| What does Artificial Intelligence enable machines to do? | carry out tasks typically associated with human intelligence — such as learning, comprehension, reasoning, problem-solving, and understanding natural language | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Foreword The National Education Policy (NEP) aims to position India as a leader in emerging knowledge fields by integrating technologies like Artificial Intelligence, Machine Learning, Big Data, and Computational Thinking into school education. It promotes technology-enabled, interactive, and gamified learning using tools such as Augmented Reality (AR), Virtual Reality (VR), and virtual labs to foster creativity, problem-solving, and interdisciplinary exploration. NCF-SE 2023 carries this recommendation further for implementation. Key Definitions Artificial Intelligence (AI) is a broad collection of technologies that enable machines to carry out tasks typically associated with human intelligence — such as learning, comprehension, reasoning, problem-solving, and understanding natural language. | 718 | definition | 1.000 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Key Definitions Artificial Intelligence (AI) is a broad collection of technologies that enable machines to carry out tasks typically associated with human intelligence — such as learning, comprehension, reasoning, problem-solving, and understanding natural language. | 3 | page=3,block=0 | 0.700 | valid |
| What is the purpose of interdisciplinary projects in the Classes 6–8 curriculum? | Cross-subject projects applying CT & AI | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum 10. Classes 6–8 Component Hours/Year Description Advanced CT Skills 40 Builds on Classes 3–5; complex situations Introductory AI Concepts 20 Foundational AI; exposure to AI tools Interdisciplinary Projects 40 Cross-subject projects applying CT & AI The syllabus for Classes 6–8 comprises three components: Advanced CT skills: The syllabus will build on the earlier classes and provide an opportunity to apply CT skills to complex situations in tandem. Total time allocated to this is 40 hours per academic year. Introductory concepts of AI: The syllabus extends the CT skills the students have gained to AI. They will be introduced to the fundamental concepts of AI and exposed to AI tools in this school stage. The total time allocated to these concepts is 20 hours per academic year. | 283 | definition | 1.000 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Classes 6–8 Component Hours/Year Description Advanced CT Skills 40 Builds on Classes 3–5; complex situations Introductory AI Concepts 20 Foundational AI; exposure to AI tools Interdisciplinary Projects 40 Cross-subject projects applying CT & AI The syllabus for Classes 6–8 comprises three components: Advanced CT skills: The syllabus will build on the earlier classes and provide an opportunity to apply CT skills to complex situations in tandem. |
| What type of pedagogy is suggested for engaging students in learning? | activity-based and experiential, engaging students through interactive and hands-on experiences. | Pedagogy and Assessment Pedagogy suggested is activity-based and experiential, engaging students through interactive and hands-on experiences. • Classes 3–5: Worksheets based on games, puzzles, and activities to enhance CT skills and creativity. • Classes 6–8: Hands-on and real-world problems, collaborative and group work to solidify and apply multidisciplinary foundational knowledge on coding, data analysis, and AI tools, aiming to learn advanced CT and problem-solving skills. Assessment approaches need to move away from traditional summative assessment to continuous, formative, and competency-based assessment. A range of assessment tools, such as problem-solving tasks, project work, reflective journals, and discussions/debates on ethical dilemmas, are to be used to assess student learning. | 46 | definition | 1.000 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Pedagogy and Assessment Pedagogy suggested is activity-based and experiential, engaging students through interactive and hands-on experiences. • Classes 3–5: Worksheets based on games, puzzles, and activities to enhance CT skills and creativity. |
| What types of patterns are identified in pattern recognition? | progressive patterns involving multiple changes | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Grade 5 Abstract Thinking Students will be able to solve complex problems with multi-layered hidden cues, using: • Different viewpoints of 3-D objects • Changes in shapes after flips, turns, cuts/folds, or rotations, and changes in order and directions (clockwise or counter-clockwise) • Hidden or missing parts in incomplete shapes or patterns • Mirror/water images and identical halves based on symmetry Pattern Recognition Students will identify progressive patterns involving multiple changes, using numbers, shapes/images, letters, or a mix. | 523 | definition | 1.000 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Grade 5 Abstract Thinking Students will be able to solve complex problems with multi-layered hidden cues, using: • Different viewpoints of 3-D objects • Changes in shapes after flips, turns, cuts/folds, or rotations, and changes in order and directions (clockwise or counter-clockwise) • Hidden or missing parts in incomplete shapes or patterns • Mirror/water images and identical halves based on symmetry Pattern Recognition Students will identify progressive patterns involving multiple changes, using numbers, |
