Computational Thinking and Artificial Intelligence - Class 6 - Teacher Handbook

Sep 15, 2026

Uploaded by Đào

Teacher guidance for “Computational Thinking and Artificial Intelligence” for Class 6, aligned with India’s NEP goals. Emphasizes computational thinking as a foundational skill that supports learning AI, covering concepts beyond AI such as cybersecurity and basic networking. Engages learners through constrained problems, dependencies, logical conditions, grids, data interpretation, and optimisation across numerical, spatial, and real-life contexts. Includes pedagogical guidance, learning resources, assessment support, and classroom implementation for competency-based learning.

LanguageEnglish

CategoryExam

FormatPDF

Pages110

Reading Time4 h 37 min

AccessFree to download

PART-1 COMPUTATIONAL THINKING

Introduction

How to Use this Book?

Patterns in Mathematics

Lines and Angles

Number Play

Data Handling and Presentation

Prime Time

Perimeter and Area

Fractions

Playing with Constructions

Symmetry

The Other Side of Zero

PART-2 ARTIFICIAL INTELLIGENCE

Introduction to Artificial Intelligence and Everyday Examples

Basic Data Concepts

Simple Pattern Recognition and Decision Making

Ethics and Digital Responsibility

CENTRAL BOARD OF SECONDARY EDUCATION Computational Thinking and Artiﬁcial Intelligence Class 6 Teacher Handbook First Edition: March, 2026 Country of Publication: India Published by: Central Board of Secondary Education, Integrated Office, Sector 23, Dwarka, New Delhi-110077 ACKNOWLEDGEMENTS Expert Committee 1. Dr. Karthik Raman, Core Leadership, IIT Madras Bodhan AI Foundation; Professor, Department of Data Science and AI, Wadhwani School of Data Science and AI, IIT Madras 2. Dr. Rajesh Kumar, Professor, Department of Electrical Engineering, MN IT, Jaipur 3. Dr. Seema Verma, Professor (ECE), Additional Project Director (Siemens CoE), NITTTR, Bhopal 4. Dr. S. Neethi , Core Leadership, IIT Madras Bodhan AI Foundation; Professor of Practice, Department of Data Science and AI, Wadhwani School of Data Science and AI, IIT Madras 5. Dr. Arun L. Naik, Associate Professor, Mathematics Education, Azim Premji University, Bengaluru 6. Dr. Aanchal Chomal, Associate Professor, School of Continuing Education and University Resource Centre, Azim Premji University 7. Dr. Ankit Vijayvargiya, Assistant Professor, School of Technology, Dhirubhai Ambani University, Gandhinagar 8. Sh. R P Singh, Associate Prof & Additional Director, CBSE 9. Mr. Mikin Lala, (IIT Roorkee and IIM Calcutta Alumnus), Field Expert 10. Ms. Rekha Malhotra, (Alumna of the British Institute (Business Management and Advertising), Frameworks Mumbai (Advanced Certification in Computer Science), and Workstation (3D Animation)), Field Expert Material Production Group 1. Dr. S. Neethi Core Leadership, IIT Madras Bodhan AI Foundation, Professor of Practice, Department of Data Science and AI, Wadhwani School of Data Science and AI, IIT Madras 2. Dr. Ankit Vijayvargiya, Assistant Professor, School of Technology, Dhirubhai Ambani University, Gandhinagar. 3. Mr. Jay Thakkar, Senior Technical Officer, Centre for Creative Learning, IIT Gandhinagar 4. Mr. Chris John, Project Scientist, Centre for Creative Learning, IIT Gandhinagar 5. Ms Rekha Malhotra {Alumna of the British Institute (Business Management and Advertising), Frameworks Mumbai (Advanced Certification in Computer Science), and Workstation (3D Animation)}, Field Expert 6. Mr. Mikin Lala, (IIT Roorkee and IIM Calcutta Alumnus), Field Expert 7. Ms. Amatullah Mustafa Neemuchwala, Field Expert 8. Ms. Telidevara Sree Lasya, Field Expert 9. Mr. Parth Oza, Field Expert 10. Mr. Deep Mayekar, Field Expert 11. Mr. Mayank Patil, Field Expert 12. Ms. Shivraj Ugale, Field Expert 13. Mr. Raj Dhorade, Field Expert 14. Mr. Nilesh Vijay Rajput, Field Expert The efforts of Prof. Manish Jain and his whole team from Centre for Creative Learning, IIT Gandhinagar are also acknowledged and deeply appreciated. PREFACE The National Education Policy (NEP) aims to position India as a leader in emerging knowledge fields by integrating technologies like AI, 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. NCFSE 23 carries this recommendation further for implementation. While Artificial Intelligence (AI) is an important requirement, Computational Thinking (CT) should be a broader skill, developing a foundation for learning AI. It can cover various aspects like Cybersecurity, basic networking, etc. Hence, CBSE approaches this by integrating Computational Thinking with AI and other technological advancements, without dependence on any platform. The book engages learners with problems involving constraints, dependencies, logical conditions, grids, data interpretation, and optimisation across numerical, spatial, and real-life contexts. It introduces foundational Artificial Intelligence concepts such as classification, pattern identificat

FAQs

What are the key computational thinking components introduced in this handbook?

Computational Thinking includes Decomposition, Pattern Recognition, Abstraction, Algorithm Design, Data Analysis, and Troubleshooting.

How does the handbook frame computational thinking in relation to AI learning?

It positions computational thinking as a broader foundation for learning AI, not only an AI-specific requirement.

What ethical topics are covered in the Artificial Intelligence part?

The content includes responsible technology use, online safety, privacy, password safety, and digital footprints, focusing on ethical awareness.

Sep 15, 2026

Uploaded by Đào