across the full Grade 4 set. |
AI literacy, Classes 6 to 8
Class 6 AI syllabus, 20 hours
| # | Unit | Hours |
|---|---|---|
| 1 | Introduction to AI and everyday examples What AI is; AI against automation; human against machine intelligence; supervised, unsupervised and reinforcement learning. | 5 |
| 2 | Basic data concepts Data types (numbers, text, images, sound); simple data organisation and representation in tables or charts. | 5 |
| 3 | Simple pattern recognition and decision making Identifying patterns in data or daily routines; making simple decisions from observations. | 5 |
| 4 | Ethics and digital responsibility Online safety, privacy, passwords, ethical use of technology, digital footprints. | 5 |
Class 7 AI syllabus, 20 hours
| # | Unit | Hours |
|---|---|---|
| 1 | AI domains Classification, regression and clustering with hands-on practice on a small dataset; computer vision, natural language processing and data science; chatbots, image recognition, translation. | 5 |
| 2 | AI in industries Healthcare, education, transport and communication; how AI affects accuracy, efficiency and productivity. | 5 |
| 3 | Data visualisation and analysis Collecting structured data; bar charts, line graphs and pie charts; interpreting patterns. | 5 |
| 4 | Ethics and AI bias awareness Bias in AI with case examples; responsible and fair use; digital citizenship. | 5 |
Class 8 AI syllabus, 20 hours
| # | Unit | Hours |
|---|---|---|
| 1 | AI project lifecycle Define the problem, collect data, test AI tools, reflect and improve; how AI learns from patterns in data. | 5 |
| 2 | Deeper dive into AI applications AI in environment, healthcare, automation and education; hands-on with no-code tools such as image classifiers, chatbots and prediction apps. | 5 |
| 3 | Data and fairness How AI uses data; identifying bias in datasets; simple strategies for fairness and inclusivity. | 5 |
| 4 | Ethics and responsible AI Privacy, misinformation and social impact; responsible use; reflection on real-world challenges. | 5 |
Assessment
The framework asks for hands-on activities, collaborative and individual projects, reflective journals, peer assessment and observation by the teachers, and names a Teacher Observation Journal at both stages. It also asks teachers to write clear and consistent rubrics themselves. Projects in Classes 6 to 8 are assessed by the computer teacher.
The three levels this software records against (emerging, developing, secure) are ours, not CBSE's. The framework asks for teacher observation and consistent rubrics without prescribing a scale.