| What does Holistic Development: Study of CT and AI contribute to? | the development of reasoning, logical thinking, creative problem-solving skills, critical thinking, and ethical decision-making abilities, leading to the individual flourishing | 2. Holistic Development: Study of CT and AI contributes to the development of reasoning, logical thinking, creative problem-solving skills, critical thinking, and ethical decision-making abilities, leading to the individual flourishing. It leads to the creation of responsible digital citizens in society. | 59 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Holistic Development: Study of CT and AI contributes to the development of reasoning, logical thinking, creative problem-solving skills, critical thinking, and ethical decision-making abilities, leading to the individual flourishing. | 14 | page=14,block=0 | 0.800 | valid |
| How are collaborative tasks incorporated in Classes 3–5? | peer discussions while solving problems using the worksheets | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum 9 Pedagogy and Assessment 9. Pedagogical Approaches Stage Approaches Classes 3–5 • Hands-on activities, games, and puzzles to teach problem- solving using the worksheets • Allowing students to interpret charts, diagrams, and any other visual representations • Teach students to break larger problems into smaller ones, to develop problem-solving skills • Use collaborative tasks and peer discussions while solving problems using the worksheets. Classes 6–8 • Use complex puzzles, riddles, and games to build on the CT abilities taught in the previous stage • Deliver fundamental concepts of AI through explanations, demonstrations and hands-on experiences. • Organise group discussions, design collaborative projects that integrate CT and AI. | 457 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Pedagogical Approaches Stage Approaches Classes 3–5 • Hands-on activities, games, and puzzles to teach problem- solving using the worksheets • Allowing students to interpret charts, diagrams, and any other visual representations • Teach students to break larger problems into smaller ones, to develop problem-solving skills • Use collaborative tasks and peer discussions while solving problems using the worksheets. |
| How will the CT curriculum for Classes 6–8 be aligned with other subjects? | closely aligned with the mathematics textbooks for each class | Syllabus for Advanced CT Skills (Classes 6–8) For Classes 6–8, the CT curriculum will build upon the foundational skills developed in Classes 3–5, introducing more advanced applications and problem-solving tasks. The design of the curriculum will be closely aligned with the mathematics textbooks for each class, ensuring seamless integration of CT concepts into existing topics. The accompanying resource book will parallel the structure of the mathematics textbook while incorporating targeted CT exercises in every chapter. This approach will allow teachers to naturally reinforce and expand CT skills as they progress through the mathematics curriculum. 10.2. | 250 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | The design of the curriculum will be closely aligned with the mathematics textbooks for each class, ensuring seamless integration of CT concepts into existing topics. | 29 | page=29,block=0 | 0.700 | valid |
| What are learners in Class 8 taught about bias in AI datasets? | find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • Explain the uses of AI in daily life and understand AI as a specific type of algorithm that uses datasets, learning, and prediction • Analyse contributions of AI to fields like healthcare, automation, and education, understanding both benefits and risks • Describe AI ethics as the values and guidelines that ensure AI is created and used responsibly 10.2. | 348 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • |
| What are learners in Class 8 taught about the importance of accountability in AI? | the importance of accountability, privacy, and serving human interests | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • Explain the uses of AI in daily life and understand AI as a specific type of algorithm that uses datasets, learning, and prediction • Analyse contributions of AI to fields like healthcare, automation, and education, understanding both benefits and risks • Describe AI ethics as the values and guidelines that ensure AI is created and used responsibly 10.2. | 524 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • |
| What are the potential consequences of bias in AI according to the Class 8 curriculum? | bias in AI leads to unfair conclusions | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • Explain the uses of AI in daily life and understand AI as a specific type of algorithm that uses datasets, learning, and prediction • Analyse contributions of AI to fields like healthcare, automation, and education, understanding both benefits and risks • Describe AI ethics as the values and guidelines that ensure AI is created and used responsibly 10.2. | 473 | relationship | 0.970 | https://cbseacademic.nic.in/web_material/CurriculumMain27/CTAI_Pri_2026-27.pdf | Computational Thinking and Artificial Intelligence Classes 3–8 Curriculum Class 8 — AI Learners will be able to: • Describe the stages of the AI project cycle: Define Problem, Collect Data, Test AI Tools, Reflect and Improve • Apply no-code tools to tackle real-world problems and reflect on their utility/effectiveness • Explain how AI uses data, find and research sources of bias in datasets, and apply basic strategies to ensure fairness and inclusivity • Recognise how bias in AI leads to unfair conclusions and realise the importance of accountability, privacy, and serving human interests • |